e-Commerce 2011

CCSIS
M
MCCSIS
Proceedings of the
IADIS International Conference
e-Commerce 2011
EDITED BY
Sandeep Krishnamurthy
IADIS INTERNATIONAL CONFERENCE
E-COMMERCE 2011
part of the
IADIS MULTI CONFERENCE ON COMPUTER SCIENCE AND
INFORMATION SYSTEMS 2011
ii
PROCEEDINGS OF THE
IADIS INTERNATIONAL CONFERENCE
E-COMMERCE 2011
part of the
IADIS MULTI CONFERENCE ON COMPUTER SCIENCE AND
INFORMATION SYSTEMS 2011
Rome, Italy
JULY 21 - 23, 2011
Organised by
IADIS
International Association for Development of the Information Society
iii
Copyright 2011
IADIS Press
All rights reserved
This work is subject to copyright. All rights are reserved, whether the whole or part of the material
is concerned, specifically the rights of translation, reprinting, re-use of illustrations, recitation,
broadcasting, reproduction on microfilms or in any other way, and storage in data banks.
Permission for use must always be obtained from IADIS Press. Please contact [email protected]
Volume Editors:
Sandeep Krishnamurthy
Computer Science and Information Systems Series Editors:
Piet Kommers and Pedro Isaías
Associate Editors: Luís Rodrigues
ISBN: 978-972-8939-51-9
iv
TABLE OF CONTENTS
FOREWORD
ix
PROGRAM COMMITTEE
xi
KEYNOTE LECTURE
xv
FULL PAPERS
MEASURABLE PARAMETERS OF E-COMMERCE SYSTEMS FOCUSED
ON WEB INTERFACE
3
Petr Suchánek, Radim Dolák and Kateřina Slaninová
EVALUATING THE READINESS TO M-GOVERNMENT
IMPLEMENTATION IN BAHRAIN
11
Ahmed Sowaileh and Ali AlSoufi
GENETIC ALGORITHM BASED OPTIMIZATION FOR E-AUCTION
19
Mourad Ykhlef and Reem AlQifari
AN EXAMINATION OF THE CONTENTS OF PRIVACY POLICIES
ON THE AUSTRALIAN LOCAL GOVERNMENT WEBSITES
27
Qiuyan Fan
TAXONOMY OF IT INTANGIBLES ASSETS BASED ON THE ELECTRONIC
GOVERNMENT MATURITY MODEL IN URUGUAY
35
Helena Garbarino, Bruno Delgado and José Carrillo
A MODEL OF CUSTOMER RELATIONSHIP MANAGEMENT FOR THE CONTEXT
OF PERMISSION-BASED E-MAIL MARKETING
43
Hsin-Hui Lin
DETECTING EMERGING TOPICS AND TRENDS
VIA SOCIAL MEDIA ANALYTICS
51
Richard Colbaugh and Kristin Glass
E-LEARNING SEEN AS AN ENTERPRISE BUSINESS PROCESS
59
Fodé Touré and Esma Aïmeur
ANALYZING SENTIMENT OF SOCIAL MEDIA CONTENT
FOR BUSINESS INFORMATICS
Kristin Glass and Richard Colbaugh
v
67
A CONCEPTUAL MODEL OF WEB ATM ADOPTION:
AN INTEGRATED PERSPECTIVE OF THE TRANSACTION COST THEORY
AND INNOVATION DIFFUSION THEORY
75
Yi-Shun Wang, Shun-Cheng Wu, Hsin-Hui Lin, Yu-Min Wang and Ting-Rong He
USING MOBILE MESSAGING SERVICES IN EDUCATION:
DETERMINANTS OF STUDENTS’ ATTITUDES
83
Boonlert Watjatrakul
INTRODUCING MOBILE SERVICES TO DEVELOPING COUNTRIES
- A SOUTH AFRICAN PERSPECTIVE
91
Carolin Löffler and Michael Hettich
THE IMPACT OF INNOVATION, STANDARDIZATION, TECHNOLOGY
MARKETING STRATEGY ON THE PERFORMANCE IN SOFTWARE COMPANY:
COMPARATIVE STUDY ON SOFTWARE TYPE
99
Sung Hee Jang, Dong Man Lee and Hyun Sun Park
E-READINESS IN JORDAN ICT SECTOR COMPANIES
107
Maha Al-khaffaf
PROMOTORS AND INHIBTORS OF ONLINE GROCERY SHOPPING
IN DEVELOPING COUNTRIES FROM THE CONSUMERS’ PERSPECTIVE JORDAN AS CASE STUDY
114
Mohammad Al nawayseh, Bader Al fawwaz and Wamadeva Balachandran
ORGANIZATIONAL CONTROL ENVIRONMENT AND COBIT’S IT CONTROL
PROCESS IMPLEMENTATION
121
Nader Rezaei and Gareth Griffiths
ACCOUNTABILITY IN SINGLE WINDOW SYSTEMS USING AN INTERNAL
CERTIFICATE AUTHORITY - A CASE STUDY ON THAILAND’S NATIONAL
SINGLE WINDOW SYSTEM
129
Potchara Pruksasri, Jan van den Berg and Somnuk Keretho
VIRTUAL RECOMMENDATION DIFFUSION AND CO-SHOPPING INFLUENCE:
THE ROLE OF DYADIC NETWORK-BASED INTERACTIONS
137
Ana Torres and Francisco Martins
WHY DO BIDDERS BID ONLINE? THE VIEW OF CUSTOMER’S VALUE
145
Chiahui Yen, Chun-ming Chang, Chih-chin Yang, Lu-jui Chen and Ming-Chang Chiang
FACTORS INFLUENCING SAUDI CUSTOMERS’ DECISIONS TO PURCHASE
FROM ONLINE RETAILERS IN SAUDI ARABIA: A QUANTITATIVE ANALYSIS
153
Rayed AlGhamdi, Ann Nguyen, Jeremy Nguyen and Steve Drew
SHORT PAPERS
THE DETERMINANTS OF ONLINE HOTEL RESERVATION
Hulisi Öğüt
vi
165
CONSUMER BEHAVIORS IN REVENUE MANAGEMENT
W.R.T AUCTION THEORY
170
Mariam Shafqat and Zeeshan Khawar Malik
IMPACT OF VALUE PROPOSITION OF E-COMMERCE BY FIRMS
ON CUSTOMERS’ ADOPTABILITY
175
Aitzaz Ali and Zeeshan Khawar Malik
CYBERCRIMES AND THE BRAZILILIAN ATTEMPT
TO DEVELOP LEGISLATION
180
Maria Eugênia Finkelstein
MULTICHANNEL RETAILING STRATEGIES IN THE JAPANESE-STYLE
DISTRIBUTION SYSTEM: THE CASE OF KINOKUNIYA’S
MULTICHANNEL STRATEGIES
185
Hyemi Bang
DEVELOPING COMMUNICATION PRACTICES BY COMPUTER
AND VIDEO-CONFERENCING SYSTEMS:
A CASE STUDY OF A FINNISH RETAIL BANK
189
Johanna Ahola and Helena Ahola
A CHOREOGRAPHY LANGUAGE FOR BUSINESS COLLABORATION:
FROM ELECTRONIC CONTRACTING
TO INTER-ORGANIZATIONAL ENACTMENT
194
Alex Norta
CHANGES IN CONSUMER ACCEPTANCE OF DIRECT BANKING IN GERMANY
FOLLOWING THE FINANCIAL CRISES
199
Dirk Braun, Jan Kaehler and Jürgen Karla
REFLECTION PAPERS
IMPACT OF E-GOVERNMENT ON THE PRIVATE SECTOR AND THE ROLE
OF PRIVATE SECTOR IN THE E-GOVERNMENT INITIATIVES
207
Hussain Kassem Wasly and Ali AlSoufi
REFLECTIONS ON PRIVACY IN NEW LOCATION BASED SERVICES
IN SOCIAL NETWORKS
211
A. Paniza-Fullana, M. Payeras-Capellà, M. Mut-Puigserver and A. Isern-Deyà
POSTERS
UTILIZING THE COMMUNICATION-TECHNOLOGY TO MINIMIZE
THE FINANCIAL NEGATIVE INFLUENCE IN THE SUPPLY CHAIN
Ming-Yaun Hsieh, Wen-Yaun Wu, Chaang-Yuan Kung and Ya-Ling Wu
vii
217
INFRASTRUCTURE MODEL FOR ASSURANCE OF AUTHENTICATION DATA
EXCHANGE FORMAT
220
Ahmed Tallat, Hiroshi Yasuda and Kilho Shin
RESEARCH ON USING E-TECHNOLOGY AND E-ACTIVITIES
WITHIN BUSINESSES
Roman Malo
AUTHOR INDEX
viii
223
FOREWORD
These proceedings contain the papers of the IADIS International Conference e-Commerce
2011, which was organised by the International Association for Development of the
Information Society, Rome, Italy, 21 – 23 July, 2011. This conference is part of the Multi
Conference on Computer Science and Information Systems 2011, 20 - 26 July 2011, which
had a total of 1402 submissions.
The IADIS e-Commerce 2011 conference is a major international event for researchers,
academics, industry specialists, practitioners & students interested in the advances in, and
applications of, e-Commerce. The participants will have an opportunity to present and
observe the latest research results, and ideas in these areas. This conference aims to cover
both technological as well as non-technological issues related to this new business
paradigm.
The Conference invited proposals from the introductory through advanced level on all
topics related to e-Commerce. Proposals which address the theory, research and
applications as well as describe innovative projects were encouraged.
The following five main areas have been the object of paper and poster submissions within
specific topics:
- Commerce Technology;
- Global e-Commerce;
- Online Management;
- Online Business Models;
- Regulatory/Policy Issues.
The IADIS e-Commerce 2011 received 112 submissions from more than 24 countries. Each
submission has been anonymously reviewed by an average of four independent reviewers,
to ensure that accepted submissions were of a high standard. Consequently only 20 full
papers were approved which means an acceptance rate below 18 %. A few more papers
were accepted as short papers, reflection papers and posters. An extended version of the
best papers will be published in the IADIS International Journal on Computer Science and
Information Systems (ISSN: 1646-3692) and/or in the IADIS International Journal on
WWW/Internet (ISSN: 1645-7641) and also in other selected journals, including journals
from Inderscience.
Besides the presentation of full papers, short papers, reflection papers and posters, the
conference also included one keynote presentation from an internationally distinguished
researcher. We would therefore like to express our gratitude to Professor Erich
Schweighofer, Vienna University, Austria, for accepting our invitation as keynote speaker.
ix
As we all know, organising a conference requires the effort of many individuals. We would
like to thank all members of the Program Committee, for their hard work in reviewing and
selecting the papers that appear in the proceedings.
This volume has taken shape as a result of the contributions from a number of individuals.
We are grateful to all authors who have submitted their papers to enrich the conference
proceedings. We wish to thank all members of the organizing committee, delegates,
invitees and guests whose contribution and involvement are crucial for the success of the
conference.
Last but not the least, we hope that everybody will have a good time in Rome, and we
invite all participants for the next edition of the IADIS International Conference
e-Commerce 2012, that will be held in Lisbon, Portugal.
Sandeep Krishnamurthy,
Program Chair
University of Washington, USA
e-Commerce 2011 Conference Program Chair
Piet Kommers, University of Twente, The Netherlands
Pedro Isaías, Universidade Aberta (Portuguese Open University), Portugal
MCCSIS 2011 General Conference Co-Chairs
Rome, Portugal
July 2011
x
PROGRAM COMMITTEE
E-COMMERCE CONFERENCE PROGRAM CHAIR
Sandeep Krishnamurthy, University of Washington, USA
MCCSIS GENERAL CONFERENCE CO-CHAIRS
Piet Kommers, University of Twente, The Netherlands
Pedro Isaías, Universidade Aberta (Portuguese Open University), Portugal
E-COMMERCE CONFERENCE COMMITTEE MEMBERS
Abel Usoro, University of the West of Scotland, United Kingdom
Adam Vrechopoulos, Athens University Of Economics And Business, Greece
Adina Magda Florea, Politehnica University Of Bucharest, Romania
Agnes Koschmider, University Karlsruhe, Germany
Ainin Sulaiman, Universiti Malaya, Malaysia
Alex Norta, University Of Helsinki, Finland
Alexios Kaporis, University Of Patras, Greece
Amar Balla, Lcms-esi Ecole Nationale Supérieure , Algeria
Amelia Badica, University Of Craiova, Romania
Ángel Herrero Crespo, Universidad De Cantabria, Spain
Antonio Ruiz Martinez, University Of Murcia, Spain
Antonio Gabriel Lopez Herrera, University of Granada, Spain
Aristogiannis Garmpis, Technological Educational Institution Of Messolong, Greece
Arthur Csetenyi, Budapest Corvinus University, Hungary
Asher Rospigliosi, Brighton Business School, United Kingdom
Blanca Hernandez, Universidad De Zaragoza, Spain
Borislav Josanov, Novi Sad Business School, Serbia
Carla Ruiz Mafe, University Of Valencia, Spain
Chia-chen Lin, Providence University, Usa
Christian Kittl , Evolaris Ebusiness Competence Center, Austria
Christian Schloegl, University of Graz, Austria
Costas Lambrinoudakis, University of Piraeus, Greece
Costin Badica, University Of Craiova, Romania
David Parry, Auckland University Of Technology, New Zealand
Dennis Tachiki, Tamagawa University, Japan
Dimitrios Rigas, De Montfort University, United Kingdom
Dimitris Geneiatakis, University Of The Aegean, Greece
xi
Dimitris Kanellopoulos, University Of Patras, Greece
Dragan Cisic, University Of Rijeka, Croatia
Eduard Cristobal, Universitat De Lleida, Spain
Eduardo Peis, University Of Granada, Spain
Ejub Kajan, State University of Novi Pazar, Serbia
Emmanouel Varvarigos, University Of Patras, Greece
Erik Rolland, University Of California, USA
Esma Aimeur, Université De Montréal, Canada
Euripidis Loukis, University Of The Aegean, Greece
Fahim Akhter, Zayed University, United Arab Emirates
Francisco J. Martinez-Lopez, University Of Granada, Spain
Franz Lehner, Universität Passau, Germany
Gen-yih Liao, Chang Gung University, Taiwan
George Weir, University Of Strathclyde, United Kingdom
Georgios Dafoulas, Middlesex University, United Kingdom
Georgios Kambourakis, University Of The Aegean, Greece
Giorgos Karopoulos, Iit-cnr, Italy
Gisela Ammetller Montes, Universitat Oberta De Catalunya, Spain
Hana Horak, Faculty Of Economics And Business, Croatia
Hans Weigand, Tilburg University, Netherlands
Harekrishna Misra, Institute Of Rural Management Anand, India
Hiroaki Fukuda, Keio University, Japan
Inma Rodriguez-Ardura, Open University of Catalonia (Universitat Oberta d, Spain
Isabel De Felipe, Universidad Politécnica De Madrid, Spain
Isabella Mader, Imac Information & Management Consulting, Germany
Ivan Bedini, Alcatel-lucent Bell Labs, Ireland
Ivan Strugar, Universitiy Of Zagreb, Croatia
Jan Richling, Technische Universität Berlin, Germany
Jemal Abawajy, Deakin University, Australia
Jens Fromm, Fraunhofer FOKUS, Germany
Jeroen Doumen, Irdeto, Netherlands
Jim Buchan, Aut University, New Zealand
Josef Herget, Danube University Krems, Austria
Joseph Heili, Chambery School Of Business, France
Julián Briz, Universidad Politécnica De Madrid, Spain
Kamel Rouibah, College Of Business Administration, Kuwait
Klaus Turowski, University Of Augsburg, Germany
Krassie Petrova, Auckland University Of Technology, New Zealand
Lorena Blasco, Universidad De Zaragoza, Spain
Marc Esteva, Iiia-csic, Spain
Marco Furini, University Of Modena and Reggio Emilia, Italy
Marco Mevius, HTWG Konstanz, Germany
Maria Papadaki, University Of Plymouth, United Kingdom
Mario Spremic, University Of Zagreb, Croatia
xii
Markus Schranz, Vienna University Of Technology, Austria
Masrah Azmi Murad, Universiti Putra Malaysia, Malaysia
Matjaz Gams, Jozef Stefan Institute, Slovenia
Michael Merz, Ponton Consulting, Germany
Michelangelo Ceci, University Of Bari, Italy
Mirjana Pejic, University Of Zagreb, Croatia
Nahed Azab, Middlesex University, United Kingdom
Noha Saleeb, American University In Cairo, Egypt
Noor Akma Mohd Salleh, University Malaya, Malaysia
Nordin Bin Zakaria, Universiti Teknologi Petronas, Malaysia
Olle Olsson, Swedish Institute Of Computer Science, Sweden
Oshadi Alahakoon, Monash University, Australia
Pedro Solana González, Universidad De Cantabria, Spain
Pedro Soto-Acosta, Universidad De Múrcia, Spain
Pere Tumbas, Faculty Of Economics University Of Novi Sad, Serbia
Peter Weiss, FZI Research Center for Information Technology, Germany
Petra Hoepner, Fraunhofer Institut Fokus, Germany
Qun Ren, Bournemouth University, United Kingdom
Rainer Schmidt, Aalen University, Germany
Rajendra Akerkar, Western Norway Research Institute, Norway
Rodziah Atan, Universiti Putra Malaysia, Malaysia
Said Assar, Institut TELECOM Sud Paris, France
Shoba Tegginmath, Auckland University Of Technology, New Zealand
Shukor Abd Razak, Universiti Teknologi Malaysia, Malaysia
Sokratis Katsikas, University Of Piraeus, Greece
Spiros Sirmakessis, Technological Educational Institute of Messolongi, Greece
Spyros Kokolakis, University of the Aegean, Greece
Stefan Fenz, Vienna University of Technology, Austria
Stefanos Gritzalis, University Of The Aegean, Greece
Steven Furnell, University of Plymouth, United Kingdom
Susanne Robra-Bissantz, University Of Braunschweig, Germany
Tadashi Nakano, Osaka University, Japan
Thanassis Tiropanis, University Of Southampton, United Kingdom
Tokuro Matsuo, Yamagata University, Japan
Vaclav Subrta, University Of Economics, Czech Republic
Vassilis Triantafillou, Technological Educational Institution Of Messlongh, Greece
Yannis Stamatiou, University Of Ioannina, Greece
Yingjie Yang, De Montfort University, United Kingdom
Zeljko Panian, University Of Zagreb, Croatia
AUXILIARY REVIEWERS
Aggeliki TSOHOU, University of Piraeus, Greece
Dimitris Geneiatakis, Columbia University, USA
Prokopis DROGKARIS, University of the Aegean, Greece
xiii
xiv
KEYNOTE LECTURE
GOVERNANCE IN E-COMMERCE
Professor Erich Schweighofer,
Vienna University, Austria
ABSTRACT
E-commerce enables businesses to buy and sell products or services over electronic systems worldwide. The latin adage “ubi commercium, ibi jus” says that the efficiency of commerce depends on
an effective law, e.g. market freedoms, legal security etc. This principle remains valid in the
commercial cyberspace. A special cyberspace jurisdiction is without question as businesses,
vendors and consumers still act and live in real space giving States the strongest role as regulator
and enforcer of cyberspace. Thus, a very complex form of multilevel governance divides the
cyberspace in many territorial jurisdictions and compliance regimes. The advantage of more
flexibility and opportunities for businesses is contracted by higher legal risks.
The main question of governance of e-commerce for vendors is identifying relevant jurisdictions.
Businesses have to know which laws apply for doing e-commerce and which laws govern the
relations with customers. A clear set of jurisdictional rules is necessary for foreseeing what
behavior may invoke the laws or jurisdiction of another state. Whereas the situation seems to be
acceptable in the EU or the U.S., many problems exist for businesses acting outside of these
markets.
From the point of view of jurisdiction, cyberspace consists of three layers: physical infrastructure,
logical infrastructure and content layer. At present, due to the principle of network neutrality, most
governmental intervention is done at the content level. Mostly only criminal and political content is
subject to blocking but an extension of strongly considered by content industries (e.g. of file
sharing). The still limited experience proves that blocking cannot substitute the required cooperation between the various regulation providers and the minimum harmonization of rules worldwide. A focus of governance on servers or communications misses the fact that e-commerce
remains an exchange of goods or services under the control of human beings establishing and using
the technological infrastructure. As in real space, e-commerce providers must have a business
license in their respective State. Activities on other countries are subject to their rules, too. In the
EU, the EC E-Commerce-Directive has set the standard that a lawful business activity in one
country may be extended to the whole EEC area (with some limits). Besides that, businesses may
use loopholes in rules of some country. Some States offer favorable regimes for e-businesses (e.g.
media companies in Island). Due to the principle of network neutrality, this practice has to be
accepted because enforcing of contradictory rules in affected other countries may be very difficult.
xv
Businesses face jurisdictional risks due to protection concerns, in particular in the interest of
consumers. The EU Brussels Regulation allows consumers to sue in their country if the business
activities are targeted to this territory. In the US, the Zippo case states that the activity level of
websites – active, passive or interactive – constitutes an important factor in asserting jurisdiction.
As IT sets the factual framework for e-commerce activities, a more developed set of rules seems to
be required. Factors may be the commerciality of the activity, the targeting of this activity to a
particular country, and reasonable care undertaken in avoiding infringement of these rules. Many
rules on business activities, consumer protection and data protection have to be taken into account.
Very often, IT may support compliance with this rules e.g. a “privacy by design” approach. Thus,
IT developers should work very closely with lawyers in designing workable systems in e-commerce
that are compatible with relevant legal systems.
xvi
Full Papers
IADIS International Conference e-Commerce 2011
MEASURABLE PARAMETERS OF E-COMMERCE
SYSTEMS FOCUSED ON WEB INTERFACE
Petr Suchánek, Radim Dolák and Kateřina Slaninová
Silesian University in Opava, School of Business Administration in Karviná
Univerzitní náměstí 1934/3, Karviná, Czech Republic
ABSTRACT
E-commerce systems became essential for providing business in internet. E-commerce system model consists on several
components with appropriate functionality. The theory and practice show that the e-commerce system can be efficient
only, if its components are well defined, stable, and are working properly and optimally. Each of these components can
be considered as a system. The effective control and monitoring of the components can be provided due to the
appropriate definition of the component attributes. The main objective of this paper is to present a basic model of ecommerce system with focus on the web interface component. For this component, there is presented the definition of
key, especially measurable, indicators of website success and performance. The last part of the paper is oriented to the
case study, in which the definition of technical parameters of e-commerce system website using expert system NEST is
presented.
KEYWORDS
E-business, business intelligence, expert systems, measurable parameters, e-commerce, web interface
1. INTRODUCTION
E-commerce systems became a standard tool for business implementation. E-commerce systems are usually
large systems containing various subsystems. The theory and practice show that the e-commerce system as a
whole is successful, only if all the subsystems are working properly and optimally, and therefore the entire ecommerce system and its all parts have to be constantly monitored. The monitoring involves the
measurement of current values, which are then compared with expected values (planned values). The modern
enterprise needs to focus on the core elements that drive profitability and growth over the short, medium and
long term (IBIS ASOCIATES, 2010). In this context, the system values are measured continuously and are
taken as a source for calculations of other key indicators that are monitored at different periods. The basic
condition for the company access is a profit. Several resulting indicators are therefore related to the profit,
and generally, are related to return on investment (ROI). Within the e-commerce system, the individual
values are usually measured through the Internet (web sites) and are analyzed with the help of instruments
contained in the Customer Relationship Management (CRM) and Enerprise Resource Planning (ERP). The
indicator measurements can be performed with a wide range of instruments. In the first group we can include
web statistics systems and clickstream analytics tools such as Google analytics, ClickTracks, Gemius, Google
AdWords, Deep Log Analyzer, WebLog Expert, SawMill, LogAnalyzer, Web Log Explorer 3.21, Geo Log
Analyzer 1.48, Nihuo Web Log Analyzer 3.11, Advanced Web Statistics 7.0, AWStats, W3Perl and more;
the second group consists of tools contained in a number of CRM systems and in the third group we can
include special software tools, for example expert systems. The main objective of this paper is to present a
basic model of the e-commerce system, to define the key indicators of website success and performance, and
to present case study with the application of expert system NEST for parameter measurements of ecommerce system website.
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ISBN: 978-972-8939-51-9 © 2011 IADIS
2. E-COMMERCE SYSTEM
E-commerce system is an information system with its own architecture. The architecture of an information
system encompasses the hardware and software used to deliver the solution to the final consumer of services.
The architecture is a description of the design and contents of a computerized system (BURD, 2005). The
system architecture must be designed so that the whole system ensures the support for all key areas which
include: administration, finance, sales, production, planning, management, logistics, service delivery,
personnel, IS/IT, and security. Each key area is usually supported (or rather, is created) by one subsystem.
In some publications, for example (GARCIA; PATERNO; GIL, 2002), there is defined the e-commerce
system as only a web server that contains all the necessary functionality. This model can be considered only
as an elementary model presenting a basic communication interface between the user and the Web server.
The modeling of e-commerce systems can be done using process oriented, value-chain oriented or multiagent oriented approach. The main model of the e-commerce system based on the process-oriented approach
is shown for example in (RAJPUT, 2000). This model can be extended, so that we can define the main
components of the e-commerce system including customers, internet, web server (web interface), CRM,
ERP, LAN (Local Network Area), payment system, delivery of goods, after-delivery (after-sales) services,
and finally, information systems of cooperating suppliers and customers (see Figure 1).
Figure 1. E-commerce system
To achieve the efficiency of the whole e-commerce system, the all subsystems from which the system is
composed, must be efficient as well. The problem with one or more of shown e-commerce system
characteristics can have an adverse effect to companies´ business activities, and can be a cause of financial
loss. The significant emphasis should put on the functionality of the information system from the point of
view of its performance. This kind of approach can also be implemented in similar solutions to interactive
systems. (BUCKI, 2007) The entire e-commerce system, as well as all of its subsystems, can be described by
a number of parameters. Furthermore, consistently with the objectives of this paper, we consider only the key
indicators of website success and performance.
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IADIS International Conference e-Commerce 2011
3. KEY INDICATORS OF WEBSITE SUCCESS AND PERFORMANCE
There are number of indicators that can be measured and calculated (INAN 2010), and by which we can
make a description of the current e-commerce system performance. Within the e-commerce systems, the
measurement can be divided into the following types:
• Performance measurement - measurement of technical parameters (for example web page load time,
speed of processing user commands, speed reporting, etc.),
• Usability testing – usability testing is done in laboratory conditions (for experienced users are set
various tasks),
• Measurement of the success – measurement of the success should answer the question how the ecommerce system helps to meet the company objectives. Outcomes of this measurement are used primarily to
the system optimization and control.
Generally, the first step is to determine all the possible data sources. In the terms of the e-commerce
system, the source data can be divided into the following groups:
• Operational characteristics – on the web interface there are, for example, number of displayed web
pages, number of website visitors; in connection with the information system there can be, for example,
number of successfully completed transactions, number of failed transactions (may be associated with system
disturbances), etc.,
• Customer data – data relate primarily to the demographic characteristics of visitors and their preferences
(city listed in the order, city listed in the query or demand, gender of customer, etc.),
• Transactional data – data directly related to the sale of goods or services. These data are the basis for
financial analysis (e.g. average order value),
• Data from other sources - other data relating to consumer behavior in the website.
As mentioned above, in this article we are interested above all the measurable parameters that can be
measured through a Web interface (web technologies).
The first group of parameters includes the key indicators for the measurement of the e-commerce system
success. In this case, the input data are the number of days (time period), site visits (unique visits), number of
demands received from the web, number of orders received from the web, number of users who have made
an order, and data from CRM and ERP (amount of orders – revenue, margin orders).
Based on these input data, there can be made the calculations, from which we can obtain sales (total
orders), margin (after deduction of all costs), conversion ratio of demands, conversion ratio of orders,
average value per order, average returns per customer, average number of order per customer, average
margin of one order, average margin per customer, average returns per visit, average margin per demand, and
average margin per visit.
These indicators are used for the basic analysis and are very important for the management activities
related to the sale, planning and finance.
Web interface is usually a part of a CRM system that is connected with the ERP. CRM and ERP are the
information systems that are at the core of the enterprise informatics. The indicators from this group belongs
to the area of IS/IT. The basic indicators for the proper operation of the information system are: system
availability, average response time, breakdown intensity, breakdown rate, average download time, failure
rate.
The integral part of the enterprise information system is created by its users at the all levels of the
corporate activities, and in particular, of the management. Each user carries out various activities, while each
of them constitutes interference in the system. In this context, there are indicators that can be included in the
administrative field, partly in the area of security and personnel. In this group of indicators, there can be
included: number of correct user intervention, number of incorrect user intervention (for example, it may be
related to poor secure system, inappropriate user interface, incompetence users), number of system
administrator intervention (corrections system) and number of users involved in processing by one
commercial transaction.
Another important area is logistics. The logistics is a channel of the supply chain which adds the value
of time and place utility. The basic indicators tracked in this area are: product availability, number
of successfully delivered products, number of unsuccessfully delivered products (for example customer
entered incorrect address or error occurred at the side of vendor or carrier), average length of warranty
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ISBN: 978-972-8939-51-9 © 2011 IADIS
service, storage costs, cost to deliver goods, average delivery time of goods, number of cooperating suppliers
offering the same goods.
The Internet has allowed the development of the new methods of marketing that provide very important
information useful for the management support and the planning. In this area, the important key indicators
are: number of unique customers, average visit frequency, number of repeat customers, margin per customer,
number of first buyer, average sales per repeat customers, average order value per repeat customer, market
share, percentage share of new vs. returning visitors, average conversion rate, average time spent on the
website, average number of pages displayed per visit, percentage share of returns (one page visits), average
number of clicks on adverts. One of the key methods of e-marketing is campaign. For example, in the
campaigns we can trace percentage share of visits according to the type of campaign and percentage share of
conversion rate according to the type of campaign. These values are the basis for the determination of index
of campaign quality.
The e-commerce systems are implemented with a goal to expanse the sales channels, and thus to increase
the profits. In this context, the important general indicator is the return on investments (ROI). To calculate
ROI in the web projects, we can use, inter alia, an online calculator on the website. In this case, the source
data can include: number of days (time period), regular fixed cost (the cost of webhosting, salary, etc.), cost
per customer acquisition, the current daily visit site, the current conversion ratio of orders, the percentage
increase of conversion ratio due to investments, percentage increase of average order value due
to investments, estimated average order value increase after, the current average margins, the percentage
increase of average margins due to investment, and estimated average margin value increase after.
Using these data, we can calculate: number of visitors, number of orders, yields, margins, fixed costs,
direct cost of acquiring visitors, profit, profit per days, and return on initial investments.
4. EXPERT SYSTEMS
Expert systems are computer programs, designed to make available some of the skills of the expert to nonexperts. Since such programs attempt to emulate the thinking patterns of the expert, it is natural that the first
work was done in Artificial Intelligence (AI) circles (SILER, BUCKLEY, 2005).
4.1 Types of Expert Systems
For different purposes of decision making, the different types of the expert systems may be used. Therefore,
it is useful to be acquainted with some of the more commonly used expert system types (RAVINDRANATH,
2003), like Forecasting Systems, Trouble Shooting Type, Monitoring, Educational Expert System, or
Planning.
The expert systems can be built using expert system shells. In essence, these are the expert systems, from
which all domain-specific knowledge has been removed (CURTIS, COBHAM, 2008).
The expert system shells are ideal for creating of small and medium-sized expert systems. Shells are
empty expert systems without the knowledge base. The shell provides the tools for the expert knowledge
representation and the inference mechanism is used to derive the conclusions based on the rules applied
to the specified value input from the users.
In the past, the expert system shells have been difficult and demanding to use – requiring the considerable
expertise in the computer science to understand how to embody the specific enterprise. The advantage of the
object oriented programming languages, such as C++ and Java, has enabled the developers of expert systems
to conceptualize and built the shells to encapsulate and represent the specific domain (CHIOZZA, 2001).
There are several expert system shells – both commercial and Open Source – to assist with the
development of the application-specific expert system. There are known several popular C/C++ based
CLIPS, FuzzyCLIPS and Jess, as well as OpenExpert (FULCHER; JAIN, 2008). Other examples of the most
famous shells are Leonardo or XPertRule.
Rules are used to create the knowledge base of the expert system. There are many alternatives for
building the knowledge base. We can use production rules, association rules, boolean logic, fuzzy rules,
semantic network, or bayesian Networks.
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5. CASE STUDY: USING EXPERT SYSTEM NEST FOR MEASURING
PARAMETERS OF E-COMMERCE WEBSITE SYSTEMS
The expert systems can be applied in many areas. Analogous to the e-commerce sphere, such systems can be
used for example for the evaluation of e-commerce website performance by the measurable parameters and
also as input information with a certain degree of uncertainty. The analysis of the e-shop websites can be
done in consultation with the experts, who deal with the problem of the e-commerce. But faster and less
expensive should be the alternative to use the expert system that is based on specific measurable parameters
and capable on evaluating the performance of the e-shop.
5.1 Expert System NEST
NEST program is an empty expert system, which includes inference mechanism. NEST was developed at the
University of Economics in Prague, Czech Republic.
The program provides a graphical user interface (GUI) for: recording of existing knowledge bases, setting
the access processing of uncertainty, management consulting (how to obtain data from the user), the target
evaluation and recommendation statement with an explanation of the findings. NEST is the program
designed primarily for the academic purposes, which puts emphasis not only on the appearance, but also
to the functionality of the program aimed at creating a knowledge base, comparing the results of consultation
in the selection of various types of work with uncertainty, etc. (IVÁNEK et all, 2007).
NEST consists of the following components:
• Stand-alone version - a program for consultation,
• Editor - The editor for creating and editing knowledge bases,
• Base converter - a program to convert knowledge bases,
• Client-server version - Remote Access NEST - Network version.
Knowledge Base of NEST is represented by:
• Attributes and propositions,
• Rules,
• Contexts,
• Integrity constraints.
The most important is the usage of attributes, propositions and rules. There will be provided detailed
description of these elements in the next part of the paper.
The proposal of the evaluation process of the e-commerce web interface with technical parameters by the
expert system NEST:
• Definition of the key website technical parameters,
• Creation of the rules for the evaluation of the key website technical parameters,
• Assignment of the rules in the knowledge base of the expert system,
• Debugging of the knowledge base,
• Verification of the knowledge base based on the evaluation of real data.
Criteria for the evaluation of the e-commerce web interface technical parameters:
• Quality of available information,
• Clarity of texts and clarity buttons and links,
• Accessibility and functionality,
• Information quality downloadable documents,
• Speed of loading pages in a browser,
• Graphic processing,
• Position of key words in the search engines (Google, Bing etc.),
• Reference,
• Speed reporting,
• Level of security (username and password, email or mobile phone order confirmation),
• Correspond to the number of steps to create a binding order,
• Confirmation steps,
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• Legislative requirements for e-shop.
5.2 Creation of Knowledge Base in Expert System NEST
The most important factor for the quality of each expert system is a good knowledge base including
knowledge expressed by the different types of rules. To acquire the knowledge, there is extremely important
to cooperate with the expert knowledge engineer or to study relevant issues.
At first, we define the attributes and derive the propositions from attributes. Then, there can be defined
the rules, which are composed of the specified propositions. For each proposition, there will be allowed
to enter the weight value from the interval [-3; 3]. If the proposition is irrelevant, then enter the weight value
is zero or you can directly select the value of the word "irrelevant". In the
Figure 2 we can see the example of created attributes and propositions for position in the search engines:
Figure 2. Example of created attributes and propositions: Position in the search engines (NEST Editor)
Example of created attribute: Position in the search engines (declaration in XML)
<attribute>
<id>Position in the search engines </id>
<type>numeric</type>
<legal_values>
<lower_bound>0,000</lower_bound>
<upper_bound>100,000</upper_bound>
</legal_values>
<comment>Position of key words in the search engines</comment>
</attribute>
Attribute called Position in the search engines has these possible propositions:
• Excellent,
• Average,
• Below average,
• Poor.
It is not easy to clearly define sharp boundaries, which may indicate a position on search engines such as:
excellent, average, below average or poor. On the Erro! A origem da referência não foi encontrada.3 we
can see the application of the fuzzy intervals for these propositions, which are also supported in the expert
system NEST.
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Figure 3. Fuzzy Intervals for Position in the Search Engine
Example of proposition: Position in the search engines – excellent and average (declaration in
XML)
<proposition>
<id>excellent</id>
<name>Position in the search engines(excellent)</name>
<weight_function>
<fuzzy_lower_bound>1,000</fuzzy_lower_bound>
<crisp_lower_bound>1,000</crisp_lower_bound>
<crisp_upper_bound>8,000</crisp_upper_bound>
<fuzzy_upper_bound>10,000</fuzzy_upper_bound>
</weight_function>
<comment>Position of key words in the search engines</comment>
</proposition>
<proposition>
<id>average</id>
<name>Position in the search engines (average)</name>
<weight_function>
<fuzzy_lower_bound>8,000</fuzzy_lower_bound>
<crisp_lower_bound>10,000</crisp_lower_bound>
<crisp_upper_bound>14,000</crisp_upper_bound>
<fuzzy_upper_bound>16,000</fuzzy_upper_bound>
</weight_function>
<comment>Position of key words in the search engines</comment>
</proposition>
Example of established rule: Position of key words in the search engines (Google, Bing etc.)
IF Position in the search engines (excellent) THEN SEO Optimization (excellent) [2,500]
Example of question during consultation: Position of key words in the search engines
Find out what position of your site will be placed when entering certain key words in the search engines
(Google).
5.3 The Consultation Process
After creating the knowledge base, the issue of the web performance measurement can be consulted in the
NEST expert system. It is needed to record data of the knowledge base before the start of consultation. We
have created a sample knowledge base called Technical evaluation of website parameters. It is saved in xml
file format.
The next step is to set the consultations parameters: type of uncertainty (standard logic, neural network or
hybrid), priority rules (from the beginning to the end, minimum length, and maximum length, defined by an
expert), default weight (unknown, irrelevant), corresponding method (dialogue, dialogue with the
questionnaire, questionnaire responses from a file upload) and type of consultation (delay, no delay). Then,
the expert system asks questions and user replies to them. After that, there are derived the final results (goal
statements) based on the responses to the questions according to the knowledge base that contains knowledge
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in the form of the rules. We have defined these final results for the e-commerce system web interface
performance: excellent, average, below average or poor.
6. CONCLUSION
E-commerce system is an information system with its own architecture, which can be described using well
defined model. The entire e-commerce system, as well as all of its subsystems, can be described by a number
of parameters. The paper is oriented to one of the subsystems, to the web interface.
The case study deals with the technical parameters of the e-commerce system web interface using expert
system NEST. NEST is an empty expert system (expert system shell) for diagnostic applications based on
rules. The main advantage of the shell is possibility to create our own knowledge base. We have defined the
key website technical parameters, the rules for the evaluation the key website technical parameters.
Consequently we have created the knowledge base which can be used for qualified assessment of the ecommerce system web interface measurement. The expert system derives results based on the responses
received concerning the defined parameters of the e-commerce web interface technical parameters. As an
example we can point out the final results for the e-commerce system web interface performance: excellent,
average, below average or poor.
In the future, the knowledge base can be improved using the expert system NEST, or any other expert
system that supports the imposition of knowledge base using XML. It is intended, that this knowledge base
became a component of the e-commerce system model defined using multi-agent approach for the future
analysis of the e-commerce systems.
ACKNOWLEDGEMENT
This research has been supported by the project SGS/24/2010 - The Usage of BI and BPM Systems to
Efficiency Management Support of Silesian University in Opava, Czech Republic.
REFERENCES
Beynon-Davies P., 2004. E-Business. Palgrave, Basingstoke.
Bucki, R., 2007. Information Linguistic Systems. Parkland, Florida: Network Integrators Associates, pp. 102.
Burd, S. D., 2005. Systems Architecture. 5 edition. Course Technology, pp. 656.
Curtis, G. and Cobham, D., 2008. Business Information Systems: Analysis, Design and Practice. Pearson Education
Limited: Harlow.
Fulcher, J. and Jain, L. C., 2008. Computational intelligence: a compendium. Springer Berlin: Heidelberg.
Garcia, F. J. et al, 2002. An Adaptive e-Commerce System Definition. Springer Berlin: Heidelberg. pp. 505-509.
Chiozza, E. and Stanford-Smith, B., 2001. E-work and E-commerce: Novel solutions and practices for a global
metworked economy. IOS Press: Amsterdam 2001.
IBIS ASOCIATES. Key Performance Indicators. 2010. Available from: <http://www.ibisassoc.co.uk/ibis-services.htm>
[5 August 2010]
Inan, H., 2010. Meauring the Success of Your Website: A Customer Centric Approach to Website Measurement. Surry
Hills NSW, Australia.
Ivánek, J. et al, 2007. Znalostní inženýrství. OPF SU, Karviná.
Knight, K., 2007. Online shopping forecast: 323 billon euro by 2011. BizReport.
Rajput, W., 2000. E-Commerce Systems Architecture and Applications. Artech House Publishers, pp. 446.
Ravindranath, B., 2003. Decision Support Systems and Data Warehouses. New Age International Publishers: New Delhi
2003.
Siler, W. and Buckley, J.J., 2005. Fuzzy expert systems and fuzzy reasoning. Wiley & Sons: New Jersey.
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IADIS International Conference e-Commerce 2011
EVALUATING THE READINESS TO M-GOVERNMENT
IMPLEMENTATION IN BAHRAIN
Ahmed Sowaileh1 and Dr Ali AlSoufi2
1
Ministry of Justice, Bahrain
2
University of Bahrain
ABSTRACT
This study is an attempt to evaluate the readiness to m-government implementation in Bahrain in order to identify the
best approach to improve the ability of Bahrain’s governmental organizations to utilize the advantages of mobile and
wireless technologies and to exploit the high mobile phone penetration by providing high quality mobile government
services. This research involves the distribution of a questionnaire to IT professionals involved in the development and
support of e-government services in Bahrain’s government organizations. The results are used to identify the strength and
weakness points that affect the adoption of m-government by Bahrain’s government organizations. Based on the results,
this research provides recommendation to enable the governmental organizations to adopt and support m-government.
KEYWORDS
Bahrain m-government e-government readiness mobile wireless e-service
1. INTRODUCTION
E-government oriented technologies and services are advancing very quickly around the world and are being
used to improve governments’ fundamental functions (Jacobfeuerborn & Muraszkiewicz, 2009; Saxena,
2005). These functions are now spreading the use of mobile and wireless technologies and creating a new
direction: the mobile government (m-government) (Kushchu & Kuscu, 2003).
Kushchu & Kuscu (2003) define M-government as the strategy and its implementation involving the
utilization of all kinds of wireless and mobile technology, services, applications and devices for improving
benefits to the parties involved in e-government including citizens, businesses and all governmental units.
The number of people having access to mobile phones and mobile internet connection is increasing
rapidly (Botha & Van Deventer, 2009; Feldmann, 2003; Novay, 2009). The mobile access anywhere and
anytime is becoming a natural part of daily life (Jacobfeuerborn & Muraszkiewicz, 2009; Barton, Zhai, &
Cousins, 2006). M-government seems to have a substantial influence on the generation of set of complex
strategies and tools for e-government efforts and on their roles and functions (Roggenkamp, 2007). With the
continuous advancements in wireless technologies and the new opportunities to provide government services
through those technologies, m-government seems to be inevitable (Kushchu & Kuscu, 2003; Sadeh, 2002).
Mobile phone penetration in Bahrain is very high. By the end of September 2010, mobile phone
penetration rate in Bahrain reached about 126 per cent, with the number of mobile subscribers increased to
1.6 million. This rate has the potential to reach 164 per cent by the year 2012, and 177 percent by the year
2014 (BMI, 2008, BMI, 2010).
Bahrain’s main e-government channel is the web based eGovernment Portal. Since this channel is
accessed mainly through personal desktop computers, it will be referred to in this study as the PC portal to
distinguish it from the Mobile Portal channel. By the end of November 2010, there were more than 150
services on the PC Portal. The Mobile Portal is the channel that hosts services that are customized for access
through mobile phones. By the end of November, 2010 it hosted 45 services (EGovernment Authority, 2010).
Most of those services are informational.
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2. PROBLEM STATEMENT
Due to the advanced status of e-government and the high mobile phone penetration, there is a great
opportunity to utilize mobile technologies to improve the delivery of e-government services in Bahrain.
The utilization of mobile services in Bahrain is moving in slow pace relative to the development of
traditional services that are accessed through desktop computers. Most of the services are implemented on the
PC Portal first. Some of the informational and simple transactional services may have their way to the Mobile
Portal, but many of the more complex services that require large amount of data and involve complicated
transactions are more difficult to deliver as mobile services. Complex services that are easily provided
through the PC Portal may need more analysis and reengineering before they can be delivered as mobile
services (Olmstead, Peinel, & Tilsner, 2007).
This research is guided by the following research questions:
1- What are the factors that affect the readiness to m-government adoption by Bahrain’s government
organizations?
2- What is the status of each readiness factor in Bahrain’s government organizations?
The aim of the research questions is to evaluate the level of readiness of Bahrain’s governmental
organizations to implement m-government by identifying factors that can affect the readiness to the
implementation of m-government, and then to measure each factor to identify the strengths that should be
utilized, and the weaknesses that have to be overcome in order to improve the ability to adopt m-government
in Bahrain.
3. M-GOVERNMENT AS AN INNOVATION OF E-GOVERNMENT
The approach that this study follows is to treat m-government as an innovation of e-government where
wireless and mobile technologies, services, applications and devices are deployed to enhance e-government.
This approach is explained in more detail later in this paper.
To identify the factors that affect the adoption of m-government, this study attempts to utilize the
Diffusion of Innovations (DOI) theory developed by Everett Rogers (Rogers, 2003) to describe how, why,
and at what rate new ideas and technology spread through cultures. DOI has been used in diverse areas such
as business, marketing, anthropology, public health, and education (Couros, 2003).
Rogers (2003) defines an innovation as an "idea, practice, or object perceived as new by a unit of
adoption".
According to Rogers (2003) “getting a new idea adopted, even when it has obvious advantages, is
difficult. Many innovations require a lengthy period of many years from the time when they become available
to the time when they are widely adopted. Therefore, a common problem for many individuals and
organizations is how to speed up the rate of diffusion of an innovation”.
M-Government and e-Government are not two separate entities (Capra, Francalanci & Marinoni, 2007).
While e-Government encompasses usage of all technologies to deliver services to citizens and improve the
activities of the government and streamline their processes, m-government is an add-on to e-government
confined to the use of mobile technologies such as mobile phones, PDAs (Personal Digital Assistant), Wi-Fi
enabled devices, bluetooth and wireless networks in delivering e-government services (Ghyasi & Kuschu,
2004).
4. THE DIFFUSION OF INNOVATIONS THEORY (DOI)
Rogers (2003) defines an innovation as an "idea, practice, or object perceived as new by a unit of adoption".
Rogers theorized that innovations would spread through a community in an S-curve, as the early adopters
select the innovation first, followed by the majority, until a technology or innovation has reached its
saturation point in a community.
According to Rogers (2003) the following attributes affect the adoption of new innovations:
1- Relative advantage: the degree to which an advantage is perceived as better than the idea it
supersedes.
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2- Compatibility: the degree to which an innovation is perceived as being consistent with the existing
values, past experiences and needs of potential adopters.
3- Complexity: the degree to which an innovation is perceived as difficult to understand and use.
4- Trialability: the degree to which an innovation may be experimented with on a limited basis.
5- Observability: the degree to which the results of an innovation are visible to others. The easier it is for
individuals to see the results of an innovation, the more likely they are to adopt it.
6- Type of Innovation Decision: is the decision optional or mandatory?
7- Change Agent’s Promotion: the extent to which the change agent supports and promotes the adoption
of the new innovation.
In addition to the five characteristics of innovations derived by Rogers (1983), Moore and Benbasat
(1991) add Image as a further construct. Image refers to the degree to which the use of the innovation is seen
as enhancing to an individual’s image or social status. The adopters of m-government are the government
organizations, and they can be divided between the five categories identified by diffusion scholars.
Figure 1. show the conceptual model used by this research to evaluate the readiness to the adoption of mgovernment in Bahrain.
Change Agent’s
Promotion
Complexity
Compatibility
Relative
Advantage
Rate of
Adoption
Type of
Innovation
Decision
Trialability
Observability
Image
Figure 1. Conceptual model of the readiness to m-government (based on Rogers (2003) and Moore & Benbasat (1991)
4.1 Research Methodology
Fifteen senior IT experts working in governmental organizations in Bahrain were interviewed in order to
build clear understanding of the important issues related to m-government in Bahrain and to evaluate the
relevance of DOI and to refine the questionnaire to make it as relevant as possible to the case of Bahrain.
A Questionnaire based on the Diffusion of Innovations theory (Rogers, 2003) was used to collect the
primary data. The questionnaire consisted of two sections. The first section consisted of 5 questions to
identify the respondents’ demographics and organizational information. The second section contained 27
items to measure the readiness to m-government adoption. All of the items in the second section were
measured using a five-point Likert scale ranging from “Strongly Disagree” to “Strongly Agree”.
The dependent variable is the Rate of Adoption and it is represented by two variables, ADOPT and
ADOPT_INDEPENDENT. ADOPT measures the perceived readiness to the adoption of m-government.
Since most of the respondents are not managers, and to avoid having results that are merely influenced by the
respondents perception of their management, ADOPT_INDEPENDENT was included to measure the
perceived rate of adoption if the respondents had independent decisions to adopt m-government. Table 1 lists
the questionnaire items with the related variable names used in data analysis.
The survey population is IT professionals involved in the development and support of e-government
services in Bahrain’s government organizations. The number of IT professional was estimated to be about
300. This number was calculated by feedback from the government organizations indicating the number of
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their IT professionals who are involved in the e-government project. A pilot test that involved twenty
respondents was conducted to evaluate the effectiveness of the questionnaire. Based on the respondents’
comments and recommendations the questionnaire was refined and tested again to confirm its usability.
5. DATA ANALYSIS AND RESULTS
About 230 respondents participated in the survey. About 20 responses were discarded because they were
incomplete. About half of the respondents used the online version and the other half filled the printed copy.
In conformance with the needs of this research, different groups of ages, years of experience, job levels and
types of work were represented as shown in Table 1.
Table 1. Respondents' demographics
Gender
Male (71%)
Female (29%)
Age Groups
20 – 30 (45%)
31 – 40 (36%)
Over 40 (19%)
Years of Experience
1 – 3 (20%)
4 – 6 (25%)
7-9 (14%)
10 or more (41%)
Job Level
Manager (20%)
Supervisor (28%)
Non-management (52%)
Type of Work
Management (20%)
Programming (29%)
Sys Admin Sys analyst Tech Support
(14%)
(14%)
(23%)
Cronbach’s alpha (Cronbach, 1970) was used to assess the reliability of the survey. All of the variables
displayed acceptable reliabilities above or equal 0.700 (Table 3) which is in the range of good reliability
(Kaiser, 1974).
Factor analysis using Principal Component with Varimax rotation was used to evaluate the construct
validity of the survey. Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy showed a value of 0.754
which is in the range of good values indicating that factor analysis should yield distinct and reliable factors
(Kaiser, 1974). The Bartlett’s Test of Sphericity was significant (p < 0.001) indicating an appropriate factor
analysis (Table 2).
Table 2. KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of
Sampling Adequacy.
Bartlett's Test of
Sphericity
0.754
Approx. Chi-Square
Df
Sig.
1373.942
171
.000
All of the items loaded properly on the expected factors. However Image was loaded with Relative
Advantage and less highly with Type of Innovation Decision. However, Moore and Benbasat (1991) argue
that Image, although it is part of relative advantage, has a unique importance and can be studied separately.
Descriptive statistics was conducted to measure the level of each DOI attribute. Table 3 summarizes the
results of descriptive and reliability analysis of the questionnaire.
To identify the variables that had the greatest influence on the adoption of m-government, a stepwise
multiple regression analysis was conducted to find the relationship between the independent variables and the
two dependent variables (ADOPT and ADOPT_INDEPENDENT). The results identified the factors that
needed special attention in the development of the target model. The regression equations for both
independent variables were statistically significant (p < .001).
About 37% of the variance in ADOPT variable was explained by the variables DECSN,
CMPLX_MINUS, AGENT, IMG and COMPAT_EXP (R2 = 0.372). The following equation was derived
ADOPT = -0.279 + 0.343 DECSN + 0.204 CMPLX_MINUS + 0.252 AGENT + 0.190 IMG + 0.114
COMPAT_EXP
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About 34% of the variance in ADOPT_INDEPENDENT variable was explained by the variables IMG,
AGENT, CMPLX_MINUS, TRI_PILOT and OBSERV_EXPECT (R2 = 0.345). The following equation was
derived
ADOPT_INDEPENDENT = -0.209 + 0.357 IMG + 0.181 AGENT + 0.207 CMPLX_MINUS + 0.250
TRI_EXPECT + 0.132 OBSERV_EXPECT
Table 3. Descriptive and reliability statistics
Variable
Relative Advantage
Compatibility
Variable Name
RA
COMPAT_VAL (compatibility with values)
COMPAT_INFRA (infrastructure compatibility)
Cronbach
’s Alpha
.771
.791
COMPAT_EXP (experience)
Complexity
Type of Innovation
Decision
Trialability
Observability
Image
CMPLX_MINUS (larger values indicate smaller complexity)
DECSN
TRI_PILOT (advantage of having pilot projects)
TRI_ACCEPT (readiness to participate in pilot projects)
OBSERV_EXPECT (observability of current services)
OBSERV_EXIST (observability of future services)
IMG
Change Agent’s
Promotion
AGENT
Rate of Adoption
ADOPT
ADOPT_INDEPENDENT
Mean
4.12
3.84
3.37
3.32
.700
.732
.702
.811
2.91
3.31
3.84
3.66
3.50
2.94
4.05
3.41
3.46
3.88
6. DISCUSSION
The first research question was “What are the factors that affect the readiness to m-government adoption by
Bahrain’s government organizations?”
The factors were identified as Relative Advantage, Compatibility, Complexity, Trialability,
Observability, Image, Type of Innovation Decision and Change Agent’s Promotion.
The second research question was “What is the status of each readiness factor in Bahrain’s government
organizations?”
The readiness questionnaire was used to measure these factors. The factors that measured high
represented the strength points that should be utilized, and the factors that measured low represented the
weakness points that need to be improved.
Relative Advantage variable measured high in the survey indicating a high degree of awareness to the
advantages of mobile services. If this variable measured low, then a long preliminary stage to convince
Bahrain’s governmental organizations of the benefits of mobile services would be needed. The results
indicate that such a long stage can be bypassed or need little effort.
Compatibility with the existing values measured high with most of the respondents believed that
providing mobile services fits well with the way they like to deliver their organizations' services.
Compatibility with the existing ICT infrastructure and past experience differed from organization to another
based on the maturity of the hardware and software platforms and the availability of experienced IT
professionals in each organization. The overall results indicate that most organizations already have hardware
and software platforms that can be utilized or need to be upgraded to support mobile services. This reveals
the existence of a good IT infrastructure that should be upgraded and utilized to support m-government
instead of being rebuilt from scratch. The same can be concluded about the existing skills.
The results revealed that Complexity of the services was one of the major barriers to implementing
mobile services in Bahrain’s government organizations. Most of the organizations had services that required
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process reengineering before they can be implemented as mobile services. And most of them also had
services that cannot be implemented as fully mobile services. In addition, regression analysis revealed that
Complexity is one of the most important factors influencing the ability and willingness to implement mobile
services. As stated in this study, providing government services from start to finish through the interface of
the mobile phone is not as easy as providing them through the interface of the traditional desktop computer.
Tackling service complexity is one of the major tasks that should be conducted to improve the adoption of mgovernment.
Regarding Trialability, majority of the respondents believed that having pilot projects to build and test
mobile government services would be useful in the implementation of mobile services. The majority also
believed that their organizations can participate in such projects. This provides an opportunity to test the
development of mobile services with a number of selected government organizations before implementing
them on a major scale. Pilot projects can provide findings that are not known before conducting the projects
and identify barriers and problems that may occur during the real project. The early identification of such
problems can greatly reduce the risks and saves valuable time and resources (Hallin & Lundevall, 2007;
Bassara et Al., 2005). It is important in this regard to target innovative organizations in such pilot projects
(Rogers, 2003). As explained earlier, the adoption of innovations starts by innovators and has a domino effect
that makes it spread to early adopters and all the way to laggards
The measurement of Observability revealed moderate results. Slightly more than half of the respondents
believed that when a government organization introduces a new mobile service, other government
organizations will know about it, and only about one third of them indicated that they know enough about the
existing mobile services on the mobile portal. Investigation and interviews with government IT experts
revealed that there are efforts to advertise government services, but they don’t go beyond announcing and
celebrating the launch of new services. The introduction of new services does not ensure that citizens and
businesses will use them (Chatzinotas, Ntaliani, Karetsos & Costopoulou, 2006). The existing marketing
procedure should be revised and enhanced so that it provides more details about the services and persuade
customers to use them.
The results confirmed the importance of the Image factor. Majority of the respondents agreed that
providing mobile services can improve the image of their organizations and that top managements would
support mobile services if they know they can improve the image of their organizations. In addition,
regression analysis indicated that this factor is one of most important factors that influence the rate of mgovernment adoption.
Regarding Change Agent’s Promotion, almost half of the respondents were satisfied with the
performance of the eGovernment Authority (eGA) in supporting mobile services. And since regression
analysis revealed that this factor is one of the factors that have great influence on the adoption of mobile
services, it is important to investigate the reasons why the other half is not fully satisfied. As a change agent,
the eGA needs continuous self-assessment to ensure it delivers the best support to enable government
organizations to adopt m-government.
Regarding Type of Innovation Decision, top managements in the government organizations don’t
require the implementation and support of mobile services except for some informational and simple services
in some organizations. Mobile services still have lower priority than other systems, and it is not expected to
increase by much in the coming three years. However most of the top management’s are expected to support
mobile services if they get more time and resources. Regression analysis revealed that Type of Innovation
Decision have strong influence on the confidence of IT professional in the ability of their organization to
adopt m-government. Managers should be supported with the required resources and skills before they can be
convinced to implement and support mobile services.
The measurement of the Rate of Adoption revealed a moderate optimism in the government
organizations’ ability to adopt m-government. About half of the respondents believed that, in three years or
less, their organizations can support mobile service to the best possible extent (ADOPT). The other half did
not have the same optimism. Regression analysis indicates that the confidence in the organizations’ ability to
support m-government is affected by the Type of Innovation Decision, Complexity, Change Agents’
Promotion, Image and Compatibility with the existing experience (COMPAT_EXP).
Majority of the respondents believed that, in three years or less, they would seriously support the adoption
of mobile services if they had the decision (ADOPT_INDEPENENT). Regression analysis indicates that this
confidence is affected mainly by Image, Change Agents’ Promotion, Complexity, the perceived advantage
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IADIS International Conference e-Commerce 2011
of having pilot projects
(OBSERV_EXPECT).
(TRI_PILOT),
and
the
expected
Observability
of
future
services
7. CONCLUSION
The results revealed the points of strength that should be utilized and the points of weakness that need to be
fixed to enable Bahrain’s governmental organization to implement effective mobile services. Based on the
findings, this research recommends the following steps to enable government organization to adopt and
support m-government:
• Provide eGA guidance and support: As a change agent, the role of the eGovernment Authority (eGA) is
very important in the implementation and adoption of m-government.
• Support top managements and allocate more time and resource for mobile services.
• Involve innovative organizations: While all government organizations should participate in the
implementation of m-government, innovative organizations should be given a special role especially at the
first stages.
• Upgrade and utilize the existing infrastructure: There is an existing infrastructure that should not be
rebuilt from scratch. It should be upgraded and utilized to implement and support mobile services.
• Train and involve the existing skills
• Tackle services complexity: Service complexity should be tackled to enable better adoption of mgovernment.
• Conduct pilot projects: to explore the implementation of mobile services and to identify the
opportunities and challenges before implementing mobile services on a major scale.
• Market beyond service launch announcement: The existing marketing procedure should be revised and
enhanced so that it provides more details about the services and persuade customers to use them.
• Exploit the Image factor: The Image factor can persuade top management to heavily support MGovernment.
• Continuously assess the performance of the eGA and the governmental organizations: The eGA and the
government organizations should evaluate their performance constantly to ensure that they provide the best
support for M-Government. Self-assessment of organizations and services is an essential part of the adoption
of m-government (Coaker & Deans, 2007).
There is a great opportunity to enhance government services using mobile technologies and it should not
be wasted. The eGovernment Authority and the government organizations are invited to study the
recommendations of this research and utilize them to exploit the advantages of mobile technologies and the
high mobile phone penetration to the best possible extent.
REFERENCES
Barton, J. J., Zhai, S., & Cousins, S. B. (2006). Mobile Phones Will Become The Primary Personal Computing Devices.
Proceedings of the Seventh IEEE Workshop on Computing Systems & Applications, Washington, USA.
Bassara, A., Wisniewski, M., Zebrowski, P. (2005). USE-ME.GOV - Usability-driven open platform for mobile
government. Proceedings of Business Information Systems (BIS) 2005, Poznan, Poland.
BMI (2008). Bahrain Telecommunication Report Q3 2008. Business Monitor International .
BMI (2010). Bahrain Telecommunication Report Q4 2010. Business Monitor International .
Botha, A & Van Deventer, A. (2009). Mobile facilitation of science and technology awareness for preschool children.
Proceedings of mLife 2009 Conference & Exhibitions, Barcelona, Spain.
Capra, E., Francalanci, C., & Marinoni, C. (2007). Soft Success Factors for M-Government. In Kushchu, I. (ed.), Mobile
Government: An Emerging Directions in E-Government (pp. 106-133). Hershey PA: IGI Publishing.
Chatzinotas, S., Ntaliani, M., Karetsos, S., & Costopoulou, C. (2006) Securing m-government services: the case of
agroportal. Proceedings of the 2nd European Conference on Mobile Government, Brighton, UK.
Coaker, B., & Deans, D. (2007). An Evaluation of U.S. City Government Wireless Networks for Mobile Internet Access.
In Kushchu, I. (ed.), Mobile Government: An Emerging Directions in E-Government (pp. 357-374). Hershey PA: IGI
Publishing.
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Couros (2003). Innovation, Change Theory and the Acceptance of New Technologies - A Literature Review. Retrieved
April 12, 2009 from http://www.arp.sprnet.org/inserv/Teacher_Leadership/COMPS/change_theory.pdf
Cronbach, L. J. (1970). Essentials of psychological testing. New York: Harper & Row.
EGovernment Authority (2010). The eGovernment Portal. Retrieved December 1, 2010 from http://www.e.gov.bh/
Feldmann, V. (2003). Mobile overtakes Internet: Implications for Policy and Regulation. Telecommunication Policy
Consultant for the International Telecommunication Union (ITU) Strategy and Policy Unit (SPU). Retrieved
September 17, 2010, from http://www.itu.int/osg/spu/ni/mobileovertakes/Resources/Mobileovertakes_Paper.pdf
Ghyasi, A. , Kushchu, I. (2004). m-Government Adoption: Cases of Developing Countries, proceedings of European
conference on e-Government, Trinity College, Dublin, June 2004.
Hallin, A., & Lundevall, K. (2007). mCity- User Focused Development of Mobile Services within the City of Stockholm.
In Kushchu, I. (ed.), Mobile Government: An Emerging Directions in E-Government (pp. 12-29). Hershey PA: IGI
Publishing.
Jacobfeuerborn, B., & Muraszkiewicz, M. (2009). Can Mobile Networks Threaten Society and Culture?. Proceedings of
mLife 2009 Conference & Exhibitions, Barcelona, Spain.
Kaiser, H.F. (1974). An index of factorial simplicity. Psychometrika, 39, 31-36.
Kushchu, I. & Kuscu, H. (2003). From e-government to m-government: Facing the Inevitable. Proceeding of European
Conference on E-Government (ECEG 2003), Trinity College, Dublin.
Kwik Surveys. (2010), About Kwik Surveys. Retrieved December 11, 2010 from http://www.kwiksurveys.com/about.php
Moore, G. & Benbasat, I. (1991) Development of an instrument to measure the perceptions of adopting an information
technology innovation. Information Systems Research 2(3), 173-191.
Novay (2009). Future Workspaces - Four challenges for knowledge workers - Effects of working anytime, anywhere.
Retrieved September 18, 2010, from https://doc.novay.nl/dsweb/Get/Document-101561.
Olmstead, P. M., Peinel, G., Tilsner D., Abramowicz, W., Bassara, A., Filipowska, A., Wisniewski, M. & Zebrowski, P.
(2007). Usability Driven Open Platform for Mobile Government (USE-ME.GOV). In Kushchu, I. (ed.), Mobile
Government: An Emerging Directions in E-Government (pp. 30-59). Hershey PA: IGI Publishing.
Rogers, R.W. (1983). Diffusion of Innovations(3rd ed.) . New York: Free Press.
Rogers, E.M. (2003). Diffusion of innovations (5th ed.). New York: The Free Press.
Sadeh, N. (2002). M-commerce : technologies, services, and business models. New York: John Wiley & Sons, Inc.
Saxena, K.B.C. (2005). Towards excellence in e-governance. International Journal of Public Sector Management, 18 (6),
498-513.
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IADIS International Conference e-Commerce 2011
GENETIC ALGORITHM BASED OPTIMIZATION FOR
E-AUCTION
Mourad Ykhlef and Reem AlQifari
King Saud University
ABSTRACT
Double Auction is a type of auction where multiple buyers and sellers compete simultaneously; each one has a price and
quantity. Then, the Auctioneer tries to match buyers and sellers according to their bidding or asking prices and quantities.
The main concern in auctions is how to match them in a way to achieve the maximum profit in the market. The utility
function is used to represent each buyer and seller preferences. Recently, some evolutionary algorithms, such as Particle
Swarm Optimization and Genetic Algorithm, were proposed and have been applied to solve winner determination
problem in variant e-auction types. In this paper, in order to reduce the spent time and provide effective matches in
double auction, Genetic Algorithm has been introduced. The key contribution of this paper is to be the first research that
represent the problem in real-value chromosome and then apply the suitable GA operators. At the end, the results of the
proposed algorithm will prove the advantages of the GA.
KEYWORDS
Double Auction, Genetic Algorithm, Utility Function, Winner Determination Problem.
1. INTRODUCTION
INTERNET auctions appeared on the scene in the mid 1990s, and quickly became one of the most successful
applications of electronic commerce (Peter 2004). Auction is defined as a market mechanism for accepting
bids or offers from buyers or sellers and then used a set of rules to allocate goods. Double auction include
multiple sellers and multiple buyers in the same market where they are competing against each other for
different items (Jin, Hyunchul & Ingoo n.d.) (Rigi, Mohammadi & Delgir 2009).
In a multi unit double auction, each participant should determine how many units of an item and in which
price is his asks or bids. When a buyer’s bid exceeds or matches a seller’s ask, a trade will occur (Dickhaut &
Gjerstad 1998). There are two kinds of Double auctions: synchronous double auction (SDA) and
asynchronous double auction (ASDA) (Dickhaut & Gjerstad 1998). Discrete or continuous time of the
trading process is the main distinction between SDA and ASDA (Jin, Hyunchul & Ingoo n.d.).
The most important issue in a double auction is how to allocate or match buyer with seller to maximize
the rewards. This problem is known as winner determination problem (TEICH et al. 2003). The most
common mechanism that has been used is the utility function. The utility function is used to represent the
participants’ preferences. The previous researchers suggested linear (Huang, Scheller-Wolf & Sycara 2002),
quasi-linear, non-linear (Jin, Hyunchul & Ingoo 2008), or a fuzzy utility (Rigi, Mohammadi & Delgir 2009)
function. In the non-linear and fuzzy utility, the participant has the flexibility to change his preferences in
each round; while in other utility, the participants has identical utility (Jin, Hyunchul & Ingoo 2008) (Huang,
Scheller-Wolf & Sycara 2002).
This paper focuses on optimization for the winner determination problem using a non-linear utility
function that has been suggested (Jin, Hyunchul & Ingoo 2008).
Genetic Algorithm (GA), which is one of the evolutionary algorithms, can be used to solve the problem in
a short time (Goldberg 1989) (Mitchell 1998). A genetic algorithm has been proposed, in this paper, to solve
winner determination problem in a multi-unit double auction. The proposed algorithm concentrates on
decreasing the time and the computational costs with effective matches. Empirical experiments have been
conducted to validate the suggestion.
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The rest of the paper is organized as follows: Double Auction, Genetic Algorithm, and Utility Function
are defined in section 2, 3, and 4. the proposed approach of applying GA to Double Auction is described in
Section 5. Experimental results are reported in Section 6. At the end, the conclusion of this paper with future
work is presented in section 7.
2. DOUBLE AUCTION
Double Auction is referring to multiple buyers and sellers competing among each other. The double Auction
is divided into a single-unit double auction and a multi-unit double auction (Wang et al. 2010). In a multi-unit
double auction, there are many sellers’ bids prices and many buyers’ bids for variety of items with multi-unit.
Trade is occurred when the buyer’s bids is greater than the seller’s asks (Bichler et al. 2002) (Jin, Hyunchul
& Ingoo n.d.) (Rigi, Mohammadi & Delgir 2009) (Phelps, Sklar & Parsons 2003). Both seller and buyer have
to determine price and quantity for each specific item as the following:
Buyer → item, price, and quantity
Seller → item, price, and quantity
The auctioneer assigns buyers to sellers based on their preferences. There are many sellers’ asks that may
satisfy some buyers’ bids and vice versa (Jin, Hyunchul & Ingoo 2008), (Rigi, Mohammadi & Delgir 2009)
(Bichler et al. 2002) (Phelps, Sklar & Parsons 2003).
The auctioneer in the synchronous auction gets all bids in a preset period of time then makes the matches
and clear the market (Jin, Hyunchul & Ingoo 2008)- (Hu & Wellman 1998).
To solve the previous problem, finding the best representation of the utility function for each bidder is
required.
Most of the previous studies focus on two features of a double auction which are price and quantity. Thus,
they not include other performance factors such as quality, warranty, shipping time and cost.
3. GENETIC ALGORITHM
Darwin's theory about evolution has an impact on Genetic algorithms. Consequently, Solutions to such
problems that have been solved by genetic algorithms is evolving (Jin, Hyunchul & Ingoo 2008).
In the 1960s, John Holland invented Genetic algorithms (GAs), and in the 1960s and the 1970s, Holland,
his students and colleagues at the University of Michigan developed GAs (Holland. 1992) (Mitchell 1998).
Genetic algorithms can be defined as a particular class of evolutionary algorithms that use techniques
inspired by evolutionary biology such as inheritance, mutation, selection, and crossover.
Algorithm starts with a set of random solutions. These solutions are represented as chromosomes that
called population. Forming a new population is driven from previous populations, hoping that the new
population will be better than the old one. Solutions which are selected to form new solutions (offspring) are
elected according to their fitness. This is repeated until stop condition (for example number of populations) is
reached.
In genetic algorithms, the term chromosome usually refers to a candidate solution for a problem that is
often encoded as a bit string. The "genes" is a part of chromosome. An allele is the gene’s value. Crossover
typically consists of exchanging genes between two single chromosomes (parents). Mutation is usually
flipping the bit at randomly chosen genes. In addition, The GA requires a fitness function which assigns a
score to each chromosome in the current population (Mitchell 1998).
4. UTILITY FUNCTION
In a double auction the trade prices is not the ideal for both sellers and buyers. The problem here is how to
achieve the best profit for all sellers and buyers according to their bids and predefined quantities.
This can be achieved through utility mechanism, meaning the gain of bidders in the auction process. The
highest utility of the seller is when it matches the highest bid price of buyers while the highest utility for
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IADIS International Conference e-Commerce 2011
buyers will be achieved when buyers get matched with the lowest bid price of sellers. Accordingly, to design
an efficient auction, the utility should be maximized (Jin, Hyunchul & Ingoo 2008).
The linear utility function that can be solved as a linear programming problem to find the optimal solution
was proposed by (Huang, Scheller-Wolf & Sycara 2002). They represented the utility as the following linear
equation (Huang, Scheller-Wolf & Sycara 2002):
Where
m
total number of sellers
n
total number of buyers
k
total number of items
price of item a traded between seller i and buyer j
quantity of item a traded between seller i and buyer j
buyer i’s willingness to receive (the minimum acceptable sell price) for item a
seller i’s willingness to pay (the maximum accept able buy price) for item a
trader i’s maximum acceptable quantity for item a
S
set of sellers, in which there are |S|= m sellers
B
set of buyers, in which there are |B|= n buyers.
a non-linear utility function is used (Jin, Hyunchul & Ingoo 2008). They suggest that each bidder has his
own utility function. Therefore, the bidder can specify his sensitivity or the range of acceptance for each
feature (price and quantity). It is shown as the following equation:
We can see that the price and the quantity have been replaced with functions. They suggest two types of
functions: the Early-growth-style and the late-growth style based on a bidder’s choice (Jin, Hyunchul &
Ingoo 2008). In Early–growth style the bidder has the most influence in changing the price or quantity.
4.1 Early-growth Style
Early-growth equations is illustrated as follows: (Jin, Hyunchul & Ingoo 2008)
Price:
Seller Quantity:
Buyer Quantity:
4.2 Late-growth Style
Late-growth equations is illustrated as follows: (Jin, Hyunchul & Ingoo 2008)
Price:
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Seller Quantity:
Buyer Quantity:
t represents number of steepness.
5. SOLVING WINNER DETERMINATION PROBLEM IN DOUBLE
AUCTION
In this section, several issues related to applying Genetic Algorithm (GA) for Winner Determination Problem
in Double Auction (GA-WDPDA) will be discussed. The discussion is about the GA that has been
developed in this paper with its representations, chromosomes, fitness evaluation and the details of its
algorithmic structure.
5.1 Chromosome
While the chromosome represents a solution, the chromosome in a double auction winner determination
problem (WDP) represents all the winners with prices and quantities of their winning bids. In a double
auction WDP, the size of chromosome is determined based on the number of possible matches. The
following table illustrates the chromosome structure which contains price and quantity that belong to each
match.
Table I Chromosome Structure
Price
Quantity
Now, the question is what is the best chromosome representation?
5.1.2 Representation
There are many types of encoding that can be chosen such as: binary encodings (Buer & Pankratz 2010),
which is the most common type; many−character; real−valued encodings (Movaghar & Khanpour 2006); and
integer encoding (Mitchell 1998). Chromosomes representation became an issue for different structures of
WDP based on the auction type. There are many alternatives to represent a chromosome based on other
problem domains.
To decide which one is the best representation for solving double auction problem, David Goldberg in his
1989 textbook (Goldberg 1989) recommends that the appropriate choice of genetic representation depends
on the problem. According to that, real-valued representation will be chosen because it is the suitable one
with constrained optimization problem.
For example: Let’s say that there are three buyers, three sellers, and two items. Table 2 illustrates the
chromosome.
5.2 Genetic Operator
The chromosome represents offspring of the existing population. This section describes three operators of
Genetic Algorithms that have been used in (GA-WDPDA): selection, crossover and mutation.
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IADIS International Conference e-Commerce 2011
Table II Chromosome
P
13
Q
6
P
12
Q
4
P
15
Q
3
P
10
Q
3
P
11
Q
2
5.2.1 Selection
Varity of techniques can be used by a Genetic Algorithm for selecting the chromosomes to be copied over
into a new population. In (GA-WDPDA), Elitism has been used which means that some of the best
chromosomes will be copied to the next population as it is without changes (Mitchell 1998).
5.2.2 Crossover
Crossover works to combine two or more solutions to create new one (i.e. offspring). It is used in a way to
come up with possibly better solutions. In most crossover operators, selecting chromosome for crossing over
is based on a probability pc known as crossover probability. In (GA-WDPDA), uniform crossover operation
has been used; crossover can be applied as shown in Figure 1.
Figure 1. Crossover Operator
5.2.3 Mutation
In the mutation, one or more genes value of a selected chromosome will be altered randomly. The mutation
is used to increase the variability of the population. Also, it ensures that every point in the search space will
be reached. There are many mutation operators that depend on the problem and the representation type. In
real-value encoding, the mutation could be done by adding or subtracting a small number to a selected genes
(Mitchell 1998). The mutation can be applied as illustrated in figure 2.
Figure 2. Mutation Operator
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5.3 Fitness Function
The fitness function is used to measure the performance of the chromosomes. It is calculated for each
chromosome by using the non-linear utility function (Mitchell 1998).
5.4 Termination
Reaching the maximum generation number could be used as termination condition. At the end, the best
chromosomes of the last iteration are considered the best solution or the best price and quantity for each
match.
5.5 GA for Winner Determination Problem in Double Auction
This section presents the algorithmic structure of GA that has been produced. GA optimizer has been used to
match traders. (GA-WDPDA) will work as the flowchart shown in Figure 3.
Figure 3. (GA-WDPDA)
6. EXPEREMENTS RESULTS
This section presents an experiment conducted on GA to test its performance. (GA-WDPDA) has been tested
with different scenarios through different number of buyers, sellers and items. (GA-WDPDA) has been
implemented using Java on Inter® Core™ 2 Duo 3 GHz computer with 4 GB RAM, running with Microsoft
Windows 7.For the controlling parameters of the GA, the crossover and mutation rates are set at 70% and
10%. During the experiments all biddings, items, population size, and generation were given by a user.
The output of this experiment is a chromosome that represents the most suitable solution; For example,
there are three buyers, three sellers and two items, and their biddings are shown in the Table III. The output
solution will be as shown in Table 6. Two experiments have been conducted in order to test the speed and
fitness of (GA-WDPDA). First experiment set the population to 20 and the generation of [20...200]. The
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IADIS International Conference e-Commerce 2011
second set the generation to 20 and the population of [20...200]. Both experiments have used the same inputs
which are seller matrix, buyer matrix and item vector.
Table 5. Input Scenario
Table 6. (GA-WDPDA) Output
The first experiment, as we can see in Figure 4, shows the spent time, in mille-seconds. In addition, the
second experiment, as shown in Figure 5, shows the utility (best fitness) of the final results of GA.
GA experiments illustrate how time will increase according to the increase of the generation or
population. Consequently, comparing the two experiments, as shown in Figure 4, GA algorithm takes less
time when increasing the population rather than when the generation is increased. In contrast, the bidders’
utility (best fitness) will increase when the populations increase more than when the generation is increased.
Based on these results, we can conclude that the size of population and generation should be
compromised in order to get better results.
Figure 4. The Effect on Time by Altering Population/Generation Size
Figure 5. The Effect on Average Fitness by Altering Population/Generation Size
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7. CONCLUSION
In this paper, a Genetic Based Algorithm has been proposed to solve winner determination problem in a
multi-unit double auction with a non-linear utility. The proposed solution is focusing on maximizing all
traders’ utility through optimization modeling based on genetic algorithm paradigm. At the end of each
round, the auctioneer gathers all participants’ biddings and then uses these data to execute the GA in order to
find an effective solution for participants. Experimental results demonstrated that this proposal has, as a
feature, high performance concerning the time of execution.
In the future, we will try to improve the performance of GA in a way to achieve better solution in less
time. We will reach that by doing some kind of hybridization genetic with other algorithms perhaps PSO or
better.
REFERENCES
Book
Goldberg, D., 1989, Genetic Algorithms, Addison Wesley.
Mitchell, M., 1998, An Introduction to Genetic Algorithm, MIT Press.
Holland., J 1992, Adaptation in Natural and Artificial, 2nd edn, MIT Press, Ann Arbor.
Journal
Buer, T & Pankratz, G 2010, 'Solving a bi-objective winner determination problem in a transportation procurement
auction', Logistics Research, vol 2, pp. 65-78.
Dickhaut, J & Gjerstad, S 1998, 'Price Formation in Double Auctions', Games and Economic Behavior, vol 20, no. 8, pp.
1-29.
Conference paper or contributed volume
Bichler, M, Kalagnanam, J, Lee, HS & Lee, J 2002, 'Winner Determination Algorithms For Electronic Auctions: A
Framework Design', In E-Commerce And Web Technologies, Springer Berlin / Heidelbergr, France.
Huang, P, Scheller-Wolf, A & Sycara, K 2002, 'Design Of A Multi-Unit Double Auction E-Market', Computational
Intelligence.
Hu, J & Wellman, MP 1998, 'Online Learning About Other Agents In A Dynamic Multiagent System', Autonomous
Agents Conference, New York.
Jin, CH, Hyunchul, A & Ingoo, H 2008, 'Utility-Based Double Auction Mechanism Using Genetic Algorithms', Expert
Systems With Applications.
Peter, WR 2004, 'Online Auction Site Management', In The Internet Encyclopedia, John Wiley & Sons, Inc.
Phelps, S, Sklar, E & Parsons, S 2003, 'Using Genetic Programming To Optimise Pricing Rules For A Double Auction
Market', Proceedings Of The Workshop On Agents For Electronic Commerce, Pittsburgh.
Rigi, M, Mohammadi, S & Delgir, M 2009, 'Designing Fuzzy Utility-Based Double Auctions Using Particle Swarm
Optimization Algorithm', IIT'09 Proceedings Of The 6th International Conference On Innovations In Information
Technology , Al Ain.
Teich, Je, Wallenius, H, Wallenius, J & Koppius, Or 2003, 'Emerging Multiple Issue E-Auctions', Erasmus Research
Institute Of Management Report.
Wang, X, Wang, X, Yi, M, Tan, Z & Huang, M 2010, 'A Double Auction Method For Resource Management And
Bidding Strategy On Grid Resources', IEEE Fourth International Conference On Genetic And Evolutionary
Computing.
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IADIS International Conference e-Commerce 2011
AN EXAMINATION OF THE CONTENTS OF PRIVACY
POLICIES ON THE AUSTRALIAN LOCAL GOVERNMENT
WEBSITES
Qiuyan Fan
University of Western Sydney, Australia
ABSTRACT
With ever increasing levels of government information and services moving online and the level of citizen data being
collected via government web sites, users are concerned about how their personal information will be collected, used and
secured. Privacy is viewed as a primary concern for e-government websites. While there are considerable studies on
consumer online privacy concerns in the research literature, few studies have focused on the privacy issues of the
constituencies of local e-government. This paper attempts to address this lack by examining the contents of privacy
policies published on the Australian local e-government sites using a content analysis approach.The research is
committed to online privacy protection with a focus on privacy policies posted on the local councils’ websites in the
GWS region, Australia.
To examine and assess how the local government authorities address online privacy issues and their degree of compliance
with legislation, this study attempts to analyse the posted privacy statements of the local government websites against the
legal mandates under which the web sites operate and identify and discuss non legal factors that may affect the quality of
these statements.
The research findings show that 43% of the websites surveyed do not display a privacy policy statement while 36%
appear to have a weak policy statement. Serious deficiencies in relation to the collection, access, amendment, use and
disclosure of personal data were found in the privacy policy statements examined. Widespread non-compliance with the
legislation indicates that the privacy statements are not effective in protecting user privacy online.
In addition to compliance with the legislation, the aspects of transparency, readability and detailed information are seen
as important for a desirable privacy policy. The lack of details, clarity and transparency in privacy policy statements
prevents users from understanding the content and potential issues in submitting their personal data. The results of the
analysis indicate attempts to display and develop an effective privacy policy have not been made by the vast majority of
the websites examined
The analyses can be used as guidelines in ensuring that an organisation’s website privacy policy is in compliance with
privacy legislation. The discussion on weakness in current privacy policy practices provides information that can guide
government authorities when they prepare for privacy policy statements for their websites.
KEYWORDS
Privacy, e-government, Australian local government websites, the privacy and personal information protection act,
privacy policy statement.
1. INTRODUCTION
Over the last decade the development of e-government initiatives has experienced substantial growth.
However, privacy concerns can limit this growth as citizens may view these initiatives as invasion of citizen
privacy by government (Belanger & Hiller 2006). A number of surveys reported that consumer concern with
privacy of information was preventing them from using websites (Green et al, 1998, Harris, 2001 & Pew
Internet, 2000).
With ever increasing levels of government information and services moving online and the level of
citizen data being collected via government websites, users of websites seem to be increasingly concerned
about their lack of control over their personal information. Privacy concerns have negative impact on
consumer online behaviour (Nemdi & Dyke, 2009). Privacy increasingly becomes a key issue that must be
addressed. Privacy and security commitments in e-government are reflected in a privacy policy displayed on
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the web site.There is evidence that the presence of a privacy statement on a web site has a positive influence
on perceived control over information privacy (Arcand et al (2007). A privacy policy plays an important role
in building trust in the online environment (OECD 2003). While there are considerable studies on consumer
online privacy and security concerns in the research literature (Hoffman et al, 1999; Earp et al, 2005; Nemati
& Dyke, 2009), few studies have focused on the privacy and security issues of the constituencies of local egovernment. This paper attempts to address this lack by examining the privacy policies published on the
Australian local e-government sites using a content analysis approach.
The remainder of this paper is structured as follows: Section 2 provides an overview of privacy and trust.
Section 3 reviews data privacy protection legislations and guidelines at both international and national level.
Section 4 and 5 introduces research context and methodology respectively. Section 6 analyses and discusses
principally the results from the research. Section 7 discusses the limitation of this study and further research.
Section 8 concludes the paper.
2. AN OVERVIEW OF PRIVACY, PRIVACY STATEMENT AND TRUST
Brandeis and Warren (1890) define privacy as the right to be left alone while Shoeman (1984, cited in
Arcand et al 2007) argues that privacy is a state or condition of limited access to individuals. Clarke (2011)
defines information privacy as the claim that personal identifiable information should not be available to
other individuals or organizations and the individual should have secondary control of the data and its use.
There are many dimensions of privacy. Hoffman et al (1999) focus on two dimensions of environmental
control and secondary use of information control and they argue that consumer’s ability to control the actions
of a web site and the use of their personal information directly affects consumer perception of security and
privacy online. The most relevant to this study is personal data protection. For the purpose of this research,
privacy is defined as the ability of an individual to control the collection of personal information and the
secondary use of whatever information that is collected about them (Schwaig, et al, 2006).
Nemdi and Dyke (2009) defined a privacy statement as ‘a formal declaration of privacy policies that is
accessible to the consumer’. Anett, et al (2009) argue ‘the best way to control information security is through
formal policy.’ A privacy policy statement deals with the collection, use, access and disclosure of personal
information. It reassures website users that you will respect their privacy and protect them from loss and
misuse and from unauthorized access, alteration/modification or disclosure of their personal information
when they use your website. Clearly an effective privacy policy statement plays an important part in reducing
privacy concerns in online environment. Many researchers suggest that the presence of a clear privacy
statement have a positive impact on consumer trust (Arcand, et al., 2007, Earp, et al., 2005). Nemati and
Dyke (2009) state that an effective way to increase user trust appears to include a privacy policy statement on
a website. Privacy has a strong influence on the level of trust an individual has with a web site and an
individual’s attitudes and perceptions regarding privacy and security have an influence on his or her
behavioural intentions to participate in an online transaction (Liu et al, 2005). There is evidence that
consumers consider the privacy disclosure an important factor in building trust (Aljukhadar, et al, 2010).
Privacy protection is a prerequisite to build trust (Liu et al, 2005).To earn trust, it has become common
practice for web sites to display a privacy statement to inform user about data handling practices (Pollach,
2007).
3. LEGISLATION PROTECTION OF INFORMATION PRIVACY
Governments and international organisations have developed laws, regulations and guidelines that govern the
collection, control, storage, use, dissemination, and destruction of personal information to secure privacy
right and attempted to formulate privacy policies based on legal principles (Whitman & Mattord, 2011). For
instances, Fair Information Practices (FIPs) are international principles that serve as the basis for the privacy
policies of many countries (Nemati & Dyke, 2009). The FIPs defines Notice, Choice, Access,
Security/Integrity, and Enforcement as five key principles of a desirable privacy policy. The Organization for
Economic Cooperation and Development (OECD) issued the Guidelines on the protection of privacy and
trans-border flows of personal data in 1980, which established eight principles including collection
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limitation, data quality, purpose specification, use limitation, security safeguards, openness, individual
participation and accountability. While they are not legally binding, the OECD guidelines are the global
standard for privacy protection and are recognized by all OECD member countries (Earp et al 2005).
In Australia a variety of federal, State and Territory Acts contains privacy protection provisions relevant
to the collection, use, disclosure, quality and security of personal information about individuals. For instance,
the federal Privacy Act 1988 provides 11 Information Privacy Principles (IPPs) for the federal public sector
and 10 National Privacy Principles (NPPs) for private sector organisations. Given the federal Privacy Act
1988 does not apply to State/Territory government agencies (except for A.C.T.), several State and Territory
Parliaments have enacted their own privacy legislation in relation to their own public sectors. For instance,
the Privacy and Personal Information Protection Act 1998 is the principal piece of legislation providing
protection of personal information for the public sector in the state of New South Wealth (NSW). The
Privacy and Personal Information Protection Act (PPIPA) 1998 deals with how all New South Wales public
sector agencies manage personal information. The Act sets out 12 Information Protection Principles (IPPs),
which apply to State and local government bodies of NSW. Those Information Protection Principals include:
Principle 1 - Collection of personal information for lawful purposes
Principle 2 - Collection of personal information directly from the individual
Principle 3 – Requirements when collecting personal information
Principle 4 – Other requirements relating to collection of personal information
Principle 5 - Retention and security of personal information
Principle 6 – Information about personal information held by agencies
Principle 7 – Access to personal information held by agencies
Principle 8 – Alteration of personal information
Principle 9 – Agency must check accuracy of personal information before use
Principle 10 – Limits on use of personal information
Principle 11 – Limits on disclosure of personal information
Principle 12 – Special restrictions on disclosure of personal information
(Source: Office of the Privacy Commissioner, 1998)
The local councils surveyed in this study are bound by the PPIPA. In order to comply with the
requirements of this Act, Council will comply with Information Protection Principles (IPPs) in relation to its
handling of personal information.
4. RESEARCH CONTEXT
This research is committed to online privacy protection with a focus on privacy policies on local councils’
websites in the GWS region. The rationale for selecting Greater Western Sydney (GWS) is based on a
number of factors. The e-government literature suggests a positive relationship between population and
strong economy and e-governance capacity at the local level. GWS is a large and dynamic region, which has
experienced strong urban and population growth. GWS has a population of about 1.9 million, which is 43%
of the Sydney metropolitan and is estimated to reach 2.5 million by 2031. The GWS’total GRP (a Gross
Regional Product) represented over one third of the Sydney GRP and over one fifth of the NSW Gross State
Product (GSP).
One of the great strengths of local government in GWS is its diversity. The population and geographic
size of councils differ greatly. There are 14 Local Government Authorities in the GWS areas. All of the local
authorities have their own government websites where the users can register for council services, to make a
request, and to apply for permits as well as to use library service online, and the governments are able to
respond electronically with users. 78.6% of the local councils are offering online submission of service
request or online application for permits via downloadable application forms on the websites (Fan 2009).
7.1% of the local government websites are offering online access to development applications (DA) which
allow residents to track the progress of the application from lodgement through to determination (Fan, 2009).
14.3% of the councils have Internet payment systems available on their websites where users can pay rates
and fees directly through council’s online payment services, while 85.7% provide a link to third party
transactional services such as BPAY and Postbillpay (Fan 2009). These online services allow the councils to
collect the personal information of the residents via their websites, which can increase some serious privacy
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concerns among users. However, there has been little research into how local government web sites protect
citizen’s personal information.
5. RESEARCH OBJECTIVES AND METHODOLOGY
The OECD guidance on policy and practice recommends that the privacy statement should accurately reflect
your organisation’s personal data practices, comply with applicable national, regional and international laws
and read smoothly (OECD 2003). Sumeeth, et al. (2009, p.93) argue ‘privacy policies are examined for their
coherence, readability and information they convey to users.’ Although Compliance with legal principles is
considered the key factor in assessing quality content of a privacy policy statement, other factors cannot be
ignored.
The primary objectives of this study are to examine the posted privacy statements of local government
websites against the legal mandates under which the web sites operate and identify and discuss non legal
aspects that affect the quality of these statements.
To examine and assess how local government addresses personal information privacy issue and their
degree of compliance with the IPPs of the PPIPA, this research systematically identify and record the privacy
policy statements posted at the 14 local government sites and then analyse what privacy measures are stated
in these statements on the local government web sites. The researcher read the privacy statements in their
entirety. Content analysis has been carried out to scrutinize the contents of privacy statements on the local
government websites.
To achieve the research objective, this study attempts to conduct two separate analyses. The first one is
focusing on compliance with the IPPs of the PPIPA. The PPIPA has extensive coverage of privacy issues and
governs the way in which public and private sector organisations collect, use, disclose, store, secure and
dispose of personal information. The 12 IPP categories were used in coding during the content analysis
process. This analysis aimed at determining whether the contents of privacy statements on the local council
websites conform to the IPPs contained in the PPIPA. The second one goes beyond the minimum legal
requirements expressed in the existing laws and policies on data privacy protection in Australia. It looks at
some non legal factors such as existence, transparency, details, clarity and readability that may affect the
effectiveness of a privacy policy statement. This analysis aims at identifying and discussing weakness in the
privacy policy statements posted on the web sites.
6. DATA ANALYSIS AND FINDINGS
6.1 An Overview of the Results
Privacy is viewed as a primary concern for e-government websites. However, few of the websites surveyed
have an explicit and comprehensive privacy statement. Six out of 14 websites provide no privacy statement.
While 3 provide a reasonable privacy policy statement, 5 present very limited and vague privacy policy
statements.
6.2 How do the Privacy Statements on the Websites Comply with the IPPs of
the PPIPA?
The discussion in this section follows the IPPs contained in the PPIPA.
Data collection and purpose specification
Principles 1 to 4 of the PPIPA specify requirements when collecting personal data. For instances, personal
data should be collected lawfully (Principle 1) and directly from individual (Principle 2). The purpose for
which personal data are collected should be specified (Principle 3) and the information collected should be
relevant to that purpose, not excessive and accurate, up-to-date and complete (Principle 4).
Only three local government web sites make an attempt to comply with these principles of the PPIPA.
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Five out of 8 available privacy policy statements fail to provide any information regarding the collection of
personal data and purpose for data collection.
Retention and security of personal data
Principle 5 requires councils to secure personal data collected from users against loss or any form of
illegal or unauthorised use and access. However, only one council website indicates they will take reasonable
steps to protect personal information from misuse, loss and unauthorised access but they cannot guarantee
security. 93% of the local government websites failed to provide a privacy statement that has any security
measures in place to protect personal data while it is being stored on or transmitted across the Internet.
To comply with this principle, a council must ensure that the personal information is kept for no longer
than is necessary for the purposes for which the information may lawfully be used and is disposed of securely
and in accordance with any requirements for the retention and disposal of personal information. Only two
privacy policy statements indicate how the councils dispose of the personal information they hold.
Information about personal information held by councils
Principle 6 requires a council to take reasonable steps to enable a person to determine if the council holds
personal information relating to that person. Only one council’s website indicates that a visitor can find out if
the councils are keeping personal data about him or her.
Access and amendment of personal information
Principle 7 requires Council to give individuals access to personal information about them while Principle
8 gives individuals right to update or amend personal information. Only one privacy statement indicates how
a visitor can access to the personal data about him or her and update and amend the information that the
council is holding.
Data quality
Principle 9 requires council to check accuracy of personal information before use to ensure that the
personal data council has recorded is accurate, complete and kept up-to-date. Only two council’s website
privacy statements were found to be in compliance with this principle.
Use and disclosure of personal information
Principle 10 specifies limits on use of personal information while Principles 11 and 12 state restrictions
on disclosure of personal information. To comply with these principles, personal data should not be used for
a purpose other than that for which it was collected unless the individual concerned has consented to the use
of the information for that other purpose. A council that holds personal information must not disclose the
information to third parties unless the disclosure is directly related to the purpose for which the personal
information was collected or necessary to prevent a serious threat to the life or health of the individual
concerned or another person. Any such data should be disclosed with the knowledge or consent of the data
subject.
Three privacy policy statements indicate that the personal data the council is holding will be used for a
purpose for which is was collected but among them only 2 privacy policy statements clearly state that the
councils will not disclose your personal information to any other person or organisation without your consent
or the disclosure of your personal information is legally required.
Although 57% of the local councils have added privacy statements to their websites, the great majority of
the privacy policy statements examined were found to have a wide array of deficiencies in relation to the
collection, use, access and disclosure of personal information. The councils are bound by the PPIPA. The
privacy policy statements published on their website should be in compliance with the IPPs to the extent
required by the PPIPA. However, compliance with the legal principles is found to be poor in this study.
6.3 Identifying and Discussing Weaknesses in the Privacy Statements
In addition to compliance with the legal principles, there are some other factors that cannot be ignored by
websites or online government service providers. The discussion in this section focuses on the non legal
factors that may affect the effectiveness of privacy policy statements.
Existence
For any local government bodies going online, a privacy policy statement is a must and adherence to
them is expected. The formation of a meaningful privacy policy statement is an essential first step to create a
positive image of what you are doing with online privacy protection (Clarke, 2011). Milne and Culnan (2002)
argue ‘while having a privacy policy does not guarantee that the organisation observes fair information
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practices, absence of a privacy policy is an indicator of a failure to observe the most basic fair information
practice principle’. In Australia, the Office of the Privacy Commissioner (2006) suggests that all
organizations should develop and display a privacy policy in an attempt to reduce privacy concerns.
However, some organizations are rather reactive about online privacy protection. The results of this research
are not promising. Of 14 local e-government sites, 6 websites have not added a privacy policy statement to
their home page.
Details
Drafting a privacy policy is not an easy task and it requires extreme care. Special attention must be paid
to details and clarity. The vast majority of the privacy policy statements studied seem thin on details about
the collection, processing, storage or transmission of personal information. 50% of the available privacy
policy statements failed to describe what information was collected, how that information could be used and
kept secure and how an individual might access to information collected about his or her. Online privacy
policies should be developed into details that ensure your constituents that all data collected about them will
be handled properly.
Transparency
More and more local council websites are capable of interacting with users and processing financial
transactions. A privacy policy statement should provide transparency in letting people know what will
happen after you give your name, email address, or other personal information to the third party. As more
people learn about what has been done with their information and information collected online, they will feel
more comfortable to use online services and information (Jensen, et al., 2005).
Automatic collection of information
In common with e-commerce firms, the government websites use cookies and web logs to collect
information about visitors to their website. These online tools in some way give website a little information
about their visitors visiting date and time, IP address, the URL of any page requested. It is important to let
your visitor know whether your website link non-personal information stored in cookies or logged
automatically with personal data about a specific individual.
Three websites tell a visitor to their site that their Internet service providers (ISPs) will record information
related to website visit such as IP address and the pages you accessed and the documents downloaded. Only
two websites notify their users that they are using cookies while one site claims that they do not use cookies
on any public areas of the site. The rest do not state if their websites use cookies.
While the above website visit information and cookies data are not defined as personal information by the
PPIPA, the data can be used to track individual online activities. The intrusive nature of cookies concerns
many Internet users. External ISPs can trace some of this information to the originating individual, which
may raise some serious privacy concerns.
Use of third party services
Most of the websites studied use third-party credit card processors but they do not provide a link to these
companies’ privacy policies. The privacy policy statements posted on the council’s websites failed to provide
any details in respect of how the third parties manage the personal information of the users of the council
websites. Such a practice would likely discourage people from using government online services as they
cannot be assured that their data are being properly protected once shared with a third party site (UN, 2008).
Users face risks to their privacy when they use these transactional facilities via the council’s web site as they
do not have established business relationship with these third parties. Users should be presented with an
explicit opt-in/opt-out option to information disclosure to a third party.
A good privacy policy will allow people to make an informed decision about whether to give their
personal information or not. It does not necessarily protect them from its misuse but it does help create some
kind of transparency in the hope to gain trust. Privacy policies enhance the transparency of the operations of
organisation and give people a better understanding of their management of personal information (Office of
the Privacy Commissioner, 2006).
Readability
The organisation’s personal data practices and legal requirements should be clearly understood and
reflected in a form of a privacy policy statement through standard and straightforward language. The
language used in privacy policies is often difficult for users to understand (Sumeeth, et al., 2009). The
readability of the privacy policy statements can also be problematic. 50% of the privacy documents examined
were poorly structured and vaguely written.
Contact details and updating
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In addition to transparency, readability and compliance with legal requirements, a good privacy policy
includes information concerning ways to contact the organization and updates to the privacy policy
statement. Privacy policies need to be updated to stay current with the frequent changes in the online
environment. Only two council’s websites show the last updated date at the top of the statement but no
indication was given of the changes made, and no chain was linked back to earlier versions. Only 2 of the
website privacy statements examined provide visitors to their websites with details of whom to contact if they
have a privacy enquiry or concerns.
7. LIMITATIONS OF THIS STUDY AND FURTHER RESEACH
This research is limited to the local council’s websites in the GWS region, Australia. The relative small
sample size makes it difficult to draw more general conclusions. The challenging results of this study suggest
that additional efforts should be taken to further examine privacy policies posted on local government
websites using a larger sample and different levels of e-government.
Earlier studies have shown that privacy statements are positively associated with trust, which has an
impact on willingness to exchange information and transact business with a web site (Hoffman et al 1999,
Nemdi & Dyke 2009). However, these prior studies primarily focus on e-commerce context. Future research
should be done to study the effect of having good privacy practice on trust and how trust influences user
behavioural intention for using e-government services. Research into privacy issues in e-government context
is not only essential to identify opportunities for and threats to local government web sites and their users but
also to improve the effectiveness of e-government initiatives.
8. CONCLUSIONS
There is an increasing risk of personal privacy invasion from using websites. Users are concerned about how
their personal information will be collected, used and secured in online environment. This has resulted in
increased privacy concerns and a lack of trust among users, which have negative impact on e-government
development. The presence of a well-written, easy to understand privacy statement appears to be an effective
method for building trust.
This study examines the contents of the privacy policy statements published on the local council’s
websites in the GWS region using a content analysis approach. The research findings show that 43% of the
websites surveyed do not display a privacy policy statement while 36% appear to have a weak policy
statement. Serious deficiencies in relation to the collection, access, amendment, use and disclosure of
personal data were found in the privacy statements examined. The great majority of the privacy policy
statements published on the local councils’ websites is not in compliance with the IPPs contained in the
PPIPA and provides little privacy protection to the users of their websites. Widespread non-compliance with
the legislation indicates that the current legislation is not effective in protecting user privacy online.
In addition to compliance with the legislation, the aspects of transparency, readability and detailed
information are seen as important for a desirable privacy policy. The lack of details, clarity and transparency
in privacy policy statements prevents users from understanding the content and potential issues in submitting
their personal data. The results of the analysis indicate attempts to display and develop an effective privacy
policy have not been made by the vast majority of the websites examined. The local governments must take
steps to ensure that their policies are posted online and remain transparency, meaningful, understandable and
accessible to users.
The presence of a privacy policy statement on websites in general indicated that e-government sites are
committed to online privacy protection. It is the responsibility of councils to ensure that privacy policy
statements published on their websites are in compliance with the legislation and address the privacy
concerns of their website users. Governments are expected to take the lead in respecting privacy and ensuring
a secure environment that can be trusted to protect personal information from loss and misuse.
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TAXONOMY OF IT INTANGIBLES ASSETS BASED ON
THE ELECTRONIC GOVERNMENT MATURITY MODEL
IN URUGUAY
Helena Garbarino1, Bruno Delgado1 and José Carrillo2
2
1
Universidad ORT Uruguay
Universidad Politécnica de Madrid
ABSTRACT
This article extends a taxonomy of IT intangible assets indicators for the Public Administration completing it in terms of
traceability with Electronic Government Maturity Model proposed by the Agency for Electronic Government and
Information Society and categorized according to a consolidated intellectual capital model. In the project proposal, the
Maturity Model is mapped with the expanded taxonomy so that it considers all of the relevant aspects associated with the
intangible IT assets of the Public Administration in Uruguay. At the end of the project the taxonomy and its relationship at
the indicator level with the Maturity Model is presented.
KEYWORDS
E-Government, intangible assets, intellectual capital, IT, public administration, indicators
1. INTRODUCTION
The purpose of this article is to provide a taxonomy of IT intangible asset indicators for the Public
Administration defined by (Garbarino and Delgado, 2011), expanding upon and completing it based on
traceability with the Electronic Government Maturity Model (hereinafter EGMM) proposed by AGESIC1 in
the ROU2. The original taxonomy is based on a set previously defined by (Zadrozny, 2005) and categorized
according to a consolidated intellectual capital model. In the project proposal, the EGMM is mapped with
expanded taxonomy so that it considers all of the relevant aspects associated with the intangible IT assets of
the Public Administration in Uruguay. At the end of the project the taxonomy and its relationship at the
indicator level with EGMM is presented.
1.1 Intangible Assets
According to (IASC, 2009), intangible assets “are characterized as identifiable assets, without physical
substance, and that are allocated for use in the production or supply of goods and services to be lent to third
parties, or for administrative ends." Baruch Lev (Lev, 2001) defines intangible assets in the following
manner: “an intangible asset is a claim to future benefits that does not have a physical or financial (a stock
or a bond) embodiment. A patent, a brand, and a unique organizational structure (for example, an Internetbased supply chain) that generate cost savings are intangible assets.”
There are several models whose purpose is to serve as tools for identifying, structuring, and assessing
intangible assets: Balanced Business Scorecard (Kaplan and Norton, 1996), Intellectual Assets Monitor
(Sveiby, 1997), Skandia Navigator (Edvinsson, 1997), Intellect Model (Euroforum, 1998), Intellectus Model
(Trillo and Sánchez, 2006), the AIE model for assessing intangibles (Hubbard, 2007) and MERITUM
(Cañibano Calvo, et al., 2002), among others. This article shall be based on the model proposed by the
1
AGESIC – Agencia para el desarrollo del gobierno de gestión electrónica y del conocimiento (ADEGMK, Agency for the
Development of Electronic Government Management and Knowledge)
ROU - República Oriental del Uruguay (ERU, Eastern Republic of Uruguay)
2
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MERITUM project, as well as the Intellect model, and its evolution: Intellectus. The first model proposes the
need of a common, internationally accepted framework of reference. This shall serve as a basis for companies
to identify, measure, and track their intangibles, since it is difficult for competitors to imitate these methods,
and they become an important sustainable advantage for companies (Kaplan and Norton, 1996). When
considering intellectual capital, there is a certain consensus comprised by three capitals: human, structural,
and relational (Cañibano, et al., 1999, Euroforum, 1998, Trillo and Sánchez, 2006).
From the strategic perspective of the company, in (Kaplan and Norton, 2004) the human capital is
measured focusing on the capabilities, education, and knowledge that people belonging to the company
possess. The idea that structural capital is divided into organizational capital and technological capital has
been adopted from the Intellectus model. This distinguishes aspects regarding business philosophy and
management, and the technological infrastructure as the knowledge that creates and administrates it.
Finally, what is referred to as relational capital in the Intellect model is divided into business capital when
observing the value it has for the organization in relation to the other basic participants of the business
(clients, suppliers, shareholders, etc.), and social capital when observing the relations to social agents of the
surroundings such as means of communication, public institutions, environmental conservation institutions,
etc. To these five capital categories must be added the proposal by (Trillo and Sánchez, 2006): cultural
capital, which is comprised by values, the organizational culture, the innovative and creative culture, and the
relational culture (Table 1).
Table 1. Intellectual capital based on (Cañibano Calvo, et al., 2002, Euroforum, 1998, Trillo and Sánchez, 2006)
Type
1
2
3
4
Name
Human Capital
Organizational Capital
Technological Capital
Business Capital
5
Social Capital
6
Cultural Capital
Attributes
Competence, Knowledge, Aptitudes, and Attitudes
Structure, Learning, and Processes
Efforts in I+D+I, Technological endowment, and Intellectual property
The value represented by the relationships that the organization maintains
with principal agents associated to the business process
The value represented by the relationships that the organization maintains
with the remaining social agents that act within their surroundings
Cultural values, Organizational culture, innovative culture, and creative and
relational culture
The importance of organizational culture is specifically considered due to the characteristics surrounding
the study. (Trillo and Sánchez, 2006) indicates the close relationship between culture and the characteristics of
the intellectual capital indicators; therefore, intellectual capital would be comprised of six elements: human
capital, organizational capital, technological capital, business capital, social capital, and cultural capital.
1.2 Application Surroundings
Contextual considerations:
Based on the characterization of the evolution of the Uruguayan state carried out by (Garbarino and
Delgado, 2011) and the need for stating the intangibles of the Public Administration, measuring their potential,
directing public policies toward a change in the focus and meaning of public service (Merino Rodríguez, et al.,
2003) (AGESIC, 2011b) and transforming it into a tool that supports the governing of IT in the State, the
model defined in (García de Castro, et al., 2004, Medina, 2003) for public Spanish companies is taken as a
basis. From here a taxonomy of intangible IT indicators is built according to the reality of the Public
Administration of Uruguay (Garbarino and Delgado, 2011).
Scope:
The scope of the proposed model refers to the Central Administration, with the exception of Autonomous
Entities and Departmental Governments (Regional Governments) and Local Councils pursuant to that set forth
by (Garbarino and Delgado, 2011) within the framework of the Constitution of the Eastern Republic of
Uruguay (ROU, 2009) and the clear separation of roles within the Public Administration.
Autonomous Entities are explicitly excluded from the scope of this work (whose management shall be
focused on the criteria of private companies and a ROI to be satisfied), as well as organisms that specialize in
regional and local policies. The central focus of the work shall therefore be the Central Administration, and as
36
IADIS International Conference e-Commerce 2011
a case study for validating comparative data, the executive unit of the Directorate General of Commerce,3
which depends on the Ministry of Economy and Finances.
1.2.1 AGESIC (AEGIS, Agency for Electronic Government and Information Society)
AGESIC4 is the "Agency for the Development of Electronic Government Management and Information
Society." Created in 2005, it depends on the President of the Republic and operates with technical autonomy.
Its mission is to lead the strategy and implementation of Electronic Government in the country as a basis for
an efficient State that is centered on the citizen; fostering the Information Society and promoting the
inclusion of Information and Communication Technology, and the quality of its use.
Its principal actions are centered on defining and disseminating the computer guidelines and overseeing
their fulfillment, analyzing technological trends, developing Information and Communication Technology
projects, advising the public institutions of the State with regard to computer material, disseminating material
regarding Electronic Government, and supporting the transformation and transparency of the State.
1.2.2 EGMM - Electronic Government Maturity Model
EGMM is an assessment guide that enables the analysis of the capabilities of services management for the
citizenry, as well as techniques and strategies (AGESIC, 2008b). It also enables the fulfillment of objectives
for efficiency and effectiveness in the use of Information Technology by the State. In Uruguay, the Public
Administration shows uneven development in its sectoral operational capabilities, in particular in its
capability of efficiently and effectively using Information and Communication Technology (AGESIC, 2009).
The objective of the model is to support the transformation of the State; ensuring the quality of
Management, overseeing the state projects, improving and increasing the number of state transactions and
services online, and strengthening the Public Administration with regard to its organization and capabilities
by means of the implementation of maturity models and continuous training.
National and international experts in Public Administration and different technical areas participated in
defining the model with the objective of obtaining a solution that is in line with the best international
practices, and adapted to the possibilities of the State of Uruguay. The model was used as an assessment tool
for current capabilities and, since it contains a list of good practices, it also serves as a behavioral instigator.
Based on the assessments that were carried out, with a definitive model and a tool for self evaluation
supporting improvement in the level of maturity in the Executive Units and the rest of the organisms of the
Public Administration, progress was made in the drafting of the roadmaps that served in improving and
leveling capabilities (AGESIC, 2009).
As seen in Table 2, the model is based on three dimensions, nine related sub areas, and 35 dependent
subcategories:
Table 2. Breakdown of Areas and Subcategories (AGESIC, 2008a, AGESIC, 2008c, AGESIC, 2011a)
Subcategory
Strategy; Governing; Value Management; External Analysis and Benchmarking
Competence; Culture; Structure; Change Management; Recognition and Rewards
Framework for measuring performance; Indicators
IT
Infrastructure; Networks and Connectivity; Integration; Architecture; Security;
Standards
Content; Architecture; Security; Standards; Privacy/Access to public information
Information
Management; Execution (processes and projects); Origin of Resources;
Operations
Fulfillment; Financing Process
Public Relations Services
Channels; Rendering of Services
Understanding of the citizens’ perspective and their needs; Satisfying the citizens;
Citizens
Participation/Adoption/Involvement with citizens
Communications Internal and External strategies; Execution; Promotion of services
Dimension
Organization
3
4
Area
Strategy
People
Performance
Technology
DGC – Website available at http://www.comercio.gub.uy
AGESIC – Website available at http://www.agesic.gub.uy/
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2. TAXONOMY
The model to be proposed shall be an extension and adaptation of the proposal by (Merino Rodríguez, et al.,
2003), which has emerged as the result of studying models such as the Intellectus (Trillo and Sánchez, 2006)
with adaptation and subsequent revision by external experts.
Given the characteristics of the surroundings presented, it is established that each one of the six capitals
that are proposed in the model shall exist in the Uruguayan Public Administration; leaving the determination
of which indicators, of those that shall be taken as a basis (Zadrozny, 2005), are appropriate for each one of the
proposed IT assets.
2.1 Indicators
Each one of the six capitals that are mentioned in Table 1 group the intangible assets associated with IT in
relation to defined EGMM. Based on the nature of the knowledge, they breakdown into a set of elements that
conceptually identify and describe homogeneous groups of intangible assets. In Table 3 below, the proposed
indicators are classified according to the type of capital they correspond to.
Table 3. Indicators and grouping by type of capital
Type
1
No.
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
1.10
2
2.1
2.2
2.3
2.4
2.5
2.6
38
Indicator
Employee Experience
Upper Management
Experience
Quality of Upper
Management
Description
Universal indicator. Applies in the context related to IT Knowledge Management.
Abilities of upper management for fulfilling the mission of the organization;
ability of upper IT management in governing the IT of the organization.
The value contributed by the quality of the management carried out by upper
management significantly influences the quality of the products and services. May
be broken down in order to measure the quality of middle management.
The alignment level of the decision-makers in the middle management chain
Aligning of middle
conditions the effectiveness of the implemented strategies.
management
The final quality of the product or service is associated to the capabilities, training,
Know-How
and knowledge regarding the operation carried out, and the objectives.
Indicators shall be constructed that enable the measurement of different
Capabilities
capabilities in order to fulfill goals. These indicators should refer to: adequately
satisfying the information demands, providing a quality service, or following the
status of good electronic Government practices.
Basic measurement for obtaining employee performance with regard to specific
Employee Added Value
operations, for example: the amount of requests received, the amount of services
carried out at the Service Desk, among others.
This indicator is relevant because of the volatility of technical support personnel
Rotation of support
due to market characteristics, the contracting methods of companies that provide
personnel
services to the state, and the horizontal operational movements between different
public concessions.
Indicator that measures the efficiency of the continuous corporate governing of IT
Training
formation and human resources training.
Measures the level of satisfaction regarding strategy, organization, operation, and
Employee satisfaction
work conditions.
Ability to attract talented There are different perceptions regarding the provision of services to the state, and
working for the state.
employees
Considering this indicator as an investment in organizational structure, it is an
Investments in Internal
improvement indicator that applies within the context.
Structure
Refers to the processes for the acquisition of IT solutions and services.
IT Acquisitions
The capability of measuring the impact of the loss of professionals within the
Loss of
organization.
Professionals/Talent
The capability of measuring lost assets regarding IT (hardware such as general
Lost Assets
infrastructure, and software such as code, executables, technical documentation of
users, and databases). Based on this indicator it may be determined how many,
which, and what percentage may or may not be accepted as a loss. This is a
measurement of the quality of asset management that should be evaluated in
strategic-monetary terms in order to support the decision-making process.
The evaluation of formalized processes is the step subsequent to the formalization
Formalized Processes
IADIS International Conference e-Commerce 2011
2.7
Structural Adaptation
2.8
Costs of Education and
Training
Informal Processes
2.9
2.10
2.11
2.12
2.13
2.14
2.15
2.16
2.17
2.18
2.19
2.20
2.21
2.22
2.23
2.24
2.25
3
3.1
3.2
3.3
3.4
3.5
3.6
3.7
Quality of Processes,
Products, or Services
Investment in IT
Staff renewal ratio
Quality of Corporate
Government
Defined strategy
Quality of the system for
recognition and rewards
Performance - strategy
level
Performance - alignment
Performance - level of
operation
Information Security
and implementation of said processes (for example under a referential ISO,
CMMI, COBIT, etc. framework)
Measurement of the relation between the IT capabilities of the organization, vs. its
operations. When the value is more than one, it can measure the additional
capabilities of offering IT services to other units, and should be related to adequate
demand management.
This is relevant for all organizations, including state organizations. One possible
indicator is the operation cost in comparison with international standards.
Within this context there are several informal processes for various reasons: lack
of resources, lack of orientation culture for processes, including quality processes,
tradition, organizational culture, and informal hierarchical relationships, among
others.
These indicators are currently measured based on international standards derived
from institutions like ISO, in such a way as to enable benchmarking.
This indicator is a fundamental element in the strategy for IT government, and
should consider the different dimensions referring to: the following of IT
principles, the IT architecture of the business and the defined infrastructure,
strategical relevance of investments (integration to the administration strategy),
and decision-making processes.
Indicator that represents the Administration's capability of renewing the IT staff.
The new public management based on transparency in managing, external and
internal auditing, focus on results, and public rendering of accounts.
Explicit definition of the mission and vision of the IT organization, as well as
plans for carrying them out.
Existence, effectiveness, and efficiency of the organization's systems for
recognition and rewards.
Existence of a model for performance indicators.
Alignment of the performance indicator model with the defined strategy.
Effective use of the model.
Security management of the information, including policies for information
security, risk management for information, the following of standards and respect
for privacy and access to public information, as well as auditing procedures
Management of capabilities based on a capabilities plan with a defined
Capabilities
management cycle.
Affective mechanisms for obtaining external resources in order to finance
External financing
Electronic Government initiatives.
Scalability of EG Services Capabilities associated with integration, adaptation, and maintenance of integrated
services on an EG platform.
Capabilities regarding the rendering of services by means of different channels
Multichannel GE
(on-site, electronic, and by telephone).
Services
Communication strategy Existence of an organic communication strategy for dissemination and awareness
of services, as well as management.
Alignment of communications management with the multichannel strategy.
Multichannel
communication
Quality and adaptation of the support systems portfolio of the organization.
Software (baseline)
Quality and adaptation of the organization's applications portfolio focused on
Software (Applications)
rendering specific services.
This applies within a context referring to the focus on acquiring and updating
Purchase of Technology
technology.
Availability of data for constructing measurements that support indicators.
Data Access Capability
Development of in-house This applies within the context referring to the management and development of
IT solutions and services on the part of the organization with its own resources.
IT
This applies within a context referring to the management and development of IT
Development of
solutions and services on the part of third parties. Outsourcing carried out at the
outsourced IT
physical limits of the organization may be distinguished from pure outsourcing for
the purpose of better oversight.
Measurement of the innovation capability regarding improvements in
Research and
effectiveness (more, and better products and services) and efficiency (less costsDevelopment
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4
5
6
3.8
Systems
3.9
3.10
3.11
Flexibility of the Physical
Plant
Plant Infrastructure
Modernity of the Plant
4.1
Lending of Services
4.2
Operations
4.3
Projects
5.1
Hierarchical knowledge
5.2
Quality of Supplier
contracts
5.3
Deployment of
communication
Organic Growth
6.1
6.2
Organizational
Reputation
6.3
Innovative culture
6.4
Focus on service and the
citizen
Focus on citizen
participation
Encouragement of
multichannel GE
Services
6.5
6.6
time-effort)
At the IT portfolio management level, the strategic relevance, effectiveness, and
efficiency of the information systems and the processes supported by IT regarding
the operations that they carry out shall be measured. Parker and Benson [19] may
be utilized in order to classify them from an economic point of view.
The volume, quality, and flexibility of the physical plant influences the
development of IT capabilities for improved performance, which should be
measured in terms of product and SW service productivity. This is an indicator
that should be supported by several measurements such as the amount of
PF/developed monthly, customer service satisfaction, the capability of a reactive
response to IT demands, and the capability of proactive proposals for IT solutions.
The evaluation of incoming or outgoing products/services to and from third parties
may be an indicator of the organization's IT capabilities. Within the current
framework of EG trends and complementing of state services (with or without an
economic relation), this could be an indicator of maturity, and therefore increase
the IT assets.
Operative management based on an operations plan with a defined management
cycle.
Project management, methodology, integration, institution analogy, and benefit
management.
This is necessary for measuring the satisfaction of citizens with the state services
(within the G2C5 context), the performance of the hierarchies in the fulfillment of
their duties, and the development of electronic government. In this sense the
development of electronic government agencies (AGESIC FOR example)
implement standardized evaluation models for measuring the dimensions of this
attribute.
The integration of products and services with different suppliers is a characteristic
of IT type architecture. Monitoring the relationship and fulfillment by means of
SLA´s5, implies the insurance of quality service.
Monitoring and control of communications while keeping in mind the public
objective (G2C, G2B, G2G, and G2E).
The measurement of the evolution of products and services offered is an indicator
of improvement and added value within the context of innovation.
The state of Uruguay, by means of AGESIC6 , is currently immersed in a
transformation process with the objective of improving its state IT capabilities;
aligning them with better practices, and international standards.
This indicator should be considered, and measured from a citizen satisfaction
point of view, because if a competition policy does not exist at the market level, it
isn't necessary to innovate in order to improve competitiveness.
Capability and focus on IT in satisfying the demands for services on the part of
citizens, companies, and government.
Capability and focus on IT in order to encourage and facilitate citizen
participation.
Focus on the promotion and encouragement of multichannel EG services, with the
objective of improving access, deployment, and the universality of services.
3. TAXONOMY TRACEABILITY PROPOSAL - EGMM
The following displays the complete relationship between EGMM at the subcategories level, and the different
indicators related, which shall enable the measurement of management, as well as each sub area, based on the
different indicators regarding taxonomy.
5
6
Service Level Agreement
AGESIC – Agency for the Development of Electronic Government Management and Knowledge.
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IADIS International Conference e-Commerce 2011
Table 4. Taxonomy traceability - EGMM
Area
Strategy
People
Performance
Technology
Information
Operations
Services
Citizens
Communications
Subcategory
Strategy
Government
Value management
External analysis and benchmarking
Competition
Culture
Structure
Change management
Acknowledgment and rewards
Framework for measuring performance
Indicators
Infrastructure
Networks and Connectivity
Integration
Architecture
Security
Standards
Content
Architecture
Security
Standards
Privacy/Access to public information
Management
Execution (processes and projects)
Origin of resources
Compliance
Financing process
Channels
Rendering of services
Understanding of the citizen's perspective and needs
Citizen satisfaction
Participation/Adopting/Involving citizens
Internal and external strategy
Execution
Promotion of services
Related indicators
2.14
2.2; 2.3; 2.5; 2.9; 2.11; 2.13; 3.5;
3.6; 5.2
2.5; 2.97; 2.10; 3.5; 3.6
2.6; 2.10; 3.7
1.1; 1.2; 1.3; 1.4; 1.5; 1.8
6.4
6.5
1.3; 1.7; 2.1; 2.4; 2.12
1.10; 2.15
1.6; 3.7
2.16; 2.17; 2.18
2.7; 3.1; 3.2; 3.8; 3.9; 3.10; 3.11; 4.1
2.7; 3.1; 3.9; 3.10; 3.11; 4.1
2.7; 3.1; 3.2; 3.8; 3.9; 3.10; 3.11; 4.1
2.7; 3.1; 3.2; 3.8; 4.1
3.1; 3.2; 4.1
3.1; 3.2; 4.1
3.4
3.4
2.19
2.19
2.19
2.20; 4.2
4.2; 4.3
3.3
3.3; 4.2
2.21
2.22; 2.23; 6.6
5.1; 6.1
6.2; 6.4
5.1; 6.2; 6.3
5.1; 6.1; 6.5
2.24
2.25
6.6
4. CONCLUSIONS AND FUTURE PROJECTS
From the preceding analysis emerges a taxonomy proposal that incorporates new indicators in order to cover
all of the dimensions of the model proposed by AGESIC, without being limited to it. Based on a consolidated
taxonomy of 38 indicators, a total of 58 indicators were reached; representing an increase of 52%.The
taxonomy obtained presents a balance of improved indicators, where the more highly covered EGMM areas
are Technology (33%) and Strategy (18%), while the least covered is Communications with 3%. The final
result achieved is a relationship with complete traceable taxonomy, where all of the sub areas of the EGMM
are covered by different indicators.
Regarding the taxonomy reference (Garbarino and Delgado, 2011), a relevant percentage increase is
observed in business capital (67%), organizational capital (19%) and technological capital (12%), with no
change in the social capital, and both cultural and human capital decreasing in a relevant manner; (40%) and
(23%) respectively.It is concluded that in order to completely cover the EGMM, and therefore serve as a
supporting reference regarding the management of intangible IT assets, the weight of the aspects associated
with human and cultural capital decreased notably in taxonomy.
7
This indicator should be included within the contexts that focus exclusively on processes.
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As a future project, the construction of the quantitative dimension for each indicator based on the
associated robust measurements, for each case, into existing valuation models of assets, or their mapping to
candidate models is proposed. This will make possible the quantified measurement of the quality of corporate
IT government with regard to the management of intangible IT assets in the public Administration of Uruguay.
REFERENCES
AGESIC, 2008a. Gobernanza en TI. Modelo de Madurez para la Gestión de Gobierno Electrónico.
http://www.agesic.gub.uy/innovaportal/v/457/1/agesic/modelo_de_madurez_para_la_gestion_de_gobierno_electronic
o.html?menuderecho=4.
AGESIC, 2008b. Memoria Anual 2008. Montevideo, Uruguay. Presidencia de la República.
AGESIC, 2008c. Modelo de madurez de Gobierno Electrónico. Montevideo, Uruguay. Presidencia de la República.
AGESIC, 2009. Memoria Anual 2009. Montevideo, Uruguay. Presidencia de la República.
AGESIC, 2011a. Madurez de Gobierno Electrónico - Cuestionario. Montevideo, Uruguay. Presidencia de la República.
AGESIC, 2011b. Plan estratégico 2011 - 2015. Montevideo, Uruguay. Presidencia de la República.
Cañibano Calvo, L., et al., 2002. Directrices para la gestión y difusión de información sobre intangibles. Fundación
Airtel Móvil. Madrid.
Cañibano, L., et al., 1999. The value relevance and managerial implications of intangibles: a literature review. Vol. No.
pp.
Edvinsson, L., 1997. Developing intellectual capital at Skandia. Long Range Planning. Vol. 30. No. 3, pp. 366-373.
Euroforum, 1998. Medición del Capital Intelectual. Modelo Intelect”, IUEE, . IUEE. San Lorenzo del Escorial , Madrid.
Garbarino, H. and B. Delgado, 2011. Taxonomía de indicadores de activos intangibles de TI para la Administración
Pública. Caso República Oriental del Uruguay. CISTI 2011. Portugal.
García de Castro, M. A., et al., 2004. La gestión de activos intangibles en la administración pública. Vol. No. pp.
Hubbard, D. W., 2007. How to Measure Anything: Finding the Value of Intangibles in Business. John Wiley & Sons, Inc.
Hoboken, New Jersey. USA.
IASC, 2009. NIC 38 Activos Intangibles. [23/04/2011]. http://www.iasb.org/NR/rdonlyres/8C28675D-FE12-468C-A7B766F8C1628673/0/IAS38.pdf.
Kaplan, R. and D. Norton, 2004. La disponibilidad estratégica de los activos intangibles. Harvard Business Review. Vol.
122. No. pp. 38 - 51.
Kaplan, R. S. and D. P. Norton, 1996. The Balanced Scorecard. Harvard Business School Press. Barcelona.
Lev, B., 2001. Intangibles: management, measurement, and reporting. Brookings Institution Press. USA.
Medina, A. S., 2003. Modelo para la medición del capital intelectual de territorios insulares. Una aplicación al caso de
Gran Canaria. Facultad de Ciencias Económicas y Empresariales. Departamento de Economía y Dirección de
Empresas Universidad de las Palmas de Gran Canaria.
Merino Rodríguez, B., et al., 2003. Capital Intelectual en la Administración Pública: El caso del Instituto de Estudios
Fiscales. España.
ROU, 2009. Constitución de la República. Constitucion 1967 con las modificaciones plebiscitadas el 26 de noviembre de
1989, el 26 de noviembre de 1994, el 8 de diciembre de 1996 y el 31 de octubre de 2004. Montevideo, Uruguay.
Poder Legislativo.
Sveiby, K. E., 1997. The intangible assets monitor. Journal of Human Resource Costing and Accounting. Vol. 2. No. 1,
pp. 73-97.
Trillo, M. A. and S. M. Sánchez, 2006. Influencia de la cultura organizativa en el concepto de capital intelectual.
Intangible Capital. Vol. 11. No. 2, pp. 164-180.
Zadrozny, W., 2005. Making the Intangibles Visible. How Emerging technologies Will Redefine Enterprise Dashboards.
IBM Research Division. New York, USA.
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IADIS International Conference e-Commerce 2011
A MODEL OF CUSTOMER RELATIONSHIP
MANAGEMENT FOR THE CONTEXT
OF PERMISSION-BASED E-MAIL MARKETING
Hsin-Hui Lin
Department of Distribution Management, National Taichung Institute of Technology
No. 129, Sec. 3, Sanmin Road, Taichung 404, Taiwan
ABSTRACT
Sending/retrieving e-mails is one of the most prevalent and frequent online activities around the world and also the best
tool for online marketing. However, abuse of unsolicited e-mails has caused much burden to both Internet users and
businesses and also reduced the effects of e-mail advertising. In nowadays, some e-commerce websites have begun to
make a clear distinction between permission-based e-mail marketing (PEM) and simultaneously posted advertising
messages (SPAM) and extensively used PEM to build long-term and lasting customer relationships. As the extant
research of PEM is very limited, this study proposes a conceptual model of customer relationship management model for
the context of permission-based e-mail marketing. The proposed model suggests that relational benefits (i.e., confidence,
social, and special treatment) and functional and process benefits (i.e., information quality, ease of use, and
entertainment) influence relationship outcomes (i.e., loyalty and online word-of-mouth) through the mediation of
relationship quality (i.e., satisfaction and commitment). The proposed model can provide some important implications on
theories and practices of PEM.
KEYWORDS
Permission-based e-mail marketing (PEM), relationship marketing, customer relationship management
1. INTRODUCTION
E-mail has become an indispensable tool for online communications. Epsilon’s 2009 Global Consumer Email
Study also confirmed that e-mail is extensively used by consumers around the world (FIND, 2010). For
businesses, e-mail is undoubtedly one of the best options for online marketing. Slack mentioned that e-mail
marketing offers fast responses along with a high rate of return due to the low cost of the medium. Businesses
are thus beginning to perceive it as a silver bullet for acquisition and retention strategies (Jupiter
Communications, 2001). Acxiom Digital and Harris Interactive pointed out in a 2006 report that 75% of adult
Internet users would open e-mails from businesses and consider those e-mails as “valuable” or “very
valuable”. For retailers, e-mail marketing is an efficient and responsive tool for maintaining customer loyalty.
It helps them communicate with customers in meaningful ways, so they can see the results of e-mail
marketing reflected on their increased revenue (Shih, 2006).
However, abuse of e-mail marketing is one negative phenomenon that bothers many people. A 2008
report released by Taiwan’s National Communications Commission (NCC) indicated that 83.9% of Internet
users in Taiwan received 10-50 unsolicited emails each day, at an average of 29 (Wen, 2009). The excessive
abuse of e-mail-based advertising generates additional burdens to consumers. The simultaneously posted
advertising messages, commonly known as SPAM, also cause a waste of corporate resources and social
costs. Abuse of e-mail marketing may mitigate the effects of advertising and displease or agitate consumers.
Besides, potential consumers may also become highly suspicious of the motives behind the e-mails originally
meant to foster customer relationships. Therefore, most businesses have become aware that in order to
achieve effective marketing, they should use e-mail marketing with more care and ethics. Now, many
businesses are beginning to make a clear distinction between e-mail marketing and spam e-mails. They seek
to adopt better and more ethical marketing strategies so as to build long-term and lasting customer
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relationships. The concept of permission marketing (PM) was introduced against this background to offer
both businesses and users a win-win solution.
By integrating customer benefits and relationship marketing theories, this paper will develop a model
consisting of antecedent, mediator, and outcome variables for PEM-based websites. In today’s business
environment where customer satisfaction and loyal customer relationship are highly emphasized, this model
is expected to help businesses develop and maintain customer relationships.
2. LITERATURE REVIEW
2.1 Permission-based Email Marketing (PEM)
PEM is commonly defined as “a method of advertising through promotional e-mails whose recipients consent
to receive commercial messages from the sender” (IMT Strategies, 1999; Tezinde, Smith and Murphy, 2002).
Permission relationships start with the consumer’s explicit and active consent to receive commercial
messages at any time. IMT Strategies (1999) pointed out another characteristic of PEM, which is that it can
offer specific, individualized messages to targeted consumers. Godin (1999) mentioned that PEM must
satisfy consumer needs and provide consumer-related information. Consumers expect to receive information
that is directly related to them and of their interest. According to Wathieu (2000), the principle of PEM is to
perform accurately targeted data mining on “right customers”. Rozanski, Bollman, and Lipman (2001)
mentioned that the main characteristic of PEM is that consumers understand what they will get, consent to
receive, and are able to terminate subscription at any time. Marinova et al. (2002) also identified three
characteristics of permission emails, including the opt-in and opt-out list, message customization, and content
relevancy with the recipient.
2.2 Relationship Marketing Model
Berry (1983) defined relationship marketing as “attracting, maintaining, and in multi-services organizations
enhancing customer relationships”. Attracting new customers is only one step in the marketing process. The
main idea of relationship marketing is to substantiate relationships, which is to view consumers as clients to
turn indifferent customers into loyal ones. Hence, relationship marketing is not just about attracting new
customers but also about keeping customers. Hennig-Thurau, Gwinner, and Gremler (2002) proposed a
relationship marketing model to investigate the antecedents and outcomes of a positive customer relationship.
Whether customers are willing to maintain the existing relationship with a business depends largely on their
evaluation of given benefits. Therefore, relational benefits are antecedent variables in the relationship
marketing model. Gwinner, Gremler, and Bitner (1998) identified three types of relational benefits, including
confidence benefits, social benefits, and special treatment benefits. Confidence benefits refer to customer
feelings of trust and anxiety reduction. Social benefits refer to the friendship, recognition, and fraternization
that might arise between the customer and the service provider. Finally, special treatment benefits refer to
price discount, speedy service or additional services that are not available to others (Bendapudi and Berry,
1997; Berry, 1995). Relationship quality is a mediator variable in the relationship marketing model. It
consists of customer satisfaction, trust, and commitment (Crosby, Evans, and Cowles, 1990; Dorsch,
Swanson and Kelley, 1998; Garbarino and Jonson, 1999; Palmer and Bejou, 2006). Hennig-Thurau et al.
(2002) identified only two components of relationship quality, namely satisfaction and commitment.
According to Armstrong and Kotler (2000), satisfaction is a function of perceived performance and
expectations which identifies a person’s feelings resulting from comparing a product’s perceived
performance in relation to his or her expectations. In this paper, satisfaction is defined as “the degree of
feeling pleased or disappointed with a product’s functional characteristics or perceived performance”. It is
one’s perception of his or her overall satisfaction with a product or service. Storbacka et al. (1994) defined
commitment as “the parties’ intentions to act and their attitude towards interacting with each other”. While
businesses tend to evaluate the effectiveness of their efforts at the end of each relationship marketing activity,
enhanced customer loyalty and positive word-of-mouth are viewed as “relationship outcomes” (Berry, 1983;
Morgan and Hunt 1994). Loyalty is a biased repurchase behavior and repatronage accompanied by a
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IADIS International Conference e-Commerce 2011
favorable attitude (O’Malley, 1998), and word-of-mouth refers to information communications directed at
other consumers at the ownership, usage or characteristics of particular goods, services or their sellers
(Westbrook, 1988).
2.3 Integration of Customer Benefits in the Traditional and the Network
Contexts
It should be noted that Hennig-Thurau et al.’s (2002) model was intended to investigate the relationship
between relational benefits, relationship quality, and relationship outcomes in the traditional context. Their
model must be extended or integrated with other components before it can be applied in the network context.
Whether in the traditional environment or the online environment, customer benefits resulting from
relationship marketing are based upon products and services (or subjects to be exchanged) and benefits
generated in the exchange or service process. The relational benefits approach assumes that both parties in a
relationship must benefit for it to continue in the long run. For the customer, these benefits can be focused
either on the core service or on the relationship itself (Hennig-Thurau et al., 2000). This is because most
relational benefits are benefits that exist above and beyond the core service provided (Gwinner et al., 1998).
In addition to relational benefits, functional benefits and process benefits should be considered in marketing
that relies on customer relationship management (Court et al., 1999; Han and Han, 2001).
In Marketing in 3-D, Court et al. (1999) introduced the idea of “functional benefits”, which are benefits
stemming from physical and mental satisfaction with the performance and quality of the product. The
benefits that exist above and beyond the core service provided are similar to the functional value in
PERVAL, which breaks down into quality and price (Sweeney and Soutar, 2001). Providing information is a
core product or service of a website. Like information quality mentioned by Rai, Lang, and Welker (2002),
informational value introduced by Eighmey (1997) can be viewed as “the degree to which information
produced has the attributes of content, accuracy, and format required by the user”. Information value
resembles content value proposed by Han and Han (2001), as both of them refer to the value and benefits of
information that a website can offer. Therefore, “information quality” corresponds to “functional benefits”
from 3-D marketing.
Besides, in the marketing process, the step next to attracting new customers is turning interested
customers into loyal ones (Berry, 1983). This concept has been introduced into management of customer
relationships in the network context. In 3-D marketing, “process benefits” are benefits that make transactions
between buyers and sellers easier, cheaper, and more pleasant (Court et al., 1999). In PERVAL, emotional
value is defined as the utility derived from the feelings or affective states that a product generates (Sweeney
and Soutar, 2001). In Eighmey (1997), entertainment value is described as the degree to which users feel
entertained by the website. Besides, ease of use measures how a website’s functions are easy to use for
general users. Therefore, we argue that “emotional/entertainment value” and “ease of use” correspond to
“process benefits” from 3-D marketing.
In both the traditional and network contexts, customer relationships are established on mutual benefits
between exchange partners (Barnes, 2001). Court et al. (1999) described “relational benefits” as the benefits
which reward the willingness of consumers to identify themselves and to reveal their purchase behavior.
Benefits such as a feel of comfort, experience of being treated as a friend, price discount, reduction of
transaction time, and individualized services can all be viewed as relational benefits. In this case, relational
benefits encompass confidence benefits, social benefits, and special treatment benefits proposed by Gwinner
et al. (1998) and Hennig-Thurau et al. (2002). Besides, according to Sweeney and Soutar (2001), customers’
social value is the utility derived from the product’s ability to enhance social self-concepts. We argue that
social value corresponds to the above-mentioned social benefits and is covered by relational benefits from 3D marketing (Court et al., 1999). The ideas of trust, interactivity, and marketing perceptions introduced by
Eighmey (1997) respectively correspond to confidence benefits, social benefits, and special treatment
benefits, which are, as aforementioned, collectively encompassed by relational benefits (Court et al., 1999).
A comparison of customer value/benefit dimensions between the traditional and network environments are
shown in Table 1.
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Table 1. A mapping table of customer value/benefit dimensions
Environment
Traditional
Author(s)
Gwinner et al.
(1998);
HennigThurau et al.
(2002)
Court et al.
(1999)
Sweeney and
Soutar
(2001)
Internet
Eighmey
(1997)
Han and Han
(2001)
This study
Value/benefit dimensions
-
Functional
Confidence
Process
Social
Special
treatment
Relationship
Functional
(price)
Functional
(quality)
-
Emotional
-
Social
-
Information
Ease of
use
Entertainment
Credibility
Interactivity
Marketing
perceptions
Social
Special
treatment
Content
Information
quality
Context
Ease of
use
Entertainment
Confidence
3. RESEARCH MODEL AND HYPOTHESES
Based on the three dimensions of customer benefits proposed by Court et al. (1999), relationship marketing
model introduced by Hennig-Thurau et al. (2002), and benefits of online customers identified by Eighmey
(1997), this paper proposed a modified customer relationship management model to investigate the effects of
customer benefits on relationship quality and relationship marketing outcomes as well as how website
operators can use PEM to develop long-term customer relationships. As shown in Figure 1, the proposed
model consists of antecedents, mediators, and outcome variables.
Korgaonkar & Wolin (1999) argued that in the cyberspace, customers can not only access some general
goods and service information but also seek information and make contacts (FAQ and e-mail) according to
personal needs. If they can obtain needed information from a website, their satisfaction with the website can
be enhanced. Ranft & O’Neill (2001) also mentioned that the prevalence and sufficiency of information on
the Internet will make website providers dare not have deceptive conducts, because a temporary short sight or
opportunistic behaviors may destroy a long-term customer relationship. They concluded that informational
quality are important for both parties of a relationship to maintain the relationship. It can be inferred that
when users perceive that PEM-based websites have more practical information, they will feel more satisfied,
be more willing to maintain relationships with the websites, and have higher intention to continue using the
websites.
H1: Informational quality has a positive influence on user satisfaction.
H2:Informational quality benefit has a positive influence on user commitment.
H3: Informational quality benefit has a positive influence on user loyalty.
Negash, Ryan, & Igbaria (2003) confirmed that system quality (ease of use) is highly correlated with
customer satisfaction. Besides, Hawkins (1994) mentioned that an ease of use interface should be
customizable, easy to understand, highly visualized, easy to browse, and effort-saving. If using Internet is
easy, customers can be more focused on continuation of their relationships. Reichheld, Markey, & Hopton
(2000) also mentioned that many successful firms have discovered that easier or faster transactions can help
consumers get needed services faster and make them more willing to make a repatronage. It can be inferred
that the more easily users can use PEM-based websites, the more satisfied they will be, the more willing they
are to maintain their relationships with the websites, and the higher their loyalty towards the websites can be.
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IADIS International Conference e-Commerce 2011
Note:- denotes the original relationship marketing model; －denotes the dimensions and paths added by this paper
Figure 1. A Conceptual Model of Customer Relationship Management for the Context of PEM
H4: Ease of use benefit has a positive influence on user satisfaction.
H5: Ease of use benefit has a positive influence on user commitment.
H6: Ease of use benefit has a positive influence on user loyalty.
Many scholars have pointed out that entertainment helps one relax his mood, pass time, and release
emotions (Eighmey, 1997; Ferguson & Perse, 2000; Papacharissi & Rubin, 2000). They proposed that
entertainment can bring positive benefits to customers in the emotional aspect, induce their positive
emotions, and help enhance their satisfaction. Besides, Papacharissi & Rubin (2000) suggests that
entertainment is an important motive for Internet use and has important influence on maintenance of Internetbased customer relationships. Reichheld, Markey, & Hopton (2000) pointed out that if consumers have an
enjoyable and pleasant experience of a transaction on the Internet, they will select websites that can provide
similar experiences for their next deal, and their intention for repeated use will be enhanced. It can be
inferred that the more pleased users can use PEM-based websites, the more satisfied they will be, the more
willing they are to maintain their relationships with the websites, and the higher their loyalty towards the
websites can be.
H7: Entertainment benefit has a positive influence on user satisfaction.
H8: Entertainment benefit has a positive influence on user commitment.
H9: Entertainment benefit has a positive influence on user loyalty.
In a transaction between a manufacturer and a buyer, confidence and trust for the other party has positive
influence on satisfaction of the transaction (Andaleeb and Anwar, 1996). We extend this conclusion to the
use of PEM-based websites. Besides, Morgan & Hunt (1994) and Garbarino & Johnson (1999) mentioned
that confidence in a service provider brings certain benefits to customers (such as reduction of transaction
costs) and will motivate users to make relational commitment to the service provider. According to Berry
(1995), when customers rely on or trust a certain service provider, they have higher loyalty to the firm and
more intention for repeated communication. It can be inferred that users who feel more confident with a
PEM-based website are more likely to feel satisfied with, be willing to maintain relationships with, and have
higher continuance of, the website.
H10: Confidence benefit has a positive influence on user satisfaction.
H11: Confidence benefit has a positive influence on user commitment.
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H12: Confidence benefit has a positive influence on user loyalty.
Price & Arnould (1999) suggests that there is a positive relationship between commercial friendship
(social benefit) and satisfaction. Previous studies have shown that social benefits are positively correlated
with customer commitment (Goodwin, 1997; Goodwin & Gremler, 1996). Berry (1995) also pointed out that
the social bonds between customers and service provider can increase customers’ commitment to the
organization and also increases customers’ intention for repeated communications. It can be inferred that
when users perceive that PEM-based websites have more friendly treatment, they will feel more satisfied, be
more willing to maintain relationships with the websites, and have higher intention to continue using the
websites.
H13: Social benefit has a positive influence on user satisfaction.
H14: Social benefit has a positive influence on user commitment.
H15: Social benefit has a positive influence on user loyalty.
According to Reynolds & Beatty (1999), special treatment benefits (such as economic savings or
customized service) offered by service providers are like a part of the services provided, so their influence on
satisfaction of the services can be expected. Besides, when customers receive special treatment benefits from
an organization, they will be faced with higher or more emotional or cognitive switching barriers (Fornell,
1992) and thus increase their commitment and continue their use of the services or goods provided by the
organization (Selnes, 1993; Hennig-Thurau et al., 2002). It can be inferred that users who feel more
economic or customized treatments with a PEM-based website are more likely to feel satisfied with, be
willing to maintain relationships with, and have higher continuance of, the website.
H16: Special treatment benefit has a positive influence on user satisfaction.
H17: Special treatment benefit has a positive influence on user commitment.
H18: Special treatment benefit has a positive influence on user loyalty.
Anderson and Srinivasan (2003) proposed that, in an e-commerce environment, higher e-satisfaction
leads to higher e-loyalty. Luarn and Lin (2003) investigated and empirically confirmed the positive
relationship between satisfaction and loyalty in an e-service environment. Henning-Thurau et al. (2002)
suggests that customer satisfaction has significant and strong influence on their word-of-mouth behavior. In
the era with highly advanced information technology, the PEM-based websites has become a new platform
for B2C business transactions and information exchanges. As a result, it is even easier for satisfied customers
to diffuse their word-of-mouth. The following hypotheses are proposed.
H19: User satisfaction has a positive influence on user loyalty.
H20: User satisfaction has a positive influence on user word-of-mouse.
Reichheld, Markey, & Hopton (2000) discovered that customers’ commitment to a website is
significantly influential to their repurchase behavior. Henning-Thurau et al. (2002) discovered that
customers’ commitment to a company positively influences their loyalty. The findings in Roberts, Varki, &
Brodie (2003) reveal that commitment has positive effects on loyalty in a high-quality relationship. Besides,
commitment can be viewed as an important predictive construct of customer’s future behavior (Garbarino &
Johnson, 1999). It has been affirmed that commitment has positive influence on word-of-mouth (Beatty,
Kahle, & Homer, 1988). The following hypotheses are proposed.
H21: User commitment has a positive influence on user loyalty.
H22: User commitment has a positive influence on user word-of-mouse.
4. CONCLUSION
The main purpose of this study is to propose a customer relationship management model for the context of
permission-based e-mail marketing. A conceptual research model and the associated hypotheses are proposed
based on previous literature. The proposed model suggests that relational benefits (i.e., confidence, social,
and special treatment) and functional and process benefits (i.e., information quality, ease of use, and
entertainment) influence relationship outcomes (i.e., loyalty and online word-of-mouth) through the
mediation of relationship quality (i.e., satisfaction and commitment). Future researchers could conduct an
empirical validation of the proposed model. The proposed model can provide some important implications on
theories and practices of PEM.
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IADIS International Conference e-Commerce 2011
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IADIS International Conference e-Commerce 2011
DETECTING EMERGING TOPICS AND TRENDS VIA
SOCIAL MEDIA ANALYTICS
Richard Colbaugh1 and Kristin Glass2
1
2
Sandia National Laboratories, Albuquerque, New Mexico 87123 USA
New Mexico Institute of Mining and Technology, Socorro, New Mexico 87801 USA
ABSTRACT
Detecting and characterizing emerging topics of discussion and consumer trends through analysis of Internet data is of
great interest to businesses. This paper considers the problem of monitoring the Web to spot emerging memes – distinctive phrases which act as “tracers” for topics – as a means of early detection of new topics and trends. We present a novel
methodology for predicting which memes will propagate widely, appearing in hundreds or thousands of blog posts, and
which will not, thereby enabling discovery of significant topics. We begin by identifying measurables which should be
predictive of meme success. Interestingly, these metrics are not those traditionally used for such prediction but instead are
subtle measures of meme dynamics. These metrics form the basis for learning a classifier which predicts, for a given
meme, whether or not it will diffuse widely. The efficacy of the proposed methodology is demonstrated through analysis
of a sample of 200 memes which emerged online during the second half of 2008.
KEYWORDS
Emerging topic detection, social media, business informatics, predictive analysis.
1. INTRODUCTION
The enormous popularity of “social media”, such as blogs, forums, and social networking sites, represents a
significant challenge to standard business models and practices, as these media move the control of information from companies to consumers (e.g., (Glance et al., 2005), (Ziegler and Skubacz, 2006), (Melville et al.,
2009)). However, social media also offer an unprecedented opportunity to increase business responsiveness
and agility. For example, recent surveys reveal that 32% of the nearly 250 million bloggers worldwide regularly give opinions on products and brands, 71% of active Internet users read blogs, and 70% of consumers
trust opinions posted online by other consumers (Universal McCann, 2010), (Nielson, 2010). Thus social
media are a vast source of business-relevant opinions, and possess a reach that rivals any traditional media
and an influence which substantially exceeds standard advertising channels.
Businesses are therefore strongly motivated to pay attention to social media and other online sources. For
instance, it is important for companies to be able to rapidly detect emerging topics of discussion and consumer trends. Customer complaints and other negative information are much easier to address if discovered
quickly, while early positive “buzz” can be leveraged and amplified. This paper considers the problem of
automated detection and characterization of emerging topics and trends in social media. Recently (Leskovec
et al., 2009) proposed that monitoring social media to spot emerging memes – distinctive phrases which act
as “tracers” for discrete cultural units – can enable early discovery of new topics and trends. These researchers present an elegant solution to the meme detection problem and show that their algorithm is efficient
enough to allow Web-scale analysis. However, a challenge with this method is the fact that the vast majority
of online memes attract little attention before fading into obscurity. In contrast, in most business applications
we are interested in those memes, and the underlying topics, that reach a nontrivial fraction of the population.
This consideration motivates our interest in predictive analysis of meme dynamics: we wish to identify
those memes which will go on to attract substantial attention, and to do so early in the meme lifecycle. This
capability is essential for practical emerging topic discovery, as it would enable early detection of the emergence of significant topics and trends. Standard approaches to predictive analysis of social diffusion phenomena like meme propagation assume, either explicitly or implicitly, that diffusion events which “go viral”
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possess more appealing “intrinsics” than those which don’t, and focus attention identifying these intrinsics
(Salganik et al., 2006). Recent research calls into question this intuitively plausible premise, indicating that
intrinsic attributes typically don’t possess much predictive power (Salganik et al., 2006), (Colbaugh and
Glass, 2009), (Colbaugh et al., 2010).
This paper proposes that generating useful predictions about social diffusion requires careful consideration of the way individuals influence one another through their social networks. We present a new predictive
methodology which exploits information about network topology and dynamics to accurately forecast which
memes will propagate widely, appearing in hundreds or thousands of blog posts, and which will not. The
particular network features used by the prediction algorithm are those identified as likely to be predictive of
meme success by our recently proposed predictability assessment method (Colbaugh and Glass, 2009). Interestingly, the metrics nominated by this theoretical analysis turn out to be fairly subtle measures of the network dynamics associated with early meme diffusion. Meme prediction is accomplished by a machine learning algorithm that, based upon very early network dynamics, is able to accurately distinguish memes which
will ultimately diffuse widely from those that will not. The efficacy of the proposed algorithm is demonstrated through an empirical study of “successful” and “unsuccessful” memes associated with topics of discussion
that emerged in social media during the second half of 2008. Perhaps surprisingly, we find that although
memes typically propagate for weeks, useful predictions can be made within the first twelve hours after a
meme is detected.
2. PROBLEM FORMULATION
The goal of this paper is to develop a methodology for early and accurate identification of “memes” that will
propagate widely, thereby enabling the discovery of emerging topics and trends which are likely to attract
significant attention. This objective leads naturally to two predictive analysis tasks: 1.) identify measurables
which are predictive of meme success (e.g., post sentiment, early meme dynamics), and 2.) use these predictive measurables as the basis for classifying memes into two groups – those which will acquire many posts
and those that won’t – very early in the meme lifecycle. To support an empirical evaluation of our proposed
solutions to the above problems, we downloaded from (Memetracker, 2010) the time series data for slightly
more than 70 000 memes. These data contain, for each meme M, a sequence of pairs (t1, URL1)M, (t2,
URL2)M, …, (tT, URLT)M, where tk is the time of appearance of the kth blog post or news article that contains
at least one mention of meme M, URLk is the URL of the blog or news site on which that post/article was
published, and T is the total number of posts that mention meme M. From this set of time series we randomly
selected 100 “successful” meme trajectories, defined as those corresponding to memes which attracted at
least 1000 posts during their lifetimes, and 100 “unsuccessful” meme trajectories, defined as those whose
memes acquired no more than 100 total posts. Note that, in assembling the data in (Memetracker, 2010), all
memes which received fewer than 15 total posts were deleted, and that ~50% of the remaining memes have
<50 posts; thus the large majority of memes are unsuccessful by our definition (as well as according to the
criteria of most business applications).
Two other forms of data were collected for this study: 1.) a large Web graph which includes the websites
that appear in the meme time series, and 2.) samples of the text surrounding the memes in the posts which
contain them. The Web graph, denoted Gweb, was obtained via Web crawling and consists of approximately
550 000 vertices/websites and 1.4 million edges/hyperlinks. Samples of text surrounding memes in posts
were assembled by selecting ten posts at random for each meme and then extracting from each post the paragraph which contains the first mention of the meme.
Meme dynamics possess several characteristics which are likely to make predictive analysis challenging.
For example, the distribution for meme success is strongly right-skewed, with most memes receiving relatively little attention and a few attracting considerable interest (Colbaugh and Glass, 2010); it is known that
predicting the evolution of such phenomena using standard methods is quite difficult (Salganik et al., 2006),
(Colbaugh and Glass, 2009), (Colbaugh et al., 2010). Memes also exhibit highly variable times to acquire
their first few posts and to accumulate their final tally of posts. Figure 1 reports the mean and median times
required for successful and unsuccessful memes to attract five, ten, and their total number of posts and illustrates the evolution of several successful memes. It is interesting to note that the median times for unsuccessful memes to attract early posts is actually shorter than the corresponding times for successful memes.
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IADIS International Conference e-Commerce 2011
Early Meme Dynamics
Successful Memes (>
>1000 posts)
#posts
5
10
total
mean (hr)
108
171
~4400
median (hr)
18.5
41.5
~4400
Unsuccessful Memes (<
<100 posts)
#posts
5
10
total
mean (hr)
375
765
~1010
median (hr)
10.1
30.5
~410
Figure 1. Meme dynamics. In the “stacked” plot at left, thread thickness corresponds to number of posts/articles mentioning the specified meme during that time period (horizontal axis) (Leskovec et al., 2009). The table at right reports the
mean and median time (in hours) required for successful and unsuccessful memes to acquire five posts, ten posts, and
their total number of posts.
3. PREDICTIVE ANALYSIS
In this section we begin by summarizing the application of the predictability assessment process proposed in
(Colbaugh and Glass, 2009), (Colbaugh et al., 2010) to a simple model of meme diffusion. This procedure
reveals two features of meme network dynamics which should be useful for distinguishing successful and
unsuccessful memes early in their lifecycle. We then develop a machine learning-based classification algorithm which employs our new network dynamics metrics to accurately predict, very early in a meme’s lifecycle, whether that meme will propagate widely or not. The performance of the prediction algorithm is illustrated through an empirical study involving successful and unsuccessful memes associated with topics of
discussion that emerged in social media during the second half of 2008.
3.1 Predictability Assessment
Here we summarize the results of applying the predictability assessment procedure derived in (Colbaugh and
Glass, 2009), (Colbaugh et al., 2010) to the task of identifying measurables which should be predictive of
meme success. The discussion begins with brief, intuitive reviews of our predictability assessment process
and social diffusion modeling framework, and then describes the main results obtained through this theoretical analysis.
Predictability. Consider a simple model of information diffusion, in which individuals combine their
own beliefs and opinions regarding a new piece of information with their observations of the actions of others to arrive at their decisions about whether to pass along the information. In such situations it can be quite
difficult to determine which characteristics of the diffusion process, if any, are predictive of things like the
speed or ultimate reach of the diffusion (Salganik et al., 2006), (Colbaugh. and Glass, 2009), (Colbaugh et
al., 2010). In (Colbaugh and Glass, 2009), (Colbaugh et al., 2010), we propose a mathematically rigorous
approach to predictability assessment which, among other things, permits identification of features of social
dynamics which should have predictive power; we now summarize this assessment methodology.
The basic idea behind the proposed approach to predictability analysis is simple and natural: we assess
predictability by answering questions about the reachability of diffusion events. To obtain a mathematical
formulation of this strategy, the behavior about which predictions are to be made is used to define the system
state space subsets of interest (SSI), while the particular set of candidate measurables under consideration
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allows identification of the candidate starting set (CSS), that is, the set of states and system parameter values
which represent initializations that are consistent with, and equivalent under, the presumed observational
capability. As a simple example, consider an online market with two products, A and B, and suppose the system state variables consist of the current market share for A, ms(A), and the rate of change of this market
share, r(A) (ms(B) and r(B) are not independent state variables because ms(A) + ms(B) = 1 and r(A) + r(B) =
0); let the parameters be the advertising budgets for the products, bud(A) and bud(B). The producer of item A
might find it useful to define the SSI to reflect market share dominance by A, that is, the subset of the twodimensional state space where ms(A) exceeds a specified threshold (and r(A) can take any value). If only
market share and advertising budgets can be measured then the CSS is the one-dimensional subset of stateparameter space consisting of the initial magnitudes for ms(A), bud(A), and bud(B), with r(A) unspecified.
Roughly speaking, the approach to predictability assessment proposed in (Colbaugh and Glass, 2009),
(Colbaugh et al., 2010) involves determining how probable it is to reach the SSI from a CSS and deciding if
these reachability properties are compatible with the prediction goals. If a system’s reachability characteristics are incompatible with the given prediction question – if, say, “hit” and “flop” states in the online market
example are both fairly likely to be reached from the CSS – then the situation is deemed unpredictable. This
setup permits the identification of candidate predictive measurables: these are the measurable states and/or
parameters for which predictability is most sensitive (Colbaugh and Glass, 2009). Continuing with the online
market example, if trajectories with positive early market share rates r(A) are much more likely to yield market share dominance for A than are trajectories with negative early r(A), then the situation is unpredictable
(because the outcome depends stronly on r(A) and this quantity is not measured). Moreover, this analysis
suggests that market share rate is likely to possess predictive power, so it may be possible to increase predictability by adding the capacity to measure this quantity.
Model. In social diffusion, people are affected by what others do. This is easy to visualize in the case of
disease transmission, with infections being passed from person to person. Information, such as that in the
topics of discussion underlying memes, can also propagate through a population, as individuals become
aware of information and persuaded of its relevance through their social and information networks. The dynamics of information diffusion can therefore depend upon the topological features of the pertinent networks.
This dependence suggests that, in order to identify features of social diffusion which possess predictive power, it is necessary to assess predictability using social and information network models with realistic topologies.
Specifically, the social diffusion models examined in this study possess networks with four topological
properties that are ubiquitous in real-world social and information networks and which have the potential to
impact diffusion dynamics:
• right-skewed degree distribution – the property that most vertices have only a few network neighbors
while a few vertices have many neighbors;
• transitivity – the property that the network neighbors of a given vertex have a heightened probability of
being connected to one another;
• community structure – the presence of densely connected groupings of vertices which have only relatively few links to other groups;
• core-periphery structure – the presence of a small group of “core” vertices which are densely connected
to each other and are also close to the other vertices in the network.
It is shown in (Colbaugh and Glass, 2009) that stochastic hybrid dynamical systems (S-HDS) provide a
powerful mathematical formalism with which to represent social diffusion on realistic networks. An S-HDS
is a feedback interconnection of a discrete-state stochastic process, such as a Markov chain, with a family of
continuous-state stochastic dynamical systems (Colbaugh and Glass, 2009). Combining discrete and continuous dynamics within a unified, computationally tractable framework offers an expressive, scalable modeling environment that is amenable to formal mathematical analysis. In particular, S-HDS models can be used
to efficiently represent social diffusion on large-scale networks with the four topological properties listed
above (Colbaugh and Glass, 2010).
As an intuitive illustration of the way S-HDS enable effective, tractable modeling of complex network
phenomena, consider the task of modeling diffusion on a network that possesses community structure. As
shown in Figure 2, this diffusion consists of two components: 1.) intra-community dynamics, involving frequent interactions between individuals within the same community and the resulting gradual change in the
concentrations of “infected” (red) individuals, and 2.) inter-community dynamics, in which the “infection”
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IADIS International Conference e-Commerce 2011
jumps from one community to another, for instance because an infected individual “visits” a new community.
S-HDS models offer a natural framework for representing these dynamics, with the S-HDS continuous system modeling the intra-community dynamics (e.g., via stochastic differential equations), the discrete system
capturing the inter-community dynamics (e.g., using a Markov chain), and the interplay between these dynamics being represented by the S-HDS feedback structure.
inter-community
dynamics
i
j
inputs
discrete
system
mode
outputs
continuous
system
inputs
k
intra-community
dynamics
Figure 2. Modeling diffusion on networks with community structure via S-HDS. The cartoon at top left depicts a network
with three communities. The cartoon at right illustrates diffusion within a community k and between communities i and j.
The schematic at bottom left shows the basic S-HDS feedback structure; the discrete and continuous systems in this
framework model the inter-community and intra-community diffusion dynamics, respectively.
Results. We have applied the predictability assessment methodology summarized above to a class of empirically-grounded S-HDS models for social diffusion, thereby obtaining a fairly comprehensive theoretical
characterization of the predictability of meme propagation on networks with realistic topologies. The main
findings, of the study, from the perspective of this paper, is a demonstration that predictability of these diffusion models depends crucially upon social and information network topology, and in particular on a network’s community and core-periphery structures. We now summarize the main conclusions of this study; a
more complete discussion of the results is given in (Colbaugh and Glass, 2010).
Community structure is widely recognized to be important in real-world networks, and there exists a
range of qualitative and quantitative definitions for this concept. Here we adopt the modularity-based definition proposed in (Newman, 2006), whereby a good partitioning of a network’s vertices into communities is
one for which the number of edges between putative communities is smaller than would be expected in a
random partitioning. To be concrete, a modularity-based partitioning of a network into two communities
maximizes the modularity Q, defined as Q = sT B s / 4m, where m is the total number of edges in the network,
the partition is specified with the elements of vector s by setting si = 1 if vertex i belongs to community 1 and
si = −1 if it belongs to community 2, and the matrix B has elements Bij = Aij − kikj / 2m, with Aij and ki denoting the network adjacency matrix and degree of vertex i, respectively. Partitions of the network into more
than two communities can be constructed recursively (Newman, 2006). With this definition in hand, we are
in a position to present the first candidate predictive feature nominated by the theoretical predictability assessment: early dispersion of a diffusion process across network communities should be a reliable predictor
that the ultimate reach of the diffusion will be significant (see Figure 3 for an illustration of the basic idea).
Analogously to the situation with network communities, there exist several descriptions of core-periphery
structure in networks. Here we adopt the characterization of network core-periphery which results from kshell decomposition, a well-established technique in graph theory which is summarized, for instance, in
(Carmi et al., 2007). To partition a network into its k-shells, one first removes all vertices with degree one,
repeating this step if necessary until all remaining vertices have degree two or higher; the removed vertices
constitute the 1-shell. Continuing in the same way, all vertices with degree two (or less) are recursively re-
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moved, creating the 2-shell. This process is repeated until all vertices have been assigned to a k-shell, and the
shell with the highest index, the kmax-shell, is deemed to be the core of the network. Given this definition, we
are in a position to report the second candidate predictive feature nominated by the theoretical predictability
assessment: early diffusion activity within the network kmax-shell should be a reliable predictor that the ultimate reach of the diffusion will be significant. An intuitive illustration of this result is depicted in Figure 4.
Figure 4. Early diffusion within the core is predictive.
The cartoon illustrates the predictive feature associated with k-shell structure: social diffusion initiated
with three “seed” individuals is much more likely to
propagate widely if these seeds reside within the network’s core (left) rather than at its periphery (right).
Note that in (Colbaugh and Glass, 2010) this result is
established for networks of realistic scale and not
simply for “toy” networks.
Figure 3. Early dispersion across communities is predictive. The cartoon illustrates the predictive feature
associated with community structure: social diffusion
initiated with five “seed” individuals is much more
likely to propagate widely if these seeds are dispersed
across three communities (right) rather than concentrated within a single community (left). Note that in
(Colbaugh and Glass, 2010) this result is established for
networks of realistic scale and not simply for “toy”
networks.
3.2 Prediction
We now turn to the task of developing a machine learning-based classifier which is capable of accurately
predicting, very early in the lifecycle of a meme of interest, whether that meme will propagate widely. Two
types of classification algorithm were tested, one simple (standard naïve Bayes (Hastie et al., 2009)) and one
sophisticated (the Avatar ensembles of decision trees algorithm (Avatar, 2010)), to allow the robustness of
the proposed approach to meme prediction to be evaluated. While the two classifiers produce qualitatively
similar results, the Avatar algorithm, denoted A-EDT, is substantially more accurate; thus in what follows
only the results obtained with A-EDT are reported.
Recall that the task of interest is to learn a classifier which takes as input some combination of relevant
post content and meme dynamics and accurately predicts whether a given meme will ultimately be successful
(acquire ≥1000 posts during its lifetime) or unsuccessful (attract ≤100 total posts). We employ standard tenfold cross-validation to estimate the accuracy of our classifier. More specifically, the set of 200 memes (100
successful and 100 unsuccessful) is randomly partitioned into ten subsets of equal size, and the A-EDT algorithm is successively “trained” on nine of the subsets and “tested” on the held-out subset in such a way that
each of the ten subsets is used as the test set exactly once.
A crucial aspect of the analysis is determining which characteristics of memes and their dynamics, if any,
possess exploitable predictive power. We consider three classes of features:
• language-based measures, such as the sentiment and emotion expressed in the text surrounding memes
in posts;
• simple dynamics-based metrics, capturing the early volume of posts mentioning the meme of interest
and the rate at which this volume is increasing;
• network dynamics-based features, such as those identified through the predictability analysis summarized in Section 3.1.
We now describe each of these feature classes. Consider first the language-based measures. Each “document” of text surrounding a meme in its (sample) posts is represented by a simple “bag of words” feature
vector x∈ℜ|V|, where the entries of x are the frequencies with which the words in the vocabulary set V appear
in the document. The sentiment and emotion of a document may be quantified very simply through the use of
appropriate lexicons. Let s∈ℜ|V| denote a lexicon vector, in which each entry of s is a numerical “score”
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IADIS International Conference e-Commerce 2011
quantifying the sentiment or emotion intensity of the corresponding word in the vocabulary V. The sentiment
or emotion score of document x can then be computed as score(x) = sTx / sT1, where 1 is a vector of ones.
Note that this simple formula estimates the sentiment or emotion of a document x as a weighted average of
the sentiment or emotion scores for the words comprising the document. (If no sentiment or emotion information is available for a particular word in V then the corresponding entry of s is set to zero.)
To characterize the emotion content of a document we use the Affective Norms for English Words
(ANEW) lexicon (Bradley and Lang, 1999); this lexicon consists of 1034 words to which human subjects
assigned numerical scores with respect to three emotion “axes” – happiness, arousal, and dominance. Previous work has shown this set of words bears meaningful emotional content (Bradley and Lang, 1999). Positive or negative sentiment is quantified by employing the “IBM lexicon”, a collection of 2968 words that
were assigned {positive, negative} sentiment labels by human subjects (Ramakrishnan et al., 2003). This
simple approach generates four language features for each meme: the happiness, arousal, dominance, and
positive or negative sentiment of the text surrounding that meme in the (sample) posts containing it. As a
preliminary test, we computed the mean emotion and sentiment of content surrounding the 100 successful
and 100 unsuccessful memes in our dataset. On average the text surrounding successful memes is happier,
more active, more dominant, and more positive than that surrounding unsuccessful memes, and this difference is statistically significant (p<0.0001). Thus it is at least plausible that these four language features may
possess some predictive power regarding meme success.
Consider next two simple dynamics-based features, defined to capture the basic characteristics of the early evolution of meme post volume:
• #posts(τ) – the cumulative number of posts mentioning the given meme by time τ (where τ is small
relative to the typical lifespan of memes);
• post rate(τ) – a simple estimate of the rate of accumulation of such posts at time τ.
Here we estimate post rate via the finite difference formula post rate(τ) = (#posts(τ) − #posts(τ/2)) / (τ/2);
of course, more robust rate estimates could be used.
The simple dynamics-based measures of early meme diffusion defined above, while potentially useful, do
not characterize the manner in which a meme propagates over the underlying social or information networks.
Recall that the predictability assessment summarized in Section 3.1 suggests that both early dispersion of
diffusion activity across network communities and early diffusion activity within the network core ought to
be predictive of meme success. This insight motivates the definition of two network dynamics-based features
for meme prediction:
• community dispersion(τ) – the cumulative number of network communities in Web graph Gweb that, by
time τ, contain at least one post which mentions the meme;
• #k-core blogs(τ) – the cumulative number of blogs in the kmax-shell of Web graph Gweb that, by time τ,
contain at least one post which mentions the meme.
These quantities can be efficiently computed using fast algorithms for partitioning a graph into its communities and for identifying a graph’s kmax-shell (Colbaugh and Glass, 2010), so the features are readily
computable for large graphs.
We now summarize the main results of the prediction study (see (Colbaugh and Glass, 2010) for a more
complete description of the results). First, using the four language features with the A-EDT algorithm to predict which memes will be successful yields a prediction accuracy of 66.5% (ten-fold cross-validation). Since
simply guessing “successful” for all memes gives an accuracy of 50%, it can be seen that these simple language “intrinsics” are not very predictive. For completeness it is mentioned that the ANEW score for “arousal” and the IBM measure of sentiment are the most predictive of the language features.
In contrast, the features characterizing the early network dynamics of memes possess significant predictive power, and in fact are useful even if only very limited early time series is available for use in prediction.
More quantitatively, applying the A-EDT algorithm together with the five meme dynamics features produces
the following results (ten-fold cross-validation):
• τ = 12hr, accuracy = 84.0%, most predictive features: 1.) community dispersion, 2.) #k-core blogs, 3.)
#posts.
• τ = 24hr, accuracy = 91.5%, most predictive features: 1.) community dispersion, 2.) post rate, 3.)
#posts.
• τ = 48hr, accuracy = 92.8%, most predictive features: 1.) community dispersion, 2.) post rate, 3.)
#posts.
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ACKNOWLEDGEMENT
This work was supported by the U.S. Department of Defense and the Laboratory Directed Research and Development Program at Sandia National Laboratories.
REFERENCES
Avatar, 2010. http://www.sandia.gov/avatar/, accessed July 2010.
Bradley, M. and Lang, P., 1999. Affective Norms for English Words (ANEW): Stimuli, Instruction Manual, and Affective Ratings. Technical Report C1, University of Florida.
Carmi, S. et al., 2007. A Model of Internet Topology Using the K-Shell Decomposition. Proc. National Academy of
Sciences USA, Vol. 104, pp. 11150-11154.
Colbaugh, R. and Glass, K., 2010. Prediction of Social Dynamics via Web Analytics. Sandia National Laboratories
SAND Report.
Colbaugh, R. and Glass, K., 2009. Predictive Analysis for Social Processes I: Multi-scale Hybrid System Modeling, and
II: Predictability and Warning Analysis. Proc. 2009 IEEE Multi-Conference on Systems and Control, Saint Petersburg, RU.
Colbaugh, R. et al., 2010. Predictability of ‘Unpredictable’ Cultural Markets. Proc. 105th Annual Meeting of the American Sociological Association, Atlanta, GA, USA.
Glance, N. et al., 2005. Deriving Marketing Intelligence from Online Discussion. Proc. 11th ACM Int. Conf. on Knowledge Discovery and Data Mining, Chicago, IL, USA.
Hastie, T. et al., 2009. The Elements of Statistical Learning. Second Edition. Springer, New York, USA.
Leskovec, J. et al., 2009. Meme-tracking and the Dynamics of the News Cycle. Proc. 15th ACM Int. Conf. on Knowledge
Discovery and Data Mining, Paris, FR.
Melville, P. et al., 2009. Social Media Analytics: Channeling the Power of the Blogosphere for Marketing Insight. Proc.
Workshop on Information in Networks, New York, NY, USA.
Memetracker, 2010. http://memetracker.org, accessed January 2010.
Newman, M., 2006. Modularity and Community Structure in Networks. Proc. National Academy of Sciences USA, Vol.
103, pp. 8577-8582.
Nielson, 2010. http://www.nielson.com, accessed July 2010.
Ramakrishnan, G. et al., 2003. Question Answering via Bayesian Inference on Lexical Relations. Proc. Annual Meeting
of the Association for Computational Linguistics, Sapporo, JP.
Salganik, M. et al., 2006. Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market. Science,
Vol. 311, pp. 854-856.
Universal McCann, 2010. http://www.universalmccann.com, accessed July 2010.
Ziegler, C. and Skubacz, M., 2006. Towards Automated Reputation and Brand Monitoring on the Web. Proc. IEEE/
ACM Int. Conf. on Web Intelligence, Hong Kong.
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IADIS International Conference e-Commerce 2011
E-LEARNING SEEN AS AN ENTERPRISE BUSINESS
PROCESS
Fodé Touré and Esma Aïmeur
Department of Computer Science and Operations Research,
Université de Montréal, Montreal, Canada
ABSTRACT
The investment in the human capital, by means of training delivered in enterprise, became an important constituent of
enterprise competitiveness strategy. Consequently business managers require the proofs of training investment yield, in
terms of tangible and intangible profits, from their human resources managers, training departments, or even from
training consultants.
To evaluate enterprise training, two models predominate, namely the model of Kirkpatrick and that of Phillips.
In this paper, we propose an approach of training project evaluation, based on business process management. It is an
approach which fills the gaps raised in the literature and ensures an alignment between training activities and business
needs.
KEYWORDS
Business Process Management, Business Intelligence, e-Learning, Evaluation, Optimization, Business Activity
Monitoring.
1. INTRODUCTION AND PROBLEMATIC
Individual and collective skills are the most important assets of organizations, and determine their
productivity, competitiveness and ability to adapt and to be proactive when uncertain. Training is a key
strategy for generating these skills for employees (Pineda, 2010). Consequently business managers require
from their human resources managers, training departments, or even of consultants working in the field of
training, the proofs of training investment yield in terms of tangible and intangible profits.
In a report entitled “Return to Enterprises on Training Investment”, the Australian government concludes
that, “unless the Return On Investment (ROI) in training is quantified, the transition towards a company with
high yield is not assured”. Besides, a national report published in 2006 underlines the necessity of
demonstrating, to the business community, the critical importance of the training in the improvement of the
yield and net enterprise profits : “if we want that Irish enterprises makes a great use of training, it is essential
to prove its contribution to the objectives of the company” (Bailey, 2007).
Measuring the value of learning is an ongoing challenge. Many organizations assess whether learners
liked a course or acquired new knowledge, but few have cracked the code on how to determine learning ROI.
The most commonly used metrics for evaluating training programs are those derived from the work of
Donald L. Kirkpatrick in the book "Evaluating Training Programs: The Four Levels (Kirkpatrick, 1994)." Dr.
Jack J. Phillips suggests another type of evaluation in his book "Return on Investment in Training and
Performance Improvement Programs (Phillips, 1997)." Phillips believes that learning professionals should
calculate costs for specific training interventions and then quantify the business benefit to determine the
organization's ROI from training. Table 1 shows the measures of course evaluation reported in the 2008
Benchmarking Study conducted by Corporate University Xchange (Rozwell, 2009).
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ISBN: 978-972-8939-51-9 © 2011 IADIS
Table 1. Course Evaluation Methods by Level (Source: Corporate University Xchange 8th Annual Benchmarking Study,
2008, in (Rozwell, 2009))
Course Method
Level 1: opinion of on the course and
instructor
Level 2: knowledge acquisition
Level 3: behavior change
Level 4: business impact
Level 5: Return On Investment (ROI )
Percentage of Courses Evaluated Using this Method
75%
47%
20%
12%
6%
There are several models in the literature. Some of these models allow calculating the return on the
invested capital, and could help organizations to make better educated decisions regarding workforce
training. The benchmark model in terms of enterprise training evaluation is that of Kirkpatrick. Kirkpatrick's
model includes four levels or steps of outcome evaluation (reaction, learning, behavior, results). In 1996,
Phillips added a fifth level. This level is solely dedicated to measuring the "Return On Investment (ROI)."
Because of the difficulties bound to the use of these models, human resource departments cannot
estimate, in a concrete way, the impact of the training on the economic and social growth of their enterprise.
Indeed, in France for instance, a synthesis entitled “Les pratiques d'évaluation des formations des entreprises
françaises”, concludes that reactions evaluation (level 1 of Kirkpatrick’s model) remains the most practised,
both by enterprises and by training institutions. Besides, methodological problems are also highlighted by
respondents, in particular for evaluation levels 3, 4 and 5 (the level 5 corresponds to Phillips’ model) and
isolation of training effects in the results. Furthermore, reports drafted by several organizations such as the
Canadian Policy Research Networks (CPRN), the Conference Board of Canada, the Canadian Council on
Learning (CCL) abound in the same sense: Canadian enterprises do not invest enough in training compared
with the other countries with economic high yield. They still hesitate to dedicate the necessary resources to
training, because of the difficulty to evaluate the impact of this investment on organizational outcome.
In this paper, we propose a training project management approach based on business process
management: going from concept to optimization, via the evaluation of the financial and none financial
return.
In the remainder of this paper, we shall present, in section 2, the two basic models for evaluating the
training in enterprise, the advantages and criticism of these models. Section 3 will be dedicated to the
presentation of our model and a final conclusion is presented in section 4.
2. EXISTING MODELS OF ENTERPRISE TRAINING PROGRAM
EVALUATION
The concept of yield covers a rather wide spectrum, going from effect perception to the return on investment
calculation. These two dimensions join the distinction made by Dunberry and Péchard (Dunberry and
Péchard, 2007) between “financial yield” to describe the measure or the calculation of what the training
brings to the organization on financial plan and “training results” to describe the impact or the effects which
are not of financial nature.
Before we present how our approach treats all these factors, it seems important to discuss the basic
models that influence the training evaluation practices in enterprise. We begin with the presentation of the
Kirkpatrick’s four levels. Afterwards, we shall see the version modified by Philips in 1996, adapted to
include a measure of the ROI.
2.1 Kirkpatrick’s four Levels of Evaluation Model
Kirkpatrick’s model began in 1959, with a series of four articles on the evaluation of training programs in the
journal “Training and Development”. These four articles defined the four levels of evaluation that would later
have a significant influence on corporate practices.
The four levels of Kirkpatrick's evaluation model essentially measure:
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Level 1 – Reaction of students. How did the trainees react after the training? Did they appreciate this
one? Are they satisfied? What they thought and felt about the training.
Level 2 – Learning. What they learnt after the training? What knowledge, skills and/or attitudes
(knowledge, know-how, and social skills) have been acquired? Have educational objectives been achieved?
The resulting increase in knowledge or capability. It is about the educational evaluation.
Level 3 – Behavior. Do the trainees use what they learned in training at their workstations? What are
the new professional behaviors that have been adopted? Extent of behavior and capability improvement and
implementation/application.
Level 4 – Results. What is the impact of the training on the results of the company? Example: decrease
in the rate of absenteeism, occupational accidents, growth of turnover, the productivity, customer satisfaction,
etc. The effects on the business or the environment resulting from the trainee's performance.
The first level evaluates participant’s satisfaction after the training and is based on several aspects of the
training (such as objectives, contents, educational methods, teaching style and material available). This
satisfaction is judged in the form of questionnaires. It is the level most frequently used (see Table 1). The
second level measures “learning” of the participants in term of knowledge, skills and attitudes that were
acquired during the training. This measure is mostly made by means of questionnaires or other systems of
systematized evaluation (examinations, for example). The third tier assesses the “behavioral changes” in the
training and the transfer of learning. It is a question of spotting the knowledge, the skills and the attitudes
acquired during the training which give rise to a re-use in the professional practice. This measure is mostly
carried out by questionnaires or interviews and can be performed several times (at the beginning, at the end
and sometimes after the training). The fourth level is the level of the "results" corresponding to the
calculation of various metrics elaborated in connection with the objectives of the training, during the design
of which, they were defined.
A certain number of authors criticize this model. First of all, it is noted that this model cannot be used to
determine cost/benefit ratio and cannot be used to emit a diagnosis when the training has not produced the
expected results. Kraiger (Kraiger, 2002) identifies five major criticisms against the model of Kirkpatrick:
1) The model has little theoretical basis and ignores all the achievements of cognitive theories of the 70s
and 80s,
2) The constructs used, such as the satisfaction or the learning, are not clearly defined, and more complex
than they appear,
3) A strict application of the approach brings illogical behaviour, like not evaluating the learning before
confirming a positive reaction while the participants might be more available.
4) The approach presumes relations between the results of the training which are not confirmed, as it is
the case between the satisfaction and the learning,
5) The approach ignores the purpose of evaluation, by inciting to estimate four levels, while in some
cases the evaluation of the other criteria would be more relevant in regards to the needs of the enterprise.
Another criticism concerns the simple/complex dilemma. At the level of the Kirkpatrick’ model, it is
translated in the following way: trainers use mainly the results obtained from levels 1 (satisfaction) and 2
(learning) as proof of the training’s success, while the exact measure of training impacts on the
performance, that the administrators would wish to obtain, is much more difficult to calculate (Goldwasser,
2001).
Consequently, although the four-level model of Kirkpatrick is widely recognized and accepted, and
although a significant number of evaluation methods find their base there, many have argued that this method
does not provide the data required by managers today, which Phillips has to overcome.
2.2 The Model of Return on Investment of Phillips
To calculate the training yield, Philips recommends adding a fifth level to the model of Kirkpatrick: the yield
of training in enterprise. He established a methodology to convert the subjective, objective, tangible and less
tangible data into monetary units. To do this, the user has to take the data obtained at the level 4 of the initial
model of Kirkpatrick and convert them in monetary values and subsequently, compare these results with the
cost of the training program. According to this model, the calculation of the yield of the training is made by
means of a process by stages which supplies a plan detailed for the planning, the collection and the data
analysis, which includes the calculation of ROI. The process begins with the evaluation planning: where
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objectives are developed and decisions taken on the way the data will be collected treated and analyzed. The
data collection is made according to training evaluation levels (level 1: reactions / satisfaction; level 2:
learning; level 3: transfer of the learning and the level 4: the organizational results). Finally, at the level of
the data analysis, we have the crucial stages for the analysis of ROI:
Isolate the effects of the training from the other factors of influence (use of one or several methods to
separate the influence of the training project from the other factors which influence the measure of the
organizational results),
Convert the data concerning the organizational impacts into money value for developing an annual
value of the project,
Profits and costs are combined in the ROI calculation,
The intangible profits are identified by this process (they are included in this category only after
having tried to convert them in money values).
However, in the literature, several criticisms are raised with regard to the model of Phillips. Nagle (2002)
relates a series of criticisms towards ROI: difficulty to have a faithful measure; expensive process; complex
process; process that can take up to one year, presence of the other factors (independent from the training)
that influence the performance of the organization.
Concerning the methodological problems, McCain (McCain, 2005) has established a list of the bias that
are likely to have an impact on the observed results and that may not necessarily come to the attention of the
training professional. We can quote the bias of a sample (selection of a non representative sample or one with
a too small size), bias in the interviews (make sure of the good understanding of the questions for example),
bias of acquiescence or neutrality according to the questions presentation.
In conclusion, this second section shows that several models of training evaluation in enterprise exist in
the literature. Nonetheless, because of the difficulties bound to the use of these models, the department of
human resources does not manage to estimate in a concrete way the impact of the training on the economic
and social growth of the enterprise. Thus, to try to bring a solution to the enterprise needs, we present in the
following section an approach of training yield evaluation, based on the business process management.
3. A MODEL OF EVALUATION OF THE TRAINING BASED ON
BUSINESS PROCESS MANAGEMENT
Business Process Management (BPM) represents a strategy of managing and improving business
performance by continuously optimizing business processes in a closed-loop cycle of modeling, execution,
and measurement (Oracle, 2008). As organizations continue to focus on improving and managing business
processes, the ability to acquire and cultivate the appropriate skilled workforce has remained a challenge.
While Business Process Management was once defined in terms of tools and technologies, it has recently
emerged as a discipline encompassing a broad spectrum of organizational practices. As a result, the skillsets
for BPM endeavors of today's organizations have gone beyond the automation of processes to encompass a
wide variety of strategic and technical skills (Antonucci, 2010).
Upon the success achieved by the BPM solutions in the management of enterprise processes, why not use
this approach to manage, efficiently, the training activities in enterprise? An affirmative answer to this
question suggests that we have to consider these activities as business processes.
Indeed, the design and implementation of a training project suppose getting through various stages: going
from the formulation of a request up to the implementation of new skills. The set of these stages,
chronologically listed, constitutes a process, in the terms of which we can record a capital gain, if everything
correctly took place (Bach, 2007). Training is a strategic tool of development. As such, it is induced by a
project, at the origin of which there were some problems that needed to be addressed:
Social problem: for example, it is necessary to decrease the number of unemployed by proposing in
particular specific trainings to help them find some work,
Enterprise problem: for example, the introduction of new machines requires the implementation of a
training for their use,
Individual problem: for example, people wishing to acquire new knowledge to increase their
professional mobility.
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For the management of the training projects in enterprise, we propose an approach based on five stages,
as shown in Figure 1.
Figure 1. Steps of management of a training program in enterprise
3.1 Stage 1: Study of Training Project
The training in the enterprise is an integrated training, which covers the personal development of the
employees, the enterprise and its services (Figure 2). It consists of a series of specific actions, intended to
resolve a problem with which the enterprise is confronted. Thus, the first stage of our approach consists in
analyzing the demand for training and associating it with elements of performance of the enterprise. It is
translated by a certain number of actions such as: the conversations of exploration of the demand, the
definition of a plan of change, needs analysis, definitions of the objectives, the definition and the choice of
performance indicators, etc.
Figure 2. The impact of an integrated training project (Bach, 2007)
3.2 Stage 2: Modeling and Validation
A process model is the formal definition of a business process. The objective of a model is to produce highlevel specifications of workflows, independently of workflow management system. Consequently, the
processes must be correctly modeled before they are implemented as workflows. The deployment of invalid
processes can lead applications based on these processes to incoherent states and can even provoke very
critical breakdowns without the slightest possibility of resumption. In other words, if a process is put in
production before being validated, it could fail during the execution and cause considerable loss to the
enterprise. To model a business process we use graphical objects developed by Workflow Management
Coalition (WfMC, 1999). In this language, the processes are modeled by using two object types: node and
flow. The node is classified in two categories: task and condition. A task, graphically represented by a
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rectangle, represents the work to be made to achieve some objectives. A condition, graphically represented
by a circle, is used to build choice structures. A flow, which is graphically represented by an arrow, links two
nodes in graph. There are several aspects in a process model validation including the structure, the dataflow,
the roles, the application interface, the temporal constraints and others. Process structure is the most
important and primary aspect of a process model. It builds the base to capture other needs aspect of the
process model. Thus, structural validation is all techniques used to identify incorrect objects combinations
and all means allowing to avoid them or possibly to correct them in order to increase the pre-execution
reliability of a process.
A Directed Acyclic Graph (DAG) can contain two types of structural conflict: deadlock and lack of
synchronization (Sadiq and Orlowska, 1999), (Van der Aalst et al., 2002), (Lin et al., 2002), (Sadiq et al.,
2004). In order to verify or to assure the correctness of a process model, several propositions were made of
among which: reduction-based algorithms (Sadiq and Orlowska, 2000) (Lin et al., 2002), graph-traversalbased algorithm (Perumal and Mahanti, 2007), approach of transformation of a non valid model into a
valid one (Liu and Kumar, 2005), hybrid approach based on reduction-based algorithms and graph-traversal
algorithm (Touré et al., 2008), approach of model conversion in Petri net (Van der Aalst et al., 2002).
For the management of a training project, there are at least two models of process: the model of process
bound to the plan of the training and the model of process bound to the stages of evaluation of the training
yield (including the stages of evaluation presented in the section 2).
3.3 Stage 3: Configuration and Execution
This stage is dedicated to the evaluation before and during the execution, the initialization of indicators by
their current values in the enterprise before the execution of the training project.
The choice of indicators depends on the type of training and especially the target objectives of the
enterprise. Table 2 presents examples of indicators.
Table 2. Some possible indicators (Bach, 2007)
Satisfaction
Security
Quantitative
- personnel turnover
- rate of absenteeism
- rate of complaints
- rate of abandonments
- numbers of complaints
- deadline of wait
- volume of dysfunctions
- number of accidents
- number of alerts
Qualitative
- index of satisfaction
- typology of complaints
- rate of recommendations
Financial
- cost replacements and
training
- cost of complaints
- gains produced by
recommendations
- typology of dysfunctions
- types of accidents / alerts
- cost of dysfunctions
- cost of accidents
The execution corresponds to the operational phase where the solution of BPM is implemented. It is in
this stage that the evaluation of levels 1, 2 and sometimes 3 of the model of Kirkpatrick (during execution
some of indicators will already be under observation) is performed.
3.4 Stage 4: Monitoring
Monitoring encompasses tracking of individual processes, such as information on their status can be easily
seen, and statistics on the performance of one or more processes can be provided. The degree of monitoring
depends on what information the enterprise wants to evaluate and analyze, and how the enterprise wants it to
be monitored, whether in real-time, near real-time or ad-hoc. Here, business activity monitoring (BAM)
extends and expands the monitoring tools generally provided by business process management System
(BPMS).
This stage of our approach consists in controlling the progress of the processes. A control based on
precise indicators and relevant in order to have dashboards allowing quick and good decision making.
The dashboard of the training has to cover two big dimensions: the efficiency and the efficacy. The
training process is said to be efficient if it gives the maximum of results by consuming the minimum of
resources and is said to be effective if it gives the expected results.
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The dashboard of the efficiency of the training will be composed of indicators on consumption of
resources and on activities output allowing the measuring of the efficiency of each of the three stages of the
process, as well as the general efficiency of the training project. Indicators below allow building the
dashboard of the efficiency of a training program: time dedicated to the identification and to the needs
analysis (combined time of the employee, his superior and the training manager), perceived usefulness of the
training / time dedicated, the gap between what the employee masters and what he has to master, the
adequate level of training to reduce or cancel the gap (beginner, intermediate, advanced), mode of training
(external, internal, coaching, e-learning, tutoring, etc.), time to design and the elaboration of the program, etc.
The indicator can be analyzed by sex, seniority, social status, type of training, or operational unity (service,
department, store, etc.). The dashboard of the effectiveness focuses either on the effectiveness of a training,
or on the global effectiveness of the training system. Its structure includes the model of training evaluation
and contains more indicators than the efficiency dashboard.
This stage allows us to calculate the tangible and intangible training benefits (without additional costs) by
using indicators values.
3.5 Stage 5: Optimization
Process optimization includes retrieving process performance information from the modeling or monitoring
phase; identifying the potential or actual bottlenecks and the potential opportunities for cost savings or other
improvements; and then, applying these enhancements in the design of the process. Overall, this creates
greater business value.
In this stage of our approach, we use machine learning algorithms (for example, logistic regression,
neural networks or support vector machines) to classify training activities according to defined criteria
(example, financial yield) and to do simulations to increase the efficiency and efficacy of training activities.
For this, we perform a pretreatment on the indicator values to have a data set for a supervised learning
algorithm, unsupervised or semi-supervised. The stages of monitoring and optimization constitute our
module of business intelligence because they allow: improving personal efficiency, speeding up the process
of decision making, increasing organizational control, encouraging exploration and discovery on the part of
the decision maker, speeding up problem solving in an organization, facilitating interpersonal
communication, promoting learning or training, generating new evidence in support of a decision, creating a
competitive advantage over competition, revealing new approaches to thinking about the problem space, and
helping automate managerial processes.
To materialize our approach, our objective is to provide a tool to help the training projects management in
enterprise with the alignment between the training activities and business needs, modeling and validating of
the training processes, execution and supervision of training projects, calculation of tangible and intangible
profits of training, classification of trainings (in two levels: enterprise - employee), trainings optimization (in
two levels: employee - enterprise)
4. CONCLUSION
Because of the difficulties resulting from the use of existing models, human resource departments cannot
manage to evaluate the impact of the training on the economic and social growth of the enterprise in a
concrete manner. Thus, trying to find a solution, we propose an approach of training yield evaluation, based
on the business process management.
The advantages obtained through our approach can be seen from two angles. In the domain of business
process management, we add a new category of business process and extend Business Process Management
System (BPMS) by adding the validation pre-execution (through our tool). Concerning the evaluation of
enterprise training, we propose a complete approach of training project management facilitating decisionmaking and the calculation of the tangible and intangible profits. With regard to the existing models, we add
a level of diagnostic (classification and optimization) allowing the understanding the dysfunctions in order to
correct them. Our approach ensures the training activities alignment with business needs and allows the ROI
calculation without additional investment. Concerning the problems raised in the literature, we reduce the
bias and additional costs bound to training yield calculation. Indeed, from training conception, we bind
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training objectives and strategies with performance improvements wished by the enterprise. Hence, from the
beginning, the enterprise should be able to connect the effects expected by the training with certain indicators
that it already uses in its current management. When financial yield evaluation will be required, it will be
thus able, without additional costs, to provide data on the quantitative indicators which will show the
evolution of productivity and quality and will be able to translate them into economic value.
REFERENCES
Antonucci, Y. L. (2010). Business process management curriculum. In Bernus, P., Blazewics, J., Schmidt, G., Shaw, M.,
Brocke, J., and Rosemann, M., editors, Handbook on Business Process Management 2, International Handbooks on
Information Systems, pages 423–442. Springer Berlin Heidelberg. 10.1007/978-3-642-01982-1 20.
Bach P., 2007. Le management de projets de formation en entreprise, administration et organisation. De Boeck &
Larcier s.a. , éditions De Boeck Université, rue des Minimes 39, B-1000 Bruxelles.
Bailey A., 2007. Un Investissement Rentable, Mettre l'investissement en formation en rapport avec les résultats
d'entreprise et l'économie. Research Report, Canadian Council on Learning (CCL).
Burkett H., 2005. ROI on a shoe-string: strategies for resource-constrained environments, Measuring more with less (part
I). Industrial and Commercial Training, vol.37, n° 1, p 10-17.
Dunberry A. and Péchard C., 2007. L'évaluation de la formation dans l'entreprise : état de la question et perspectives.
Research Report, Canadian Council on Learning (CCL).
Goldwasser, D., 2001. Beyond ROI (training) . Training, vol 38, number. 1.
Kirkpatrick D. L., 1994 . Evaluating training programs : the four levels. Berrett-Koehler ; Publishers Group West
[distributor], San Francisco : Emeryville, CA :, xv, p. 229
Kraiger, K., 2002. Decision-based evaluation. In Creating, implementing and managing effective training and
development. State-of-the-art lessons for practice. Society for Industrial and Organizational Psychology ed., pp. 331375: Jossey-Bass.
Lin H., Zhao Z., and Li H., and Chen Z., 2002. A Novel Graph Reduction Algorithm to Identify Structural Conflicts.
HICSS, p. 289.
Liu R. and Kumar A., 2005. An Analysis and Taxonomy of Unstructured Workflows. Business Process Management,
p. 268-284.
McCain, D.V., 2005. Evaluation Basics. ASTD Press, Alexandria.
Nagle, B., 2002. ROI gives a way to ROE. Candian HR Reporter, vol. 15, no. 13, p. 7.
Oracle, 2008. Business Process Management, Service-Oriented Architecture, and Web 2.0: Business Transformation or
Train Wreck?. An Oracle White Paper , Updated August 2008.
Perumal S. and Mahanti A., 2007. Applying Graph Search Techniques for Workflow Verification. HICSS, p. 48.
Phillips, Jack J., 1997. Return on investment in training and performance improvement programs. Gulf, Houston
Pineda, P. (2010). Evaluation of training in organisations: a proposal for an integrated model. Journal of European
Industrial Training, 34 Iss: 7:673–693.
Rozwell C., 2009, Forget ROI, Measure Time to Competency to Calculate Learning Value. Gartner Research, ID
Number: G00169917
Sadiq W. and Orlowska M. E., 2000. Analyzing process models using graph reduction techniques. Inf. Syst., vol. 25,
n°2, p. 117—134, Elsevier Science Ltd., Oxford, UK, UK.
Sadiq, S., Orlowska M. E., Sadiq W. and Foulger C., 2004. Data flow and validation in workflow modelling. ADC '04:
Proceedings of the 15th Australasian database conference, Australian Computer Society, Inc., p. 207—214,
Dunedin, New Zealand.
Touré F., Baïna K., and Benali K., 2008. An Efficient Algorithm for Workflow Graph Structural Verification. OTM
Conferences (1), Lecture Notes in Computer Science, Springer, vol. 5331, p. 392-408. Mexico
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Workflow Graphs. CAiSE, p. 535-552.
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ANALYZING SENTIMENT OF SOCIAL MEDIA CONTENT
FOR BUSINESS INFORMATICS
Kristin Glass1 and Richard Colbaugh2
1
New Mexico Institute of Mining and Technology, Socorro, New Mexico 87801 USA
2
Sandia National Laboratories, Albuquerque, New Mexico 87123 USA
ABSTRACT
Inferring the sentiment of social media content, for instance blog postings or online product reviews, is both of great
interest to businesses and technically challenging to accomplish. This paper presents two computational methods for
estimating social media sentiment which address the challenges associated with Web-based analysis. Each method
formulates the task as one of text classification, models the data as a bipartite graph of documents and words, and
assumes that only limited prior information is available regarding the sentiment orientation of any of the documents or
words of interest. The first algorithm is a semi-supervised sentiment classifier which combines knowledge of the
sentiment labels for a few documents and words with information present in unlabeled data, which is abundant online.
The second algorithm assumes existence of a set of labeled documents in a domain related to the domain of interest, and
leverages these data to estimate sentiment in the target domain. We demonstrate the utility of the proposed methods by
showing they outperform several standard methods for the task of inferring the sentiment of online reviews of movies,
electronics products, and kitchen appliances.
KEYWORDS
Sentiment analysis, social media, business informatics, machine learning.
1. INTRODUCTION
The enormous popularity of “social media”, such as blogs, forums, and social networking sites, represents a
significant challenge to standard business models and practices, as these media move the control of
information from companies to consumers (e.g., (Glance et al., 2005), (Ziegler and Skubacz, 2006), (Melville
et al., 2009), (Kaplan and Haenlein, 2010), (van der Lans et al., 2010)). However, social media also offer
unprecedented opportunities to increase business responsiveness and agility. For example, recent surveys
reveal that 32% of the nearly 250 million bloggers worldwide regularly give opinions on products and
brands, 71% of active Internet users read blogs, and 70% of consumers trust opinions posted online by other
consumers (Universal McCann, 2010), (Nielson, 2010). Thus social media is a vast source of businessrelevant opinions. Moreover, this information has a reach that rivals any traditional media and an influence
which substantially exceeds standard advertising channels.
Businesses are therefore strongly motivated to pay attention to social media and other online information
sources. For instance, it is crucially important for companies to be able to rapidly discover and characterize
both negative and positive sentiment expressed by current and potential customers. Complaints and other
negative views are easier to address if detected quickly, while early positive “buzz” can be reinforced and
amplified. Identifying nascent consumer concern or enthusiasm about topics which are relevant to company
business can be of great strategic advantage. Indeed, the relevance and timeliness of the information available
in social media has the potential to revolutionize the way business is conducted in many sectors.
While monitoring social media is of considerable interest to businesses, performing such analysis is
technically challenging. The opinions of consumers are typically expressed as informal communications and
are buried in the vast, and largely irrelevant, output of millions of bloggers and other online content
producers. Consequently, effectively exploiting these data requires the development of new, automated
methods of analysis (e.g., (Glance et al., 2005), (Ziegler and Skubacz, 2006), (Melville et al., 2009), (Kaplan
and Haenlein, 2010), (van der Lans et al., 2010)). Although powerful computational analytics have been
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derived for traditional forms of content, less has been done to develop techniques that are well-suited to the
particular characteristics of the content found in social media.
This paper considers one of the central problems in the new domain of social media analytics: deciding
whether a given document, such as a blog post or forum thread, expresses positive or negative opinion
toward a given topic. The informal nature of social media content poses a challenge for language-based
sentiment analysis. While statistical learning-based methods often provide good performance in unstructured
settings like this (e.g., (Pang and Lee, 2008), (Dhillon, 2001), (Kim and Hovy, 2004), (Sindhwani and
Melville, 2008), (Colbaugh and Glass, 2010), (Pan and Yang, 2010), (Blitzer et al., 2007), (He et al., 2009)),
obtaining the required labeled instances of data, such as a lexicon of sentiment-laden words for a given
domain or a collection of “exemplar” blog posts of known polarity, is expensive and time-consuming for
Web applications.
We present two new computational methods for inferring sentiment orientation of social media content
which address these challenges. Each method formulates the task as one of text classification, models the
data as a bipartite graph of documents and words, and assumes that only limited prior information is available
regarding the sentiment orientation of any of the documents or words of interest. The first algorithm adopts a
semi-supervised approach to sentiment classification, combining knowledge of the sentiment polarity for a
few documents and a small lexicon of words with information present in a corpus of unlabeled documents;
note that such unlabeled data are readily obtainable in online applications. The second algorithm assumes
existence of a set of labeled documents in a domain related to the domain of interest, and provides a
procedure for transferring the sentiment knowledge contained in these data to the target domain. We
demonstrate the efficacy of the proposed algorithms by showing they outperform several standard methods
for the task of inferring the sentiment polarity of online reviews of movies, electronics products, and kitchen
appliances.
2. PRELIMINARIES
We approach the task of estimating the sentiment orientations of a collection of documents as a text
classification problem. Each document of interest is represented as a “bag of words” feature vector x∈ℜ|V|,
where the entries of x are the frequencies with which the words in the vocabulary set V appear in the
document (perhaps normalized in some way (Pang and Lee, 2008)). We wish to learn a vector c∈ℜ|V| such
that the classifier orient = sign(cTx) accurately estimates the sentiment orientation of document x, returning
+1 (−1) for documents expressing positive (negative) sentiment about the topic of interest.
Knowledge-based classifiers leverage prior domain information to construct the vector c. One way to
obtain such a classifier is to assemble lexicons of positive words V+⊆V and negative words V−⊆V, and then
to set ci= +1 if word i∈V+, ci= −1 if i∈V−, and ci=0 if i is not in either lexicon; this classifier simply sums the
positive and negative sentiment words in the document and assigns document orientation accordingly. While
this scheme can provide acceptable performance in certain settings, it is unable to improve its performance or
adapt to new domains, and it is usually labor-intensive to construct lexicons which are sufficiently complete
to enable useful sentiment classification performance to be achieved.
Alternatively, learning-based methods attempt to generate classifier vector c from examples of positive
and negative sentiment. To obtain a learning-based classifier, one can begin by assembling a set of nl labeled
documents {(xi, di)}, where di∈{+1, −1} is the sentiment label for document i. The vector c then can be
learned through “training” with the set {(xi, di)}, for instance by solving the following set of equations for c:
[XTX + γI|V|] c = XT d,
nl×|V|
(1)
nl
Where matrix X∈ℜ
has document vectors for rows, d∈ℜ is the vector of document labels, I|V|
denotes the |V|×|V| identity matrix, and γ≥0 is a constant; this corresponds to regularized least squares (RLS)
learning (Hastie et al., 2009). Many other strategies can be used to compute c, including Naïve Bayes (NB)
statistical inference (Pang and Lee, 2008). Learning-based classifiers have the potential to improve their
performance and to adapt to new situations, but realizing these capabilities requires that fairly large training
sets of labeled documents be obtained and this is usually an expensive undertaking.
Sentiment analysis of social media content for business applications is often characterized by the
existence of only modest levels of prior knowledge regarding the domain of interest, reflected in the
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availability of a few labeled documents and small lexicon of sentiment-laden words, and by the need to
rapidly learn and adapt to new domains. As a consequence, standard knowledge-based and learning-based
sentiment analysis methods are typically ill-suited for business informatics. In order to address this challenge,
the sentiment analysis methods developed in this paper enable limited labeled data to be combined with
readily available “auxiliary” information to produce accurate sentiment estimates. More specifically, the first
proposed method is a semi-supervised algorithm (e.g., (Sindhwani and Melville, 2008), (Colbaugh and Glass,
2010)) which leverages a source of supplementary data which is abundant online: unlabeled documents and
words. Our second algorithm is a novel transfer learning method (e.g., (Pan and Yang, 2010)) which permits
the knowledge present in data that has been previously labeled in a related domain (say movie reviews) to be
transferred to a new domain (electronics reviews).
documents
words
Figure 1. Cartoon of bipartite graph model Gb, in which documents (red vertices) are connected to the words (blue
vertices) they contain, and the link weights (black edges) can reflect word frequencies
Each of the algorithms proposed in this paper assumes the availability of a modest lexicon of sentimentladen words. This lexicon is encoded as a vector w∈ℜ|Vl|, where Vl = V+∪V− is the sentiment lexicon and the
entries of w are set to +1 or −1 according to the polarity of the corresponding words. The development of the
algorithms begins by modeling the problem data as a bipartite graph Gb of documents and words (see Figure
1). It is easy to see that the adjacency matrix A for graph Gb is given by
 0
A= T
X
X
0 
(2)
Where the matrix X∈ℜn×|V| is constructed by stacking the document vectors as rows, and each ‘0’ is a
matrix of zeros. In both the semi-supervised and transfer learning algorithms, integration of labeled and
“auxiliary” data is accomplished by exploiting the relationships between documents and words encoded in
the bipartite graph model. The basic idea is to assume that, in the bipartite graph Gb, positive/negative
documents will tend to be connected to (contain) positive/negative words, and positive/negative words will
tend to be connected to positive/negative documents.
3. SEMI-SUPERVISED SENTIMENT ANALYSIS
We now derive our first sentiment estimation algorithm for social media content. Consider the common
situation in which only limited prior knowledge is available about the way sentiment is expressed in the
domain of interest, in the form of small sets of documents and words for which sentiment labels are known,
but where abundant unlabeled documents can be easily collected (e.g., via Web crawling). In this setting it is
natural to adopt a semi-supervised approach, in which labeled and unlabeled data are combined and
leveraged in the analysis process. In what follows we present a novel bipartite graph-based approach to semisupervised sentiment analysis.
Assume the initial problem data consists of a corpus of n documents, of which nl << n are labeled, and a
modest lexicon Vl of sentiment-laden words, and suppose that this label information is encoded as vectors
d∈ℜnl and w∈ℜ|Vl|, respectively. Let dest∈ℜn be the vector of estimated sentiment orientations for the
documents in the corpus, and define the “augmented” classifier caug = [destT cT]T∈ℜn+|V| which estimates the
polarity of both documents and words. Note that the quantity caug is introduced for notational convenience in
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the subsequent development and is not directly employed for classification. More specifically, in the
proposed methodology we learn caug, and therefore c, by solving an optimization problem involving the
labeled and unlabeled training data, and then use c to estimate the sentiment of any new document of interest
with the simple linear classifier orient = sign(cTx). We refer to this classifier as semi-supervised because it is
learned using both labeled and unlabeled data. Assume or ease of notation that the documents and words are
indexed so the first nl elements of dest and |Vl| elements of c correspond to the labeled data.
We wish to learn an augmented classifier caug with the following three properties: 1.) if a document is
labeled, then the corresponding entry of dest should be close to this ±1 label; 2.) if a word is in the sentiment
lexicon, then the corresponding entry of c should be close to this ±1 sentiment polarity; and 3.) if there is an
edge Xij of Gb that connects a document x and a word v∈V and Xij possesses significant weight, then the
estimated polarities of x and v should be similar. These objectives are encoded in the following minimization
problem:
min c Taug Lc aug + β1
c aug
nl
∑
Vl
(d est,i - d i ) 2 + β 2
i =1
∑ (c
i
- wi )2
(3)
i =1
Where L = D − A is the graph Laplacian matrix for Gb, with D the diagonal degree matrix for A (i.e., Dii =
Σj Aij), and β1, β2 are nonnegative constants. Minimizing (3) enforces the three properties we seek for caug,
with the second and third terms penalizing “errors” in the first two properties. To see that the first term
enforces the third property, observe that this expression is a sum of components of the form Xij(dest,i − cj)2.
The constants β 1, β2 can be used to balance the relative importance of the three properties.
The caug which minimizes the objective function (3) can be obtained by solving the following set of linear
equations:
L 13
L 14 
L 11 + β1 I nl L 12
 β1 d 


 0 
L 21
L 22
L 23
L 24 


c aug = 
(4)

β 2 w 
L 31
L 32 L 33 + β 2 I V L 34 
1




L 41
L 42
L 43
L 44 
 0 

Where the Lij are matrix blocks of L of appropriate dimension. The system (4) is sparse because the data
matrix X is sparse, and therefore large-scale problems can be solved efficiently. Note that in situations where
the set of available labeled documents and words is very limited, sentiment classifier performance can be
improved by replacing L in (4) with the normalized Laplacian Ln=D−1/2LD−1/2, or with a power of this matrix
Lnk (for k a positive integer).
We summarize this discussion by sketching an algorithm for learning the proposed semi-supervised
classifier:
Algorithm SS:
1. Construct the set of equations (4), possibly by replacing the graph Laplacian L with Lnk.
2. Solve equations (4) for caug = [ destT cT ]T (for instance using the Conjugate Gradient method).
3. Estimate the sentiment orientation of any new document x of interest as: orient = sign(cTx).
4. CASE STUDY ONE: MOVIE REVIEWS
This case study examines the performance of Algorithm SS for the problem of estimating sentiment of online
movie reviews. The data used in this study is a publicly available set of 2000 movie reviews, 1000 positive
and 1000 negative, collected from the Internet Movie Database and archived at the website (Pang, 2009). The
Lemur Toolkit (Lemur, 2009) was employed to construct the data matrix X and vector of document labels d
from these reviews. A lexicon of ~1400 domain-independent sentiment-laden words was obtained from
(Ramakrishnan et al., 2003) and employed to build the lexicon vector w.
This study compares the movie review orientation classification accuracy of Algorithm SS with that of
three other schemes: 1.) lexicon-only, in which the lexicon vector w is used as the classifier as summarized in
Section 2, 2.) a classical NB classifier obtained from (Borgelt, 2009), and 3.) a well-tuned version of the RLS
classifier (1). Algorithm SS is implemented with the following parameter values: β1 = 0.1, β2 = 0.5, and k =
10. A focus of the investigation is evaluating the extent to which good sentiment estimation performance can
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be achieved even if only relatively few labeled documents are available for training; thus we examine
training sets which incorporate a range of numbers of labeled documents: nl = 50, 100, 150, 200, 300, 400,
600, 800, 1000.
Figure 2. Results for the movie reviews case study. The plot shows how sentiment estimation accuracy (vertical axis)
varies with number of available labeled movie reviews (horizontal axis) for four different classifiers: lexicon only
(black), NB (magenta), RLS (blue), and Algorithm SS (red).
Sample results from this study are depicted in Figure 2. Each data point in the plots represents the average
of ten trials. In each trial, the movie reviews are randomly partitioned into 1000 training and 1000 test
documents, and a randomly selected subset of training documents of size nl is “labeled” (i.e., the labels for
these reviews are made available to the learning algorithm). As shown in Figure 2, Algorithm SS outperforms
the other three methods. Note that, in particular, the accuracy obtained with the proposed approach is
significantly better than the other techniques when the number of labeled training documents is small. It is
expected that this property of Algorithm SS will be of considerable value in business informatics applications
that involve social media data.
5. TRANSFER LEARNING SENTIMENT ANALYSIS
This section develops the second proposed sentiment estimation algorithm for social media content. Many
business informatics applications are characterized by the presence of limited labeled data for the domain of
interest but ample labeled information for a related domain. For instance, a firm may wish to ascertain the
sentiment of online discussions about its new line of kitchen appliances, and may have in hand a large set of
labeled examples of positive and negative reviews for its electronics products (e.g., from studies of previous
product launches). In this setting it is natural to adopt a transfer learning approach, in which knowledge
concerning the way sentiment is expressed in one domain, the so-called source domain, is transferred to
permit sentiment estimation in a new target domain. In what follows we present a new bipartite graph-based
approach to transfer learning-based sentiment analysis.
Assume that the initial problem data consists of a corpus of n = nT + nS documents, where nT is the (small)
number of labeled documents available for the target domain of interest and nS >> nT is the number of labeled
documents from some related source domain; in addition, suppose that a modest lexicon Vl of sentimentladen words is known. Let this label data be encoded as vectors dT∈ℜnT, dS∈ℜnS, and w∈ℜ|V|, respectively.
Denote by dT,est∈ℜnT, dS,est∈ℜnS, and c∈ℜ|V| the vectors of estimated sentiment orientations for the target and
source documents and the words, and define the augmented classifier as caug = [dS,estT dT,estT cT]T ∈ ℜn+|V|.
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Note that the quantity caug is introduced for notational convenience in the subsequent development and is not
directly employed for classification.
In what follows we derive an algorithm for learning caug, and therefore c, by solving an optimization
problem involving the labeled source and target training data, and then use c to estimate the sentiment of any
new document of interest via the simple linear classifier orient = sign(cTx). This classifier is referred to as
transfer learning-based because c is learned, in part, by transferring knowledge about the way sentiment is
expressed from a domain which is related to (but need not be identical to) the domain of interest.
We wish to learn an augmented classifier caug with the following four properties: 1.) if a source document
is labeled, then the corresponding entry of dS,est should be close to this ±1 label; 2.) if a target document is
labeled, then the corresponding entry of dT,est should be close to this ±1 label, and the information encoded in
dT should be emphasized relative to that in the source labels dS,; 3.) if a word is in the sentiment lexicon, then
the corresponding entry of c should be close to this ±1 sentiment polarity; and 4.) if there is an edge Xij of Gb
that connects a document x and a word v∈V and Xij possesses significant weight, then the estimated
polarities of x and v should be similar.
The four objectives listed above may be realized by solving the following minimization problem:
min c Taug Lc aug + β 1 d S,est - k S d S
c aug
2
+ β 2 d T,est - k T d T
2
+ β3 c - w
2
(5)
Where L = D − A is the graph Laplacian matrix for Gb, as before, and β1, β2, β3, kS, and kT are
nonnegative constants. Minimizing (5) enforces the four properties we seek for caug. More specifically, the
second, third, and fourth terms penalize “errors” in the first three properties, and choosing β2 > β1 and kT > kS
favors target label data over source labels. To see that the first term enforces the fourth property, note that
this expression is a sum of components of the form Xij (dT,est,i − cj)2 and Xij (dS,est,i − cj)2.The constants β1, β2,
β3 can be used to balance the relative importance of the four properties.
The caug which minimizes the objective function (5) can be obtained by solving the following set of linear
equations:
L + β I

L 12
L 13
 β1 k S d S 
1 nS
 11

 L 21
 c aug = β 2 k T d T 
L 22 + β 2 I nT
L 23
(6)




 β 3 w 
L 31
L 32
L 33 + β 3 I V 


Where the Lij are matrix blocks of L of appropriate dimension. The system (6) is sparse because the data
matrix X is sparse, and therefore large-scale problems can be solved efficiently. In situations where the set of
available labeled documents and words is very limited, sentiment classifier performance can be improved by
replacing L in (6) with the normalized Laplacian Ln or with a power of this matrix Lnk.
We summarize the above discussion by sketching an algorithm for the proposed transfer learning
classifier:
Algorithm TL:
1. Construct the set of equations (6), possibly by replacing the graph Laplacian L with Lnk.
2. Solve equations (6) for caug = [dS,estT dT,estT cT]T.
3. Estimate the sentiment orientation of any new document x of interest as: orient = sign(cTx).
6. CASE STUDY TWO: PRODUCT REVIEWS
This case study examines the performance of Algorithm TL for the problem of estimating sentiment of online
product reviews. The data used in this study is a publicly available set of 1000 reviews of electronics
products, 500 positive and 500 negative, and 1000 reviews of kitchen appliances, 500 positive and 500
negative, collected from Amazon and archived at the website (Dredze, 2010). The Lemur Toolkit (Lemur,
2009) was employed to construct the data matrix X and vectors of document labels dS and dT from these
reviews. A lexicon of 150 domain-independent sentiment-laden words was constructed manually and
employed to form the lexicon vector w.
This study compares the product review sentiment classification accuracy of Algorithm TL with that of
four other strategies: 1.) lexicon-only, in which the lexicon vector w is used as the classifier as summarized in
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IADIS International Conference e-Commerce 2011
Section 2, 2.) a classical NB classifier obtained from (Borgelt, 2009), 3.) a well-tuned version of the RLS
classifier (1), and 4.) Algorithm SS. Algorithm TL is implemented with the following parameter values: β1 =
1.0, β2 = 3.0, β3 = 5.0, kS = 0.5, kT = 1.0, and k = 5. A focus of the investigation is evaluating the extent to
which the knowledge present in labeled reviews from a related domain, here kitchen appliances, can be
transferred to a new domain for which only limited labeled data is available, in this case electronics. Thus we
assume that all 1000 labeled kitchen reviews are available to Algorithm TL (the only algorithm which is
designed to exploit this information), and examine training sets which incorporate a range of numbers of
labeled documents from the electronics domain: nT = 20, 50, 100, 200, 300, 400.
Figure 3. Results for the consumer product reviews case study. The plot shows how sentiment estimation accuracy
(vertical axis) varies with number of available labeled electronics reviews (horizontal axis) for five different classifiers:
lexicon only (orange), NB (black), RLS (magenta), Algorithm SS (blue), and Algorithm TL (red).
Sample results from this study are depicted in Figure 3. Each data point in the plots represents the average
of ten trials. In each trial, the electronics reviews are randomly partitioned into 500 training and 500 test
documents, and a randomly selected subset of reviews of size nT is extracted from the 500 labeled training
instances and made available to the learning algorithms. As shown in Figure 3, Algorithm TL outperforms
the other four methods. Note that, in particular, the accuracy obtained with the transfer learning approach is
significantly better than the other techniques when the number of labeled training documents in the target
domain is small. It is expected that the ability of Algorithm TL to exploit knowledge from a related domain
to quickly learn an effective sentiment classifier for a new domain will be of considerable value in business
informatics applications.
ACKNOWLEDGEMENT
This research was supported by the U.S. Department of Defense and the Laboratory Directed Research and
Development Program at Sandia National Laboratories.
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REFERENCES
Blitzer, J. et al., 2007. Biographies, Bollywood, Boom-boxes, and Blenders: Domain Adaptation for Sentiment
Classification. Proc. 45th Annual Meeting of the ACL, Prague, CZ.
Borgelt, C., 2009. http://www.borgelt.net/bayes.html, accessed December 2009.
Colbaugh, R. and Glass, K., 2010. Estimating Sentiment Orientation in Social Media for Intelligence Monitoring and
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Dhillon, I., 2001. Co-clustering Documents and Words Using Bipartite Spectral Graph Partitioning. Proc. ACM Int. Conf.
Knowledge Discovery and Data Mining, San Francisco, CA, USA.
Dredze, M., 2010. http://www.cs.jhu.edu/~mdredze/, accessed December 2010.
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Discovery and Data Mining, Chicago, IL, USA.
Hastie, T. et al., 2009. The Elements of Statistical Learning. Second Edition, Springer, New York, USA.
He, J. et al., 2009. Graph-based Transfer Learning. Proc. 18th ACM Conf. Information and Knowledge Management,
Hong Kong.
Lemur, 2009. http://www.lemurproject.org/, accessed December 2009.
Kaplan, A. and Haenlein, M., 2010. Users of the World, Unite! The Challenges and Opportunities of Social Media.
Business Horizons, Vol. 53, pp. 59-68.
Kim, S. and Hovy, E., 2004. Determining the Sentiment of Opinions. Proc. Int. Conf. Computational Linguistics.
Melville, P. et al., 2009. Social Media Analytics: Channeling the Power of the Blogosphere for Marketing Insight. Proc.
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Nielson, 2010. http://www.nielson.com, accessed July 2010.
Pan, S. and Yang, Q., 2010. A Survey on Transfer Learning. IEEE Trans. Knowledge and Data Engineering, Vol. 22, pp.
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Pang, B. and Lee, L., 2008. Opinion Mining and Sentiment Analysis. Foundations and Trends in Information Retrieval,
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Ramakrishnan, G. et al., 2003. Question Answering via Bayesian Inference on Lexical Relations. Proc. 41st Annual
Meeting of the ACL.
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2008 IEEE Int. Conf. Data Mining, Pisa, IT.
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Ziegler, C. and Skubacz, M., 2006. Towards Automated Reputation and Brand Monitoring on the Web. Proc. IEEE/ACM
Int. Conf. Web Intelligence, Hong Kong.
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IADIS International Conference e-Commerce 2011
A CONCEPTUAL MODEL OF WEB ATM ADOPTION: AN
INTEGRATED PERSPECTIVE OF THE TRANSACTION
COST THEORY AND INNOVATION DIFFUSION THEORY
Yi-Shun Wang1, Shun-Cheng Wu2, Hsin-Hui Lin3, Yu-Min Wang4 and Ting-Rong He5
1
Department of Information Management, National Changhua University of Education, Taiwan
2
Department of International Business, Vanung University, Taiwan
3
Department of Distribution Management, National Taichung Institute of Technology, Taiwan
4
Department of Information Management, National Chi Nan University, Taiwan
5
CyberLink Corporation, Taipei, Taiwan
ABSTRACT
With the initial success of the traditional internet banking, several banks in Taiwan have been transferring their attention
to implementing Web Automatic Teller Machines (Web ATMs). Due to the multi-channel nature of online banking
services and the difference in equipment requirement between the traditional Internet banking and Web ATM, users’
adoption of traditional internet banking does not promise their adoption of Web ATM. Thus, this study proposes a
conceptual model for exploring the factors influencing the usage behavior of Web ATM by integrating the innovation
diffusion theory (IDT) and transaction cost theory (TCT). The proposed model suggests that perceived relative
advantage, perceived complexity, perceived compatibility, perceived asset specificity, perceived uncertainty, and
perceived transaction frequency are potential determinants of user adoption of Web ATM. The proposed model can
provide some important implications for Web ATM adoption research and practice.
KEYWORDS
Web ATM adoption; Internet banking; Innovation Diffusion Theory (IDT); Transaction Cost Theory (TCT)
1. INTRODUCTION
Continued information technology (IT) innovation and widespread usage of Internet communication have
altered people’s lifestyles and social behavior, especially in terms of money management. Increasingly,
transactions are being conducted via cyberspace rather than through traditional physical channels. Intensive
electronic commerce demand necessitates improvements to the design and delivery of personal financial
services; traditional branch-based retail banks are therefore compelled to provide customers with convenient
online banking services. Online banking is a system that allows individuals to perform banking transactions
at home, via the internet. There are two kinds of online banking systems launched by almost every bank in
Taiwan, including the traditional Internet banking systems (henceforth, ‘Internet banking’) and the Web Auto
Teller Machine (Web ATM) systems.
With the initial success of the Internet banking implementation, many banks in Taiwan have been
implementing a newly-innovated IT service, Web ATM, which can perform all secure online transaction
functions as provided by a physical ATM other than deposits and withdrawals. Different from the Internet
banking systems which users can use to conduct banking transactions as long as they have the PC-connected
Internet, valid accounts, and passwords, and are therefore easy to be attacked by hackers, Web ATM provides
a more secure platform for online banking. Actually, due to the secure concerns, most banks in Taiwan have
disabled the function of non-designated fund outward transfer in their Internet banking services. This has
made some inconvenience for the users of Internet banking. Furthermore, a bank’s Internet banking services
can only be used by the bank’s customers who have previously applied for the bank’s Internet banking
accounts and passwords. Thus, Internet banking systems can only provide services for dedicated customers.
On the other hand, installation of an IC card reader and a Web ATM driver allows any PC connected to the
Internet to serve as a Web ATM platform, which can offer a highly secure, non-dedicated environment for
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home banking transactions. By inserting any bank’s ATM card into the card reader and browsing the Web
ATM platform website of a specific bank, users can conduct various secure banking transactions at any time
of day, including balance inquiries, fund transfers, and bill or tax payments. Therefore, like physical ATM
systems, a bank’s Web ATM systems can provide secure, non-dedicated banking services for all customers
who have any bank’s ATM cards. Whereas, unlike physical ATM, Web ATM services can save users time
and money in terms of locating a physical ATM, travelling to that ATM, and queuing for service.
Importantly, Web ATM is not a transitional technology or a substitute for Internet banking, but it is a
complement for Internet banking. Actually, most banks in Taiwan have provided dual online banking service
options (i.e., Web ATM and Internet banking services) for their customers. Thus, Web ATM is a new IT
phenomenon and its potential success in Taiwan can provide several important implications for online
banking practitioners all over the world. Most customers may use banking services from multiple channels,
including branch banking, telephone banking, physical ATM, Internet banking, and Web ATM. The multichannel strategy has become the most popular business model for banks (Ho & Wu, 2009). Therefore, many
banks in Taiwan have invested a great deal of money in implementing and promoting Web ATM systems and
taken advantage of Web ATM as a multi-channel marketing opportunity to increase their service quality,
customer satisfaction, customer retention, and online service revenues.
However, due to the multi-channel nature of online banking services and the difference in equipment
requirement between the traditional Internet banking and Web ATM, users’ adoption of Internet banking
does not promise their adoption of Web ATM. While many banks are currently making considerable
investments to make use of the Web ATM systems, potential users may not choose to adopt them in spite of
their availability, security, and convenience. Therefore, how to lead customers to adopt the new online
banking services is an important issue for the bank industry. Specifically, Web ATM implementation success
may depend largely on whether or not users are willing to adopt a new form of IT that is different from what
they have used in the past – to use Web ATM systems, users are required to install an IC card reader and a
specific driver. Thus, the behavioral model of Web ATM adoption may somehow differ from that of
traditional Internet banking adoption. While many prior studies have investigated the factors influencing user
acceptance of Internet banking (e.g., Wang, Wang, Lin, & Tang, 2003; Chau & Lai, 2003; Chan & Lu, 2004),
little research has been conducted on the factors affecting user adoption of Web ATM. Thus, there is a need
for research to investigate the factors that influence Web ATM adoption.
Since the adoption of Web ATM can be viewed as the adoption of an innovation and the selection of a
transaction method, this study employs the Innovation Diffusion Theory (IDT) and the Transaction Cost
Theory (TCT) to investigate the factors that affect user adoption behavior of Web ATM. Specifically, this
study proposes a conceptual model for exploring the factors influencing the usage behavior of Web ATM by
integrating IDT and TCT. The proposed model suggests that perceived relative advantage, perceived
complexity, perceived compatibility, perceived asset specificity, perceived uncertainty, and perceived
transaction frequency are potential determinants of user adoption of Web ATM. The proposed model can
provide some important implications for Web ATM adoption research and practice.
2. THEORETICAL BACKGROUND
2.1 Previous Research on Internet Banking Acceptance
Many prior studies have investigated the factors influencing user acceptance of Internet banking (e.g., Wang
et al., 2003; Chau & Lai, 2003; Lai & Li, 2005; Cheng, Lam, & Yeung, 2006; Muniruddeen, 2007; Yiu,
Grant, & Edgar, 2007; Amin, 2009; Lee, 2009; Chan & Lu, 2004; Aderonke & Charles, 2010; Chang &
Rizal, 2010). However, most of them focus mainly on extending the technology acceptance model (TAM)
(Davis, 1989) to explain user intention to use the traditional Internet banking. TAM suggests that user IT
adoption behavior is determined by the intention to use a particular system, which in turn is determined by
the user attitude. Two beliefs, perceived usefulness and perceived ease of use, are instrumental in
determining the user attitude. Previous studies have found that the effects of user attitude and use intention
are not always significant (Lederer, Maupin, Sena, & Zhuang, 2000; Kamarulzaman, 2007). Hence, several
studies ignored the construct of use intention or user attitude, and instead they investigated the direct effect of
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perceived ease of use and/or perceived usefulness on usage behavior (Burton-Jones & Hubona, 2006; Chau,
1996; Kamarulzaman, 2007; Kolodinsky, Hogarth, & Hilgert, 2004; Lederer et al., 2000).
This study is different from prior studies that focused mainly on investigating the factors affecting user
intention to use Internet banking by extending the TAM, and focuses primarily on exploring the factors
influencing the usage behavior of Web ATM by integrating the innovation diffusion theory (IDT) and
transaction cost theory (TCT). IDT developed by Rogers claims five technological characteristics as
antecedents to any adoption decision: relative advantage, compatibility, complexity, trial ability, and
observability (Roger, 1983, 1995). However, previous research found that only relative advantage,
compatibility, and complexity were consistently related to innovation adoption (Tornatzky & Klein, 1982).
Further, relative advantage and complexity are conceptually overlapped with TAM’s perceived usefulness
and perceived ease of use, respectively (Moore & Benbasat, 1991). Therefore, similar to TAM, IDT is
suitable to investigate the usage behavior of Web ATM. Different from Internet banking users who do not
have to install additional equipments other than their Internet-connected computers, Web ATM users must
have or purchase an IC card reader and install a Web ATM driver for using the Web ATM. This implies that
transaction costs associated with using Web ATM, such as asset specificity, may be influential in user
adoption of Web ATM. Consequently, the study integrates the IDT and TCT to analyze the usage behavior of
Web ATM. This study also represents three aspects of extensions from previous online banking acceptance
research, including context extension (i.e., from Internet banking to Web ATM), theory extension (i.e., from
TAM to IDT and TCT), and dependent variable extension (i.e., from usage intention to usage behavior).
2.2 Innovation Diffusion Theory
IDT is a broad social psychological theory that purports to describe the patterns of adoption, explain the
mechanisms, and assist in predicting whether and how a new invention will be successful (Rogers, 1983,
1995). Rogers (1995) defines an innovation as an idea, practice, or object that is perceived as new by an
individual or another unit of adoption, and diffusion as the process by which an innovation is communicated
through certain channels over time among the members of a social system. Innovation diffusion is achieved
through user adoption, which means ‘the acceptance into use and the continued use of a new idea or thing’
(Chen, Gillenson, & Sherrell, 2002). IDT can help to explain the innovation decision process and to examine
the concerns that users has in terms of adopting a new innovation; therefore, it is used as the theoretical
foundation for the research model of this study.
IDT has been widely applied in explaining IT adoption behaviors (e.g., Chen et al., 2002; Moore &
Benbasat, 1991; Hsu, Lu, & Hsu, 2007; Wang & Liao, 2008). As noted earlier, IDT posits a set of innovation
attributes to explain the rates of adoption by users: relative advantage, compatibility, complexity, trial ability,
and observability. Also, previous research found only relative advantage, compatibility and complexity to be
consistently related to innovation adoption (Tornatzky & Klein, 1982). In this study, these three attributes are
used to explain user adoption of Web ATM.
2.3 Transaction Cost Theory
TCT (Coase, 1937; Williamson, 1975, 1985) has been widely applied to explain information systems
outsourcing behaviors (e.g., Ang & Straub, 1998; Aubert, Rivard, & Patry, 1996; Wang, 2002; Watjatrakul,
2005). TCT is based on two behavioral assumptions: bounded rationality and opportunism. Bounded
rationality posits that humans are unlikely to have the sufficient abilities, time, information or resources to
consider every state-contingent outcome associated with a transaction that might arise, whereas opportunism
means that humans will act to further their own self-interests, which makes allowances for guile (Williamson,
1985). Williamson (1985) also suggests that three transaction dimensions influence the type of governance
structure chosen for the transaction: asset specificity, uncertainty, and frequency.
Recently, TCT has also been used to explain IT adoption behaviors (Liang & Huang, 1998). Given that
users’ adoption and usage of Web ATM represent a kind of transaction behavior between users and banks
that provide Web ATM services, users may take into consideration the transaction costs involved in bilateral
exchange while deciding whether or not to adopt Web ATM systems. As such, TCT is appropriate for
explaining why users are willing to adopt the new Web ATM technology rather than continuing to use their
current methods of conducting banking transactions, especially since adopters will be required to obtain an
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IC card reader to switch to the new banking method. On this basis, TCT is used as the theoretical foundation
for the research model of this study. That is, the three transaction dimensions (i.e., asset specificity,
uncertainty, and frequency) are hypothesized to be the determinants of Web ATM adoption.
3. A CONCEPTUAL MODEL OF WEB ATM ADOPTION
The research model used to guide the study is shown in Figure 1; it depicts that perceived relative advantage,
perceived complexity, perceived compatibility, perceived asset specificity, perceived uncertainty, and
perceived transaction frequency are the potential determinants of Web ATM adoption. Moreover, Web ATM
adoption, defined as whether or not the user has adopted the Web ATM service, is the dependent variable in
the research model. It is limited to the actual use of Web ATM, rather than the behavioral intention to use
Web ATM. The proposed constructs and hypotheses in the research model are all based on the IDT, TCT and
information systems literature. The following sections elaborate on the theory base and derive the
hypotheses.
3.1 Perceived Relative Advantage
Rogers (1983) defines ‘relative advantage’ as the degree to which an innovation is perceived as better than
the idea it supersedes. Thus, relative advantage can be considered as the degree to which a new innovation
surpasses current practices. In this study, perceived relative advantage is defined as the user’s subjective
evaluation of the benefit brought by Web ATM usage against that brought by traditional banking behavior. In
fact, perceived relative advantage is conceptually similar to perceived usefulness in the technology
acceptance model (TAM), which reflects the extent to which the user believes that using a particular
information technology can enhance his/her operation performance (Davis, 1989). The ultimate reason that
bank customers adopt a Web ATM system is that they believe the system provides more benefits as
compared to the method(s) that they have previously used to conduct their banking transactions. It is
expected that there is a positive relationship between perceived relative advantage and Web ATM adoption.
Thus, following hypothesis is presented:
H1: Perceived relative advantage has a positive influence on Web ATM adoption.
3.2 Perceived Complexity
Complexity is the degree to which a certain innovation is difficult to understand and use (Rogers, 1983). It is
the opposite of ease of use, which reflects the extent to which the user believes that using a particular system
is free of effort (Davis, 1989). Thus, perceived complexity in this study is defined as the extent to which the
user believes that using a Web ATM is difficult. It is believed that the perceived complexity of an innovation
leads to user resistance due to a lack of user skills and knowledge (Rogers, 1983). Users who perceive a new
innovation as a complex system will tend to decline the adoption of the new system. Thus, this study presents
the following hypothesis:
H2: Perceived complexity has a negative influence on Web ATM adoption.
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Figure 1. A Conceptual model of Web ATM adoption
3.3 Perceived Compatibility
Compatibility is usually defined as a measure of the degree to which an innovation is perceived as being
compatible with existing values, past experiences, and the needs of potential adopters (Rogers, 1983).
Tornatzky & Klein (1982) found that an innovation is more likely to be adopted when it is compatible with
users’ job responsibility and value system. Based on the previous literature, perceived compatibility in this
study is defined as the degree to which a Web ATM system is perceived as being compatible with existing
values, past experiences and the needs of potential adopters. Chen et al. (2002) contend that greater
compatibility leads to a faster rate of adoption. Previous empirical research also found that perceived
compatibility has a significant influence on behavioral intention to use information systems (Chen et al.,
2002; Wang & Liao, 2008). It is believed that higher perceived compatibility will results in higher Web ATM
usage. Thus, the following hypothesis is presented:
H3: Perceived compatibility has a positive influence on Web ATM adoption.
3.4 Perceived Asset Specificity
Williamson (1985) defines asset specificity as durable investments that are undertaken in support of
particular transactions, and the opportunity cost of (such) investment is much lower in best alternative uses.
According to Erramilli & Rao (1993) and Heide (1994), asset specificity refers to investments in physical or
human assets that are dedicated to a particular business partner and whose redeployment entails considerable
switching costs. As such, a specific asset is significantly more valuable in a particular exchange than in an
alternative exchange and results in a ‘lock-in’ effect that causes hold-up problems (Barney, 1999;
Williamson, 1975). Thus, the value of assets with high specificity is greatly diminished if they must be
redeployed. Since the first-time adopters of Web ATM need to invest in or acquire an IC card reader in order
to conduct Web ATM transactions, they may take into consideration the potential transaction costs resulting
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from investing in and/or redeploying the transaction-specific asset. If users believe that the use of Web ATM
requires specific assets, their transaction cost of using Web ATMs increases, making them less likely to adopt
the systems. Thus, this study proposes the following hypothesis:
H4: Perceived asset specificity has a negative influence on Web ATM adoption.
3.5 Perceived Uncertainty
All transactions are conducted under a certain level of uncertainty. Uncertainty arises from imperfect
foresight and the human inability to solve complex problems associated with the transaction, which can be
regarded as the cost associated with the unexpected outcome and asymmetry of information (Williamson,
1985). TCT posits that the level of uncertainty is likely to affect whether a decision maker chooses to
insource or outsource (Watjatrakul, 2005). Wang (2002) found that uncertainty has a positive influence on
the contractor’s post-contractual opportunism as perceived by the client, but a negative influence on the
success of software outsourcing.
Perceived uncertainty in this study is defined as the extent to which the user believes that using Web
ATMs includes the possibility of security and privacy threats. Wang et al. (2003) suggest that users’
perception as to the extent to which Internet banking systems ensure that their transactions are conducted
without any breach of security and privacy protection is an important consideration that will affect Internet
banking use. Previous empirical studies also found that security and privacy concerns were a significant
antecedent of behavioral intention to use electronic/mobile banking systems (e.g., Liao & Cheung, 2002;
Wang et al., 2003; Luarn & Lin, 2005; Lee, 2009). Thus, it is expected that as the perceived uncertainty of
using Web ATMs increases, users’ adoption of Web ATM decreases. The following hypothesis is presented:
H5: Perceived uncertainty has a negative influence on Web ATM adoption.
3.6 Perceived Transaction Frequency
Transaction frequency refers to the frequency with which transactions recur (Williamson, 1985). Higher
transaction frequencies provide companies with a motive to employ hierarchical governance structures, as
these structures make it easier to recover large transactions of a recurring kind (Williamson, 1985; Teo,
Wang, & Leong, 2004). Many researchers have failed to confirm empirically that transaction frequency is
related to a choice of governance structure (e.g., Anderson, 1985; Malz, 1994; Rindfleisch & Heide, 1997).
While some studies investigating the factors that affect online shopping behavior chose to omit this construct
from their research models (e.g., Teo et al., 2004; Liang & Huang, 1998), when transactions are supposed to
occur at a high frequency, both transaction parties are likely to desire a specific or convenient platform to
deal with the repeated transactions. Thus, this study continues to explore the relationship between perceived
transaction frequency and Web ATM adoption behavior.
Perceived transaction frequency is herein defined as the extent to which the user perceives that he or she
has to frequently conduct banking transactions. Since Web ATMs enable bank customers to administrate
their bank accounts or conduct banking transactions without adhering to normal limitations associated with
time and location, it is expected that in order to reduce the transaction costs of banking, users with high
scores on perceived transaction frequency will have a higher propensity to adopt Web ATMs than those with
low scores. Thus, this study proposes the following hypothesis.
H6: Perceived transaction frequency has a positive influence on Web ATM adoption.
4. CONCLUSION
This study proposes an integrated model of IDT and TCT to explore and explain user adoption behavior of
Web ATM. Different from prior studies that focused mainly on investigating the factors affecting user
intention to use traditional Internet banking by TAM-based model, this study presents the factors influencing
the usage behavior of Web ATM by integrating IDT and TCT. Thus, this study represents three aspects of
extensions from previous online banking acceptance research, including context extension (i.e., from Internet
banking to Web ATM), theory extension (i.e., from TAM to IDT and TCT), and dependent variable
extension (i.e., from usage intention to usage behavior). Future researchers could conduct an empirical
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validation of the proposed model. The proposed model will be able to provide a useful framework for bank
managers to assess, develop, and promote better user-acceptance of Web ATM systems. This study also
argues that banks could take advantage of Web ATM as a new, multi-channel service opportunity to increase
their service quality, customer satisfaction, customer retention, cost effectiveness, and online service
revenues.
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USING MOBILE MESSAGING SERVICES IN EDUCATION:
DETERMINANTS OF STUDENTS’ ATTITUDES
Boonlert Watjatrakul
Department of Information Technology
Faculty of Science and Technology
Assumption University, Bangkok, Thailand 10240
ABSTRACT
The impressive use of mobile messaging services is spread into educational institutions. Many universities start using
mobile text messages to communicate with their students. The study empirically investigates factors affecting students’
attitudes toward using the university’s mobile messaging service. It employs the survey method using a structural
equation modeling technique to investigate inter-relationships among the study constructs in the anticipated model and
propose the modification model. The results show that students’ attitudes toward using the university’s mobile messaging
service are influenced by perceived utility, perceived control, social norm and existing knowledge about mobile
communication. Privacy concern and information seeking behavior, however, do not have statistically significant effects
on students’ attitudes toward the university’s mobile messaging service. The study fills the gap in literatures and assists
universities to manage their mobile messaging service effectively. The paper concludes with a discussion of implications
and limitations of the study.
KEYWORDS
Electronic commerce, Mobile commerce, Mobile messaging, Attitude, Education
1. INTRODUCTION
Currently, mobile messaging plays an important role for e-commerce firms. The global mobile messaging
market, including SMS (short messaging service), MMS (multimedia messaging service), mobile e-mail and
mobile IM (instant messaging), will reach USD 233 billion by the end of 2014. Among the mobile messaging
services, SMS yielded the highest revenue in 2009 and annual worldwide SMS traffic volumes will break 6.6
trillion in 2010 (Portio research, 2010). In addition, most people have their own mobile phones. E-commerce
firms, therefore, trend to use more mobile commerce by means of mobile messaging service to communicate
with and advertize their products or services to their customers. Mobile messaging is not only considerably
used in commercial firms but also gradually extended to educational institutions. Most universities perceive
the benefits of using mobile messaging services to enhance communication among university staff,
instructors and students. They trend to use SMS to contact their students. The mobile messaging provides
universities with cost effectiveness, flexibility, traceability and personalization. On the other hand, students
can receive the university’s messages anywhere and anytime.
The two common mobile messaging services used in educational institutions include direct messaging
and query messaging. The direct messaging send messages directly from universities to students’ mobile
devices. Its main objectives are to inform information update and ask questions. For examples, universities
can send messages to remind or change appointments, ask a reason for unauthorized absences, and inform
class cancellation and school closing (Watjatrakul and Barikdar, 2007). The query messaging uses an
automated responding system to send messages in response to the students’ query messages. To retrieved
content from the system, students must send a query message, pre-specified texts or numbers by the
universities, to match the value stored in the system. Students can query specific information such as their
grade release, class schedules and examination schedules from the automated responding systems via their
mobile phones. In general, the university’s mobile messaging services are free services for students;
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however, students should permit universities to send them messages by registering to the university’s
messaging system.
Previous studies attempted to understand the factors affecting consumer’s adoption of the firm’s mobile
commerce (e.g., (Sultan and Rohm, 2008; Wais and Clemons, 2008)). Limited research, however, has studied
student’s adoption of the university’s mobile messaging service. This study will fill this gap in literatures. In
addition, the communication of mobile message content can only be effective if message recipients permit
the continuous reception of messages on their mobile phone (Godin, 1999). It is important, therefore, to
understand what factors affect student’s attitudes toward receiving the university’s mobile messages.
Accordingly, this study develops the research model to understand the key drivers of students’ attitudes
toward using the university’s mobile messaging service. This study will enable universities to understand
students’ concerns about using their mobile messaging services and improve their services effectively.
2. FACTORS AFFECTING STUDENTS’ ATTITUDES TOWARD MOBILE
MESSAGING SERVICES
Almost every student in universities are using mobile messaging either SMS, MMS, mobile e-mail or mobile
instant messages. However, mobile messaging service is not well established in most educational institutions
in Thailand. As most students have not yet had the chance to use mobile messaging service from their
universities, the actual use of mobile messaging service in a university cannot be measured. Investigation of
students’ attitudes toward using mobile messaging service, therefore, is appropriated and practically valuable
for predicting usage behavior (Bauer et al., 2005). Attitude towards behavior is an individual’s belief of the
performing behavior and the individual’s subjective evaluation of the belief (Ajzen, 1991). The following
sections provide the anticipated factors affecting the students’ attitudes toward using the university’s mobile
messaging service and their inter-relationships.
2.1 Perceived Utility
Many academics posit that consumer’s perceptions of technology utility strongly influence their attitudes
toward using the technology (Davis, 1989; Taylor and Todd, 1995). When consumers perceive some benefits
in receiving advertising messages on their mobile phones, they are more likely to receive and read the
advertising messages (Kavassalis et al., 2003). The utilities of mobile commercial messages are commonly
defined as information, entertainment and social utilities (Bauer et al., 2005). Information utility refers to the
messages providing timely, useful and up-to-date information. Entertainment utility refers to the messages
providing the recipients with excitement and enjoyableness while social utility refers to the messages that
enable the recipients to demonstrate and share their innovativeness to their community (Bauer et al., 2005).
Unlike commercial messages, the university’s mobile messages are more focus on information utility rather
than entertainment and social utilities. It can be speculated that the higher the students’ perceived utility of
the university’s mobile messages, the more the students’ attitudes toward using the university’s mobile
messaging service.
H1: Perceived utility of the university’s mobile messaging service positively influences students’ attitudes
toward using the university’s mobile messaging service.
2.2 Perceived Control
Perceived control refers to people’s perceptions of their abilities to perform a given behavior or activity
(Jayawardhena et al., 2009). Under the theory of planned behavior, perceived control is not actual control but
the perception of control associated with psychological interest (Ajzen, 1991). Individuals have fully control
over technology when they can decide at will to perform it or not to perform it. If they lack control over it,
their attitudes toward using the technology are thwarted. In addition, individuals who are able to control the
innovative technology will trailer the technology to benefit themselves. Therefore, the more control over the
mobile service, the more perceived utility of the service.
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H2: Perceived control over the mobile messaging service positively influences students’ perceived utility
of the university’s mobile messaging service.
The concept of perceived control is similar to self-efficacy that has been used to understand technology
adoption (Mathieson, 1991). In the mobile marketing area, the feeling of lack of control may prevent
consumers from participating in mobile marketing service (Jayawardhena et al., 2009). Accordingly, students
are more willing to use the university’s mobile messaging service, if they can control over the university’s
mobile messaging service. For example, students can control the number of messages they received, choose
the type of mobile messages (e.g., text, picture or video messages), select the message content to be received,
and cancel the permission to receive mobile messages. Therefore, the higher the student’s perceived control
over the mobile messages, the higher the students’ attitudes toward using the university’s mobile messaging
service.
H3: Perceived control over the mobile messaging service positively influences students’ attitudes toward
the university’s mobile messaging service.
2.3 Existing Knowledge
Existing knowledge affects the cognitive process of acceptance decision (Barutcu, 2007). Consumers’
existing knowledge about mobile communication determines their abilities to understand the features and
usage of mobile marketing services. According to the diffusion theory, technology complexity restrains the
use of the technology. When users perceived difficulty of using an innovative technology associated with
services, they are unlikely to adopt the services. In other words, consumers’ knowledge about mobile
communication services decreases the difficulty to use the services and increases positive attitudes toward the
services (Moreau et al., 2001). Accordingly, students familiar with the mobile communication technology are
more likely to use the university’ mobile messaging service.
H4: Existing knowledge about mobile communication positively influences students’ attitudes toward
using the university’s mobile messaging service
2.4 Information Seeking Behavior
Personal propensity to search and use information is an important construct in the analysis of consumer
behavior (Bauer et al., 2005). Although mobile messages can be personalized to individual preferences, the
personal relevance of the messages still relies on the individual propensity to search information. It has been
reported that individuals displaying a strong tendency towards information seeking behavior tend to exhibit a
high propensity to search and use new information (Raju, 1980) and it affect their attitude towards adopting
mobile marketing. Accordingly, individuals who seek information for their personal interests such as
information update and product comparison enjoy reading more informed messages via the mobile phone. It
can be inferred that students who prefer to search new information for their personal interests are more likely
to subscribe to the university’s mobile messaging service to receive university’s news update and specific
information such as exam schedule and grade release.
H5: Information seeking behavior positively influences students’ attitudes toward using the university’s
mobile messaging service.
In addition, information seeking behavior is related to individual propensity to search information for new
knowledge (Bauer et al., 2005). In relation to mobile communication, individuals having a strong information
seeking behavior have a tendency to acquire information for knowledge update about mobile communication
and, hence, enhance their knowledge about mobile communication.
H6: Information seeking behavior positively influences students’ existing knowledge about mobile
communication.
2.5 Privacy Concern
Consumer’s privacy is perceived as the main risk of mobile commerce (Mitchell, 1999). Mobile medium
enables businesses to reach consumers anytime and anywhere. This creates the potential of risk associated
with privacy concern. The recipient’s phone number might be misused by a sender such as sending unwanted
advertising messages or giving the phone numbers to others. As the mobile messaging service is new for
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university students, students lack of experience with this new service and find themselves in a situation of
high risk of privacy infringement. Using the university’s messaging service, students are aware of receiving
too many messages, unwanted messages or repeated messages from their universities or unauthorized
senders. Students therefore try to reduce these risks associated with personal privacy resulting in the tendency
to deny the university’s mobile messaging service.
H7: Privacy concern negatively influences students’ attitudes toward using the university’s mobile
messaging service.
2.6 Social Norm
Social norm refers to the normative beliefs concerning the expectation from other people (Ajzen, 1991).
Individuals are motivated by other expectations to approve or disapprove of their performing a given
behavior. In case of technology adoption, social norm associates with the motivations of individuals who
believe they should use technologies for positioning themselves in a reference group (Igbaria 1993).
Individuals, therefore, tend to adopt technology to gain acceptance from their community (Hsu and Lu,
2004). Accordingly, students are more likely to use the university’s mobile messaging service, if others in
their community (e.g. friends, instructors) perceive that the service is valuable for them.
H8: Social norm positively influences students’ attitudes toward using the university’s mobile messaging
service.
In summary, the factors affecting students’ attitudes toward the university’s mobile messaging service
and their inter-relationships can be depicted in Figure 1.
Perceived
Control
H2
Perceived
Utility
H3
Existing
Knowledge
H6
Information
Seeking
H4
H5
H1
Attitudes
toward the
university’s
MMS
H8
Privacy
Concern
H7
Social
Norm
Figure 1. The anticipated model
3. METHODOLOGY AND RESULTS
The self-administered questionnaire used as the survey instrument was developed and adapted from the
previous literatures (Jayawardhena, 2009; Bauer et al., 2005; Shimp and Kavas, 1984; Raju, 1980). It
consisted of two sections. The first section contained the statements aimed at addressing the study
hypotheses. The second section requested the respondents’ biographic details. Respondents had to indicate
their agreement with the statements using a five-point Likert scale (1=strongly disagree, 5=strongly agree).
Two hundred and sixty seven students at two universities participated in this survey but only two hundred
and fifty seven questionnaires were usable, giving a response of 96.25 %. This high response rate resulted
from the questionnaires being administered in the class rooms. The usable data at 257 were higher than a
‘critical sample size’ of 200 to provide sufficient power for data analysis using the structural equation
modeling technique (Garver and Mentzer, 1999; Barrett, 2007). Most respondents are Thai (75.5%) and their
ages are between 18 and 24 years (82%). 60 % of respondents are males and 10% of them have never
received any mobile advertising messages.
To check unidimensionality, the principal component factor analysis with varimax rotation was
performed. Items with factor loading values lower than 0.5 were abandoned from further analysis. The results
show that seven eigenvalues are greater than one, suggesting seven extractable factors. Table 1 indicates all
items load above 0.65 on their respective factors, attesting convergent and discriminant validities of each
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factor (Campbell and Fiske 1959). In addition, internal consistencies (Cronbach’s alpha, α) of the factors are
above 0.75, indicating a reasonably good reliability.
Table 1. Factor loadings and reliabilities
Factors
Perceived utility (PU)
Loadings
.840
.857
.817
.811
.801
.817
.680
.854
.842
.853
.864
.849
Existing knowledge (EK)
Information seeking (IS)
Social influence (SI)
Cronbrach’s α
.895
Factors
Perceived
control (PC)
.766
Privacy
concerns (PR)
.867
Attitudes
toward using
MMS (AT)
Loadings
.816
.848
.751
Cronbrach’s α
.804
.824
.877
.797
.793
.793
.744
.807
.857
.797
The Confirmatory Factor Analysis (CFA) utilizing the Maximum Likelihool estimation method was
conducted with the AMOS (version 18) package. The results shown in Figure 2 indicate that all respective
factors excluding privacy concern and information seeking behavior provide significant effects on designated
factors (H1-4, H6 and H8 are accepted). Privacy concern on receiving the university’s mobile messages and
information seeking behavior show no significant effects on students’ attitudes toward using the mobile
messaging service from the university (H5 and H7 are rejected). Information seeking behavior, however, has
a significant effect on students’ knowledge about mobile communication.
Fit indices of the anticipated model provide a reasonable model’s fit. Goodness-of-Fit Index (GFI) is
0.869 which is slightly below the acceptable threshold at 0.9 (Graver and Mentzer, 1999). Root Mean Square
Error of Approximation (RMSEA) is .066 slightly above the acceptable threshold at 0.05 for a good model’s
fit (Hoe, 2008). In addition, Non-Normed Fit Index (NNFI), Comparative Fit Index (CFI), Incremental Fit
Index (IFI) and Minimum Discrepancy per Degree of Freedom (χ2/df) are at .910, .922, .923 and 2.114
respectively, indicating a good fit of the model (Steiger, 1990; Graver and Mentzer, 1999; Hoe, 2008).
PC1
. 80
PC2
. 83
PC3
. 66
PC1
PU 1
PC
.83
. 46**
PR1
PR2
PU 2
.87
. 68
PU
. 87
.77
PC2
PC3
PU1
.80
.83
.82
PC
.44**
.86
PU
.67
.83
.25**
.20*
PU 3
PU 4
. 28**
. 74
EK1
.74
PU4
EK2
.83
.58
PR3
.45**
.04
. 74
E K1
AT 1
. 72
E K2
. 85
E K2
. 62
EK
.23*
. 79
AT
. 81
.57 **
IS1
IS2
IS3
.12
. 86
EK2
SN
.26**
IS2
AT2
SN 2
IS3
AT3
.24**
.77
IS
.86
.43**
.88
. 85
* p<. 01, ** p < . 00 1
Figure 2. Results of the anticipated model
SN1
SN
.75
.69
AT1
.62
.63
.60**
SN 1
AT
.61
AT 3
IS1
.96
IS
AT 2
.24*
. 77
EK
PU3
.41**
.83
PR
PU2
.77
.85
SN2
* p < .01, ** p <.001
Figure 3. Results of the final model
Re-specified models were tested to find the best fit model. The final model omits the insignificant
relationships appeared in the anticipated model and adds two significant relationships; the relationships
between existing knowledge and perceived control and between information seeking behavior and social
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norm. Figure 3 shown above indicates that all causal relationships of the final model are statistically
significant.
Fit indices of the final model are improved indicating that the final model fits the empirical data better
than the anticipated model. Table 2 compares the important fit indices (GFI, NNFI, CFI, IFI, RMSEA and
χ2/df) of the final model and those of the anticipated model. It shows that all fit indices of the final model
provide a better model’s fit.
Table 2. Comparison of the model’s fit indices
Fit Indices
Goodness-of-Fit Index (GFI)
Non-Normed Fit Index (NNFI)
Comparative Fit Index (CFI)
Incremental Fit Index (IFI)
Root Mean Square Error of Approximation (RMSEA)
Minimum Discrepancy per Degree of Freedom (χ2/df)
Threshold
>.90
>.90
>.90
>.90
<.05
< 3.0
Value (anticipated
model)
.869
.910
.922
.923
.066
2.114
Value (final
model)
.922
.957
.965
.965
.050
1.641
4. DISCUSSION
According to the anticipated model, the study found that perceived utility, perceived control, knowledge of
mobile communication and social norm have statistically significant effects on students’ attitudes toward
using the university’s mobile messaging service. Perceived utility of mobile messages in terms of timely, upto-date, and customized messages is perceived by students as a key factor to use the university’s mobile
messaging service [H1]. Students have positive toward using the university’s mobile messaging service when
they perceive that they are able to control the service such as selecting the types of messages received (i.e.,
text, video message), controlling the number of messages received or cancelling the permission to send the
university’s mobile messages [H3]. When students are able to control the messaging service, they can
customize the service to fit their needs [H2]. Moreover, students having knowledge about mobile
communication have positive attitudes toward using the university’s mobile messaging service [H4]. This
knowledge is significantly influenced by their personal information seeking behavior [H6]. The study also
indicates that social norms affect students’ attitudes toward using the university’s mobile messaging service
[H7]. Students, therefore, are motivated by other persons’ expectations to support their attitudes toward using
the university’s mobile messaging service.
Importantly, this study found that privacy concern and information seeking behavior that have been tested
for user’s adoption of mobile messaging service in the business context (commercial messages) do not fully
apply to the adoption of the mobile messaging service in the education context. Students do not have
significant concerns about privacy intrusion bothering them to use the university’s messaging service [H7].
Perhaps, students believe their universities will not send unnecessary or duplicated messages through their
mobile phones. In other words, when the recipients trust the message senders, their privacy concerns about
the sender’s messages will be decreased. The results also show that information seeking behavior does not
have a significant effect on the students’ attitudes toward using the university’s mobile messaging service
[H5]. In this light, students may perceive that information of the university’s mobile messages (e.g.,
university news, student’s grade and class schedule) is also available in other communication channels
including the university’s web site, email and newsletter. It is not necessary, therefore, to use the university’s
mobile messaging service to get the same or even less information. This implies that the university’s mobile
messaging service is perceived by students as a new communication channel for the university to deliver
them information.
According to the final model, the significant associations among multiple predictors and the students’
attitudes toward using the university’s mobile messaging service provided in the anticipated model are
remained. To make a better fit of the anticipated model, two significant relationships between the existing
constructs are added. First, information seeking behavior statistically affects social norms. Students
displaying a strong tendency towards information seeking behavior tend to listen to other persons to support
their decisions. Second, existing knowledge about mobile communication statistically affects the perceived
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IADIS International Conference e-Commerce 2011
control over the mobile services. The more the students are familiar with mobile communication technology,
the more the students want to gain control over the university’s mobile messaging service. For example,
students want to be able to select the types of messages or cancel their permissions for the universities to
send mobile messages because they know that the mobile technology capabilities can respond to their wants.
5. IMPLICATIONS AND LIMITATIONS
The study has theoretical and practical implications. This study fills the gap in literatures by providing the
model to understand factors affecting students’ attitudes toward the university’s messaging service. The
model suggests that some factors affecting consumers’ attitudes towards the mobile commercial services (in
previous studies) are not always apply to the mobile education services. For practical implications, the study
provides guidance for universities to increase students’ attitudes toward using the university’s mobile
messaging service. According to the perceived utility’s effects, universities ought to send mobile messages
perceived by students and their colleagues as useful and gratitude information. A survey may be periodically
used to examine whether students’ satisfaction with the university’s mobile messages. In terms of the
perceived control’s effects, students should be able to cancel their mobile messaging service if they do not
want to receive any future messages. The university may offer students with the opt-out method by sending a
unsubscribe message to the particular number. According to the social norm’s effect, university instructors
and staff should encourage students to use the university’s mobile messaging service as people who are
important to students have significant affect students’ attitudes toward using the services. Instructors may
encourage their students to register for the university’s mobile service to easily obtain their grades and check
their exam schedule.
Although the study empirically tests several key factors affecting students’ attitudes toward using the
university’s mobile messaging service, there are some significant limitations. The generalizability of the
findings might be questioned as the data were only collected at two universities and nonrandom samples.
Future research should reexamine the respective constructs and their inter-relationships. Some additional
factors such as culture of mobile service usage, language and the readiness of mobile messaging technology
may influence students’ attitudes toward the university’s mobile messaging service when the research model
is applied to some particular circumstances (i.e., developing vs. developed country, native- vs. multilanguage university environment). In addition, the study focused on a text messaging service that currently
dominates the mobile messaging market (Poritio research, 2010). Other mobile messaging services including
multimedia messaging service (MMS), mobile e-mail and mobile instant messaging (IM), however, will soon
be used more by students. Future research, therefore, should apply the research model to examine other
mobile messaging services.
6. CONCLUSION
The study aims to understand factors affecting students’ attitudes toward using the mobile messaging service
in the education context. It employs the structural equation modeling (SEM) technique to examine interrelationships among the study constructs derived from the previous studies in the mobile commerce area. The
results show that some factors affecting consumers’ attitudes toward using mobile commercial messages do
not affect students’ attitudes toward using the university’s mobile messages. The study model indicates that
perceived utility, perceived control, social norm and personal existing knowledge about mobile
communication have effects on students’ attitudes toward using the university’s mobile messaging service.
Privacy concern and information seeking behavior do not have direct effects on students’ attitudes toward
using the university’s mobile messaging service. The implications of this study enable universities to
understand students’ adoption of their mobile messaging services and manage their mobile messaging
services effectively.
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IADIS International Conference e-Commerce 2011
INTRODUCING MOBILE SERVICES TO DEVELOPING
COUNTRIES - A SOUTH AFRICAN PERSPECTIVE
Dr. Carolin Löffler and Michael Hettich
Institute of Information Systems
University of Erlangen-Nuremberg, Lange Gasse 20, 90403 Nuremberg, Germany
ABSTRACT
Globally acting service providers are often presented with the challenge how to evaluate a potential market for their
business. Similar models build on a general approach but fail to include the service-specific requirements of the vendor.
This study thereby creates an assessment scheme that evaluates a market for its capability to adopt a mobile service. This
scheme is based on the widely known e-readiness rankings which measure the degree to which a country is ready to
obtain benefits by using information and communication technology.
The created framework is then tested by evaluating the South African environment and whether providing a mobile
loyalty service is feasible in this country. The study also shows how the service has to be modified to raise the probability
of adoption.
Conclusions of the work are as follows: South Africa has shown to be a possible country for the introduction of mobile
services. However, certain modifications (e.g. mobile website access, SMS option) for the targeted service have been
identified as critical success factors.
KEYWORDS
Mobile services, mobile service adoption, m-readiness, mobile loyalty, South Africa
1. INTRODUCTION
Every successful service provider has to deal with the issue of developing a suitable growth strategy. This
strategy involves a qualified, long-term, global performance plan to achieve corporate objectives (Haller
2002).
Haller points out two core questions:
1. On which markets does the service provider want to compete with which services?
2. What competitive advantage distinguishes the provider from others?
In order to answer the first question, the service provider needs a way to select markets according to their
economic attractiveness. An evaluation of the market helps the key decision makers to avoid markets where
their value proposition is likely to fail.
The service lifecycle model (Figure 1) provides a comprehensive understanding of service development
in general. The model helps us to identify the important steps for the re-engineering of a service for an
international context. In order to create a strategy for the international adoption and expansion of the service,
the requirements clearly have to be reconsidered (Figure 1, A). The objective here is to create an assessment
scheme that shows the determinants that affect the adoption in the market. The collected environmental data
is then being used to redesign the service concept and adapt it to these newly found requirements (Figure 1,
B). If necessary, the service is adjusted to improve the value proposition and increase the adoption rate. This
might also imply other variants that need to be technically designed and implemented to enable the service
delivery (Figure 1, C). This article focuses on the requirements definition – the firste step of the service reengineering. There are no existing frameworks that target that specific step. All existing frameworks focus
mainly on general electronic readiness of countries (Dada 2006). But service provider still struggle at
introducing mobile services (Bouwman et al. 2009). Therefore the aim of this article is to create a framework
that enables the assessment of countries in regards to any mobile service. The developed assessment
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framework is then applied to the business environment of South Africa considering the mobile loyalty service
mBonus.
Service
re-engineering
B
Finding and
assessing ideas
Define
requirements
Design
Implementation
Service
Delivery
Replacement
C
A
Service
creation
Service
engineering
Service
management
Figure 1. Service lifecycle model
2. MOBILE LOYALTY SERVICE MBONUS
mBonus is a service for consumers to collect loyalty points at retailers using their mobile phones. After
reaching a certain amount of loyalty points (loyalty points cannot be traded between shops) the consumer
receives a bonus (e.g., one coffee for free) and the collection process starts over again. All relevant data is
accessed via the iphone and stored on a central server instead of a plastic or paper-based card. The system
especially meets the needs of small and medium-sized companies. Retailers gain a competitive advantage and
improve customer relationship management by analyzing consumer data. mBonus is strongly based on
permission marketing to foster customer acceptance. Communication with consumers is customized
according to their individual preferences. The current mBonus service is developed for the German market
(Löffler and Bodendorf 2010).
3. M-READINESS
3.1 Framework Development
When designing a mobile service for a country (or a set of countries), several requirements have to be
analyzed to indicate whether this offering can actually provide value in the given environment.
Some of these indicators provide additional input for the later phases of service design and help to adjust
the critical design issues that can mitigate the negative effects of the environment.
In order to get a more structured view of the environment, the benchmarking framework “E-Readiness”
(Electronic Readiness) was used in this study. It measures the degree to which a country, nation or economy
is ready, willing or prepared to obtain benefits by using information and communication technologies (ICTs)
(Dada 2006). These indices are used to compare countries by summarizing a broad set of characteristics for a
given nation. E-readiness assessments are conducted yearly by various organizations such as the United
Nations Public Administrations Network (UNPAN), the World Bank and the Economist Intelligence Unit1
(EIU). This study is referring to the EIU version because most of the data is publicly available.
In 2010, they renamed these “e-readiness rankings” to “digital economy rankings” to reflect the
increasing influence of ICT in economic and social progress. In fact, they claim that virtually all countries in
the report have already achieved “e-readiness” to one degree or another (Economist Intelligence Unit 2010).
Most countries that are not reflected in the report are suffering from the so-called “global digital divide”:
This humanitarian issue describes the fact that receiving, downloading and sharing information is seen as
fundamental human right such as jobs, shelter, food, healthcare and drinkable water. People that are not able
1
The “Economist Intelligence Unit” is the business information arm of “The Economist Group” which also publishes “The Economist”.
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IADIS International Conference e-Commerce 2011
to participate in this digital experience are being hindered in their development. For example, Finland (4th in
the EIU rankings, 85% of population have internet at home) has already gone so far to pass a bill to enshrine
internet access as a human right, whereas countries such as Congo (not listed in EIU, 0.1% of population
have internet at home) are still poles apart from this state2. This situation is leads the focus of this assessment
is on the transfer of a mobile service from a developed country to an emerging or developing country.
Differences in terms of infrastructure, business opportunities and political stability tend to be negligible when
comparing two developed countries, giving minimal input to adjust the service to the market.
Table 1 shows the e-readiness criteria that are divided into six categories.
Table 1. Subcategories of e-readiness and m-readiness
2
Categories
E-readiness EUI subcategories
Modified m-readiness subcategories
Connectivity
and
technology
infrastructure
Broadband quality
Broadband affordability
Mobile phone penetration
Mobile quality
Internet user penetration
International Internet bandwidth
Internet security
Mobile phone access
Smart phone penetration
Feature phone penetration
Basic phone penetration
Mobile quality
Internet user penetration
Mobile internet user penetration
International Internet bandwidth
Business
environment
Overall political environment
Macroeconomic environment
Market opportunities
Policy towards private enterprise
Foreign investment policy
Foreign trade and exchange regimes
Tax regime
Financing
Labor market
Overall political environment
Macroeconomic environment
Market opportunities
Policy towards private enterprise
Foreign investment policy
Foreign trade and exchange regimes
Tax regime
Financing
Labor market
Social and
cultural
environment
Educational level
Internet literacy
Degree of entrepreneurship
Technical skills of workforce
Degree of innovation
Educational level
Digital literacy
Degree of entrepreneurship
Technical skills of workforce
Degree of innovation
Legal
environment
Effectiveness of traditional legal framework
Ease of registering a new business
Laws covering the Internet
Level of censorship
Electronic ID
Effectiveness of traditional legal framework
Ease of registering a new business
Laws covering the Internet
Level of censorship
Restrictions on technology standards
Government
policy and
vision
Government spending on ICT as proportion of GDP
Digital development strategy
E-Government strategy
Online procurement
Availability of public services for citizens
Availability of public services for businesses
E-Participation
Government spending on ICT as proportion of GDP
Digital development strategy
E-Government strategy
Online procurement
Availability of public services for citizens
Availability of public services for businesses
E-Participation
Consumer
and business
adoption
Consumer spending on ICT per head
Level of e-business development
Use of Internet by consumers (e-business)
Use of online public services by citizens
Use of online public services by businesses
Consumer spending on mobile services per head
Use of mobile services
Popularity of similar services
Fuchs and Horak (2008) suggest various solutions to bridge the digital divide.
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In this study each e-readiness category and its subcategories has been evaluated according to the adoption
of a mobile service. Within this process, further criteria have been introduced and others have to be removed
if they are not relevant for the adoption process3.
The result is a mobile service readiness4 assessment scheme to evaluate the readiness of a given country
to adopt a mobile service.
In our study we figured out that the importance of the categories “Business environment”, “Government
policy and vision” and other subcategories remain important for assessing the environment in order to
introduce a mobile service. Those categories were not changed in this study. Hence, this article concentrates
only on the modified and adjusted subcategories.
Connectivity and technology infrastructure: Mobile phone penetration is usually measured by the number
of subscriptions per 100 people. It is crucial to exactly define “subscriptions” in this matter: Some
measurements only use the number of (post-paid) contracts (ITU 2003) which are obtainable from cell
providers, as it is done in the EIU rankings. However, this does not include pre-paid SIM (Subscriber
Identity Module) cards which are almost exclusively used in developing countries (James and Versteeg
2006). In this environment, people also often share phones and/or SIM cards because they are not able to
afford a mobile device themselves. In least developed countries, people build even build a business model
upon this approach: They rent out mobile phones, similar to phone booths for fixed lines. This usage
behavior means that the actual penetration rate is even higher than the “subscription” value suggests (James
and Versteeg 2006). Based on these observations, mobile phone penetration is replaced with mobile phone
access in the m-readiness assessment. Another indicator within the environment that has an obvious
influence on the mobile service is the presence of various models and the functionality that come with them.
However, the number of available models on the market is extremely high and each model is able to perform
many different functions. In order to reduce this complexity for the assessment, a three-fold classification is
used in this study (partially based on Admob 2010): Smartphones, feature phones and basic phones. For
people in developing countries, mobile browsing is very often the primary way of accessing the Internet
(Rice and Katz 2003). Computers and electricity are scarce in rural areas which makes mobile phones with
long lasting batteries vital. This shows the importance of offering services for the internet as well as a mobile
version that is customized to the properties of smart phones and feature phones. To reflect this in the mreadiness assessment, the additional factor mobile internet user penetration is added which indicates how
much of the population is already using the internet on a mobile device.
Social and cultural environment: Besides using demographics as indicator for the social and cultural
environment category, assessing the level of mobile literacy requires extensive research of people and their
mobile usage patterns by using qualitative and quantitative methods (Hargittai 2005). Since more profound
research in this direction still needs to be conducted, the more general indicator “digital literacy” is used in
the m-readiness assessment. This is based on the assumption that whoever is able to use the internet, will also
be able to use a mobile phone. However, feature revisions of the mobile readiness assessment might be able
to utilize more sophisticated statistics in terms of mobile usage and then introduce a mobile literacy indicator.
Legal environment: In terms of information technology, many countries are more restrictive from the
beginning and do not allow certain technologies to be deployed which are already used in most other
countries. Egypt, for example, had banned the commercial use of the global positioning system (GPS). Many
mobile phones such as the Apple iPhone, Nokia N95 or the Blackberry Torch have built-in GPS and were not
allowed to be imported or used in this country (Elyan 2008) which slowed down the adoption of mobile
services for many years. China does not allow devices that do not support their own wireless standard
“WAPI” (Wireless Authentication and Privacy Infrastructure). This was the reason why Apple introduced the
iPhone in China as late as 2009 since they had to create a special variant that includes the WAPI protocol
(Fletcher 2010). These government restrictions can significantly impede the adoption of a mobile service and
therefore have to be investigated during the environment assessment. This is reflected in the “restrictions on
technology standards” indicator.
Consumer and business adoption: Whereas connectivity, business, social, cultural and the legal
environment indicate whether a mobile service can potentially be successful in a country, this category
3
The evaluation uses various assumptions to correlate the findings from the environment assessment with the adoption of the mobile
service. These assumptions are necessary since there is almost no research existing in this field. Further studies could look exclusively at
each of these categories and approve or disprove these assumptions.
4
After now referred to as “m-readiness”.
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IADIS International Conference e-Commerce 2011
scrutinizes existing implementations and their adoption by people and companies. The e-readiness scores put
high emphasis on the extent to which a country’s citizens engage in the use of the internet and online
services. Similar to this approach, the m-readiness assessment aims to gather data on how much consumer
spend on mobile services. Additionally the m-readiness assessment comprises the usage of mobile services
in general and the popularity of similar mobile services in the country. If a mobile service aims to replace
or supplement an existing service, it is necessary to analyze its success and its drivers. The service design has
to take this knowledge into account and can build on the existing success but needs to create additional value
to achieve adoption of the newly designed service.
3.2 Mobile Loyalty Service Assessment for South Africa
South Africa (SA) has undergone a remarkable transition since the end of the apartheid regime in 1994.
Before that year, the country’s economy was dominated by the white minority and blacks remained without
basic political and economic freedoms. Since then, SA has gained stability and turned itself into one of the
emerging markets with the lowest risk spreads (Rodrik 2008).
After being selected to host the FIFA World Cup 2010, even more eyes were directed at the country at the
tip of the “black continent”. The following years will need to show whether SA can maintain the momentum
and generate more growth after this milestone event.
In the mobile field, South Africa has definitely already gained momentum over the last ten years.
Whereas a mere 23% of the population was listed as mobile subscribers in 2001, this number climbed to 92%
in 2009 (ITU 2010).
Another growing market can be found in loyalty programs, which is seen in a “pre-millennium stage
relative to others” (Deon 2007). Deon also mentions that the key to this market could be the increase of
mobile access within the population.
These facts underline why South Africa presents an optimal opportunity to introduce the mobile loyalty
service mBonus in a developing environment.
The following m-readiness assessment further analyzes this environment according to the structure
defined in chapter 3.1. Qualitative research in the form of semi-structured interviews was used to gather
additional data from small and micro-sized enterprises in Cape Town. In a further study this data was used to
conduct the service design and maximize economic and consumer value.
Connectivity and technology infrastructure: A recent report by the ITU (ITU 2010) states a 10.7:1 ratio of
mobile subscribers to fixed lines and a 92.67% of the population being mobile subscribers. Other data by
Teleography (Teleography) used in the article “Mobil in Afrika” (Sokolov 2008) confirms this. A factor that
is not reflected in the above figure is the number of people who neither own a cell phone nor own an active
SIM card but share a phone with someone else, for example within the family. This behavior tends to be very
common especially in poor areas of the country (Scott et al. 2005). This high mobile phone penetration in
combination with the above mentioned “culture of sharing” leads to the assumption that in South Africa a
100% penetration of mobile users can be expected. By 2014 it is expected that every mobile phone sold in
South Africa will be a smart phone (Inggs 2009), a mere 0.2% of the population owned an iPhone in June
2010 (Macforrest.com). Smart phones will become more important in this market, but they are currently only
used by a fraction of the population. In general, detailed data on handset penetration by type is rarely
available. Admob (2010) shows that although Nokia has a 23% worldwide share, they account for more than
two thirds of the devices used in Africa. Nokia’s advantage in this market is their focus on feature- and basic
phones that have shown their advantage in developing countries during the past decade (Lindholm et al.
2003). Their low-end devices (e.g. Nokia 1100, Nokia 3310, and Nokia 1600) are popular in South Africa
(Kreutzer 2009) because they are very affordable in combination with a pre-paid subscription. A good
indicator to assess the number of active feature phones in the South African market is the user number of
active MxIt users, the popular mobile communication service. The service has gathered more than 10 Million
registered users in SA (Mobile Industry Review 2009) and is rumored to have reached the 15 Million mark in
2010. Although some users are actually not aware of it, every phone that supports MxIT also supports the
mobile Internet, since it is using the mobile data network to communicate with their servers. Considering
these numbers, a mobile service needs to target the feature phone segment and offer an alternative for basic
phone users in order to reach a broad audience in this environment. A study conducted by technology
research group “world wide worx” on mobile internet penetration found out: Although 60% of users in the
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market have internet-capable phones, only 21% report that they use this form of access (World wide worx
2010). According to the study, many people either don’t know how to use it or they are not aware that they
are using it because they are only accessing it through a branded application (e.g. MxIT, Facebook). Others
seem to be too concerned of the costs (World wide worx 2010). With decreasing costs and improved usability
through technology lifecycles, the mobile internet penetration could rise to 15 Million users over the next
years making it an important target for mobile marketers as well as the mobile loyalty service provider.
Business environment: Still recovering from the apartheid regime, the distribution of income in SA is
among the most unequal in the world. The level of relative affluence is equal to any country in the developed
world but also the amount of poverty is at a point where it is usually associated with developing countries
(Economist Intelligence Unit, 2008b, p. 19). The South African Department for Trade and Industry (DTI)
praises the country for being the “economic powerhouse of the African continent” (Department of Trade and
Industry 2010). The gross domestic product (GDP) is four times that of its geographic neighbors and 30% of
the entire GDP of Africa.
Social and cultural environment: South Africa has adopted the International Computer Driving License
(ICDL) in 2007. This internationally recognized standard acts as a benchmark for digital literacy amongst all
citizens (ICDL 2010). However, no data is available on how many people already passed the test and possess
this certification. In their 2008 country profile, the EIU describes computer literacy in SA as “low” – but also
mentions that this is an area of growth (Economist Intelligence Unit 2008). With the increasing (mobile)
internet penetration throughout the last two years, digital literacy has sincerely reached a medium level.
Legal environment: No restrictions on technologies that could be utilized as part of the mobile loyalty
service could be found.
Consumer and Business Adoption: Usage prices for mobile communication are higher than in almost any
other comparable country in the world (ResearchICTafrica 2010). Consumers who are not able to afford
these prices often use methods such as “beeping ” as an alternative form of communication. However, the
Average Rate per User (ARPU) is forecasted to remain stable at around ZAR 145 over the next four years
(MarketResearch.com 2010) which is about 10% of the average monthly income of a black SA citizen. The
implications for the design of the mobile loyalty service remain vague but it can be assumed that the
additional costs for the usage of the service should not exceed an estimated 10% of the monthly ARPU
(≈ZAR 14). Numerous mobile services are already widely available in SA. A service that has been al-ready
been mentioned at various points of this paper is MxIt. A total user base of 14 Million shows how widely
adopted a mobile service can be.
The top 10 sites accessed from South African hints to other popular mobile services (Opera Software
2010): Facebook.com, Google.com, Mxit.com,
Youtube.com, Wikipedia.org, My.opera.com, Getjar.com, Zamob.com, Yahoo.com, Blinko.co.za. It can be seen that among the top 3 accessed sites, two are
social communication platforms. Facebook already is the primary way for millions of people worldwide to
stay in touch with friends and relatives (Morgan Stanley 2009). MxIT is offering similar services, but its
popularity remains restricted to the African continent. An implication for the design of the mobile service
could be to integrate social networks in order to create more value for the customer. Mobile loyalty services
offer many advantages over traditional paper or plastic loyalty cards (chapter 2). The popularity of these
traditional systems can have various implications on the adoption of the mobile loyalty service mBonus. One
example shows the complexity of this problem: If people haven’t widely adopted loyalty cards, why did
they? Did they not see the extra value offered by the loyalty schemes or were they just bothered by the cards
they had to carry? Two studies are currently looking at this issue and the willingness of customers to replace
plastic cards with a mobile loyalty system: One of them is being done for Germany; the other one represents
a comparative study in the South African environment. Both are using a quantitative research approach in
combination with the technology acceptance model to collect and analyze data. The latter study will
contribute to the lack of research on the popularity of loyalty cards in South Africa. The only source that
provides information in this area is a case study by Deon (2007) who claims that “South Africa is poised to
become a loyalty marketing gem”. He identifies a growing potential and identifies the “black diamond”
market, represented by the under-served market of the black middle class. However, his paper lacks a strong
foundation supported by relevant and up-to-date data. Personal observations in SA have shown that loyalty
cards are popular, with prominent examples such as the “vida e caffé” coffee shops or the “Kauai” fast food
restaurants.
At this point, it can only be stated that traditional loyalty programs exist in SA until further studies
evaluate their acceptance and popularity.
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4. CONCLUSION AND FURTHER RESEARCH
Having applied the mobile service readiness assessment on the South African environment, one mandatory
conclusion needs to be whether this market is suitable for the introduction of a mobile loyalty service. The
answer is “Yes” – but with certain restrictions.
First of all, the targeted businesses need to possess employees with a certain skill level that is needed to
operate the mobile loyalty service mBonus and understand the benefit of it. Usability and documentation of
the service have to be aligned with the abilities of the average small business owner. Secondly, the shop itself
needs to have a permanent location and a recognizable identity or otherwise a true relation with the customer
cannot emerge.
The service itself will need to adapt its implementation by adapting the service delivery and offering
multiple variants of the application to maximize the reachable consumer base. By providing a set of variants,
the service can go along with the technology lifecycle and enable a richer experience, in case the customer
acquires or temporarily uses a newer device.
After these adjustments have been made, further studies can look at the acceptance and integrate the
customer to further tweak the offerings.
In terms of methodology, the findings showed the relevance of a framework that evaluates a given
environment for the factors affecting the adoption of a mobile service. Similar evaluation schemes do not
cater the mobile requirements enough. The created mobile readiness assessment scheme should hereby be
considered as a first explorative approach to this new field in the area of strategy planning.
Each category of the assessment hereby has the potential of being a separate study by itself: At this point,
mere assumptions of the influence of these categories to the adoption of the mobile service could be made.
What further complicated these evaluations was the incomplete data within some of the categories.
Future studies will need to rely on more exhaustive data sets to confirm or negate these hypotheses. By
then applying the methodology to multiple other countries, the substance of the mobile service readiness
assessment can eventually be demonstrated.
REFERENCES
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Bouwmann, H., Carlsson C., Walden, P., Molina-Castillo, F. J. Reconsidering the actual and future use of mobile
services. Information Systems and E-Business Management, 7(3), 301-317.
Dada, D. 2006. E-Readiness for Developing Countries: Moving the focus from the Environment to the Users. The
Electronic Journal on Information Systems in Developing Countries, 27(6), 1–14.
Deon, O. 2007. South Africa poised to become a loyalty marketing gem. Journal of Consumer Marketing, 24(3), 180–
181.
Department of Trade and Industry 2010. Why Invest in South Africa? Retrieved from http://www.dti.gov.za
/investing/whyinvestinsa.htm.
Economist Intelligence Unit 2008. South Africa - Country Profile 2008.
Economist Intelligence Unit 2010. Digital economy rankings 2010.
Elyan, T. 2008. Ban on commercial use of GPS in Egypt has consumers frustrated. Retrieved from
http://www.dailystaregypt.com/article.aspx?ArticleID=16972.
Fletcher, O. 2010. Apple tweaks Wi-Fi in iPhone to use China protocol. Retrieved from http://www.pcworld.com
/article/195524/.
Fuchs, C., and Horak, E. 2008. Africa and the digital Divide. Telematics and Informatics, 25, 99–116. Retrieved from
http://fuchs.icts.sbg.ac.at/divide.pdf.
Haller, S. 2002. Dienstleistungsmanagment: Grundlagen, Konzepte, Instrumente (2. überarb. und erw. Aufl.).
Wiesbaden: Gabler.
Hargittai, E. 2005. Survey Measures of Web-Oriented Digital Literacy. Social Science Computer Review, 23(3), 371–
379. Retrieved from http://ssc.sagepub.com/content/23/3/371.full.pdf#page=1&view=FitH.
Inggs, M. 2009. South Africa - Smartphones 'Are Taking Over'. Retrieved from http://allafrica.com/stories
/200908240056.html.
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ICDL 2010. Mission and values. Retrieved from http://www.icdl.org.za/about.php?id=9.
ITU 2003. Mobile overtakes fixed: Implications for Policy and Regulation.
James, J. and Versteeg, M. 2006. Mobile phones in Africa: how much do we really know?
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Indicators/Indicators.aspx#.
Kreutzer, T. 2009. Generation Mobile: Online and Digital Media Usage on Mobile Phones among Low-Income Urban
Youth in South Africa (Master Thesis). University of Cape Town, Cape Town.
Lindholm, C., Keinonen, T., and Kiljander, H. 2003. Mobile usability: How Nokia changed the face of the mobile phone.
New York: McGraw-Hill. Retrieved from http://www.loc.gov/catdir/bios/mh041/2002044394.html /
Loeffler, C., and Bodendorf, F. 2010. Mobile Loyalty Services - a Retailer and Consumer Survey. Proceedings ICIME,
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MarketResearch.com 2010. South Africa Mobile Operator Forecast 2010. Retrieved from http://www.marketresearch.com/product/display.asp?productid=2794760&g=1.
Mobile Industry Review 2009. Mxit - South Africa's No. 1 Mobile Social Networking Startup. Retrieved from
http://www.mobileindustryreview.com/2009/02/mxit.html.
Morgan Stanley 2009. The Mobile Internet Report Setup. Retrieved from http://www.morganstanley.com
/institutional/techresearch/mobile_internet_report122009.html.
Opera Software 2010. State of the Mobile Web. Retrieved from http://media.opera.com/media/smw/2010
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ResearchICTafrica 2010. South African Sector Performance Review 2009/2010. Retrieved from http://www.researchictafrica.net/new/images/uploads/SPR20092010/SA_SPR-final-web.pdf.
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dropouts. Telecommunications Policy, 27, 597–623. Retrieved from http://www.sciencedirect.com/science?_
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Rodrik, T. 2008. Understanding South Africa's economic puzzles. Economics of Transition, 16(4), 769–797. Retrieved
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Sokolov, D. A. J. 2008. Mobil in Afrika - Das Handy revolutioniert den Kontinent. c't, (21), 106–111.
World wide worx (27.05.210). The mobile Internet pinned down. Retrieved from http://www.worldwideworx.com
/2010/05/27/the-mobile-internet-pinned-down/.
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THE IMPACT OF INNOVATION, STANDARDIZATION,
TECHNOLOGY MARKETING STRATEGY ON THE
PERFORMANCE IN SOFTWARE COMPANY:
COMPARATIVE STUDY ON SOFTWARE TYPE
Sung Hee Jang, Dong Man Lee and Hyun Sun Park
Business of Administration, Kyungpook National University
1370 Sankyuk-dong, Buk-gu, Daegu, 702-701, South Korea
ABSTRACT
The purpose of this study is to examine the factors influencing performance of software companies. This model tests
various theoretical research hypotheses related to innovation, standardization, technology marketing strategy and
software type. Smart PLS (Partial Least Square) 2.0 and SPSS 15.0 have been utilized for deriving the study results. The
result of hypothesis testing is as follows. First, standardization and technology marketing strategy positively influence
financial performance. Second, innovation, standardization, technology marketing strategy positively influence technical
performance. Finally, mobile and non-mobile software companies was shown that innovation, standardization, and
technology marketing strategy has different effects to financial and technical performance.
KEYWORDS
Innovation, Standardization, Technology Strategy, Performance, Software Company, Software Type
1. INTRODUCTION
In the world of globalization now in progress, while there is evolution in capital, manpower, and resources
free movement in the global world, diffusion of global sourcing and infinite economy have been intensified.
Accordingly, for the sustainable growth of our future domestic economy, service-oriented knowledge
economy’s movement is essential. Software (SW)’s role has been emphasized as the possible core-base of
knowledge and information’s accumulation · organization · utilization. In particular, SW and R&D,
manpower training and knowledge with the OECD's investment as three indicators of knowledge-based
society have established itself as key elements.
Software industry is said to be all industries involved in a series of steps of software development,
distribution, maintenance, etc. The software industry can be defined as software development · manufacture ·
production · distribution, etc. and related services, and information system operating in related industries.
According to Korea Software for Market Analysis and Forecasts Report Domestic software market in 2010,
in a scale of US$3.18 billion is expected to be among the annual growth of 7.0% over the previous year, is
also expected to grow 7.2% in the long term average to US$4.205 billion in the year of 2014. In Korea ICD,
software market recent international economic situation is recovering steadily improving the performance of
the major corporate customers and is expected to increase investment and as a result, overall domestic
demand for investment in software and the market was expected to grow steadily (Korea IDC, 2010).
Meanwhile, software companies include in the study about standardization and flexibility of software
processes and project performance (Liu et al., 2008), the software flexibility and project management control
factors that impact on performance (Wang et al., 2008), a study on the project risk and performance (Suh and
Jeong, 2002),
Studies on the effect of performance of product innovation considering the product
development process and the knowledge acquisition process (Jordan and Segelod, 2006), success factors of
software ventures (Ahn and Kim, 2002), and a study on the profile of uncertainty and project performance
(Na, 2004). There is a lack of researches regarding software company’s innovation, standardization, and
technology marketing strategy.
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The paradigm of the recent market evolved into an open market; even in mobiles for users, there is a
growing interest for the provision of a variety of applications and content to enable mobile software platform.
In the future mobile software’s dependence to wireless internet service and mobile devices, applications and
content will increase. In the mobile software market initiative to ensure competition is expected to be keen.
Therefore, there is an expected difference of the impact of software companies and mobile software
companies and non-mobile innovation, standardization, technology marketing strategy on the performance of
software companies.
The purpose of this study is to verify the factors affecting the performance of software companies’
innovation, standardization, technology marketing strategy and depending on the type of software, whether
there are differences in these factors. To achieve the research objectives, demonstration software for
companies in Korean were investigated. The result of the study that identifies the factors affecting Korean
software companies will provide the strategic implications.
2. RESEARCH MODEL AND HYPOTHESES
2.1 Innovation
Software innovation can be related to several aspects of the product, such as its features and performance
parameters, the impression of its newness according to various market actors, and the novelty of its
architectural structure (Jordan and Segelod, 2006). Garcia and Calantone (2002) provided novelty of product
innovation for customers (newness) and defined the novelty of the market and technology and market
expertise and technical know-how. Jordan and Segelod (2006) been suggested to be able to lead software
product advantage, product newness and company structural change. The software innovation project
outcomes will be improved. Thus, based on previous literature and the arguments presented above, the
followings are hypothesized:
H1-1: Innovation has a positive effect on the financial performance.
H1-2: Innovation has a positive effect on the technical performance.
2.2 Standardization
In the software development process, standardization can be said as the procedure of documenting the
development of the software or technical information. Nidumolu (1996) categorized standardization as output
controls standardization and behavior controls standardization. Because of the influence affecting software
process performance and product performance these standardized residual risks were negatively affected. Shu
and Jeong (2003) formulated the procedure regarding the development and standardization of technical
requirements and they found out that standardization improves process performance. Na (2004) studied about
the impact of standardization and requirements uncertainty to software project performance and found out
that standardization of software development reduces the risk of residual. Liu et al. (2008) software process
standardization improved project performance and found out that software flexibility was also a significant
influence. Thus, based on previous literature and the arguments presented above, the followings are
hypothesized:
H2-1: Standardization has a positive effect on the financial performance.
H2-2: Standardization has a positive effect on the technical performance.
2.3 Technology Marketing Strategy
Technology marketing strategy, while supporting the business strategy in the position to lead the business
strategy linked to each other organically, the lower companies reserve technical resources based on external
business attribute acts as the main expression. In companies developed superior software products are being
introduced to many customers and in order to be continually utilized, especially in order to ensure
insufficient sales force in normal sized enterprises technology-based strategies are important for product
sales. In marketing of software products customer-facing products is essential, distribution may depend on
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the specific hardware and in virtual space, regardless of the intent of the provider you choose a product that
can have a variety of distribution channels. (Pihlava, 1996).
Ahn and Kim (2002), on the study of factors affecting performance of software ventures, technology
strategy affects performance is studied. In technology marketing strategy characteristics of technology and
software products, technology and product development strategies, technology marketing strategy was set up
as a study. Technology and product development strategy and technology marketing strategy showed the (+)
effect on company performance. Similarly, Ahn and Kim (2001) stated that the technology marketing
strategy improves performance of customer, internal processes, learning, and innovation. Thus, based on
previous literature and the arguments presented above, the followings are hypothesized:
H3-1: Technology marketing strategy has a positive effect on the financial performance.
H3-2: Technology marketing strategy has a positive effect on the technical performance.
2.4 Software Type
Recent mobile devices such as smart phones, including the tablet expands the prevalence of competition in
the mobile software market is unfolding. According to increased use of mobile devices, mobile software
industry continues to grow, mobile software companies and non-mobile software companies and innovation,
standardization, technology marketing strategy expects to influence the performance of software companies.
Thus, based on previous literature and the arguments presented above, the followings are hypothesized:
H4-1: Innovation’s impact on financial performance will differ depending on the type of software.
H4-2: Innovation’s impact on technical performance will differ depending on the type of software.
H5-1: Standardization’s impact on financial performance will differ depending on the type of software.
H5-2: Standardization’s impact on technical performance will differ depending on the type of software.
H6-1: Technology marketing strategy’s impact on financial performance will differ depending on the type
of software.
H6-2: Technology marketing strategy’s impact on technical performance will differ depending on the
type of software
The research model is presented as in Figures 1.
Figure 1. Research Model
3. RESEARCH METHODOLOGY
3.1 Operational Definition of Variables and Measurement Items
Innovation was defined as a new platform or module level than traditional software products. Standardization
has been defined as the extent standardized and documented software development process. Technology
marketing strategy was defined as the extent analysis of ideas and economic for software’s marking and
development. Financial performance was defined as software related to corporate financial and technical
performance were defined as the number of new products development and R & D budgets percentage
increase.
Measurements in previous studies were developed in order to use empirically validated metrics. Except
for the demographic variables, all variables were measured as 7-point scale. Table 1 is a summary of
measurement items.
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Table 1. Measurement Items
Variables
Innovation
Standardization
Technology
marketing
strategy
Financial
performance
Technical
performance
Measurement Item
- Feature set differences over the closest prior developed product
-New platform for an existing software product
-New modules for an existing software product
-Product performance compared to closest available competitive product in
the relevant market segment
-To what extent does the software organization use a standardized
software development process?
-To what extent does the software organization use a standardized and
documented software development process on each project?
-To what extent is a mechanism used for ensuring compliance with the
software engineering standards?
- Degree to correspondence closely to development of trade
- Degree to secure product supply chain and cooperation
-Thorough data gathering and evaluation
-Thorough analysis of feasibility
- Increase of average sales
-Increase of net profit
-Level of increment on the return on invested capital
-Improvement of cash flow
- Increase the number of degree of development of new software products
- Increase in R & D budget, and feeding rate
Indicators
Related Literature
4
Jordan and
Segelod(2006)
3
Liu et al.(2008)
4
Ahn and Kim(2002)
4
Rai et al.(2006), Yao
et al.(2007)
2
3.2 Sample and Survey Research Methods
Data for this study were collected from August 1, 2010 to October 31. After removing the unsuitable
questionnaires, a total of 100 survey data were considered to be analyzed. The statistical analysis used in this
study was Smart PLS 2.0 and SPSS 15.0. PLS (Partial Least Square) is one of the two generation structural
equation models for the analysis of the amount of multivariate. It is to use the main factor analysis, the
normal distribution, and a structural equation’s large restriction on the data collections, due to its free from
severe assumptions. The existing methods of structural equation’s goal are to estimate the relevance of the
model but independent variables indicated by the value R2 predicts better how much dependent variables
change. Research models have early stages of theory development and are an appropriate way when it hasn’t
been verified thoroughly yet (Teo et al., 2003). In previous studies of social enterprises, because of the few
studies in environmental uncertainties and related entrepreneurial spirit and achievements, PLS was utilized
as the appropriate analytical techniques in this study.
There are 89 males and 11 females. In the number of employees, there are 35 companies (35.0%) that
have the 10 to 30 employees and 26(26.0%) companies have less than 10 employees. In annual sales, 46
companies (46.0%) had less than US$10 billion and 27 companies (27.0%) have US$ 10 billion – US$50
billion. In software type, 47 companies are mobile companies and 53 companies are non-mobile companies.
Table 2 shows the characteristics of the sample data.
Table 2. Sample Characteristics
Classification
Gender
Number of Employees
Annual Sales
S/W type
102
Male
Female
Total
Less than 10
10~30
30~50
50~110
More than 110
Total
Less than US$10 billion
US$10 billion~ US$50 billion
US$50 billion~ US$110 billion
More than US$100 billion
Total
Mobile S/W company
Non-mobile S/W company
Total
Frequency
Percentage (%)
89
11
100
26
35
16
12
11
100
46
27
17
10
100
47
53
100
89.0
11.0
100.0
26.0
35.0
16.0
12.0
11.0
100.0
46.0
27.0
17.0
10.0
100.0
47.0
53.0
100.0
IADIS International Conference e-Commerce 2011
4. RESULTS AND DATA ANALYSIS
4.1 Reliability and Validity Analysis
In this study, Cronbach's α coefficient was used to verify the reliability of measurement tools. In the
reliability analysis, Cronbach's α of all variables were above 0.8. Thus, overall reliability is higher and all
configuration concepts used can be seen as reliable. In order to verify constructs between reliability and
validity, the value of the concept of reliability (ICR) and Average Variance Extracted (AVE) were calculated.
If the reliability concept is higher than 0.7 (Chin, 1998), it considers valid. Parameters and limits in this study
are exceeded and values exceed 0.5. Thus, it has reliability and validity. Table 3 shows the reliability and
validity analysis.
Table 3. Reliability and Validity Analysis
Variables
Innovation
Standardization
Technology marketing strategy
Financial performance
Technical performance
Item
Factor loading
IN1
IN2
IN3
ST1
ST2
ST3
TS1
TS2
TS3
TS4
FP1
FP2
FP3
FP4
TP1
TP2
.870
.953
.898
.934
.943
.825
.858
.863
.865
.872
.891
.946
.879
.888
.949
.950
AVE
ICR
Cronbach’s ⍺
.824
.933
.895
.814
.929
.887
.747
.922
.888
.813
.946
.924
.902
.948
.891
4.2 Correlation Analysis
Correlation analysis is an analytical technique to measure how close two variables are. Analysis is used to
verify the multi-collinearity between the independent variables put together with the analysis of multivariate
analysis. There is analyzed with the structural model since there are no multi-collinearity problems as shown
in Table 4.
Table 4 is presented on the diagonal square root of the AVE values. The square root of AVE exceeded
0.707. If the correlation coefficient exceeded its value, the validity between each component of the concept
can be secured (Yi and Davis, 2003). The AVE values for all variables’ square root showed to be bigger than
the correlation coefficient between the concepts. Since the correlation coefficient exceeded its value, it
proved the existence of discriminant validity.
Table 4. Correlation Analysis
Variables
IN
.908++
ST
Innovation
Standardization
.246
.902
Technology marketing
.514
.393
Financial performance
.154
.321
Technical performance
.487
.278
++
The values are presented on the diagonal of the square root of AVE
TS
FP
TP
.902
.411
.562
.842
.479
.954
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4.3 Hypothesis Testing
The results: First, innovation appears to have (+) positive effects on technical performance. Hypothesis 1-2
(path coefficient = 0.267, t = 8.079) was adopted. And innovation appears to influence (-) negatively on
financial performance. Hypothesis 1-1 (path coefficient =- 0.089, t = 2.458) was rejected.
Second, standardization appears to have a (+) positive effects on financial performance and technical
performance. Hypothesis 2-1 (path coefficient = 0.194, t = 6.279) and Hypothesis 2-2 (path coefficient =
0.053, t = 1.914), respectively were adopted.
Third, technology marketing strategy appears to positively influence financial performance and technical
performance. Hypothesis 3-1 (path coefficient = 0.380, t = 14.421) and Hypothesis 3-2 (path coefficient =
0.404, t = 10.281), respectively were adopted.
Table 5 is a summary on the results of hypothesis testing.
Table 5. Hypothesis Testing Results
Channel
H1-1 Innovation -> Financial performance
H1-2 Innovation -> Technical performance
H2-1 Standardization -> Financial performance
H2-2 Standardization -> Technical performance
H3-1 Technology marketing -> Financial performance
H3-2 Technology marketing -> Technical performance
Significance level: *: p<0.1 **: p<0.05 ***: p<0.01
Path Coefficient
-.089
.267
.194
.053
.380
.404
t value
2.458
8.079***
6.279***
1.914**
14.421***
10.281***
Test Results
Not-accept
Accept
Accept
Accept
Accept
Accept
4.4 Software Type
In this study, we verified whether there are differences between mobile software company (n = 47) and nonmobile software company (n = 53). In Figure 3, mobile software companies and non-mobile software
companies is a result of the structural model analysis. In mobile software companies, innovation,
standardization, technology marketing strategy appear to improve financial performance and technical
performance but for non-mobile software companies, standardization had a significant impact on financial
performance and technology marketing strategy appears to (+) positively influence financial and technical
performance.
Figure 2. Path Analysis of the Type of Software
A comparison of the difference between the path coefficients, Chin et al. (1996) proposed a formula. This
formula was applied in the studies of Keil et al. (2000), Ahuja and Thatcher (2005).
pi : i second path coefficient , ni : i second sample size
SEi : i second path, the standard error of coefficient, tij degrees of freedom : n1+n2-2
The above formula for calculating the non-mobile software, mobile software companies and enterprises
value of the path coefficients and standard errors can be found in Table 6. Using the formula above, the result
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IADIS International Conference e-Commerce 2011
is also shown in Table 6. The results, all path coefficients and t value of the difference appeared significantly
H4-1, H4-2, H5-1, H5-2, H6-1, H6-2 and were both adopted.
Regarding technology marketing strategy and their impact on the technical performance, non-mobile
software company has higher path coefficient than mobile companies. Mobile software companies, all the
rest of the path coefficient was higher than the non-mobile software companies.
Table 6. Analysis of the Difference between the Type of Software
Hypothesis
H4-1
(Innovation
-> Financial performance)
H4-2
(Innovation
-> Technical performance)
H5-1
(Standardization
-> Financial performance)
H5-2
(Standardization
-> Technical performance)
H6-1
(Technology marketing strategy
-> Financial performance)
H6-2
(Technology marketing strategy
-> Technical performance)
Path coefficient
Standard error
Coefficient t value of
difference
Path coefficient
Standard error
Coefficient t value of
difference
Path coefficient
Standard error
Coefficient t value of
difference
Path coefficient
Standard error
Coefficient t value of
difference
Path coefficient
Standard error
Coefficient t value of
difference
Path coefficient
Standard error
Coefficient t value of
difference
Mobile
S/W
0.062
0.033
Non-mobile
S/W
-0.551
0.032
Test Results
Accept
94.215***
0.348
0.016
0.011
0.038
Accept
56.495***
0.210
0.023
0.189
0.028
Accept
4.067***
0.124
0.022
-0.069
0.026
Accept
39.796***
0.458
0.022
0.272
0.038
Accept
29.454***
0.391
0.024
0.482
0.029
Accept
16.966***
Significance level: ***: p<0.01
5. CONCLUSION
The purpose of this study is to verify the factors (innovation, standardization, technology marketing strategy)
affecting software company's performance and whether there are differences depending on the type of there
software. To achieve the research objectives an empirical study was conducted between 100 software
companies in Korea. The results of this study can be summarized as follows.
First, it was found out that innovation improves the technical performance but decreases financial
performance. Innovative software products has a significant impact on software companies’ new products,
the extent of R & D budgets but to develop innovative new software product a lot of cost and effort is needed
so it can be interpreted as a negative (-) effect on financial performance.
Second, standardization improves both financial and technical performance. Software companies to
improve the performance of the standardization process have become important. Standardization of software
has developed software developer systematic and consistent software, because improve the financial and
technical performance in software company.
Third, technology marketing strategy influences financial performance and technical performance. In
order to develop software technology, collect ideas and a feasibility analysis. To ensure cooperation and
product supply chain, technology strategy is trying to improve financial and technical performance of
software companies.
Finally, for mobile software companies and non-mobile software companies it was shown that innovation,
standardization, technology marketing strategy has different effects to financial performance and technical
performance. The mobile companies indicate that innovation and standardization improve financial and
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ISBN: 978-972-8939-51-9 © 2011 IADIS
technical performance. Therefore, this study implies that mobile software developer importantly considers
innovation, standardization and technology marketing strategy.
This study has some limitations. First, in this study of the factors affecting software companies,
considered were only innovation, standardization and technology marketing strategy. In future research, there
is a need to consider other factors. Second, this study the performance of software companies’ financial
performance and technical performance show the only factors considered. In future researches, we may be
able to measure performance using software quality and performance of software companies using balanced
scorecard (BSC) in order to make better decision making in technology management strategy.
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Business,” Korean Management Review, Vol. 31, No. 2, pp. 431-461.
Ahn, Y. S. and Kim, H. S., 2001, “An Empirical Analysis on the Performance Factors of Software Venture Business in
the Perspectives of BSC and Subjective Performance,” Information Systems Review, Vol. 3, No. 1, pp. 31-46.
Ahuja, M. K., and Thatcher, J. B., 2005, "Moving Beyond Intentions and Toward the Theory of Trying: Effects of Work
Environment and Gender on Post-Adoption Information Technology Use,” MIS Quarterly, Vol. 29, No. 3, pp. 427459.
Chin, W. W. et al. 1996, “A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effect:
Results from a Monte Carlo Simulation Study and Voice Mail Emotion/Adoption Study,” 17th International
Conference on Information Systems, OH, 1996, pp. 21‐41.
Chin, W. W., 1998, “The Partial Least Squares Approach to Structural Equation Modeling,” In G. A. Marcoulides(ed.),
Modern Methods for Business Research, Lawrence Erlbaum Associates, Mahwah, NJ, pp. 295-336.
Garcia, R. and Calantone, R., 2002, “A Critical Look at Technological Innovation Typology and Innovativeness
Terminology: A Literature Review,” The Journal of Product Innovation Management, Vol. 19, No. 2, pp. 110-132.
Jordan G. and Segelod, E., 2006, “Software Innovativeness: Outcomes on Project Performance, Knowledge
Enhancement, and External Linkages, ” R&D Management, Vol. 36, No. 2, pp. 127-142.
Keil, M., et al., 2000, “A Cross-Cultural Study on Escalation of Commitment Behavior in Software Projects,” MIS
Quarterly, Vol. 24, No. 2, pp. 299-325.
Korea IDC, 2010, Korea Software Market Analysis and Forecasts Report.
Liu et al., 2008, “The Impact of Software Process Standardization on Software Flexibility and Project Management
Performance: Control Theory Perspective,” Information and Software Technology, Vol. 50, No. 9-10, pp. 889-896.
Na, K. S. et al., 2004, “The Impacts of Requirement Uncertainty and Standardization on Software Project Performance: A
Comparison of Korea and USA," Journal of Information Technology Applications & Management, Vol. 11, No. 2,
pp. 15-27.
Nidumolu, S. R., 1996, “Standardization Requirements Uncertainty and Software,” Information & Management, Vol. 31,
No. 3, pp. 135-150.
Pihlava, S., 1996, A Process Improvement Experience in Small PC Software Companies, Master’s Thesis in Helsinki
Univ. of Technology.
Rai, A. et al., 2006, “Firm Performance Impacts of Digitally Enabled Supply Chain Integration Capabilities," MIS
Quarterly, Vol. 30, No. 2, pp. 225-246.
Shu, C. K. and Jeong, E. H., 2003, “The Effect of Project Risk and Risk Management on Software Development Project
Performance,” Asia Pacific Journal of Information Systems, Vol. 13, No. 2, pp. 199-217.
Teo, H. H. et al., 2003, “Predicting Intention to Adopt Interorganizational Linkage: An Institutional Perspective,” MIS
Quarterly, Vol. 27, No. 1, pp. 19-49.
Wang E. T. G. et al., 2008, “The Effects of Chang Control and Management Review on Software Flexibility and Project
Performance,” Information & Management, Vol. 45, No. 7, pp. 438-443.
Yao, Y. et al., 2007, “An Inter-organizational Perspective on the Use of Electronically-enabled Supply Chains,” Decision
Support Systems, Vol. 43, No. 3, pp. 884-896.
Yi, M. Y. and Davis, F. D., 2003, “Developing and Validating an Observational Learning Model of Computer Software
Training and Skill Acquisition,” Information Systems Research, Vol. 14, No. 2, pp. 146‐169.
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IADIS International Conference e-Commerce 2011
E-READINESS IN JORDAN ICT SECTOR COMPANIES
Maha Al-khaffaf
Applied SciencesUniversity
Department of Management Information Systems
166 Shafa Badran 11391, Amman- Jordan
ABSTRACT
This research analyzes the current status of e-readiness by measuring the accomplished achievements that make ICT
sector companies in Jordan ready to host e-transactions (or so-called e-readiness). A questionnaire study was conducted
among 300 upper and middle management level in order to accomplish the research aim that focus on analyzing the
effect of e-readiness enablers on the stage of e-readiness in the targeted companies. The study found that Jordanian
business environment encourages e-readiness in Jordan ICT sector companies, the study recommends improving the
coordination process between public enterprises and the Ministry of Communication and Information, Management
should define the focus, direction, and scope phasing required for their e-readiness plans.
KEYWORDS
E-readiness, ICT, Business environment, Culture and Regulation.
1. INTRODUCTION
E-Readiness is defined as the degree to which a society is prepared to participate in the Digital economy, the
digital economy can help to build a better society. there are number of main areas of activities that contribute
to the overall e-Readiness of a country; Access and connectivity, training, education and public awareness,
government Leadership, business and Private Sector Initiatives and Social Development. Hence, the
equation of ICTs plus e-skilled people seems to be the formula towards e-readiness (Ozmen, 2003). Ereadiness is progressing around the world, but as it’s achieving, it is growing more complex; the connections
must be fast, secure and affordable. Likewise, governments must demonstrate their commitment to digital
development not only through broad policy, but also in practical ways, such as delivering public services to
citizens and business via electronic channels (The Economic Intelligent Agency, 2010). This research project
examines these outcomes, in order to analyze the current state of e-readiness in Jordan ICT sector companies
by documenting some of the e-readiness indicators; figures, numbers and facts as it obtained by Jordanian
public intuitions such as ministry of communication and information technology and discussing and
analyzing e-readiness enablers and studying its effect on the e-readiness stage, using an appropriate research
method; a questionnaire distributed to ICT sector companies in Jordan.
2. LITRATURE REVIEW
E-Readiness can be interpreted as a measure of the extent of the adoption of ICT as the means of interaction
between the government, citizens, and the businesses within a regulatory framework in a country (Peters,
2005). It can be used as an important indicator of its proximity to becoming an e-society. Technology
competence, firm scope and size, consumer readiness, and competitive pressure are significant adoption
drivers, while lack of trading partner readiness is a significant adoption inhibitor (Zhu & Kenneth L.
Kraemer, 2002) as electronic-business intensity increases, two environmental factors. Consumer readiness
and lack of trading partner readiness become less important. Firms are more cautious into adopting ebusiness in high electronic business intensity countries, which seems to suggest that the more informed firms
are less aggressive into adopting e-business. (Selim, 2008) attempts to explore the internal and external
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factors affecting the adoption and acceptance of e-commerce by businesses in developing countries. The
study indicated that most of the firms were either at the first or second stage on the e-commerce 5-stage
adoption ladder. This indicated that the e-commerce adoption is not matching and far less than the IT
readiness of both the firms and the country. In the (E-Readiness Rankings 2007) introduced by The
Economist Intelligence Agency, investment in technology have been seen as an essential requirement, as is
investment in human capital and the promotion of favorable business and legal conditions for online activity
to thrive. E-readiness is ultimately about giving digitally enabled people and businesses as many options as
possible to determine their own most productive path forward. However, the (e-readiness rankings in 2006)
concluded that E-readiness is rightly seen as an enabler of globalization. Yet the relationship is also
increasingly converse, as sources of digital services and supports emerge in some corners of the world that
help to increase the e-readiness of countries in others. (Yalamov, 2002) introduces e-readiness assessment as
a policy tool for development. In Bulgaria transitional context; the assessment pointed out two critical factors
- the indicator of internet usage in business and teachers' readiness for the networked world. A framework for
measuring national e-readiness introduced by (Mr. Bui, 2003) proposed algorithm provides a structured and
methodical approach, rather than relying on intuition and risky conjecture in national e-strategy decisions.
The study framework evaluates the e-readiness of a nation based on eight factors such as digital infrastructure
and macro economy. The study identifies 52 surrogate measures that can be used to quantify these factors
and describe an algorithm to calculate an overall e-readiness index for a country, by using data published by
different world organizations, measures for ten East Asian countries, the USA, and other countries. (Arce and
Hopmann, 2002) concludes that there is a huge unsatisfied demand compared to existing service which can
be covered by traditional technology. The study teaches that 20 hours of internet at home exceeds 80% for
the families; mainly for education. Transportation, communication or other household necessities are 60%,
and they have to spend more than their complete family budget for education. While the past decade Jordan
has seen notable improvements in networked readiness and e-readiness in general, many challenges
remain.(Al-Khateeb, 2001) However, personal computers are not generally affordable because of low
average incomes which remain a great impediment to the spread of Internet use. E-commerce activity is
minimal, although it has adequate e-commerce readiness requirements, but it still lacks some standards and
success factors of E-readiness (Shannak &. Al-Debei, 2006). Furthermore, Jordanian company’s application
of an e-commerce business is small. Jordan’s labor pool is well educated, and ICT education is a top national
priority; the curriculum has been revised at all levels to reflect a new ICT focus.
3. RESEARCH MODEL
Ha1
Business
environment
Ha2
Culture
Main H
Regulation
Technological
support
Ha3
Ha4
Figure 1. Research Model
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E-readiness
IADIS International Conference e-Commerce 2011
4. RESEARCH METHODOLOGY
Cronpach alpha have been used to determine the variable reliability, the study shows a clear statistical
acceptance because (α) values are greater than accepted percent 0, 06. In which Cronpach alpha for all the 16
research questions was .905.
Factor analysis, KMO and Bartlett test multiple regression analysis and Sequential regression analysis
have been used as a statistical methods to analyze the data collected in this study. However, a literature
review was used for descriptive knowledge about E-Readiness model and the requirements of E-Readiness.
The study population is formed from ICT sector companies in Jordan, which were divided in two main
companies; the ministry of communication and information (with its all department distributed in Jordan) and
the national center for information technology.
5. MESURING THE RELATIONSHIP BETWEEN DEPENDENT AND
INDEPENDENT VARIABLE USING MULTIPLE REGRESSION
Multiple regressions have been used in this research hence it is an appropriate analysis for research question
were the relationship between two or more variables, and one dependent variable. (Malhotra, 2000) This
research have used this type of analysis in order to analyses the relationship between the independent
variables that consist 2 factors and the dependent variable.
5.1 Sub Hypothesis1 Ha
There is a direct effect of economic environment on e-readiness stage
Table 1. Multiple regression of hypothesis one
Variable
Economic
environment
Political stability
R Square
F
Sig
Internet Usage
Beta
Sig
.393
.000
.158
T
6.61
.008
2.666
.161
22.945
.000
Computer Usage
Beta
Sig
T
.697
.000
15.484
E-Readiness Stage
Beta
Sig
T
.731
.000
16.224
.082
.091
.070
1.820
.520
131.212
.000
.059
1.945
.500
120.371
.000
From the table above the multiple regressions result shows that there is a direct effect of business
environment on the e-readiness stage. Where R 2 = .500 which means that the independent variable
explained 50% of variance in e-readiness stage because (F= 120.371, p< .05) so we reject the null hypothesis
and accept the alternative which indicates the effect of business environment on e-readiness stage. To
determine which dimension effect the variable, the beta value shows that there is a direct effect of economic
environment on e-readiness stage ( Beta = .731,p<.05) but the model show there is no direct effect of political
stability on e-readiness stage in which ( Beta =.091, p>.05) .
5.2 Sub Hypothesis 2 Ha
There is a direct effect of culture on E-readiness stage.
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Table 2. Multiple regression of hypothesis two
Variable
Social
aspects
Value and
ethics
R Square
F
Sig
Internet Usage
Beta
Sig
.390
.000
T
6.131
Computer Usage
Beta
Sig
.297
.000
T
4.400
E-Readiness Stage
Beta
Sig
.492
.000
T
8.800
.059
.876
.296
4.890
.202
3.666
.380
.179
26.121
.000
.000
.258
41.500
.000
.000
.362
71.30
.000
From table (2) above the multiple regressions result shows that there is direct effect of culture on the ereadiness stage. Where R 2 =. 362 which means that the independent variable explained 36% of variance in
e-readiness stage because (F= 71.30, p< .05) so we reject the null hypothesis and accept the alternative which
indicates the effect of culture on e-readiness stage. To determine which dimension effect the variable, the
beta value shows that there is a direct effect of social aspects on e-readiness stage
(Beta = .492, p< .05) on the other hand the model shows that there is a direct effect of value and ethics on
e-readiness stage in which (Beta = .202, p > .05).
5.3 Sub Hypothesis 3 Ha
There is a direct effect of regulation on E-readiness stage.
Table 3. Multiple Regression of hypothesis three
Variable
Electronic
law
Legislation
Internet Usage
Beta
Sig
.303
.000
T
5.131
Computer Usage
Beta
Sig
.013
.819
T
.230
E-Readiness Stage
Beta
Sig
T
.334
.000
4.231
.187
3.160
.407
7.011
.355
R Square
F
Sig
.002
.139
19.014
.000
.000
.163
24.583
.000
.000
6.553
.200
39.600
.000
From table (3) above the multiple regressions result shows that there is direct effect of culture on the ereadiness stage. Where R Square = .200 which means that the independent variable explained 20% of
variance in e-readiness stage because (F= 39.000, p < .05) so we reject the null hypothesis and accept the
alternative which indicates the effect of regulation on e-readiness stage. To determine which dimension
effect the variable, the beta value shows that there is a direct effect of electronic law on e-readiness stage
(Beta = .334,p< .05) on the other hand the model shows that there is a direct effect of legislation on ereadiness stage in which (Beta = .355, p < .05).
5.4 Sub Hypothesis 4 Ha
There is a direct effect of technological support on E-readiness stage.
Table 4. Multiple regression of hypothesis four
Variable
IT
development
Spread of IT
R Square
F
Sig
110
Internet Usage
Beta
Sig
.217
.000
T
3.584
Computer Usage
Beta
Sig
.064
.254
T
1.144
E-Readiness Stage
Beta
Sig
T
.201
.040
2.088
.224
3.697
.461
8.218
.433
.000
.092
12.637
.000
.000
.219
34.972
.000
.000
223
38.393
.000
7.771
IADIS International Conference e-Commerce 2011
Table (4) shows that there is direct effect of technological support on e-readiness stage. Where R Square
= .223 which means that the independent variable explained 22% of variance in e-readiness stage because
(F= 38.393, p< .05) so we reject the null hypothesis and accept the alternative which indicates the effect of
technological support on e-readiness stage. To determine which dimension effect the variable, the beta value
shows that there is a direct effect of IT development on e-readiness stage (Beta = .201,p< .05) on the other
hand the model shows that there is a direct effect of spread of IT on e-readiness stage in which (Beta =.433,
p< .05).
5.5 Main Hypothesis Ha
There is a direct effect of (business environment, culture, regulation, technological support) on E-readiness
stage.
Table 5. Multiple regression of hypothesis five
Variable
R
R2
F
Sig
Business
environment
Culture
.789
.490
11.387
.000
.799
.553
81.234
.000
Regulations
.745
.589
60.102
.000
Technological
support
.748
.597
42.323
.000
Factor 1(BE)
Factor 2(PS)
Factor 1(SA)
Factor 2(VE)
Factor 1(EL)
Factor 2(R)
Factor 1(ITD)
Factor 2(ITS)
Beta
T
.756
.126
.390
.090
.126
.102
.206
.147
9.023
3.029
4.591
.443
3.007
.679
2.648
.903
(BE): Business Environment, (PS): Political Stability (SA): Social Aspects (VE) Values and ethics (EL):
Electronic Law (R): Regulations (ITD) information technology development. (ITS): Information Technology
Spread.
Table (5) shows that there is direct effect of e-readiness enablers (business environment, culture,
regulation and technological support on the e-readiness stage where:
1- R2 for the business environment equals .789 which means that the independent variable explained 78%
of variance in e-readiness stage because (F= 20.121, p< .05) so we reject the null hypothesis and accept the
alternative which indicates the effect of business environment on e-readiness stage. To determine which
dimension effect the variable, the beta value shows that there is a direct effect of economic environment (F1)
on e-readiness stage (Beta =. 756,p< .05) on the other hand the model shows that there is a direct effect of
political stability (F2) on e-readiness stage in which ( Beta =.126, p < .05).
2- R2 for the culture equals .799 which means that the independent variable explained 79, 9 % of variance
in e-readiness stage because (F= 781.234, p< .05) so we reject the null hypothesis and accept the alternative
which indicates the effect of culture on e-readiness stage. To determine which dimension effect the variable,
the beta value shows that there is a direct effect of social aspect (F1) on e-readiness stage
(Beta =. 390, p< .05) on the other hand the model shows that there is a direct effect of values and ethics
(F2) on e-readiness stage in which
(Beta = .090 p < .05).
3- R2 for the regulation equals .589 which means that the independent variable explained 58, 9 % of
variance in e-readiness stage because (F= 60.102, p< .05) so we reject the null hypothesis and accept the
alternative which indicates the effect of culture on e-readiness stage. To determine which dimension effect
the variable, the beta value shows that there is a direct effect of electronic law (F1) on e-readiness stage
(Beta = .126, p< .05) on the other hand the model shows that there is no direct effect of regulation (F2) on ereadiness stage in which (Beta= .062p < .05).
4- R2 for the technological support equals .597 which means that the independent variable explained 59.7
% of variance in e-readiness stage because (F= 42.323, p< .05) so we reject the null hypothesis and accept
the alternative which indicates the effect of technological support on e-readiness stage. To determine which
dimension effect the variable, the beta value shows that there is a direct effect of IT development (F1) on e-
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ISBN: 978-972-8939-51-9 © 2011 IADIS
readiness stage (Beta = .106,p< .05) on the other hand the model shows that there is no direct effect of IT
spread (F2) on e-readiness stage in which (Beta = .147p < .05).
6. CONCLUSION
With its relatively limited natural resources, Jordan relies heavily on its educated and talented people. One of
the sectors that depend on human elements is Information Technology (IT) Therefore; Jordan’s vision is to
become an Information Technology hub for the region. Based on the research results e- readiness weakness
reasons in targeted companies were; lack of trust of the electronic services, lack of efficiency of the
regulative rules concerned in the trading operations through Internet (such as electronic signature), the high
cost needed by the internet infrastructure and The high cost of managing the web site limits the spread of the
service. This research provides an appropriate model that can be used to assess e-readiness directly by
assessing the e-readiness enablers that is required to be e-ready. It offers a transparent situation analysis
about the current state of e-readiness in Jordan ICT sector, by analyzing and discussing the problems that
face brick and mortar companies. It recommends improving the legal system concerned with the use of ebusiness in Jordan to meet the details that could face the citizen while using internet and e-business. The best
practices can be used by organizations to improve the overall quality of IT software development and support
through the life-cycle of software development projects, with particular attention to gathering and defining
requirements that meet business objectives.
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context. .WIDER Conference (world institute for development economics research. The new economy in development.
Helsinki ,Finland.10-11 May
Tung X. Bui and collaborator (2003) A framework for measuring national e-readiness, Electronic Business journal, Vol.
1, No. 1, 2003 3 Inderscience Enterprises Ltd.
Turabian, Kate L. (1971) Manual Writers of Term Papers, Thesis and Dissertation. Chicago. University of Chicago
Press.
Truong, D., & Rao, S. S. (2003) Development of a contingency model for adoption of electronic commerce. Paper
presented at the Annual Meeting Proceedings of the Decision Sciences Institute.
Turban, E., King, D., Viehland, D. W., & Lee, J. (2006). Electronic Commerce: Managerial Perspective, Pearson
Education, Inc., Upper Saddle River, New Jersey, USA.
Vosloo, S. E. & Roode, D. (2006) who’s Best Practice? A Critical Analysis of the World Summit Awards, Presented at
the 14th European Conference on Information Systems, June 2006, Sweden. (Status: accepted, in press)
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PROMOTORS AND INHIBTORS OF ONLINE GROCERY
SHOPPING IN DEVELOPING COUNTRIES FROM THE
CONSUMERS’ PERSPECTIVE-JORDAN AS CASE STUDY
Mohammad Al nawayseh, Bader Al fawwaz and Prof. Wamadeva Balachandran
Brunel University / West London, UK
ABSTRACT
This study is one of the first attempts to investigate the expected consumer willingness towards online grocery shopping
in the Jordanian context as a case of the developing countries. It seeks to explore the Jordanian consumer’s general
attitude towards buying grocery on the internet with respect to promoting and inhibiting factors. This study was
conducted by formulating hypotheses. These hypotheses were investigated by designing appropriate questionnaire, the
collected data then analyzed using SPSS. The results obtained that the overall mean of the OGS promoting factors is
greater than the overall mean of the OGS inhabiting factors. From this analysis it was conducted that the Jordanian
consumer’s are willing to adopt online grocery shopping.
KEYWORDS
Online Shopping; Online Grocery Shopping (OGS); Inhibiting Factors; Promoting Factors; Jordan; Developing
Countries.
1. INTRODUCTION
In the era of globalization, the Internet has been increasingly used to facilitate online business transactions,
not only between different business entities, but also between business entities and consumers. One of the
Internet business applications that received much attention in the last few years is Online Grocery Shopping
(Belsie, 1998). Electronic grocery shopping means: ordering of groceries online; the electronic grocery stores
offer an electronic ordering interface, and the retailer takes care of packaging and delivery of the goods to the
customer. Online Grocery Shopping has many potential benefits to consumers, particularly in terms of better
prices, large selection, convenience and time-savings. In addition, the retailers will ultimately obtain
significant benefits as it will lead to more efficient use of workforces and simplification of building
infrastructure. However, groceries are one of the most difficult objects of trade for electronic commerce;
material flows are different from information flows, the number of frequent customers is large, and the
shopping basket will contain many items (Kurnia, et al., 1999). Furthermore, it is more local than global, for
example, selling digital products are easily accessible throughout the world. It is also more difficult than
electronic commerce of many other products such as books or clothing, because of low value-to-weight ratio
of groceries and shelf time limitations of perishable goods. The Delivery systems with temperature controlled
storage also causing additional difficulties to Online Grocery Shopping (Kurnia, et al., 1999). While ecommerce adoption has been concentrated in developed countries, especially online grocery commerce; there
is still doubt about the positive expectations of e-Commerce for developing countries. This could be
explained by the differences in e-Commerce readiness, business conditions and consumers’ attitudes towards
online shopping between these countries (Odera, 2003). This study would try to identify the Jordanian
consumer willingness to adopt e-grocery shopping in general, also to highlight the nature of expected
consumer attitudes towards online grocery shopping expressed by the gained benefits or the faced barriers.
The results of this study can serve as a basis for future exploration. It is also hoped to benefit grocery product
retailers, and those who are planning to invest in this new retail format in future.
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2. REVIEW OF LITERATURE
Online Grocery Shopping was first offered in United States in the late 1980s (Belsie, 1998) as many of USbased retailers such as Peapod, Streamline, Netgrocer have entered the market. Since then European
countries like Switzerland, Sweden, Denmark, Finland, UK and other developed nations such as Australia,
Japan and Singapore followed the market trends and many big grocery retailers have also appeared in these
countries such as Tesco, Sainsbury, Albert Heijn and Carrefour (O'Connor, 1998). Table (1) gives examples
from the world leading grocery companies. Initially there was a lot of optimism about selling groceries online
and this industry will be among the fastest growing online businesses around the world because of the Highvolume, low-margin industry (such as food and logistics) and it will turn to the Net cost savings from
automation. However, the optimism was replaced by scepticism when Webvan (the pioneer of online grocery
business based in USA) decided to file for bankruptcy in July 2001 due to its inability to find an optimal and
sustainable business model (Jan, et al., 2000). After that various aspects of online grocery shopping have
been studied to identify the characteristics that can contribute to building a successful online grocery
business; many of these studies have compared the successful and less successful companies in this industry
and others related to the customer’s attitudes and willingness towards online grocery shopping.
Table 1. Grocery retailers
Tesco
UK
The biggest
supermarket
chain in the UK
Web van
USA
Started as a
pure e-grocer
in1999
Streamline
USA
Started as a
pure egrocer in
1992
Peapod USA
Investments
in e-grocer
development
Main
operational
mode
US $58 million
Approx US $
120 million
Approx US
$80 million
Approx US $
150 million
Industrialized
picking from the
supermarket
Highly
automated
picking in
distribution
centre (DC)
Current
status
The biggest egrocer in the
world.
Expanding its
operations
outside the UK.
Partnering with
Safeway and
Groceryworks.
Operations
ceased July
2001
Picking
from the
distribution
centre,
reception
boxes, value
adding
services
Parts of
operations
were sold to
Peapod in
September
2000. The
rest of
operations
ceased in
November
2000.
Background
Carrefour
France
The largest
hypermarket
chain in the
world in terms of
size
Approx US $ 100
million
Ito-Yokado
Japan
The largest
supermarket chain
in the Japan
Picking from
both DC and
stores
Picking from the
supermarket
Picking from the
supermarket
Bought by
global grocery
retailer Royal
Ahold. Second
biggest e-grocer
in the world.
announced that it
was “highly
likely” that it
would dispense
with its
Champion fascia,
with all stores
expected to be
rebranded under
the Carrefour
name
There are 174 ItoYokado stores
operating in Japan.
Expanded
to China, where
they formed a
joint venture
with Wangfujing
Department
Store and China
Huafu Trade &
Development
Group Corp
Started home
delivery service
before the
Internet in 1989
Approx US $ 140
million
Source: Tanskanen, Yrjola and Holmstrom, 2002.
Retail Index, siamfuture, 2010.
In the developing countries, retailers are still at the fancy stage about this kind of retailing. However , a
very few successful online grocery retailers appeared especially in china and Indonesia such as Suguo and
Carrefour as a kind of foreign and national investments (Kurnia, et al., 2004). These companies are facing
significant barriers to implement their online business models, due to poor national infrastructure, weak legal
framework, inadequate IT skills, lack of timely and reliable systems for the delivery of physical goods, low
bank account and credit card penetration, low income, and low computer and Internet penetration. On the
other hand, only a few identifiable e-grocery shopping driving forces were found such as cost reduction,
trading partner demands and telecommunication privatization (Kurnia, et al., 2004, 2006). In the Hashemite
Kingdom of Jordan as a case of the developing countries E-Commerce in general is almost not popular
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among customers and retailers and it is in a very early stage of development, As There are a few websites
that offer merchandizes that can be bought online with the use of credit cards. The following are four
examples of E-Commerce websites: http://www.zalatimosweets.com , http://www.mazaiic.com ,
http://www.jormall.com, http://www.buyfromjordan.com.
However , during the last decade, Jordan has witnessed improvements in the E-commerce sector
according to the 2007 e-readiness rankings from the (Economist Intelligence Unit) in terms of (Connectivity
technology infrastructure, Business environment, Social and cultural environment, Legal environment,
Government policy and vision, Consumer and business adoption) . These improvements were due to the
large efforts that going to improve competition and foreign investment policies also as a result of lunching
several initiatives and strategies implemented by the government and the private sector such as Reach
initiative (2000-2004) and the national strategy for electronic trade (2008-2012).
3. METHODOLOGY
The study was carried out using the survey approach. This section provides a description bout the research
instrument design, the sampling procedure and data collection technique. A specially designed questionnaire
was distributed among 200 randomly selected customers, out of which 178 were returned. Only a total of 150
responses were used for the final analysis. The others were discarded, mainly due to missing values. The
survey was carried out in three major cities in Jordan; Amman, Irbid and Karak, since they are the highly
populated areas in the Middle, North and south of Jordan respectively. In order to reduce misinterpretations,
the questionnaire was made bilingual, using Arabic and English. The original English version was translated
into Arabic using the back-to-back translation method (Zikmund, 1997). Also a pilot study was conducted
before the questionnaire was sent out. It was conducted with 10 respondents and helped in refining the
questions and the layout of the questionnaire. The questionnaire was divided into four parts; the first part was
asking about the respondents demographic variables such as gender, age, etc (table 2). The second part was
asking about the ICT skills and the internet access (how, where and how often). The third part was asking
about the traditional way of grocery shopping including the frequency of shopping, time of shopping and the
type of shops in order to analyze the respondents’ answers. The last part which is the main core of this paper
was asking about the expected benefits and barriers of online grocery shopping using the 5-point likert scale
ranging from 1 (‘strongly disagree’) to 5 (‘strongly agree’) for each item . Fourteen statements were used to
measure if the Jordanian consumers are favorable to the idea of purchasing grocery online or not. We used
the statistical analysis tool SPSS to test the validity of our main hypothesis.
Table 2. Demographic Variables of the respondents
Item
Gender
Age
Education level
Income level
Access to credit cards
Employment Status
Area of living
116
Male
Female
18-29
30-50
>50
Lower education
High school
Bachelor
Graduate
<300
300-500
>500
Yes
No
Public sector
Private sector
Not working
Rural
Suburban
urban
Frequency
91
59
79
57
14
7
22
100
21
21
100
29
112
38
105
29
16
25
58
67
Percent
60.7
39.3
52.7
38
9.3
4.7
14.7
66.7
14
14
14.7
66.7
74.7
25.3
70
19.3
10.7
16.7
38.7
44.7
IADIS International Conference e-Commerce 2011
4. RESULTS AND DISCUSSION
4.1 Benefits from Online Grocery Shopping
Online grocery customers benefit from convenience and higher quality, fresher food (T. C. Fishman) of this
kind of shopping. Online conveniences include the ability to:
(1) Add to the saved shopping list over several days.
(2) Email lists to other family members.
(3) Comment on items.
(4) Receive personalized coupons.
(5) Sort items by calorie count or nutritional information such as sodium content.
(6) Order the ingredients for “one click meals” automatically from online recipes.
(7) Help elderly and disabled customers in home shopping.
Furthermore, according to (Burke, 1997; Darian, 1987) Electronic grocery shopping saves consumers’
time; Due to less transportation time, less waiting time and less planning time and absolutely this is perfect
for busy and relatively affluent consumers who are willing to pay for delivery because of the convenience.
Another advantage of electronic grocery shopping is achieved when a large number of shops give consumers
the ability to select among them according to the brand, prices and others. online grocery store also gives
consumers the ability to carry out transactions at any time of the day (Cheah, 2001; Jan, 2002) since they are
operating 24 hours a day and seven days a week. Table (3) includes the possible benefits from adopting
online grocery shopping (OGS). From the answers of the respondents we see that the majority of them
believe that there are benefits from online grocery shopping and also shows that online shopping will save
their time get the highest average which means it is the most expected benefit from shopping online.
According to the SPSS analysis it was found that the overall Mean (4.11) is greater than mean of the scale
which is 3, this gives an indicator of a positive attitude from the respondents toward the benefits of OGS in
general. The decision here cannot determine on the Mean alone because we have to ensure that the data is not
concentrated in the neutral area. So we need first to put a hypothesis and test it:
Table 3. Benefits to adopt OGS.
Benefits
Enjoyment and fun.
Good selection, availability and quality.
Good price, deal, and comparison.
Broader supply and far shopping.
Easy to use.
Saving my time.
Reduces transport cost.
Convenient for people with specific considerations (female, elders and
physical).
All paragraphs
Mean
3.97
4.19
4.13
4.01
4.14
4.21
4.17
Std.
Deviation
1.013
0.953
0.902
1.007
0.983
0.945
0.923
4.09
0.976
4.11
0.665
4.1.1 Hypothesis One
H0: there are no expected benefits from Online Grocery Shopping according to the customer’s opinion in
Jordan. (Null Hypothesis).
HA: there are expected benefits from Online Grocery Shopping according to the customer’s opinion in
Jordan. (Alternative Hypothesis).
In order to test this hypothesis we need to use the One-Sample T-Test table (4). The decision rule here is
to accept the null hypothesis H0 if the calculated value of T is less than the tabulated one and to reject the
null hypothesis H0 if the calculated value is greater than the tabulated one. It is found here that T calculated =
39.641 is greater than T-tabulated = 1.96(confidence interval =0.95%, DF=∞). Therefore the null hypothesis
HO is rejected and the alternative hypothesis HA is accepted, because the Mean is more than 3 and the Tcalculated is more than T-tabulated (This means that the data is not concentrated on the neutral area and there
is an actual existence for the benefits from OGS) and T Sig. (0.000) is less than (0.05) (Rifat.2003)
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Table 4. Results for the first hypothesis using the one sample t-test.
H1
Test Value = 1.96
t-calculated
df
39.641
149
Sig.
tailed)
.000
(2-
4.2 Resisting Online Grocery Shopping
Consumers’ traditional shopping habits are difficult to change (T. C. Fishman) as well as they may be
reluctant to pay the delivery charge. The demand is increasing and the customer income also increasing so it
is critical for e-grocers to provide high quality products and service to gain customers loyalty. If consumers
are disappointed from their online shopping experience they may stay away and from the other side
discouraging others from trying online grocery shopping. The uncertainty of product quality is another factor
discouraging consumers from buying groceries on the internet. Some offerings need to be consumed before
the quality can be ascertained (Ward and Lee, 2000; Morganosky), since Customers desire to see and touch
products, particularly fresh products. Three specific risk factors can prevent widespread customer acceptance
of online grocery shopping:
 Perceived or actual lack of security or privacy of online transactions. This issue is the most
overwhelming barrier to purchase online (Kaur, 2005).
 There is also a great concern among consumers with regard to the delivery process of groceries
purchased online according to (Keh ; Shieh, 2001).Difficulties in making accurate and timely deliveries to
consumers, also the perceptions that online delivery services are premium services and therefore may be
more expensive than traditional grocery stores.
 Social needs in conventional purchasing this mean that many people go shopping since they can interact
with other people (Darian, 1987) and (Tauber, 1972).
Table (5) includes the possible barriers to adopt online grocery shopping (OGS). From the answers of the
respondents we can see that the majority of them believe that there are barriers to adopt online grocery
shopping.
Table 5. Barriers to adopt OGS
Barriers
The service availability.
The delivery issue.
The lack of trust and concerns about the security and privacy of personal
information issue.
The technology factors (It skills and web features) is obstacle to
shopping online.
The product selection (brand, quality, freshness and taste).
The social and cultural issues.
All paragraph
Mean
3.58
3.71
Std.Deviation
1.166
1.266
3.80
1.274
3.72
1.199
3.84
3.53
3.73
1.232
1.283
0.976
The results shows that the product selection item get the highest average which mean it is the most
expected barriers to adopt online grocery shopping. According to the SPSS analysis it was found that the
overall Mean (3.73) is greater than mean of the scale which is 3, this gives an indicator of a positive attitude
from the respondents toward the barriers of online grocery shopping OGS in general. The decision here
cannot determine on the Mean alone because we have to ensure that the data is not concentrated in the neutral
area. So we need to put another hypothesis and to test it:
4.2.1 Hypothesis Two
H0: there are no barriers for Online Grocery Shopping according to the customer’s opinion in Jordan.
HA: there are barriers for Online Grocery Shopping according to the customer’s opinion in Jordan.
In order to test this hypothesis we need to use the One-Sample T-Test, table (6). Also the decision rule
here is to accept the null hypothesis H0 if the calculated value of T is less than the tabulated one and to reject
the null hypothesis H0 if the calculated value is greater than the tabulated one. It is found here that T
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IADIS International Conference e-Commerce 2011
calculated = 22.190 is greater than T-tabulated = 1.96 (confidence interval =0.95%, DF=∞). Therefore the
null hypothesis H0 is rejected and the alternative hypothesis HA is accepted, because the Mean is more than
3 and the T-calculated is more than T-tabulated (This means that the data is not concentrated on the neutral
area and there is an actual existence for the barriers to adopt OGS) and T Sig. (0.000) is less than (0.05)
(Rifat.2003).
Table 6. Results for the second hypothesis using the one sample t-test.
H2
Test Value = 1.96
t-calculated
df
Sig. (2-tailed)
22.190
149
.000
5. CONCLUSION
The preliminary findings from our survey suggest a number of important factors which either promote or
inhibit Internet users to participate in OGS. According to our study results, the majority of the respondents
were confident that there are benefits that promote the adoption of online grocery shopping in Jordan.
However, they also believe that there are inhibiting factors to adopt online grocery shopping. The study also
shows that the main motivation for OGS is time saving and the main inhibitor is the customers’ preference to
touch and see the product to check its characteristics before purchasing. Further research needs to be done to
explore the customer’s willingness, attitudes and behavior towards this kind of online shopping in the
developing countries .the researchers should also look to the retailer’s point of view about OGS in terms of
inhibitors, benefits and the profitable business models.
REFERENCES
Alba, J.et.al. 1997. Interactive home shopping: consumer, retailer and Manufacturer incentives to participate in electronic
grocery shopping. Journal of Marketing 6, 38, 53.
Belsie, L. (1998) A Mouse in the Bakery Aisle? The Christian Science Monitor, http://www.csmonitor.com, last accessed
July 2001.
Burke, R.R., 1997. Do you see what I see? The future of virtual shopping. Journal of the Academy of Marketing Science
25, 352,360.
Cheah, K.H. (2001) Issues Related to Internet Shopping: An Ethnic Comparison, MBA Dissertation, University of
Malaya, Kula Lumpur.
Darian, J.C., 1987. In-homeshopping: are there consumer segments? Journal of Retailing 63, 163,186.
Ezlika Ghazali et.al, 2006, exploratory study of buying fish online: are Malaysians ready to adopt online grocery
shopping?
Jan Holmström et.al. (2002), the way to profitable internet grocery retailing –six lessons learned.
Kaur, K. (2005) Consumer Protection in E-Commerce in Malaysia: An Overview.
Keh, T.K. and Shieh, E. (2001) ‘online grocery retailing: success factors and potential pitfalls’, Business Horizon, Vol.
44, No. 4, pp.73–84.
Kurnia, S. and Johnston, R.B. (1999) The Mutuality of ECR Benefits, Costs and Risks in Supply Chain Reform, The
third Collaborative Electronic Commerce Technology and Research, Wellington, New Zealand.
Meddeh, M., 2008, Startup Arabia. http://www.startuparabia.com/2008/09/jordans-internet-penetration-rategrows-to-21.
Morganosky, M.A. and Cude, B.J. (2000) ‘Consumer response to online grocery shopping’, International Journal of
Retail and Distribution Management, Vol. 28, No. 1, pp.17–26.
O'Connor, R., 1998. Europe trails U.S. in web grocery shopping. Chain Store Age 74 (6), 70, 72.
Odera-Straub, M., E-commerce and Development: Whose Development? The Electronic Journal on Information Systems
in Developing Countries, 2003. 11(2): p. 1-5.
Reach 1.0, 2000, <http://www.reach.com.jo>.
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Rifat O. Shannak, Mu’taz M. Al-Debei, 2003, the current state of e-commerce in Jordan: applicability and future
prospects. An empirical study .Internet and Information Technology in Modern Organizations: Challenges &
Answers 457.
Roberts, M., Xu, X.M. and Mettos, N. (2003) ‘Internet shopping: the supermarket model and Customer perceptions’,
Journal of Electronic Commerce in Organizations, Vol. 1, No. 2, April–June, pp.32–44.
Rochester, N.Y., 2009. Internet penetration in Jordan doubles to 36% in two years strategies. Harris Interactive, Inc
Sherah Kurnia, 2004, Identifying e-Commerce Adoption Driving Forces and Barriers: The Case of the Indonesian
Grocery Industry.
Sherah Kurnia, 2006, Exploring e-Commerce Readiness in China: The Case of the Grocery Industry.
Stephen Hawk ,2004, Comparison of B2C e-commerce in developing countries, Electronic Commerce Research 14 (3)
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Tauber, E.M., 1960. Discovering newproduct opportunities with problem inventory analysis. Journal of Marketing 24,
67.70.
T. C. Fishman, "Click here for tomatoes," in Money Magazine, 2005, pp. 143-146.
Ward, M.R. and Lee, M.J. (2000) ‘Internet shopping, consumer search and product branding’, Journal of Product and
Brand Management, Vol. 9, No.1, pp.6–20.
Zikmund, W.G. (1997) Business Research Methods, 5th ed., the Dryden Press, Fort Worth.
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IADIS International Conference e-Commerce 2011
ORGANIZATIONAL CONTROL ENVIRONMENT AND
COBIT’S IT CONTROL PROCESS IMPLEMENTATION
Nader Rezaei1 and Gareth Griffiths2
1
2
Oxford Azad University, Stroud Court, Eynsham, Oxford, OX29 4DA, UK
Bangor University, Bangor Business School, Bangor, Gwynedd, LL57 2DG, UK
ABSTRACT
The implementation of IT control processes (ITCP) is affected by organizational control environment (CE). This paper
presents the results of an experimental study exploring the influence of organizational CE components (Corporate Ethical
Environment, Commitment to Component, Board of Director and Audit Committee, Management Philosophy and
Operating Style, Organization Structure, Assign Authority and Responsibility and Human Resource Policies and
Practices) based on COSO framework on four domains (Plan and Organize, Acquire and Implement, Deliver and Support
and Monitor and Evaluate) of ITCPs based on COBIT framework. One hundred and ninety eight relatively experienced
external and internal auditors and accounting managers responded to the mail survey. Results reveal the association
between CE components and ITCPs. The results of study could help auditors and managers and other practitioners in
designing and implementing IT control systems.
KEYWORDS
Internal control; Control environment; Information technology; IT control processes
1. INTRODUCTION
The pervasive use of IT has created a critical reliance on IT and exposed many organizations against new
risks (Haes and Grembergen, 2008, Abu-Musa, 2008). Management of these risks requires specific focus on
IT governance (ITG). Therefore, implementing effective ITG is necessary for organizations with expended
dependencies on IT (Bodnar, 2006). ITG involves IT risks and managing the strategies and policies for the
use of IT to support organization’s objectives. It includes leadership and organizational processes that ensure
the enterprise’s IT supports the business strategies and objectives (COBIT4.1, 2007) and aligns IT to the
business needs (Haes and Grembergen, 2008).
Business IT alignment debates have been intensified during recent years among practitioners and
academics (Larsen et al, 2006) and several ITG models have been created (Haes and Grembergen, 2008). The
Control Objectives for Information and related Technology (COBIT) has been developed as an acceptable
and applicable standard (Larsen et al, 2006) for alignment between use of IT and organizations business
objectives (Ridley et al, 2004). COBIT has been created and introduced by the Information Systems Audit
and Control Association (ISACA). It is one of the well-built and multilateral ITG frameworks that allow
bridging the gap between business risk, control needs, value creation and technical issues (Bodnar, 2006).
The preliminary step in the implementing IT control processes is the review of the organization control
environment to obtain the information required for management to make decisions on the necessary controls.
The necessity of various controls differs according to CE characteristics and organizational contingencies
(Lee and Han, 2000). CE is one of five internal control components that Internal Control Integrated
Framework issued by Committee of Sponsoring Organizations of Treadway Commission (COSO) identified
it as the foundation for all other components of internal control (D’Aquila, 1998).
Despite the apparent importance of the CE, little empirical research has been conducted to investigate the
relationship between the CE and ITCPs implementation. Therefore, this research was carried out to reveal
whether there is a relationship between CE and ITCPs implementation. Consequently, this study addresses
the major CE components affecting ITCPs implementation. The literature on CE theory as well as COBIT’s
ITCPs is reviewed and a research model is proposed. The main results of empirical survey for proposed
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model is analyzed and discussed. Finally, a summary of the findings and recommendations for ITCPs
practitioners and researchers are presented.
2. THEORICAL FRAMEWORK
Organizations employ control frameworks to establish and assess of internal controls. The Treadway
Committee suggested COSO framework as a proper base for internal control assessments. COSO is a highly
conceptual framework that most organizations employ it for the evaluation of control at a relatively general
level. It is not adequate for practical level and such electronic business environment with specific and
specialized IT processes (Tuttle et al, 2007). For this reason, ITG has emerged to control the formulation and
implementation of IT strategy and ensure the fusion of business and IT (Heas and Grembergen, 2008).
Within concentrated IT environment, COBIT as a tool for ITG is applied COSO supplemental framework
(Tuttle et al, 2007).
The COBIT is a set of best practices for IT management. It is one of the strongest practices available to
help an organization to determine whether IT supports the strategies of an organization (Marnewick, 2010).
The COBIT assists meet the several needs of management in technical issues, control needs and business
risks. It provisions good practices across domains and processes framework and presents activities in a
practicable and logical structure. The four high level domains, Planning and Organization (PO), Acquisition
and Implementation (AI), Delivery and Support (DS), and Monitoring and Evaluating (DE) comprise of 34
ITCPs with detailed control objectives (Funilkul et al, 2006).
2.1 IT Control Processes
Since IT plays an essential role in a company’s internal control system, and ITCPs have attracted board level
attention (Grant et al, 2008), most organizations have utilized ITG tools such as COBIT framework for
guidance to establish and evaluate IT controls and for compliance with new legal requirements same as the
Sarbanes–Oxley Act (SOX) (Bernroider and Ivanov, 2010). There is no framework that comprehensively
covers the total spectrum of structures and processes relevant to ITG except COBIT (Abu-Musa,
2008).COBIT provides managers, auditors, and IT users with a set of performance measures, key goal
indicators, diagnostic tools and best practices, to help them in maximizing the benefits derived through the
use of IT (COBIT 4.1, 2007,Abu-Musa, 2008).
COBIT defines IT activities in a generic process model within four domains (PO, AI, DS, and ME)
covering the IT traditional responsibility areas of plan, build, run and monitor (COBIT 4.1, 2007, Miroslavet
al, 2008). Within each domain there are definite processes that organizations should address to achieve
specific IT related control objectives (Tuttle et al, 2007). PO domain refers to strategy and tactics, and
involves in establishing the best way that IT can contribute to the accomplishment of the business objectives.
AI domain addresses the identification and providing solutions and applications that will meet business
functional requirements. In addition AI is in responding to business and IT environmental changes. DS
domain is concerned with the delivery and support of required services. It is involved in service levels and
continuity, ensuring systems security and configuration, management of performance and operation, thirdparty services, problems and help desk services, and user training. ME domain includes IT performance
management, internal control evaluation, regulatory compliance and governance to regularly assess over time
for control requirements. These four domains and 34 IT processes mainly provide comprehensive dimensions
of an organization’s IT processes performance and capability that need to be managed.
2.2 Control Environment
The topics of CE are often difficult to grasp (Sanchez et al, 2007) due to its abstract and diffused concept.
Nevertheless, the auditing standards emphasize the importance of control environment and its comprehensive
consideration has been required (e.g. SAS No. 109). The way business activities are organized, objectives
founded and risks assessed has been influenced by the CE. Many factors determine the CE and some are
discussed below. The CE questionnaires and checklists organize CE components into seven dimensions:
corporate ethical environment (CEE); commitment to competence (CC); board of directors or audit
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committee (BOAD); management’s philosophy and operating style (MPOS); organizational structure (OS);
assignment of authority and responsibility (AAR); and human resource policies and practices (HRP). In this
study we use this categorization. It (independent variables in the research model) will be discussed and
hypotheses are developed as follows.
2.2.1 Corporate Ethical Environment
The company’s objectives and the way they are obtained are based on ethical values which are translated into
behavior standards (COSO, 1992). The CEE includes polices about acceptable business practices, procedures
for complying with regulations and policies regarding illegal acts. Furthermore it indicates management’s
reactions to noncompliance with ethics and regulation and governing relationships with customers, creditors,
suppliers, regulators and etc. Valentine et al (2002) explored the CEE was significantly associated with the
employees’ organizational commitment. Rae and Subramaniam (2008) demonstrated that internal controls
quality is significantly and positively related to CEE. In this study we expect that the ITCPs for control over
information and management of IT related risks are influenced by integrity and ethical values. Thus the first
hypothesis of the study is as follows:
H1. Companies with high level in CEE components are more likely to have high level implementation of
ITCPs.
2.2.2 Commitment to Competence
An organization needs to identify the required competence level for its different job tasks and to transform
those requirements into necessary levels of skill and knowledge (Moeller, 2007). In other word, the
organization should identify competencies, retain individuals with those competencies and periodically
evaluate competencies (Rittenberg et al, 2009). CC is made by placing the proper people in appropriate jobs
and providing adequate training (Moeller, 2007). Deron (2008) investigated the effects of intensification
employee competence and its impacts on improving quality performance in small-company environment.
The results demonstrated that developing competence result in enhanced quality and ultimate cost reductions.
Bassellier et al (2003) explored the concept of IT competence of business managers as a contributor to their
intention to champion IT within their organizations. This component of CE is critical for ITCPs, as people
are important assets, and governance and the ITCPs are heavily dependent on the motivation and competence
of personnel. Thus, we argue that with increasing levels of CC, the implementation of ITCPs can be
enhanced based on the preceding discussion, the second hypothesis is as follows:
H2. Companies with high level in CC components are more likely to have high level implementation of
ITCPs.
2.2.3 Board of Directors or Audit Committee
Members of the board of directors are elected by shareholders as representatives and have responsibility for
management surveillance and evaluating organization’s strategic plans (Rittenberg et al, 2009). Factors of a
capable board and audit committee include independence from management, experience of its members,
extent of its involvement of activities, and the appropriateness of its actions (COSO, 1994). Beasley (1996)
found that firms with significantly higher percentage of outside board members have fewer frauds; however
the existence of audit committee does not affect the probability of fraud. Zhang et al (2007) investigated a
relationship between audit committee quality and internal control weakness. It was stated firms are more
likely to be identified with an internal control weakness, if their audit committees have less experiences and
independence. In this manner, Li et al (2007) explained companies with more IT experienced board members
and higher level of independent board directors is less likely to have IT control material weakness. We expect
that board and audit committee characteristics are associated with IT control processes implementation
quality. Therefore, our third hypothesis is:
H3. Companies with high level in BDAC components are more likely to have high level implementation
of ITCPs.
2.2.4 Management’s Philosophy and Operating Style
The way the business is run and its risk acceptance is significantly affected by MPOS (Harrer, 2008). The
components of MPOS includes attitudes toward timely financial reporting and accurate disclosures, emphasis
on meeting financial and operation objectives, ability to adapt new roles response to changes, concerns to
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reliability and accuracy of information and accounting estimates, and concerns about internal controls and
business environment. Chiesa (1999) studied management control styles over R&D units. It is found that the
control relies on managers’ mind set and attitude and the certain types of managerial styles to be appropriate
to certain types of R&D organization structures. In this manner clearly the research activities require higher
degrees of autonomy. ITCPs should be aligned with enterprise’s management aims and directions including
expectations regarding delivery of value from IT investments and appetite for risk. The forth hypothesis
attempts to investigate the influences of MPOS on ITCPs implementation.
H4. Companies with high level in MPOS components are more likely to have high level implementation
of ITCPs.
2.2.5 Organizational Structure
The OS provides an overall framework for planning, executing, controlling, and monitoring operations for
achieving entity-wide objectives. Significant aspects relevant to OS include appropriateness of organization
size and complexity, defining important areas of authority and responsibility, segregating duties, smoothing
flows of information and creating proper lines of communicating and reporting (COSO, 1994). Ouchi (1977)
attempted to uncover the relationship between control and structure. He argued that approximately 33 percent
of the variance in the control mechanisms can be defined by company structural characteristics. Lee et al
(2000) revealed that large and complex organizations with integrated IT applications are positively correlated
with external formal controls and automated controls. For these reasons and following these studies, the
relationship between companies appropriate OS and ITCPs implementation is probed. The supposed
hypothesis is as follow:
H5. Companies with high level in OS components are more likely to have high level implementation of
IT control processes.
2.2.6 Assignment of Authority and Responsibility
Authority and responsibility are intertwined with the organization’s structure (Rittenberget al, 2009). The
company should assign limitations of authority, assign responsibility to employees and establish reporting
relationships (Harrer, 2008). Authority and responsibility for operating activities are generally assigned by
business practice polices on the delegation of authority and responsibilities, authorization hierarchies and
reporting relationships (Dauber et al, 2009). We posit that the adequacy of company’s policies regarding the
assignment of responsibility and the delegation of authority help companies improve IT related control
processes. Based on the above arguments, we produce our sixth hypothesis:
H6. Companies with high level in AAR components are more likely to have high level implementation of
IT control processes.
2.2.7 Human Resource Policies and Practices
Human resource policies and practices relate to hiring, direction, training, evaluating, advising, promoting,
rewarding and remedial actions (COSO, 1994). The organization’s HRPP should support integrity, ethical
behavior, and competence and management should encourage its employees with the appropriate tools and
training to succeed (Rittenberget al, 2009).
Choi et al (2009) examined the effect of human resource investment in internal control over financial
reporting on the existence of internal control weaknesses. They measured firm’s human resource investment
by the ratio of the number of employees involved with the internal controls implementations to the total
number of employees. It was found out that the proportion of internal control personnel is negatively
associated with the existence of internal control weaknesses. This paper aims to explore the HRPP effects on
IT control processes implementation. This concern made the basis for development of the following research
hypotheses:
H7. Companies with high level in HRPP components are more likely to have high level implementation
of IT control processes.
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3. RESEARCH METHODOLOGY
3.1 Data Collection
The data for this study were collected using questionnaire designed to measure the perceived IT controls,
control environment and demographic information. Data about IT control processes implementation were
obtained using questions developed based on COBIT’s framework and organization’s control environment
data were collected using questions developed based on guidelines established by COSO (1994). Pre-testing
and piloting are important steps in the development of the questionnaire. Several useful suggestions and
comments came. These were used to refine the questionnaire in order to prepare the questionnaire for the
pilot study. A sample of 650 CPAs (including 270 external auditors, 210 internal auditors and 170 accounting
and financial managers) was randomly selected. A packet containing the questionnaire and a stamped selfaddressed envelope was mailed to each of the 650 CPAs. Only 198 questionnaires were received out of the
650 questionnaires, that 174 questioners were usable. The usable response rate for detailed analysis was
26.7%.
3.2 Measures, Measurement Reliability, and Validity
The measures were adapted from COBIT and COSO framework as explained above and a multiple 5 point
Likert scale is used to quantify measures in the questionnaire. Reliability and validity tests were conducted
for the collected data. A reliability analysis was conducted by using Cronbach’s alpha model on the collected
data. All scales exceed 0.738. The result shows that the questionnaire design is moderate to high reliable, and
the collected data are reliable and consistent (Bagozzi, 1994). In this study, the measures are pretested by
both practitioners and two academics to enhance the content validity of the instrument.
4. DATA ANALYSIS AND RESULTS
Multiple regression analysis was carried out to analyze collected data and examine the significance of the
relationship between individual variables of organizational CE and ITCPs implementation. Table 1 presents a
set of regression analysis with the four domains of ITCPs as dependent variables and the CE components as
independent variables. All the regression models deduce to have significant F ratios (p-value < .001), with
= 0.245, 0.283, 0.223, o.217).
good explanatory power (Adjusted
The results of table 1 indicate that companies with high level in CEE components are more likely to have
high implementation of PO and ME control processes. Despite the overall effects of ethical values on
employees and managers performance (Valentine et al, 2002), and it’s positively relations with internal
control quality (Rae and Subramaniam, 2008), our evidence reveals that some of ITCPs (PO and ME) are
affected by the components of CEE. For examples, the definition of strategic IT plan (PO1) is developed
based on acceptable business practices.
In this study, the obtained results for CC are similar to CEE so that, companies with high level in CC
components are related to high implementation of PO and ME. The previous studies have substantiated the
effects of employee and mangers IT competence on improving quality of performance (Deron, 2008),
championing IT (Bassellier et al, 2003) and establishing controls on specific IT system (EDI) (Lee and Han,
2000). The process of IT human resources management (PO7) entails management awareness of employee’s
required skills and knowledge and competency level. In the monitoring and evaluation processes, the
compliance with external requirements (ME3), among other necessities, implies to personnel competence and
certifications requirements.
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Table 1. Multiple Regression Results
Dependents
Plan & Organize
Independent
Constant
CEE
CC
BDAC
MPOS
OS
AAR
HRPP
Adjusted
F
Significant F
Constant
CEE
CC
BDAC
MPOS
OS
AAR
HRPP
Adjusted
F
Significant F
Beta
S.E.
Acquire &Implement
t Value
p Value
.470
.407
.172
.078
.167
.068
.255
.076
.164
.083
.081
.075
-.066
.071
.035
.075
.277
.245
8.739
.000
Delivery & Support
1.156
2.357
2.226
3.556
2.239
1.068
-.944
.495
.250
.020
.027
.000
.027
.287
.346
.621
Beta
S.E.
t Value
.723
.075
.113
.131
.177
.193
.046
.116
.256
.223
7.943
.000
.355
.070
.060
.068
.073
.066
.062
.067
2.034
1.015
1.501
1.802
2.404
2.532
.655
1.607
p
Value
.044
.312
.135
.073
.017
.012
.514
.110
Beta
S.E.
-.027
.400
.073
.078
.132
.067
.204
.076
.187
.081
.037
.073
.161
.069
.192
.074
.313
.283
10.357
.000
Monitor & Evaluate
t Value
-.068
1.011
1.815
2.897
2.604
.494
2.349
2.756
Beta
S.E.
t Value
.286
.176
.154
.176
.116
-.007
.019
.197
.250
.217
7.746
.000
.406
.079
.068
.077
.082
.074
.070
.076
.703
2.369
2.067
2.428
1.575
-.088
.271
2.739
p
Value
.946
.313
.071
.004
.010
.622
.020
.007
p
Value
.483
.019
.040
.016
.117
.930
.787
.007
The relations of BDAC domain to internal controls has been considered and investigated more than other
CE domains in the previous studies. As Zhang et al, Li et al (2007), and Hoitash et al (2009) have
authenticated the positive relationship between strong BDAC and quality of internal controls. We found that
three domains of ITCPs including PO, AI and ME are significantly supported by BDAC. Board of directors
steer the enterprise’s strategic IT plan (PO1) to extend the organization’s strategies and objectives and
satisfies the business requirement (COBIT 4.1, 2007). Moreover audit committee should monitor IT
performance (ME1) and IT’s contribution on business and evaluate to what extent planned IT objectives have
been achieved, budgeted IT resources (AI5) used, set performance IT targets met and identified IT risks
(PO9) mitigated (COBIT 4.1, 2007).
According our findings, the implementation of ITCPs domains are mostly influenced by MPOS along
with BDAC, so that, the implementation of PO, AI and DS are significantly supported by MPOS. MPOS
affects ITCPs in strategic and operational levels. Management with identification of business environment
determines business requirements for IT and expands a strategic IT plan (PO1). Responding to business IT
requirements entails change management process (AI6) and management ability to adopt new roles (COBIT
4.1, 2007).
OS fails to affect the implementation of PO, AI and ME domains. Only the DS processes implementation
is significantly supported by OS. Appropriate OS helps to manage the configuration (DS9) of IT
infrastructure, resources and capabilities. It makes smooth information flows across the organization and
optimizes data management (DS12). Organization with proper OS supports IT security systems (DS5) and
minimizes vulnerabilities. It manages physical environment (DS12) and protects computer assets business
data (COBIT 4.1, 2007).
While AI is significantly affected by AAR, the AAR fails to influence other ITCPs domains (PO, DS and
ME). AAR and OS are two least impressing CE components on ITCPs domains. Detailed description of
duties, properly delegation of control responsibilities and establishment of reporting relationships streamline
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maintaining application software and automated solutions (AI2) and enable operation and use (AI4).
Adequacy assignment of responsibility and authority limit determination affect change management (AI6)
and procuring IT resources (AI5) for responding to business IT requirements in alignment with the business
strategy (COBIT 4.1, 2007).
HRPP significantly supports AI and ME domains of ITCPs but the effect of HRPP on PO and DS is not
confirmed. Organization’s human resource policies particularly training programs are critical factor of
changes management (AI6) for responding to business IT requirements in employment and maintenance of
automated solutions (AI1) and application software (AI2). Implementing and installing new or changing
solution systems (AI7) require employing new personnel or providing training and promoting programs for
current personnel. The results shows that the ME processes depend more than other CE components to
HRPP. Basically, the successful implementation of ME processes without effective HRPP is not possible.
5. CONCLUSION
This study considered the effects of control environment components on IT control process domains
implementation separately. It shows plan and organize is significantly affected by corporate ethical
environment, commitment to component, board of director and audit committee and management philosophy
and operating style. Acquire and implement processes are significantly supported by board of director and
audit committee, management philosophy and operating style, assignment authority and responsibility and
human resource policies and practices. Delivery and support is significantly influenced by management
philosophy and operating style and organization structure. And finally monitor and evaluate processes are
significantly supported by corporate ethical environment, commitment to component, board of director and
audit committee and human resource policies and practices. The results indicate board of director and audit
committee with management philosophy and operating style have the most impact on IT control processes
among others. Whereas organization structure and assignment authority and responsibility have the minimum
supports. Furthermore, there is evidence that IT control process domains except delivery and support
processes are affected by control environment components uniformly and delivery and support domain
processes are influenced less than others.
The results of this study provide some insights on control environment components that necessitate the
effective implementation of IT control process domains. The tasks of designing control systems are complex
and unstructured especially in e-commerce and IT concentrated environment. And there is not a homogenous
situation and way to implementation of control systems as accomplish by managers and auditors. Many
alternatives models of IT controls exist, and many control environment components affect the design of
controls. The results of this study may help managers and auditors analyze organizational control
environment and concentrate their limited IT resources to effectively design and implement IT control
processes. It attracts management to consider the various dimensions of control environment to appropriate
invest on IT resources for implementation IT control processes.
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ACCOUNTABILITY IN SINGLE WINDOW SYSTEMS
USING AN INTERNAL CERTIFICATE AUTHORITY - A
CASE STUDY ON THAILAND’S NATIONAL SINGLE
WINDOW SYSTEM
Potchara Pruksasri1, Jan van den Berg1 and Somnuk Keretho2
1
Section of ICT, Faculty of Technology, Policy and Management
Delft University of Technology, Delft, Netherlands
2
Department of Computer Engineering, Faculty of Engineering
Kasetsart University, Bangkok, Thailand
ABSTRACT
A single window system (SWS) concerns a single-entry facility for electronic documents exchange between
governmental departments and business partners and is aimed to reduce time and costs of international cross-border trade.
Recently, the country of Thailand also started to design and implement a SWS based on modern information
technologies. This includes the set-up of a public key infrastructure (PKI) to facilitate secure e-message exchange. An
analysis of the information flows that are taking place in the prototype SWS proposed revealed us however that, next to
improvements, some basic requirements with respect to the accountability of individual back office employees are not
met. The first aim of this paper is to reveal this accountability problem. In addition we propose a possible solution for the
shortcomings discovered, which basically boils down to extending the PKI with an internal certificate authority.
KEYWORDS
Single window, accountability, non-repudiation, digital signature, PKI.
1. INTRODUCTION
Looking at worldwide international trade, one soon discovers that developing countries experience many
difficulties in keeping up with the new developments of efficient and effective settlement of goods. This also
holds for the country of Thailand that still faces basic problems with respect to the time needed and costs
involved for the cross-border import and export of commodities. Thailand’s exporting procedures simply
consume much more time and costs than, for example, countries of the European Union (EU). One of the
main reasons of the inefficiency of the import and export processes is the way customs in Thailand work. An
exporter, for example, has to pursue several quite complex procedures involving many governmental
departments. Therefore, it takes on average 14 days for getting his products exported (Worldbank, 2010).
This is much longer than the period needed in many countries of the EU, like 5 days for Denmark and 6 days
for The Netherlands.
A possible way to reduce time and costs of cross-border trading is the establishment of a modern
document exchange system for customs and other stakeholders of the port community. Such a system is
provided by a so-called Single Window System (SWS), which can take care of the electronic documents’
exchange between governmental entities (G2G) and between business and governmental organizations
(B2G). Both the SWS concept and its related guidelines have been provided by the United Nations (UN)
(UN/CEFACT, 2005). However, these recommendations concern guidelines of generic nature and should
therefore be refined and adjusted to the circumstances of individual countries. This also holds for the ways in
which secure information and communication technology should be deployed (Stijn et al., 2010).
Looking more specifically at customs’ procedures, it is very common that, in order to facilitate the proper
import and export of goods, many documents have to be exchanged between several governmental
departments. During this information exchange, all kinds of data processing activities are executed. In the
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less developed countries including Thailand, this data processing is usually still paper-based. In such a
business process, an employee, having finalized a specific verification, registration or other data processing
activity, has to put a signature in a specific box on the relevant document. In this way, accountability is
implemented meaning that each mutation in any document can be unambiguously linked to the person who
made the mutation. For easy-to-understand reasons related to the identification of (possible) fraud, smuggle,
and other safety and security incidents, the preservation of accountability is essential, and should therefore be
guaranteed when adopting a modern SWS.
The Royal Thai government and industries, being aware of their backlog in the speed of executing import
and export processes, have decided in 2004 to also adopt a national SWS. This circumstance motivated us to
use the ‘Thailand National SWS’ project as a case study for understanding the way accountability can be
guaranteed in a SWS implementation. The Thailand case can actually be considered as an important
prototypical case since other countries in the region (and even the rest of the world) have also expressed their
interest in the soon adoption of a SWS in order to further improve global trade procedure (Phuaphanthong et
al., 2010). A further motivation for this research is found in the fact that a short literature review soon
revealed that, despite the availability of many papers around the (general) notion of accountability (Lin et al.,
2010) (Nakahara and Ishimoto, 2010), specific analyses of accountability in the environment of SWSs around
import and export processes of goods were not available.
To summarize, this paper aims to analyze accountability in the import and export processes of goods (as a
sub-activity in the global supply chains), to come up with solution requirements, to analyze to what extent a
prototypical current SWS specification takes these requirements into account, and to propose solutions for
the imperfections detected. To do so, we structured the rest of this paper as follows. Section 2 is devoted to
the background underlying SWSs and PKI. In section 3, we look at accountability (as part of information
security) requirements inside SWS environments, hereby identifying certain upcoming problems. Using the
PKI-based techniques introduced in section 2, we propose in section 4 a generic solution for these problems.
Finally, in section 5, we present our conclusions and outlook.
2. BACKGROUND
2.1 Single Window Systems in General
There is no single definition for the concept of SWS. In case of using it in a trading environment, a SWS is a
facility that allows trade and transport partners to lodge standardized information with just one single entry
point in order to fulfill all import, export, and transit-related regulatory requirements (UN/CEFACT, 2005).
In 2005, the Association of South East Asian Nations (ASEAN) signed an agreement (ASEAN, 2005) to
establish and implement a new information & communication system that aims to accelerate customs
clearance of goods and, more generally, to improve efficiency of trading activities in and between the
countries of south-east Asia. This system is often denoted as the ‘ASEAN Single Window’. By the
agreement, each participating country promised to build their national SWS such that it facilitates
information exchange between governmental organizations, traders and other stakeholders inside each
country in the first place and later on, cross border communication between international supply chain
partners.
2.2 The Thailand National Single Window System
One of the countries that signed the 2005-ASEAN agreement was Thailand. Its national SWS under
development aims to support both Government-to-Government (G2G), and Business-to-Government (B2G),
and Business-to-Business (B2B) communication (UN/CEFACT, 2005).
Looking at the information exchange architecture of Thailand’s national SWS, four principal sub-steps of
data flow between traders/business partners and governmental departments can be identified:
• Step 1 – Submitting a Declaration. To start, traders or similar business partners contact one of the
Gateway Services Providers (GSPs) to submit a set of customs declaration documents related to the
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import/export of their goods by using software provided by the one of Value-Added Service Companies
(VAS) (Keretho, 2008a). In all cases, the data elements of several request forms, permits and certificates are
transformed into XML format (W3C, 2008)and submitted by VAS software according to some certain
legitimate (business process) steps. Second, a digital signature of the submitter is added based on the user’s
private key as made available by the existing Public Key Infrastructure (PKI).
Figure 1. The Thailand National Single Window Model (adapted from (Keretho, 2008b)).
• Step 2 - Forwarding a Message to the national SWS. In the second step, a GSP connects to the national
SWS using the so-called ‘Single Entry’ point in the private Government Information Network (GIN). After
SWS receipt of the different user’s declaration messages, the data are standardized and harmonized into a
basic set of data elements.
• Step 3 - Message Flows inside the national SWS. The messages inside the national SWS flow around
based on the ebMS message services protocol (OASIS, 2002b) (and its related components CollaborationProtocol Profile (CPP) and the Collaboration-Protocol Profile Agreement (CPA)) (OASIS, 2002a). To secure
messages exchange inside the SWS, a secured communication channel such as Secure Socket Layer (SSL)
(IETF, 2008)is applied as well.
• Step 4 – Responding incoming Messages. After receipt of the electronic messages at the destination
computer, the incoming data are processed and a response message is composed. The latter is sent back as a
reply to the GSP the incoming message originated from. On behalf of the submitting exporter, the submitter’s
VAS software will check at regular time intervals whether the replied message has already been arrived and,
if so, will report that to the exporter.
2.3 Public Key Infrastructure and Digital Signatures
The National SWS concerns an information communication network system that applies several technologies
and standards. Information Security (IS) is one of major topics of concern in SWS design. The key security
characteristics of IS, namely, Confidentiality, Integrity, Availability (CIA Triad model (Johnson, 2010)) and
Accountability (Barbar, 2001) should all be dealt with in SWSs. As has been motivated in the introduction,
we here especially take a look at the security requirement of accountability. As enforced by the law, evidence
is usually required with respect to the fulfillment of the IS requirements, especially that of accountability.
The usual technologies that implement the IS requirements make use of a Public Key Infrastructure (PKI)
(Haidar and Abdallah, 2009). A PKI is an IS supporting architecture that usually applies a combination of
private and public key cryptography (Diffie and Hellman, 1976). A standard PKI implementation includes
Digital Certificates and Digital Signatures to provide evidence for the fulfillment of accountability. To
guarantee that a genuine public key is used (i.e., that the public key truly belongs to the intended person),
digital certificates are used. A specific trusted third party named a Certificate Authority (CA) is the
organization issuing digital certificates, usually based on the X.509-v3 standard (ITU, 1997). A digital
certificate contains, among others, a version number, name of algorithm used, issuer name, user ID, user’s
public key, period of validity, and a signature created by the CA. The CA signature concerns a generated
hash code of the unsigned certificate encrypted by the private key of the CA. To prove authenticity of the
public key of a certain user, the hash code of his unsigned certificate is first calculated. Next, the CA
signature on the certificate is decrypted using the public key of the CA (that is supposed to be known to
everybody), the resulting value of which is compared to the obtained hash code. If they are equal, the verifier
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can be sure that the user’s certificate is genuine indeed, including the user’s public key value. In the same
way CAs can sign digital certificates, users can sign messages that are sent to e-counterparts. Using such a
scheme, non-repudiation can be implemented. If, for example, recipient receives a message from sender
signed by sender with (s)he private key, the recipient can always prove later on that the received message
must have been created by sender (provided her private key was not been stolen). It should be clear that, in
this way, accountability can be implemented as well: by enforcing that each employee digitally signs a
message containing data (s)he has prepared, the receiver of that message can always prove that the signing
employee was the originator of the message. In other words, the data in the message and the signing
employee are unambiguously linked to each other.
3. ACCOUNTABILITY ANALYSIS
To analyze possible problems related to the accountability requirements of future SWSs, we performed a case
study. We first discuss security issues in the classical, paper-based systems. Next we analyze the same issues
in the SWS to be used in Thailand.
3.1 Accountability in Classical, Paper-Based Systems
As a prototypical example of exporting a good, we focus in the case study on the information flow related to
an export permit request of sugar. If the documents’ exchange is paper-based, the process starts when the
sugar exporter prepares the documents for the permit request: the set of required documents includes a
request form, a purchasing contract, a declaration form, and one or more financial documents (Keretho,
2010). These documents are next sent to the Centre of Production Management (1st department) for doing
some checks. If the checking yields a positive outcome, the competent officer will provide the permit on
behalf of the department (s)he is working in: to do so, (s)he personally signs the documents. Then, the sugar
exporter has to return (physically) to the 1st department to collect the permit. In the next step, (s)he has to
contact the Office of the Cane and Sugar Board (OCSB, 2nd department) by sending the request form, the
received permit, and other related documents. The OCSB checks the documents on completeness and
correctness, and provides, in case of approval, a permit document to the exporter. Again, the sugar exporter
has to return physically to the OCSB to collect the new permit. While executing these activities, the exporter
also has to prepare documents for the Office of Atoms for Peace (3rd department). This is needed in this case,
since a so-called ‘radio certificate’ is required for the export of sugar. Again, the exporter has to send the
request, to wait some time (some days), and finally has to collect the certificate.
Based on the above-given scenario, we can identify certain problems related the manual document flow.
A first observation is that the described process typically takes ten days for document processing, waiting and
collecting (Keretho, 2010). Secondly, if certain actors in the document intentionally work together to fool the
authorities, this is possible. For example, in the step of sending the documents to the OCSB (2nd department),
the exporter must hand over an export permit from the Centre of Production Management (1st department) to
the OCSB. If the exporter creates an illegal export permit based on a counterfeited signature that he next
sends to the OCSB, that OCSB might validate that document. The incorrect validation activity by the OCSB
might not be detected because the OCSB cannot check each single permit in such careful manner that all
forging activities are discovered.
The above-described problems are serious ones. Therefore, the minimal requirements for the future
electronic exchange of documents in the proposed SWS in Thailand include reduction of execution time and
improvement of the secure communication between governmental organizations.
3.2 Information Flow in the National SWS of Thailand
The case study of exporting sugar can also be used to describe the prototypical document flow in the
designed national SWS of Thailand. By introducing this new IT-based system, the information exchange
between most stakeholders will change. To illustrate, we again describe the document flow (figure 2). To
start, the exporter now submits the request just one time by sending it to the governmental departments.
When the first department has completed the data processing activities needed, the officer in the first
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department directly forwards the relevant documents to the second department. So, the exporter does not
need to (physically) collect and forward the documents him(her) self. On the one hand, this shorter process is
assumed to reduce cost for the exporter, and on the other hand, it does not give the exporter an opportunity to
create a forged document. So we immediately observe that the proposed system has some promising
properties related to cost reduction and prevention of counterfeiting activities. We now continue our analysis
to investigate whether we can also identify certain drawbacks of the new system.
Figure 2. The electronic document flow.
3.3 Governmental Message Exchange in the Future
Thailand’s national SWS is currently in its first phase of development. In the remainder, we focus on the
paperless message exchange between two governmental entities (Keretho, 2008a) (see also Figure 3):
• Step 1: The officer who works in the first back office of 1st department (system A) logs on into the
system. At regular moments in time, the officer receives a request message related the export of a certain
good like, e.g., sugar. The officer needs to process the data. After having finished his (her) administrative
activities, (s)he should send a message to one of the other government agencies in the back office.
• Step 2: In order to send information to any other organization via the national SWS, the officer has to
prepare the document by, first, transforming the data into an ‘ebXML document’ and, second, put a digital
signature on the ebXML document: to sign, the officer uses the departmental private key.
• Step 3: After having finished all necessary work, the relevant data are sent to the national SWS using
specific ebMS Gateway communication software. The governmental department can access directly to the
national SWS via the private network of government (GIN). Therefore, the ebMS Gateway of the department
can be considered as the middle tier between the back office system and the SWS. The communication
software establishes the connection to the Gateway server using a security protocol such as Secure Socket
Layer (SSL). The electronic documents are sent in the format of digital signed XML.
• Step 4: The ebMS Gateway is usually located in a high-stable and secure network system. One side of
this server is connected to the network system of the gateway and the other side to the National SWS (NSW)
on the private network. The electronic messages from gateway are next sent to the NSW network and then
flow inside the NSW to the destination server as specified in the message header.
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• Step 5: After message arrival at the destination server (sometimes it is on the same gateway network), it
is stored on that server. There the message is stored until the software from the destination back office system
(system B) pulls it out. In this step, the back office system B sweeps the message back based on the message
header information which defines the destination to this back office over the secure network in a way as was
already described in step 3.
• Step 6: Here, the electronic message with digital signature and digital certificate arrives at the
destination server that also is located on the private network. The destination server first verifies the digital
signature at the Digital Certificate and next checks authenticity and accountability according the principles as
explained in section 3. At this stage, the message has arrived at the destination back office system, and it is
ready for being similarly processed in the next step of the message exchange process.
Figure 3. The Information flow inside the Single Window System.
3.4 Accountability Problems in the SWS
In the paper-based information exchange system, a responsible officer has to sign a document for approval
before sending it to the next actor in the process. It means that the officer who signed the documents is truly
accountable for the data contained in documents. In case of any fault, the officer can be held responsible for
the identified errors, whatever their character might be, intentional of unintentional. The same accountability
requirement should, of course, be met in the NSW, when all kinds of electronic documents are flowing
around between different governmental entities. The important detail here is that any officer, before sending
a message, signs it by using the departmental private key. This way of working may cause a severe
accountability problem with respect to information that is being exchanged: If a certain IS problem (related to
correctness, completeness, confidentiality, etc.) is found in the data of an electronic document caused by the
incorrect information supply of a certain officer, such an incorrectness can, in the current set-up, not be
traced back to its creator. The back-checking procedure that is usually started after detection of the IS
problem in order to find the person who (un)intentionally made the error, is doomed to fail, simply because
the digital signatures in use are at departmental level and are not personalized signatures. In short, we may
say that a current omission discovered in the designed national SWS in Thailand concerns the guarantee of
accountability at departmental level while, in practice, accountability at a personalized level is truly required.
In Thailand, the companies acting as CA service provider are in their start-up phase. Related to that one
soon discovers that the prices for deploying digital certificates are still quite high while the governmental
departments have limited budgets. In practice, it may not be possible to buy a digital certificate for every
officer who works on an electronic system related to the NSW system. Therefore, we decided to look for an
alternative solution, the design of which is shown in the next section.
4. PROPOSED SOLUTION
According to Thailand’s Electronic Transaction Act (No.2) 2008 (the Electronic Transaction Law), a digital
signature can be used in a similar way as a physical signature when signing documents. The key idea behind
the solution for the described accountability problem is based on a so-called Internal Certificate Authority
(ICA) system. An ICA system can be considered as a natural extension of the well-known PKIs. The
components of an ICA-based system consists of the ‘internal registration unit’, a set of ‘digital signatures’, a
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set of ‘internal digital certificates’, an ‘internal verification process’ and an ‘extended trust model’. The
internal registration unit is a unit to manage user-related data in the ICA system of each department. The
main responsibilities of this unit are to create, record, revoke and control digital certificates. A new user of
the back office system must register to the internal registration unit to get his personal keys (private and
public). The system generates a key pair and a digital certificate for the new user after recording the user
information in the system. The private key and digital certificate can be stored and distributed in several
formats with protected by password at least, for example, in a smart card or USB stick. The digital
certificates are also stored on the ICA server to allow Internal Certificate Authorities’ inspection and
verification from the back office. The digital signature is set when an officer wants to send an electronic
document to another employee. (S)he can create a digital signature by means of the private key. The back
office system must support the proper creation of a digital signature for signing approved electronic
documents. When signed documents arrive at their (internal) destination, the process to verify the origin of
the message is executed. First, the digital certificate is verified based on the digital signature of the ICA. If
the digital certificate has shown to be genuine, the digital signature of the signed document is checked using
the public key found in the certificate. In this way, the link between the document and its creator is verified.
The receiving officer further processes the document and may send it, in the same way, to another internal
employee until the document is sent to the NSW in the last step.
Figure 4. The Internal Certificate Authority.
Figure 5. Thailand Trust Model.
As long as the processes are properly working, it is not necessary to perform an extra internal verification.
If an error is detected however, an internal verification step is needed to discover the error source.
Verification starts by checking the digital signature of the: First, the system can simply request the ICA
server for the digital certificate of the officer who signed the document. It is then used to decrypt the
signature’s hash value and compared to the hash value of the received message and if they are not equal, an
accountability error has been found in this step. The efficiency of the proof could be increased by working
with log files where time stamps of documents and log files are being compared. In Thailand, the trust model
related to the used PKI is prescribed by the Government: see figure 5. The Ministry of ICT operates as
Nation Root Certification Authority of Thailand (NRCA). In order to create an ICA in the back office
system, the current trust model in part of government CA should be extended to governmental department
level. The CA server should be placed into the back-end system of every department in order to control the
use of internal digital certificate. It should further interoperate with the governmental CA in order to
complete the full ‘chain of trust’ needed in this environment.
5. CONCLUSIONS
The development of the Single Window System (SWS) in Thailand is still in its starting phase of design and
implementation. From our, on information security focusing case study we learned that the safeguarding of
accountability concerns a serious problem in the currently proposed prototypes. More precisely, we
discovered that the SWS prototype to be used to exchange electronic documents between governmental
agencies has certain vulnerabilities: in case of an (intentional of unintentional) error made by a certain
officer, it might be difficult of even impossible to trace back to the source of the mistake. This thwarts the
possibility to make employees truly responsible and liable for their activities. The underlying reason relates
to the use of certificates and digital signatures at departmental level instead of at personalized level because
of the limited budget. To solve the problem, we propose an internal PKI at department level, based on
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Internal Certificate Authorities (ICAs), which can be linked to the existing governmental PKI infrastructure
with the national root CA. Future research will focus on the implementation of this idea of introducing
departmental PKIs. Modern IT technologies including web services are supposed to be very helpful here.
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Keretho, S. 2008b. Thailand Single-Window e-Logistics for Trade Facilitation Enhancement. UNESCAP-UNECE
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Nakahara, S. & Ishimoto, H. Year. A study on the requirements of accountable cloud services and log management. In:
Information and Telecommunication Technologies (APSITT), 2010 8th Asia-Pacific Symposium on, 15-18 June
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Oasis, 2002a. Collaboration-Protocol Profile and Agreement Specification Version 2.0, The Organization for the
Advancement of Structured Information Standards.
Oasis, 2002b. Message Service Specification Version 2.0, The Organization for the Advancement of Structured
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Phuaphanthong, T., Bui, T. & Keretho, S. 2010. Harnessing Interagency Collaboration in Inter-Organizational Systems
Development: Lessons Learned from an E-government Project for Trade and Transport Facilitation International
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Stijn, E. V., Phuaphanthong, T., Keretho, S., Pikart, M., Hofman, W. & Tan, Y.-H. 2010. An Implementation Framework
for e-Solutions for Trade Facilitation. Accelerating Global Supply Chains with IT-Innovation ITAIDE Tools and
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W3c, 2008. Extensible Markup Language (XML) 1.0 (Fifth Edition), The World Wide Web Consortium
Worldbank, 2010. Doing Business 2010 : Comparing Regulation in 183 Economies Washington, DC, MACMILLAN.
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VIRTUAL RECOMMENDATION DIFFUSION AND
CO-SHOPPING INFLUENCE: THE ROLE OF DYADIC
NETWORK-BASED INTERACTIONS
Ana Torres and Francisco Martins
Faculty of Economics - University of Porto
Rua Dr. Roberto Frias, 4200-464 Porto - Portugal
ABSTRACT
In this paper we examine how the virtual recommendation may influence co-shopping behavior specifically associated
with “match dyad” within online social networks. Drawing on better match theory in economics and social network
literature, we develop and propose a conceptual model describing how different antecedents of customer’s
recommendation influence their intentions and leads to positive outcomes, such as recommendation behavior and coshopping influence. We also describe which consumer and network characteristics accentuate this influence examining
the moderator effect of customers’ incentives, network structure and interactivity. The study contributes to propose that
“match dyad” in small social network provide high-quality valuable information that will improve the match between the
product and the potential customer and, matched online social connections, act as a proxy for information about the
potential market that is difficult and expensive to measure or observe directly such as customer needs, and to access. The
paper concludes with a consideration of the implications of predictions for marketing practice.
KEYWORDS
Virtual recommendation, co-shopping, digital networks interactions.
1. INTRODUCTION
The attraction and stability of a social network depends on the willingness of members to actively
participate by sharing information and offering personal opinions or recommendations and influence others
to co-shop. Online social networks provide the structural route for social interactions and reciprocating
behaviors which encourages virtual recommendation diffusion and co-shopping response. While Internet
users may also spread electronic content by posting URLs in chat rooms or personal blogs in social
networking sites, these actions are more similar to broadcasting to many audiences comprised of individuals
who the senders may not know or intend to target (Ho and Dempsey, 2010). Research consistently
demonstrates that informal market assistance, in the form of information and recommendations, has a strong
impact on consumer preferences and choices: they receive inspiration for how to act, what to choose, and
which new items to try (Wikström et al., 2002). Moreover, fellow community members offer credible sources
of information and motivate others to co-shop (Chan and Li, 2010, Nelson and Otnes, 2005). Likewise a
“matchmaker” the Internet shopper has the knowledge of better sites to shop, product novelty or promotions
to recommend their peers with similar consumption needs. Online communities and social networks have
received much attention, both from academics and business; however the economic leverage of peer-to-peer
interactions in personal networks of influence for market potential attraction has been neglected. Despite the
power of online social networks for social contagium and information diffusion (Rezabakhsh et al., 2006,
Cole, 2007) less research, however, has explored the role of match dyads in close electronic networks of
relations on matched recommendation diffusion and social influence on co-shopping behavior. Whereas ebusinesses look for adequate answer for virtual collaborative recommendation diffusion and how to target
those people with the highest network value, we should also ask what drives consumers sharing market
information, offering personal opinions and give free and voluntary market recommendation through their
network of connections.
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In light of this, we aim to study and to propose a conceptual model (Fig. 1) describing how different
antecedents of customer’s recommendation influence their intentions and leads to positive outcomes, such as
recommendation behavior and co-shopping influence. We describe how the customer’s e-satisfaction and
switching costs precede and contribute to his/her recommendation intention. We also describe how
recommendation intention leads to positive outcomes, such as recommendation behavior and co-shopping
influence and the reciprocal interplay among these three constructs and their effects on future behavior. We
also describe which consumer and network characteristics accentuate this influence examining the moderator
effects of customers’ incentives, network structure and interactivity. Building on the central prediction of the
“better match” theory in economics (Castilla, 2005, Simon and Warner, 1992), the proposition here is that if
individual similarities and close ties in small networks help to determine better-matched recommendations;
and, to determine whether “match dyads” help to explain better recommendation diffusion and co-shopping
influence. To the best of our knowledge no other study have sought to determine whether customer’
recommendation made through online social contacts are better matched than those made through other
channels, none have focused specifically on the performance implications of customer virtual
recommendation diffusion on future sales or co-shopping influence by using current customers’ online
connections. One way to make progress on this subject is to directly examine the relationship between
personal networks, recommendation behavior and co-shopping influence via customer’s referrals as
indicators of preexisting matched social connections. Theoretically, this study contributes to propose that
“match dyad” social network ties provide high-quality valuable information that will improve the match
between the product and the potential customer and better match referrals act as a proxy for information
about the potential market that is difficult and expensive to measure or observe directly such as customer
needs, and to access. Both these characteristics and behaviors are not only relevant from a measurement
imperative in the sense of being unobservable but also managerially significant in the sense that they provide
specific guidance to managers on targeting more effective referral customers.
2. CONCEPTUAL FRAMEWORK AND HYPOTHESIS
Figure 1 depicts the hypothesized relationships between the key constructs in our conceptual framework their
antecedents and moderator factors. This section provides a theoretical rationale for the expected relationships
and proposes research hypothesis.
e-Satisfaction
H1
Recommendation
intention
Switching costs
H3
Recommendation
behaviour
Co-shopping
influence
H2
Network size and
interactivity
Note:
H4
Hypothesized effect
Voluntary collaboration
and incentive seeking
moderator effect
Figure 1.Conceptual Model
2.1 Drivers of Customer Recommendation
Satisfaction and switching costs are referred in the IS literature as the main drivers of customer retention and
loyalty. First, regarding e-satisfaction extent research find that customer satisfaction is a key construct which
influence commitment-base loyalty outcomes, repurchase intentions and word-of-mouth (Oliver, 1999,
Srinivasan et al., 2002). We define customer e-satisfaction as an affective-based commitment, which refers to
favorable feelings toward an e-tail provider that currently offers some benefits and satisfactory experiences
with complete online purchase. According to the model proposed in this study, e-satisfaction serve as the
basis for the formation of customer recommendation which represents the dedication-commitment (e.g.
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authentic loyalty) to the online provider. The rationale behind this proposition is that (1) a customer considers
satisfactory online purchase experiences as a cue from which to infer the future value to favor a long-term
relationship with the online provider, and (2) highly satisfied consumer is more likely to take on behavioral
intentions such as repurchase intention and recommendation. Such a dedication leads to behavioral outcomes
oriented toward supporting and strengthening the relational bond with the incumbent provider (Reichheld and
Schefter, 2000). Similarly, Oliver’s (1999) attitude-based framework offers a theoretical explanation of the
causal link between customer satisfaction and loyalty outcomes. In particular, Oliver posits that advocacy
behavior (e.g., providing referrals to others) is one of the most distinctive dedication-based outcomes. The
reason behind this argue is that the very act of referring a friend puts the actor’s social image at risk, and thus
word-of-mouth would not occur without the person’s faithful dedication, or loyalty. Consistent with these
arguments, much research demonstrates that the greater the degree of dedication a customer has to an online
service, the more likely he or she is to say positive things about the service to others (Anderson and
Srinivasan, 2003, Reichheld and Schefter, 2000, Srinivasan et al., 2002). In essence satisfaction is a
necessary condition for loyalty, yet loyalty may occur without satisfaction due to the effect of switching
costs. A basic premise of this reasoning is that consumers start to feel dependent on a provider because of
economic, social or psychological investments that would be useless in other provider. Hence, switching
costs by definition are sunk costs means the potential losses that could result from terminating the existence
relationship with an incumbent provider and establish a new one which ultimately leads to behavioral
outcomes that are performed reluctantly just to avoid the termination of a relationship (Burnham et al., 2003,
Jones et al., 2000, Lam et al., 2004). Indeed, in the IS literature switching costs and loyalty have seldom been
examined simultaneously and the key concepts in past research were treated as constraint-based loyalty
outcomes, such as use intentions, inattentiveness to alternatives and willingness to pay more (Kim and Son,
2009). However, such a constraint-based commitment is more prevalent in a contractual service context due
to initial monetary investments that leads to customer lock-in effect (Zauberman, 2003).
In this study switching costs are conceptualized as an affective-level construct arise because of one´s
perceptions about the investments devoted to a certain provider and future benefits loss from ongoing
interactions that are not easily transferable to other provider. A basic premise for this reasoning is that online
retailers are currently offered to customers highly personalized services (e.g. e.mail messages with
personalized offers, customized settings) and loyalty rewards (e.g. rewarding customers for repeated
purchase). In this sense, personalization costs, resulting from the customer recognition the benefits loss of
personal profile accumulated in the website and the effort to set up once again personal information, and
loyalty rewards loss costs resulting entirely from firm´s actions affect switching costs. But people tend to
expect that a similar amount of time and effort will be required to switch to a new web retailer, affecting both
overall switching costs. Thus, personalization and loyalty rewards affect switching costs in the sense that are
non-transferable customer-specific investments that relate to one’s history of interacting with an online
retailer over time. In such case, the customer may need to stick the current provider not because of
constraints but because of dedication. To the best of our knowledge, this study is a first attempt to show the
influence of switching costs on true dedication-commitment behavior, e.g. customer recommendation. The
rationale behind this proposition is that as consumers perceived future benefits loss of accumulated customer
investments that are not transferable, it is reasonable to expect that through this mechanism online customers
with higher switching costs will consider defecting to another e.tail provider less attractive and they tend to
repeat purchases because they believe their ongoing interactions with the online provider will be beneficial in
the long run. Thus, it is reasonable to expect they will eventually tell others the benefits on maintaining
ongoing relationship with the provider which positively influences recommendation behavioral intentions.
Taken together we expect that only truly satisfied customers perceiving the future benefits on maintaining
an ongoing relationship with the current provider will recommend the online retailer repeatedly or say
positive things about the service based on a rational faith that the online retailer will continue to offer
ongoing benefits and an excellent value. Therefore we propose the following: e-satisfaction (H1) and
switching costs (H2) will be positively related to recommendation intention.
2.2 Virtual Recommendation and Co-Shopping Influence
Social interactions and reciprocating behaviors in electronic networks provide the structural route for virtual
recommendation and co-shopping response. The rationale behind this premise is that consumers seek others’
advices to solve consumption-related problems and they forward online content giving opinions and
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suggestions about purchase opportunities (Ho and Dempsey, 2010). Likewise market mavens (Price et al.,
1995) internet shopper has the knowledge of better sites to shop, product novelty or promotions to
recommend their acquaintances and network peers with similar consumption needs. Meanwhile members
reciprocate the support they receive by those matched valuable resources. Research provides evidence that
social interactions, including reciprocating behaviors, reflect processes of receiving and giving various
resources. The helper who provides resources, such as information or social support, receives reciprocal
expressions of gratitude, and admiration or recognition from the helped. Moreover, reciprocity as a collective
behavior, pertains to the value dimension of reciprocity, a generalized moral norm that states people should
reciprocate by repaying those who provide direct help (Hars and Qu, 2002). In this context, resource
exchange theory (Foa, 1971) posit that individuals share information as a valuable resource and social
systems facilitate the exchange of various types of resources by matching available resources with needs.
However, whether a resource exchange occurs depends on the appropriateness of the environment and the
exchangers' capability and motivation to give and receive. In this sense, we claim that Internet facilities, such
as interactivity, rich media and communication tools of higher addressability (e.g. e.mail, blogs, message
board in social networks) allow consumers to interact and enable convenient and efficient resource
exchanges. These features reflect the central components that help generate efficient, useful and rich
information resources for consumers in matched needs and thus motivate them to engage in reciprocal
interactions. However, the impact of consumers' reciprocal interactions on consumption behavior remains
largely absent from research, but reciprocity should provide community members with a stable and safe
social context (Wikström et al., 2002) in which they exchange resources and shop together.
In this study, we define co-shopping influence as a response of matched recommendations influence on
others peers joint consumption action. In our conceptualization, co-shopping “influence” is a feedback
mechanism sustained on network peers’ reciprocal interactions giving response of “better matched”
recommendation influence in joint consumption action. We note here that such joint action may not
necessarily be contemporaneous; members can perform their respective parts at different times (Bagozzi and
Dholakia, 2004:247). Few researchers have conceptually examined the co-shopping construct in depth. In
general, the findings of such studies are quite mixed. For example Bagozzi and Dholakia (2004) find the coshopping phenomenon as “we-intentions” defined as a commitment of an individual to engage in joint action
and involves an implicit or explicit agreement between the participants to engage in that joint action; (Chan
and Li, 2010) found that are more related to motivations and benefits of community group-based
consumption behavior, e.g. “Let's buy this product together to get bigger discounts” and, (Mangleburg et al.,
2004) found that were more likely a phenomenon of teenagers' shopping with friends, related to peer
influence and enjoyment of shopping with pals. By extending better match theory, in our perspective coshopping influence as a response or feedback mechanism of the influence of matched recommendations on
joint purchase action is supported by social interactions and dyadic reciprocating behaviors.
Another aspect of virtual recommendation that has not been investigated relates to expectations that an
individual's collective efforts will be reciprocated in form of co-shopping response enhancing ongoing
recommendations. Broadly speaking we suggest the role of reciprocating behavior as a response of coshopping influence 1) is a substantiation of “better matched” recommendations and 2) a self-reinforcing
mechanism ensuring ongoing recommendations. The rationale behind this proposition is that prior research
indicates the role of reciprocity may be relevant to ensure ongoing contributions to electronic networks.
When there is a strong norm of reciprocity in the collective, individuals trust that their knowledge
contribution efforts will be reciprocated by peer recognition thereby rewarding individual efforts as future
returns to maintain ongoing contributions (Hars and Qu, 2002, Wasko and Faraj, 2005). According, social
exchange theory sustains all interactions as exchanges of rewards and the valuation of rewards varies by
persons reflecting their own preferences, e.g. which arise from the feeling of being rewarded just by being in
a relationship (Blau, 1964). Moreover, feedback as always has positive effect in that it shows consumers
referrals that people are using their recommendations individuals who receive expressions of gratitude and
recognition from others peers are more motivated to engage in ongoing recommendations. Hence, coshopping influence providing feedback of “better matched” recommendations is a self-reinforcing
mechanism for it encourages the referral to expend additional effort and ongoing recommendations.
Therefore, we propose the following: (H3) Recommendation intention and behavior will be positively related
and, (H4) Recommendation behavior and co-shopping influence will be reciprocally related.
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2.3 Network Size and Interactivity – The Role of Match Dyads
Online social networks of influence provide the structural route for social interactions and reciprocating
behaviors which encourages virtual recommendation diffusion and co-shopping response. The rationale
behind this proposition is supported by social networks literature, which refers the “small worlds” are
structured on close social bounds and “match dyads” are more exposed to social contagium. Networks of this
kind have received little attention, yet they appear to have an enormous potential for information diffusion
and social influence (Duncan, 1999; Van Den Bulte and Wuyts, 2007).
First, we consider network size influence on recommendation behavior and co-shopping influence.
Broadly speaking, we predict that customer recommendations made through personal contacts are better
matched than those made through other channels, sustained on individual’s similarities and match dyads in
small networks which are more likely to impact recommendation behavior and co-shopping influence. Here,
we use a direct measurement of what constitutes “match dyads”: an objective measure of network size and
ties to test a “better match” proposition, that is, if match dyads in close networks helps to increase the
prediction accuracy of recommendation diffusion on co-shopping influence. Research provides evidence that
smaller networks (those with fewer than 50 members “everybody knows everybody else”) are characterized
by strong relational ties, rather than weak ties which result in stronger and multifaceted interpersonal
relationships between consumers influencing sharing behavior “I am willing to share personal information
and experiences with close friends, not with anonymous people” (Algesheimer et al., 2005); strong feelings
of social identity, shared history, individuals have similar needs, shared interests and consumption tendencies
“other Network members and I have close friendship ties and share the same objectives and
interests”(Bagozzi and Dholakia, 2006, Dholakia et al., 2004). Small world contact networks are structures
with startlingly efficient process performance is premised on the existence of shortcuts, are a potential
structural basis of reliable flows of information, influence, material like a simple model of disease
transmission (Friedkin, 2011) When these networks of relations form a closed network, individuals’
asymmetries are pooled and information transmission is faster (Lippert and Spagnolo, 2008). A network of
interpersonal influence, actors are structurally equivalent i.e. the social positions and opinions of actors and
any dissimilarity is reduced by the social influence process, and structurally equivalent actors will adopt an
innovation at approximately the same time (Friedkin and Johnsen, 1997). Based on previous research and
“better match” theory we suggest that social bonds and strong ties in close network of connections enhances
the likelihood of “better matched” recommendations, based on individuals’ similarities, shared needs and
previous awareness of consumption behavior tendencies, which in turn are more likely to positively influence
co-shopping.
Second, we consider how social interactions level in electronic networks of connections influence
recommendation intentions and behavior. Individuals are increasingly interacting in the cyberspace and they
successfully use e-mail, blogs, virtual communities, social sites for networking (Cole, 2007). We assume
these exponentials electronic communications provide a base for linking resources and speed information
diffusion to potential market. Forward online content requires low effort as it can be either directly attached
to electronic communication channels like emails/instant messaging or be stored at specific URLs, which are
shown in the body of electronic communications (Ho and Dempsey, 2010). Moreover, they also
communicate extensively with one another online (e.g. through e.mail, social network sites and other
interactive communications) and often keep offline social relationships. This relational capital provides a
base for enduring ties (Cole, 2007) and requires intensive interaction and close social bounds which is crucial
for social exchange and influence in establishing a basis for trustworthy recommendation for economic
exchange (Balasubramanian and Mahajan, 2001).
Researchers agree that interactivity is a key Internet feature which facilitates peer-to-peer reciprocal
interactions. Furthermore, we also suggest the strong effect of social bonds in close networks encourages
individuals’ reciprocal interactions which also encourage resource sharing, voluntary collaboration, and
cooperation, which are critical for recommendation diffusion and co-shopping influence. In line with this
rationale, Chan and Li (2010) find the strength of social bounds that consumers established in the community
positively influences the consumer´s reciprocating behaviors which in turn induce co-shopping intentions.
This finding give support to our rationale that dyadic network-based reciprocal interactions rather than
generalized provides the structural route for virtual recommendation contribution For example, researchers
have noted that higher participation levels lead to higher levels of involvement in the communities. These
findings imply that individual level of interactions in social networks will contribute to sharing market
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information and recommendation diffusion in the network. In our perspective this “e-linking value” is
supported by “match dyad” in close networks that people who connect to more others likely sustain their
contributions to the network through reciprocal interactions sharing and speed market information. Hence,
we suggest that networked-based peer-to-peer interactions level is likely to positively impact the strength of
recommendation behavioral intentions and co-shopping influence.
Taken together we propose the following: the positive impact of consumers' recommendation behavioral
intentions on co-shopping influence is stronger for members of small networks than for members of large
social networks and for network members with higher interactions level than for members with lower
interactions.
2.4 Voluntary Collaboration and Incentive Seeking
There exist some unobserved individual characteristics that lead to higher recommendation level. This
assumption is consistent with sociological and psychological theories which posit what drives sharing market
information is a combination of intrinsic and extrinsic individual motivations. We discuss here two individual
dimensions that prior research indicates may be relevant to explain recommendation diffusion and coshopping influence in social networks of connections: “voluntary collaboration” and “incentive seeking”.
First, consider the customers’ reasons to give free and voluntary market information and personal
recommendations. By voluntary collaboration we mean what induce people to engage in spontaneous sharing
behavior to give free and voluntary market or product recommendation into the Network of connections. The
construct receives theoretical support both from previous research on market helping behavior (Price et al.,
1995) and group-based consumer interactions (Dholakia et al., 2004, Hars and Qu, 2002, Wasko and Faraj,
2005) and altruism literature on arousal of “match dyad” empathy and reciprocity.
Extensive research provides evidence what drives consumers to engage in voluntary collaboration sharing
resources, offering personal opinions and give free and voluntary market information, answering other’s
questions, influencing peer consumers, helping them making good purchase decisions, and even validating
their past decisions and behaviors encompasses individual’s altruistic characteristics (Hars and Qu, 2002; Ho
and Dempsey, 2010) and helping market behavior defined as acts performed in the marketplace that benefit
others in their purchases and consumption (Price et al. 1995). As Nelson and Otnes (2005) note in their
netnography study, online social connections initiate helping behaviors and feelings of moral obligation to
help, which sustain commitments to the community. For exemple, Hars and Qu (2002) measure altruism as “I
don’t care about money”, “Recognition from others is my greatest reward”, “Community members should
help each other out”, or “I deeply enjoy helping others—even if I have to make sacrifices” to explain
motivations to engage in virtual collaboration in open source online communities.
Moreover, the relationship with altruism and sharing market information appears particularly salient in
close networks: the role of empathic emotions and caring responses gained from strong relational ties boost
altruistic motivations. This rationale is also supported by social exchange theory which posits all interactions
as exchanges of rewards and, distinguishes between extrinsic and intrinsic rewards that arise from the feeling
of being rewarded just by being in a relationship which valuation varies by persons reflecting their own
preferences (Blau, 1964). On the basis of prior research we expect the greater the consumers' level of
altruism the more likely they are to engage in spontaneous sharing behavior to give free and voluntary market
or product recommendation into the network of connections with matched needs.
Secondly, consider the “incentive seeking”. The emergence of the incentive motive suggests that
consumers use brand communities to obtain rewards and incentives in exchange for their community
participation. In certain cases, brand communities and e.tail sites tend to provide monetary and nonmonetary
incentives such sales promotions as community events, contests, sweepstakes, and coupons as rewards for
member’s participation and recommendation diffusion. This suggests that consumers are already aware of the
fact that a number of e.retailers offer a variety of promotions and future rewards therefore, they may join
such communities mainly for reasons associated with the incentives offered there. Evidence from this belief
is provided by few empirical studies that find monetary compensations and future rewards (e.g. “I receive
some form of explicit compensation, salary, contract for participating in the project”, “Participating in the
project makes me more marketable”) are more significant predictor of community contribution than intrinsic
or altruistic motivations (Hars and Qu, 2002, Sung et al., 2010). An explanation for this behavioral
motivation is that a surprisingly large number of participants were paid for their open-source efforts which in
some way poisoned the voluntary collaboration engagement. These findings suggest that such monetary
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incentives play a significant role in motivating consumers less altruistic and less motivated to process and
sharing market information for free in large networks. In certain cases, while members of small networks
may hope their recommendation behavior is interpreted by the sender as altruistic, what they are really
seeking is some sort of incentive. Furthermore, in some cases e-retailers offer such monetary incentives on
the base of referrals effectiveness, which mean new customers’ first purchases. From a marketing standpoint,
rewarding individual efforts and ensuring ongoing recommendations, managers cannot only generate positive
word-of-mouth among consumers, which in turn can reinforce the consumer–brand relationship but also
drive customers to engage in more purchase-related behaviors and co-shopping influence. Such possibilities
imply that such monetary incentives may play a significant role in motivating consumers to engage in
ongoing recommendations into the network on a regular basis. This process is consistent with social
exchange theory in the sense that "incentive seeking" helps explain when members choose to participate and
contribute in a manner that maximizes their total social-interaction utility.
Taken together we propose the following: The positive relationship between recommendation intentions
and behavior is stronger for customers engaged in voluntary collaboration. And, the positive and reciprocal
relationship between recommendation behavior and co-shopping influence is stronger for customers seeking
a monetary incentive.
3. CONCLUSION
By extending better match theory this study propose that “match dyad” in small networks of connections
provide high-quality valuable information that will improve the match between the product and the potential
customer. Under this assumption, online social connections, act as a proxy for information about the potential
market that is difficult and expensive to measure or observe directly such as customer needs, and to access.
As we discuss earlier, close networks are characterized by strong relational ties, rather than weak ties, due to
a shared history and social identity, individuals shared needs and consumption tendencies. Therefore, we
deduce this networked consumer likewise a “matchmaker” will provide better matched connections that leads
to “better matched recommendation” diffusion which are more likely to influence co-shopping. In this sense
they provide e-business “better matched” resources as a prime tool to attract new customers more efficiently
and speed to market product novelty or business information that will leverage the economic value of social
network of influence. From a marketing standpoint these networked-based social interactions are crucial to
disseminate and speed to market product recommendation, to target viral consumers to create an effective
customer referral program and benefit from network externalities. Such benefits imply that social contagium
gained from online social networks is both cost effective and powerful which leverage their economic value
for potential market attraction (Balasubramanian and Mahajan, 2001).
This study contributes to a new research stream on networked customers to better understand e-consumer
traits, behavioral intentions and potential influence so they could be effectively profiled as a Match-NetPromoter to be involved in the collaborative recommendation process in the Network, turning dyadic-intotriadic relationships. Besides, for firms there is a lot of interest in increasing market share by targeting and
making marketing alliances with those most likely to influence others. Linking bridges with unconnected
individuals, through customers’ networks, joining people by similarity capturing resources from different
Networks in a constructive fashion: looking for synergy and combinational customer needs and preferences.
This matched dyads synergies introduce customers as an information resource and a co-developer of firm
value-creation. So, the study also contributes in the sense that provides specific guidance to managers on
actions they can take: targeting networked e-influential’ customers to develop efficient customer’ referral
programs and “croudsourcing” strategy. Using “better matched” resources as a prime “tool” for capturing
new customers to create an entire referral chain shows the importance of using the best customers like a
valuable asset, as an alternative to resource based view.
ACKNOWLEDGEMENT
Research for this paper was supported by PhD grant from the Portuguese Science Foundation.
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WHY DO BIDDERS BID ONLINE? THE VIEW OF
CUSTOMER’S VALUE
Chiahui Yen1, Chun-ming Chang2, Chih-chin Yang3, Lu-jui Chen1 and Ming-Chang Chiang4
1
Department of International Business, Ming Chuan University,
250 Zhong Shan N. Rd., Sec. 5, Taipei 111, Taiwan
2
Department of Tourism Information, Aletheia University,
No.32, Chen-Li St., Tamsui, Taipei County, 251, Taiwan
3
Department of Information and Electronic Commerce, Kainan University,
No. 1 Kainan Road, Luchu, Taoyuan County 33857, Taiwan
4
Graduate Institute of Biotechnology, Chinese Culture University,
55 Hwa-Kang Road, Yang-Ming-Shan, Taipei 111, Taiwan
ABSTRACT
The success of online auction is founded on bidders enjoying shopping benefits and creating customer value in online
auction. This study investigates the importance of bidder’s perceived value along with the cost and benefit aspects.
Therefore, this study proposed an integrated transaction cost economics (TCE) and expectancy confirmation theory
(ECT) to understand the determinants of bidder’s perceived value. We collected data from survey questionnaire, and total
594 valid questionnaires were analyzed. A structural equation modeling (SEM) is used to assess the relationships of the
research model. The findings show that satisfaction has significant influence on bidder’s perceived customer value, while
transaction cost is negatively associated with customer value. Bidder’s satisfaction is determined by trust and
confirmation, as well as e-service quality of auctioneer and seller. Moreover, auctioneer’s asset specificity and product
uncertainty are positively associated with bidder’s perceived transaction cost. Bidder’s interaction frequency between
bidder and seller is negatively associated with their transaction cost.
KEYWORDS
Customer Value, Satisfaction, Online Auction, Transaction Cost Economics (TCE), Expectancy Confirmation Theory
(ECT)
1. INTRODUCTION
Consumer-to-consumer (C2C) commerce has become a popular e-commerce application of the Internet. With
their low cost of operation, flexible operating time, low barriers to entry, completeness of services offered,
and media coverage of the operations of successful online auction sellers, the success of online auctions has
inspired numerous new market entrants, making them the most popular emerging business sector (Yang and
Huang 2011). The supreme example of C2C is online auction which is unique in the realm of e-commerce
and one of the most successful business innovations on the web. With the popularity of online auctions, how
to increase customer value is crucial for online auctioneer and seller. Customer value is created when the
benefits to the customer associated with a product or a service exceed the offering's costs to the bidder.
Benefits are made tangible for the bidder through increased margins, while cost refers to transaction cost.
Therefore, how to reduce transaction cost and increase benefit are pivotal to achieve bidder’s perceived
value.
From the buyers who shop for practical needs or for fun to the sellers who do business as a source of
income, the nature of online auctions is transaction. Rooted in economic theory, TCE theoretically explains
the buyer-supplier relationship in management and marketing empirical studies (Ghoshal and Moran 1996;
Rindfleisch and Heide 1997).TCE assert that the total cost incurred by a party can be grouped largely into
transaction costs and production costs. Transaction costs are well defined as the costs of all the information
processing necessary to coordinate the work of people and machines that perform the primary processes (Son,
Narasimhan et al. 2005). A number of studies indicate that consumers’ willingness to buy online is negatively
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associated with their perceived transaction cost (Liang and Huang 1988; Devaraj, Fan et al. 2002; Teo and
Yu 2005). Accordingly, this study examines the bidder’s perceived customer value from the economic aspect
by drawing on TCE.
Oliver (1980) originally developed his expectation confirmation theory (ECT) to explain and predict
consumer satisfaction and loyalty intention, and proposed that consumers’ post-purchase satisfaction is
jointly determined by pre-purchase expectation and confirmation. Satisfaction, in turn, is believed to
influence post-purchase intention to repurchase a product or reuse a service (Hsu, Yen et al. 2006). In the
past decade, most studies have confused users’ continuance with acceptance decisions. Those studies
implicitly considered continuance as an extension of acceptance behaviors. Recently, many studies have
provided evidence that user behavior has different features over the adoption stage and post-adoption
(Khalifa and Liu 2003; Hsu, Yen et al. 2006). Hence, ECT is adopted in this study because it is suitable for
gaining a more comprehensive understanding of the online bidder’s post-adoption behavior.
The research purposes of this study are as follows: to examine how the economic dimension based on
TCE constructs has an impact on their behavior, and, to investigate how the bidder’s behavior dimension
based on ECT constructs has influence on their perceived customer value.
2. LITERATURE REVIEW
2.1 Transaction Cost Economics
TCE were originally proposed by Coase (1973), which theoretically explains why a transaction subject
chooses a particular form of transaction instead of others (Williamson 1975). There are two assumptions
underlying the choice between market and hierarchy, i.e., bounded rationality and opportunism. Bounded
rationality refers to the fact that people have limited memories and limited cognitive processing power.
People cannot digest all the information they have and cannot accurately work out the consequences of the
information opportunism states that people will act to further their own self-interest. That is, some people
may not be entirely honest and truthful about their intentions some of the time (Williamson 1981; Teo and
Yu 2005). Moreover, TCE are constituted by three situational conditions, i.e., asset specificity, uncertainty,
and frequency (Williamson 1975).
TCE have attracted considerable attention in IS research in analyzing transaction efficiency and its effect
on IS usage. Some studies divided TCE constructs into several sub-dimensions. For instance, Liang and
Huang (1988) propose that the transaction cost of a product on the web is determined by the uncertainty and
asset specificity. They operate cost constructs as comparison cost, examination cost, negotiation cost,
payment cost and delivery cost, and divide uncertainty construct into product uncertainty and process
uncertainty. Four specificities are proposed as physical asset specificity, human asset specificity, brand name
specificity, and temporal specificity. Similarly, Teo and Yu (2005) and Teo et al. (2004) also examine TCE
sub-constructs in the online shopping context. Devaraj et al. (2006) analyze the economic aspects of
consumer transactions through incurred costs and the social aspects through patterns of behavior. Devaraj et
al. (2002) take the view that TCE explains the external cost and TAM represents internal cost-benefit, which
captures consumers’ perception in an e-commerce environment. Expanding Devaraj et al.’s (2002) work,
Jones and Leonard (2007) adapt their framework in C2C e-commerce. The findings indicate that TAM, TCE,
and SERVQIAL all have an impact on satisfaction in C2C e-commerce. Consequently, the TCE framework
alone is inadequate for fully explaining the outcome of e-commerce (Bunduchi 2005).
2.2 Expectancy Confirmation Theory
In order to help gain a thorough understanding of the underlying phenomena, the ECT is presented for the
evaluation of continued usage. ECT is adopted here because it has been widely used in the marketing field of
consumer behavior to study post-purchase phenomena, including consumer satisfaction, repurchase
intentions and complaining behaviors. The ECT model originally developed by Oliver (1980) theorizes that
consumers’ post-purchase satisfaction is jointly determined by pre-purchase expectation and disconfirmation.
Satisfaction, in turn, is believed to influence post-purchase intention to repurchase a product or reuse a
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service. Recently, ECT has been used to understand individuals’ intentions in the e-commerce context. Some
studies asserted that confirmation had a significant effect on satisfaction, which in turn had a positive
influence on IT continuance usage
It is noticeable that some researchers conduct a longitudinal study to understand the adoption and postadoption user behavior over different stages. Bhattacherjee and Premkumar (2004) explored how users’
beliefs and attitudes change during the course of IT usage. Similarly, Khalifa and Liu (2003) validated the
role of satisfaction at different adoption stages. Their results both show that confirmation and performance
are important factors in explaining post-adoption satisfaction. Hsu et al. (2006) proposed an extended model
of TPB by incorporating constructs drawn from ECT and to examine the antecedents of users’ intention to
continue using online shopping. They conducted a longitudinal study to validate that confirmation plays an
important role in shaping the user’s belief during the pre-usage and usage stages.
3. RESEARCH MODEL AND HYPOTHESES
In this study, we develop research model integrated TCE and ECT to investigate bidder’s perceived customer
value. Research model and hypotheses is shown as Figure 1.
According to TCE, it comes from three variables that are employed to characterize any transaction—
frequency, uncertainty, and asset specificity. First, Uncertainty refers to the degree to which the future states
of the environment cannot be accurately anticipated or predicted due to imperfect information (Pfeffer and
Salancik 1978). In buyer–seller relationships, perceived uncertainty is defined as the degree to which the
outcome of a transaction cannot be accurately predicted by the buyer due to seller and product related factors
(Pavlou, Liang et al. 2007). Second, asset specificity refers to the lack of ease with which the human capital,
physical assets, and facilities specifically tied to the manufacturing of an item can be used by alternative
users or put to alternative uses. As asset specificity increases, due to transactors’ fear of opportunism, more
complex governance structures are required to eliminate or attenuate costly bargaining over profits from
specialized assets. Thus, transaction costs are presumed to increase with an increase in asset specificity
(Williamson 1981; Teo and Yu 2005). Third, frequency refers to the recurring nature of the transactions
(Devaraj, Fan et al. 2002). The effect of frequency on transaction cost is strong. In Internet environment,
buying frequency has an influence on consumers’ perceived transaction cost and their willingness to buy
online (Teo and Yu 2005). C2C e-commerce highlights the interpersonal communication through interaction
between bidders and sellers. Therefore, these lead to the following hypotheses:
H1: Bidders’ perceive product uncertainty is positively associated with their transaction cost of online
auction.
H2: Bidders’ perceive auctioneer’s asset specificity is positively associated with their transaction cost of
online auction.
H3: Bidders’ interaction frequency with seller and auctioneer is negatively associated with their
transaction cost of online auction.
Kotler (1980) indicated that creating customer value means meeting target customers’ needs and
increasing customers’ purchasing intentions. Perceived value represents a tradeoff between two variables:
transaction cost and satisfaction. Transaction cost describes what must pay to perform a certain behavior, e.g.
bidding in online auction. In contrast, satisfaction can be described as the bidder having a positive emotional
state resulting from purchasing through an auctioneer or from transacting with the seller. Therefore,
H4: Bidders’ transaction cost of online auction is negatively associated with their perceived customer
value.
H5: Bidders’ satisfaction of online auction is positively associated with their perceived customer value.
According to ECT, confirmation can be described as bidders’ subjective judgments resulting from
comparing their expectations and their perceptions of performance received. Therefore, confirmation is
determined by the combination of expectation and perceived performance. In this study, we assume that
overall e-service quality could be viewed as auctioneer’s and sellers’ performance. Besides, customers form a
feeling of satisfaction or dissatisfaction based on their confirmation level. A moderate satisfaction level will
be maintained by confirmation, enhanced by the delight of positive confirmation, and decreased by the
disappointment of negative confirmation. Many studies (Mckinney, Yoon et al. 2002; Khalifa and Liu 2003)
found that there is a strong link between confirmation and satisfaction and concluded that confirmation plays
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a dominant role in satisfaction. Moreover, in online auction environment, where bidders rely on IT-mediated
interactions, successful transaction depends on trust. Many studies highlight the role of trust in forming
customer’s satisfaction. Therefore,
H6: Bidders’ confirmation of online auction is positively associated with their satisfaction.
H7: Overall e-service quality of online auction is positively associated with bidders’ confirmation.
H8: Overall e-service quality of online auction is positively associated with bidders’ satisfaction.
H9: Bidders’ trust in online auction is positively associated with their satisfaction.
4. METHODOLOGY AND DATA ANALYSIS
4.1 Instrument Development and Research Design
Measure items for the research constructs were compiled from validated instruments to represent each
construct, and wording was modified to fit the context of an online auction. All transaction cost constructs
were based on economics literature and derived from prior e-commerce studies. Items for measuring product
uncertainty and asset specificity were adapted from Liang and Huang (1988) as well as Devaraj et al.(2002).
Items for measuring interaction frequency were developed following Teo and Yu (2005) and modified to fit
the online auction context. Items for measuring transaction cost were based on Liang and Huang (1988) as
well as Teo and Yu (2005). Moreover, items for measuring perceived customer value were developed
following Parasuraman et al.’s (2005) perceived value as well as DeLone and McLean’s (2003) net benefits.
Scale items for satisfaction were adapted from Oliver’s (1980) as well as Bhattacherjee and Premkumar’s
(2004). Items for measuring confirmation were adapted from Bhattacherjee (2001a) (2001b) as well as
Bhattacherjee and Premkumar (2004). Items for measuring overall e-service quality were based on
Parasuraman et al.’s (2005) definition and modified to fit the online auction context. Trust was based on
Mayer et al.’s (1995) definition and adapted form Gefen et al. (2003).
Except for demographic questions, most items were measured using a five-point Likert scale with anchors
ranging from strongly disagree (1) to strongly agree (5). In order to avoid response bias in the form of
acquiescence or affirmation (Netemeyer, Bearden et al. 2003), items of product uncertainty are negative
statements. As opposed to Teo and Yu’s (2005) as well as Liang and Huang’s (1988) scale, items of
transaction cost are used negative worded instead of positive sentences. As to items of asset specificity, we
use subjective sentences to capture respondents’ perception rather than subtractive worded. Thus, items of
asset specificity and transaction cost are required reverse coding.
In order to target buyers of online marketplace, a web-based survey was employed. This study was
supported by Yahoo! Kimo and the survey questionnaire was put at the head of the forum to promote this
survey. The questionnaire consisted of an instruction page that opened a separate web browser window
containing the items to be assessed. All the buyers who had a reputation record in Yahoo! Kimo auction were
welcomed to participate in this survey, while some prizes were offered to improve the number of high quality
responses. Because we are interested in the repurchase intention of buyers, we only considered respondents
who completed a bidding procedure to ensure that they had sufficient online auction experience, including
browsing, gathering product information, evaluating the bidding price, making bidding decisions, and
completing a transaction by offering payment and address information. By the time this survey was closed,
594 valid questionnaires had been received and were analyzed. There was no missing data in the sample
because participants could not submit their response unless it was complete.
4.2 Reliability and Validity of Research Constructs
The research was analyzed using structural equation model (SEM), supported by LISREL 8.54. The
adequacy of the measurement model was evaluated on the criteria of reliability, convergent validity, and
discriminant validity. First, reliability is the extent to which varying approaches to construct measurement
yield the same results (Campbell and Fiske 1959) and is examined using the composite reliability values. As
shown in Table 2, the values of composite reliability ranged form 0.81 to 0.91, which well above the
recommended level of 0.70 and indicating adequate reliability. Second, convergent validity is adequate when
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constructs have an average variance extracted (AVE) of at least 0.5 (Fornell and Larcker 1981). All AVEs
ranged from 0.50 to 0.65, which suggesting the principal constructs capture higher construct-related variance
than error variance. Third, for satisfactory discriminant validity, the square root of the AVE should exceed
the correlation shared between the construct and other constructs in the model (Fornell and Larcker 1981).
The correlations among all constructs are all well below the 0.90 threshold, suggesting that all constructs are
distinct from each other (Hair, Black et al. 2006). Comparison of construct correlation and the square root of
the AVE was shown in Table 2. Off-diagonal elements are the correlations among constructs, which ranged
form -0.04 to 0.72. Diagonal elements are the square root of the AVE, and all these values exceed the interconstruct correlations.
Table 1. Results of reliability and convergent validity
Construct
Items and Factor loading
Composite
reliability
Perceived customer value (CV)
Confirmation (CON)
Transaction cost (TC)
CV1=0.80 CV2=0.85 CV3=0.78 CV4=0.78
CON1=0.78 CON2=0.88 CON3=0.87 CON4=0.84
TC1=0.57 TC2=0.71 TC3=0.63 TC4=0.82
TC5=0.77
SAT1=0.77 SAT2=0.82 SAT3=0.78 SAT4=0.80
TFR1=0.89 TFR2=0.89 TFR3=0.58 TFR4=0.50
TAS1=0.80 TAS2=0.80 TAS3=0.69
TUN1=0.71 TUN2=0.88 TUN3=0.88 TUN4=0.69
SQ1=0.71 SQ2=0.84 SQ3=0.86 SQ4=0.81
TR1=0.66 TR2=0.87 TR3=0.85 TR4=0.84
0.88
0.91
0.83
Average
variance
extracted
0.65
0.71
0.50
0.87
0.82
0.81
0.87
0.88
0.88
0.63
0.55
0.58
0.63
0.65
0.65
Satisfaction (SAT)
Interaction Frequency (TFR)
Asset specificity (TAS)
Product uncertainty (TUN)
Overall e-service quality (SQ)
Trust (TR)
Table 2. Results of discriminant validity
Perceived customer value (CV)
Satisfaction (SAT)
Confirmation (CON)
Transaction cost (TC)
Interaction Frequency (TFR)
Asset specificity (TAS)
Product uncertainty (TUN)
Trust (TR)
Overall e-service quality (SQ)
CV
0.81
0.72
0.58
-0.46
0.41
-0.41
-0.06
0.54
0.47
SAT
CON
TC
TFR
TAS
TUN
TR
SQ
0.79
0.69
-0.47
0.31
-0.38
-0.09
0.64
0.54
0.84
-0.42
0.27
-0.32
-0.16
0.69
0.55
0.71
-0.29
0.30
0.10
-0.44
-0.36
0.74
-0.44
-0.04
0.27
0.20
0.76
-0.05
-0.30
-0.35
0.79
-0.14
-0.05
0.81
0.49
0.81
Off-diagonal elements are the correlations among constructs. Diagonal elements (in bold) are the square root of the AVE, and these
values should exceed the inter-construct correlations for adequate discriminant validity
4.3 Model Testing Results
The overall fit of model was tested to evaluate the correspondence of the actual or observed input matrix with
that predicted from our proposed model. The summary of the overall fit indices was shown in Figure 1. For
models with good fit, the ratio of chi-square to the degree of freedom (χ2/d.f.) should be less than 3.0
(Carmines and McIver 1981), and RMSEA should be lower than 0.06 (Hu and Bentler 1999). GFI, and CFI,
should exceed 0.9 (Hair, Black et al. 2006) and so should NNFI (Bentler 1988). The value of χ2/d.f. is 2.8,
NFI is 0.96, CFI is 0.98, and RMSEA is 0.055.
The SEM approach was also used to test the hypothesized relationships in the research model. Figure 1
illustrates the estimated coefficients and their significance in the structural model, where all relationships
were statistically significant. Product uncertainty, asset specificity, and interaction frequency all had
significant effects on transaction cost (β= 0.13, 0.32, -0.13 ; t= 2.95, 5.26, -2.42, respectively). Thus, H1,
H2, and H3 were supported. Perceived customer value was strongly predicted by transaction cost and
satisfaction (β= -0.13, 0.80 ; t= 3.92, 15.78, respectively), as well as H4 and H5 were supported. The path
between overall e-service quality and confirmation was significant ( β= 0.64; t= 12.87), and H7 was
supported. Confirmation, overall e-service quality, and trust positively influenced satisfaction (β= 0.47,
0.20, 0.31; t= 9.82, 3.86, 7.00, respectively), as well as H6, H8, and H9 were supported.
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H1
0.13**
Product
uncertainty
H2
Transaction cost
Asset specificity 0.32***
In the
Interaction
Frequency
H4
-0.13***
H3
-0.13*
Perceived
customer value
Overall e-service
quality
In the
H8
0.20***
H5
0.80***
H7
0.64***
Confirmation
H6
0.47***
Satisfaction
In the
Trust
H9
0.31***
Significance level:
*p value<0.05,
**p value<0.01,
***p value<0.001
Figure 1. Research model and path analysis
5. CONCLUSION
The relationship of findings presented to the research questions will be discussed in this section. First, this
study examines TCE to evaluate the transaction cost in online auction environment. Auctioneer’s asset
specificity and product uncertainty are positively associated with bidder’s perceived transaction cost.
Bidder’s interaction frequency between bidder and seller is negatively associated with their transaction cost.
Second, our findings validate ECT to show that bidders’ confirmation is positively associated with their
satisfaction, and their satisfaction is positively associated with customer value. Bidder’s satisfaction is
determined by trust and confirmation, as well as e-service quality of auctioneer and seller. Finally, the
findings show that satisfaction has significant influence on bidder’s perceived customer value, while
transaction cost is negatively associated with customer value.
By synthesizing the above conclusion and discussion, several implications can be drawn from this
research. First, from the bidder’s perspective, the strength of the relationship between satisfaction and
customer value has been found to vary significantly. How to create customer value becomes the most
important issue in the online auction marketplace. Second, auctioneers’ performance (i.e. e-service quality) is
important to influence bidder’s perceived value. Auctioneer should construct a legal and safe infrastructure,
to establish an efficient environment, and to facilitate trading activities. Finally, expanded from buyer-seller
relationships in B2C, C2C not only has bidder-seller relationships, but also has a bidder-auctioneer (i.e. buyer
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toward website) connection. Online auctioneers play as intermediaries to connect bidders and sellers. Further,
anyone with an Internet connection can easily become a bidder or seller, and this highlights the importance of
establishing self-regulating trust mechanisms to allow transactions to take place smoothly between
geographically separated strangers.
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FACTORS INFLUENCING SAUDI CUSTOMERS’
DECISIONS TO PURCHASE FROM ONLINE RETAILERS
IN SAUDI ARABIA: A QUANTITATIVE ANALYSIS
Rayed AlGhamdi, Ann Nguyen, Jeremy Nguyen and Steve Drew
School of ICT, Griffith University
ABSTRACT
This paper presents the preliminary findings of a study researching the diffusion and the adoption of online retailing in
Saudi Arabia. It reports new research that identifies and explores the key issues that positively and negatively influence
the decision of Saudi customers to buy from online retailers in Saudi Arabia. Although Saudi Arabia has the largest and
fastest growth of ICT marketplaces in the Arab region, e-commerce activities are not progressing at the same speed.
While the overall research project involves exploratory research using mixed methods, the focus of this paper is on a
quantitative analysis of responses obtained from a survey of Saudi customers, with the design of the questionnaire
instrument being based on the findings of a qualitative analysis reported in a previous paper. The main findings of the
current analysis include a list of key factors that affect Saudi customers' purchase from Saudi online retailers, and
quantitative indications of the relative strengths of the various relationships.
KEYWORDS
E-commerce, Online retail, Online customers, Saudi Arabia, Quantitative analysis, Factors
1. INTRODUCTION
The revolution of electronic commerce (e-commerce) has started in the 90s in the developed world. Many
commercial organizations around the world have introduced e-commerce models in their businesses, seeking
the many benefits that the online channel can provide (Laudon and Traver 2007). Basically, e-commerce is
commerce enabled by Internet technologies, including pre-sale and post-sale activities (Whiteley 2000;
Chaffey 2004) and online retailing is a model of business to customer (B2C) e-commence which is online
version of traditional retail (To & Ngai 2006). Since 2000, e-commerce's rapid growth is obvious in the
developed world. Global e-commerce spending has currently reached US$10 trillion and was US$0.27
trillion in 2000 (Kamaruzaman, Handrich & Sullivan 2010). The United States, followed by Europe,
constitutes the largest share with about 79% of the global e-commerce revenue (Kamaruzaman, Handrich &
Sullivan 2010). However, the African and Middle East regions have the smallest share with about 3% of the
global e-commerce revenue (Kamaruzaman, Handrich & Sullivan 2010).
Regarding Saudi Arabia, the world's largest oil producer (CIA 2009), e-commerce is still underdeveloped.
Although Saudi Arabia has the largest and fastest growth of ICT marketplaces in the Arab region (Saudi
Ministry of Commerce 2001; Alotaibi and Alzahrani 2003; U.S. Commercial Services 2008; Alfuraih 2008),
e-commerce activities are not progressing at the same speed (Albadr 2003; Aladwani 2003; CITC 2007).
Only 9% of Saudi commercial organizations, mostly medium and large companies from the manufacturing
sector, are involved in e-commerce (CITC 2007). This paper is part of a research project studying the
diffusion of online retailing in Saudi Arabia. The focus of this paper is on the investigation of factors that
affect Saudi customers’ decisions to purchase from online retailers in Saudi Arabia.
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2. LITERATURE REVIEW
Information and Communication Technology (ICT) plays a significant role in the countries’ economies. Over
the last decade, the Saudi government has concentrated on this field to become the largest and fastest
growing ICT marketplace in the Arab region (Saudi Ministry of Commerce 2001; Alotaibi and Alzahrani
2003; U.S. Commercial Services 2008; Alfuraih 2008). The Saudi government has introduced policies to
encourage public and private organizations to adopt ICTs (Al-Tawil, Sait and Hussain 2003). In Saudi
Arabia, so far, the effort towards e-commerce development have not reached its originally stated aspirations;
neither what it sees as the world’s expectations of a country of the level of importance and weight in the
global economy like Saudi Arabia. The government support for e-commerce development seems to be
missing which represents a key for online retail growth in Saudi Arabia (AlGhamdi & Drew 2011and
AlGhamdi, Drew & Alkhalaf, 2011). Official/government information/documents about e-commerce in
Saudi Arabia are not sophisticated. The official discussion to introduce e-commerce in Saudi Arabia started
in 2001. In that year, Saudi Ministry of Commerce established a permanent technical committee for ecommerce including members from the Ministries of Commerce, Communication and Information
Technology and Finance. It also includes members from the Saudi Arabian Monetary Authority (SAMA) and
King Abdulaziz City for Science and Technology (KACST) (Saudi Ministry of Commerce 2001). The roles
of this committee are to follow the developments in the field of e-commerce and take the necessary steps to
keep pace with them. However, this committee does no longer exist. The role of e-commerce supervision in
the country has been transferred to the Ministry of Communications and Information Technology since 2005.
So far, the efforts of e-commerce support by Ministry of ICT are hapless. A phone call made to Ministry of
ICT followed by e-mail on April 2011 seeking further information about e-commerce support and
development. The answer was that the Ministry of ICT in Saudi Arabia is still in its early stages of studying
e-commerce. Currently, they are conducting a survey on e-commerce in Saudi Arabia and a report may be
published in May/June 2011.
According to EUI (2010) report which assessed the quality of 70 countries’ ICT infrastructure and the
ability of their government, businesses and people to use ICT, Saudi Arabia ranked 52 in e-readiness. The
extent of Internet access in Saudi Arabia indicates its e-commerce readiness (Sait, Altawil, and Hussain
2004). The Internet was introduced in Saudi Arabia in 1997 (Alzoman 2002). Only King Abdulaziz City for
Science and Technology (KACST) provides Internet access; therefore, all Internet users in Saudi Arabia go
through KACST (Algedhi 2002; Saudi Internet 2007b). The Internet users increased from one million (5% of
the population) in 2001 to 11.2 million (41%) in 2010 (MCIT 2010). “Broadband subscriptions have grown
from 64,000 in 2005 to over 3.2 million at the end of Q3 2010” (MCIT 2010). However, broadband
subscriptions remain very low compared to the developed nations.
The Arab Advisor Group carried out an extensive survey in mid-2006, targeting Internet users in four
Arab countries (Saudi Arabia, UAE, Kuwait and Lebanon). The survey covered Internet usage and, ecommerce activities in these countries. While UAE ranked first in the rate of annual spending on e-commerce
per capita, Saudi Arabia ranked first in the overall money spent on e-commerce activities. As for the
prevalence of e-commerce activities among the population, UAE ranked first at 25.1%, Saudi Arabia second
at 14.3%, Kuwait third at 10.7% and Lebanon last at 1.6% (AAG 2008). A recent survey of Saudi Arabia’s
Internet users found that around 3.1 million Saudis have purchased online. Airline tickets and hotels
bookings take the largest percentage of these purchases (ACG 2009, AAG 2011). Although the youth are the
majority population of the six Gulf countries (GCC: KSA, UAE, Kuwait, Oman, Qatar and Bahrain),
increasingly using the latest technologies, online shopping remains under-developed, mainly because of “the
relatively low levels of internet usage and low credit card penetration” (ACG 2009). Approximately 45% of
GCC populations have purchased online.
Several studies have been conducted to discover the reasons behind the slow e-commerce developments
in the Arab world in general and Saudi Arabia in particular. The reasons were mainly involved ICT
infrastructure, trust and privacy issues, cultural issues, and the absence of clear regulations, legislation, rules
and procedures on how to protect the rights of all involved parties (Albadr 2003; Aladwani 2003; Al-Solbi
and Mayhew 2005; CITC 2006; Alfuraih 2008; Alraw; Sabry 2009 and Alghaith, Sanzogni and Sandhu,
2010). Although Saudi Arabia contributes to the efforts of UNCITRAL (United Nations Commission into
International Trade Laws) (Saudi Ministry of Commerce 2001), there is a need to have major development in
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terms of e-commerce regulations, legislations and rules to protect the rights of all parties involved in ecommerce transactions (Albadr 2003; Al-Solbi and Mayhew 2005).
Other challenges involve the mailing system (Alfuraih 2008). Before Saudi Post was established in 2005,
individuals had no home addresses (Saudi Post 2008); therefore, to receive mail, individuals had to subscribe
to have a mailbox in the post office (Alfuraih 2008). In 2005, the postal delivery to homes and buildings was
approved by Saudi Post (Alfuraih 2008; Saudi Post 2008). While this service is still relatively new, Saudi
Arabia is very late in providing individual addresses. Problems with adopting this service might be the
citizens' lack of awareness of this service or the importance of mailboxes, their ignorance of the direct
addresses for their houses with numbers and streets names, or their mistrust of receiving their mail in this
way. Consequently, more efforts are needed to motivate the citizens owning house mailboxes and solve the
problems that they face.
At the end of 2010, Saudi Post launched an electronic mall, “the first online marketplace in Arabic and
English” (E-mall 2010), giving Saudi retailers the chance to sell their products online and benefit from cheap
delivery fees. In March 2011, e-mall administrators revealed that to date, there are 50 sellers, 50,000 buyers,
which is a 10% increase in buyers and sellers. 2,000 deals have taken place, totalling 2 million KSR, with the
preferred payment method being SADAD (Al-Mohamed 2011). It seems Saudi Post adopting online mall to
encourage more citizens subscribe in their services including having a home mailbox.
The culture of people to buy in Saudi Arabia is still a key factor influences retailers to adopt online sale
channel. The difficulty to attract customers buying online is the first answer that you get when you ask a
retail decision maker in Saudi Arabia why you do not adopt and use online retail channel. There is an
emphasis on this factor making it a key concept for deterring the diffusion of e-retail systems in Saudi Arabia
(AlGhamdi, Drew & Al-Ghaith 2011). However, the spending of online retailing in Saudi Arabia is growing.
Online retail sector size estimated to about SAR 3 billion (US$1= SAR 3.75). This figure represents 20% of
the total Electronic Trading in Saudi Arabia. The average value of what a customer pays for each online
purchase is about SAR400 (Hamid 2011). This spending of growing community of online customers vs the
slowness of retailers to introduce online sale channel in Saudi Arabia is an indicator that retailers in Saudi
Arabia are not realizing the importance of online retail yet.
Up to date, no single study has been founded studding customers behaviours, drivers and inhibitors to
purchase online from retailers in Saudi Arabia. As stated by retailers, the major concerns for them that the
customers’ behaviour to buy online is frustrated and that is what discourages them introducing online sales
channel (AlGhamdi, Drew & Al-Ghaith 2011). In contrast, Internet customers in Saudi Arabia are growing
and a number of their online spending goes overseas. For this reason, this research explores the factors
influencing Saudi customers’ decisions to purchase from online retailers in Saudi Arabia. The study, firstly,
used qualitative approach to explore the issues. The purpose of this paper is to follow up the qualitative study
in order to test the findings in a wider sample.
The qualitative study by AlGhamdi, Drew & AlFaraj (2011) established a list of factors that inhibit
customers to purchase online from an e-retailer in the KSA. These inhibitors are (1) lack of home mailbox,
(2) feeling uncomfortable paying online with a credit card, (3) do not know e-retailers in Saudi Arabia, (4)
lack of experience in buying online, (5) not having easy and fast access to the Internet, (6) lack of physical
inspection of a product, (7) personal information (name, mobile number, e-mail etc) privacy, (8) lack of clear
regulations and legislation for e-commerce in the KSA, (9) lack of the language understanding if the website
or part of it is in English, (10) not trusting e-retailers in Saudi Arabia. The qualitative study also established a
list of incentives that may encourage customers to purchase online from e-retailers in the KSA. These
enablers are (1) competitive prices, (2) owning a home mailbox, (3) easy access and fast speed of the
Internet, (4) provision of educational programs, (5) local banks make it easy to own a credit card, (6)
professional and easy to understand design of the e-retailer’s website, including showing complete
specifications with photos of the products, (7) existence of a physical shop besides the online shop (Brick and
click), (8) existence of online payment options other than credit cards, (9) existence of government support,
supervision and control. So, the purpose of this paper is to establish numerically the relative strengths of
these inhibiting and enabling factors.
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3. RESEARCH METHODOLOGY
The whole project studying online retail in Saudi Arabia is built on the combination of qualitative and
quantitative approaches. Qualitative study conducted first for exploration purpose and followed by
quantitative approach based on qualitative findings for testing purpose. This type of approach is called
exploratory mixed methods design (Creswell 2008, p. 561) which is done “to explore a phenomenon, and
then [collect] quantitative data to explain relationships found in the qualitative results” (Creswell 2008, p.
561). The mixed methods approach helps to provide an in-depth investigation of the research problem (Morse
2003; Johnson & Onwuegbuzie 2004; Greene 2007; Alise and Teddlie 2010; Feilzer 2010).
While the qualitative study was conducted in a separate research (AlGhamdi, Drew & AlFaraj 2011), the
focus of this paper is on quantitative analysis based on the qualitative findings. In the qualitative study
(AlGhamdi, Drew & AlFaraj 2011), interviews were conducted with 16 Saudi participants (eight males and
eight females) aged from 16 to 45 years. A qualitative content analysis was used to identify the factors that
positively and negatively influence customers’ decision to purchase from online retailers in Saudi Arabia.
In this paper, a questionnaire survey based on the qualitative study’s findings is used to gain more
information about the relative strengths of these factors (for the survey questionnaire, please contact the main
author). Typically a question that asks for information about the participant’s background and attributes
would provide a set of choices, plus an open answer (e.g., “other”) where the participant could insert
additional information if he or she wishes. The two key questions are “What factors inhibit or discourage you
from buying online from e-retailers in Saudi Arabia?” and “What would enable you to buy online from eretailers in Saudi Arabia?” The participants would be given a list of 11 options to select from for the former
question, and 10 options for the latter (in each case, the last option is “other reasons”). Respondents may
select as many of the available options as they wish, including the open answer. The survey questions are in
Arabic.
Two forms were distributed. Paper and online surveys were collected, with 50% for each form. The aim is
to collect answers from 700 participants which are still ongoing; however, up-to-date the total number of
participants reported in this paper reached 412. They were selected randomly with consideration to represent
50% of each gender, cover different age groups, and come from different cities in Saudi Arabia.
4. RESULTS AND DATA ANALYSIS
This section presents a summary and analysis of the responses collected to date from 412 participants. Male
respondents account for 50% of the sample, and female respondents 50%. Respondents aged 15-25 represent
27.2% of the sample, compared with 49.0% for those aged 26-35 and 23.8% for those aged 36 and over.
About 28.6% of the sample are residents of the capital city (Riyadh), compared with 26.0% for Jeddah,
11.7% for Al-Baha, 28.2% for residents of smaller cities, and the remaining 5.8% for residents of smaller
urban centres.
Table 1 reports our findings with respect to the relative importance of factors that inhibit Saudi customers
from making online purchases from Saudi e-retailers. In this table, the inhibitors are listed in the order in
which they are presented to the respondents. Figure 1 illustrates the same information, but with each
inhibitor being ranked according to its relative weight, from being most frequently selected to least.
Table 1. Inhibitors of online purchases by Saudi customers from Saudi vendors
Identifier
IN1
IN2
IN3
IN4
IN5
IN6
IN7
IN8
IN9
IN10
IN11
156
Inhibitor
Lack of experience in buying online
Not trusting e-retailers in Saudi Arabia
Not having easy and fast access to the Internet
Cannot inspect product, worry about quality
Lack of mailbox for home
Do not know e-retailers in Saudi Arabia
Not comfortable paying online using credit card
Do not understand if website (or part) is in English
No clear regulations & legislations for EC in KSA
Don't trust that personal info. will remain private
Others
Selected by % of respondents
40.8
38.6
7.3
58.0
31.8
38.6
27.7
20.9
53.4
44.7
6.1
Rank
4
5
10
1
7
6
8
9
2
3
11
IADIS International Conference e-Commerce 2011
Physical inspection
Regulations and legislation
Personal information privacy
Lack of experience
Not trusting e-retailers
Do not know e-retailers in KSA
Lack of home mailbox
Uncomfortable using credit card
Website language
60%
40%
20%
0%
Figure 1. Factors inhibiting online purchases by Saudi customers from Saudi e-retailers
From Table 1 and Figure 1, it can be seen clearly that the most serious inhibitors tend to be related to a
lack of trust and/or experience with online purchasing. For example, Inhibitor IN4 (Customers cannot
inspect product and worry about product quality) is ranked 1, being cited by 58.0% of the respondents.
Similarly, IN10 (Customers do not trust that their personal information, such as name, mobile phone number,
etc, will remain private) is selected by 44.7% of respondents (ranked 3). IN2 (Customers do not trust eretailers in Saudi Arabia) which refers directly to a lack of trust in Saudi e-retailers, is cited by 38.6% of
respondents (rank 5). In the same vein, 40.8% of the respondents indicate that lack of experience in buying
online (IN1) is a major inhibitor in their case (ranked 4), and 38.6% indicate that they don’t know Saudi eretailers well (IN6, ranked 6). It appears that in the minds of many Saudi customers, a lack of clear
government regulations and legislations on e-commerce may have been a key contributor to this general lack
of trust and experience: IN9 is chosen by 53.4% of respondents (ranked 2).
Interestingly, while a lack of a home mailbox (IN5, ranked 7) or being uncomfortable with using a credit
card to make online payments (IN7, ranked 8) may deter significant percentages of the people in the sample
(31.8% and 27.7%, respectively), numerically these are clearly less important than the trust/experience
issues. It is rather re-assuring to find that lack of a command of English (IN8) is a relatively minor issue
(20.9%, ranked 9). In view of recent IT infrastructure developments in Saudi Arabia it is not surprising that
lack of ready access to fast Internet connections (IN3) is largely a non-issue (7.3%, ranked 10).
Table 2 and Figure 2 present basic survey results with regard to factors that would tend to enable or
encourage customers to purchase online from Saudi e-retailers.
Table 2. Enablers of online purchases by Saudi customers from Saudi vendors
Identifier
EN1
EN2
EN3
EN4
EN5
EN6
EN7
EN8
EN9
EN10
Enabler
Owning house mailbox
Easy access & fast Internet speed
Competitive prices
Local banks make owning credit cards easier
Provision of educational programs
Government support, supervision & control
Well-designed retailer websites (photos of products)
Physical shop as well as online shop
Trustworthy payment options other than credit cards
Others
80%
60%
40%
20%
0%
Selected by % of respondents
37
33
57
21
29
58
37
65
45
7
Rank
5
7
3
9
8
2
6
1
4
10
Brick and Click
Government support
Competitive prices
Online payment options
Owning home mailbox
Professional website design
Easy access and fast Internet
Educational programs
Easy of owning a credit card
Others
Figure 2. Factors facilitating online purchases by Saudi customers from Saudi e-retailers
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ISBN: 978-972-8939-51-9 © 2011 IADIS
The top two enablers of Saudi online purchases are both measures with the potential to alleviate the
trust/experience issues identified above as key inhibitors: EN8 (the presence of a physical shop as well as an
online shopfront) is selected by 65% of the respondents (ranked 1) and EN6 (government support,
supervision and control of e-commerce) is selected by 58% (ranked 2). Similarly, EN5 (provision of
educational programs) is seen by 29% of respondents as an enabler (ranked 8).
Other enablers that can be readily anticipated by the above analysis of inhibitors are EN9 (development of
trustworthy and secure payment options other than credit cards) which is cited by 45% of the respondents
(ranked 4), EN4 (local banks making it easier for customers to own credit cards) which is selected by 21%
of the respondents (ranked 9), and EN1 (owning a home mailbox), chosen by 37 % (ranked 5).
A very important enabler (57%, ranked 3) that is not directly anticipated by the inhibitors analysis is EN3
(e-retailers being able to offer competitive prices). Similarly, EN7 (professional and easy-to-understand
retailer websites, including product photos and complete specifications) is seen by 37% of the respondents as
an enabler (ranked 6). Both of these results point to the type of features or attractions that Saudi e-retailers
will need to provide to succeed.
A result that seems slightly anomalous, given other existing information about Internet access in Saudi
Arabia, is that EN2 (easy access and fast Internet speed) is nominated as an enabler by a significant
percentage of the respondents (33%, ranked 7).
Delving more deeply into the details of the individual responses allows us to gain further insights into key
inhibitors of the demand for goods and services provided by the Saudi e-retail sector. Table 3 presents data
relating to the interactions between inhibitors and customer attributes.
Table 3. Inhibitors of purchases from Saudi e-retailers and attributes of potential Saudi customers
All respondent customers
Males
Females
Age 15-25
Age 26-35
Age 36 and over
Main city residents
Small city residents
Very small city residents
Have no mailbox
Mailbox at agency
House mailbox
Have credit card
No credit card
Home access to internet
No home access to Internet
Have bought online
Have not bought online
Bought online from KSA
Bought from foreigners only
Inhibitors and Attributes of Customers
Percentage of respondents selecting
% of
IN1
IN2
IN3
IN4
IN5
IN6
IN7
IN8
sample
100.0
40.8
38.6
7.3
58.0
31.8
38.6
27.7
20.9
50.0
33.0
43.2
7.8
51.0
32.5
41.3
28.2
16.5
50.0
48.5
34.0
6.8
65.0
31.1
35.9
27.2
25.2
27.2
50.0
44.6
8.9
58.9
34.8
42.0
24.1
27.7
49.0
34.7
37.6
7.9
56.9
32.2
38.6
24.3
17.3
23.8
42.9
33.7
4.1
59.2
27.6
34.7
38.8
20.4
66.0
37.9
36.0
4.4
59.2
27.2
38.2
29.0
17.3
28.2
46.6
48.3
13.8
56.9
43.1
38.8
25.0
27.6
5.8
45.8
20.8
8.3
50.0
29.2
41.7
25.0
29.2
49.5
51.5
34.3
6.9
55.9
40.7
35.3
23.5
22.5
37.4
30.5
42.2
8.4
59.7
27.9
40.9
29.2
18.8
13.1
29.6
44.4
5.6
61.1
9.3
44.4
38.9
20.4
42.0
23.1
43.9
6.4
53.8
28.3
42.2
31.2
12.7
57.3
54.2
35.2
8.1
61.9
34.7
36.4
25.4
27.1
90.3
40.9
38.7
3.5
58.6
30.4
38.2
27.2
21.0
9.7
40.0
37.5
42.5
52.5
45.0
42.5
32.5
20.0
41.5
15.2
45.0
7.0
48.5
25.1
43.9
23.4
12.9
58.5
58.9
34.0
7.5
64.7
36.5
34.9
29.9
26.6
14.1
24.1
36.2
3.4
56.9
19.0
39.7
27.6
22.4
27.4
10.6
49.6
8.8
44.2
28.3
46.0
23.0
8.0
IN9
IN10
53.4
64.1
42.7
48.2
56.9
52.0
53.7
55.2
41.7
47.1
64.3
46.3
66.5
44.5
54.6
42.5
63.2
46.5
55.2
67.3
44.7
46.6
42.7
42.9
46.0
43.9
42.3
49.1
50.0
45.1
45.5
40.7
49.7
41.5
44.4
47.5
45.6
44.0
41.4
47.8
Data presented in Table 3 suggest that despite recent efforts to encourage Saudi residents to acquire
mailboxes, many still have no access to mailboxes (49.5% of our sample) and only a small minority have
home mailboxes (13.1%). Inevitably this would have a negative influence on the feasibility of conducting eretail purchases. Another interesting statistic is that more than one-half (57.3%) of the respondents don’t
have a credit card. To some extent this is related to a cultural issue over the question of credit and interest
rates, and points to the desirability for alternative online payment arrangements that are secure and effective.
Our analysis thus far has been based on the entire sample of respondents. Additional useful insights can
be gained by focusing on a subset of this sample, namely the respondents who have already made some
online purchases in the past. As can be seen from Table 3, 41.5% of the participants report having done so.
There is a strong association between owning a credit card and having bought online: Of the 173 respondents
who own a credit card, 116 say that they have bought online, a much higher percentage (67.05%) than for the
sample as a whole.
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IADIS International Conference e-Commerce 2011
Of the 171 respondents who have made online purchases, a majority have bought from overseas eretailers only: they represent 27.4% of the whole sample, compared with 14.1% for those who have bought
from vendors in Saudi Arabia (most, if not all, of the latter buyers have also bought from overseas vendors).
From interviews for the previous qualitative analysis and from follow-up enquiries as part of the current
analysis, it would appear that this (approximate) 2:1 imbalance is attributable largely to the reputation of
global online retailers such as Amazon.com, eBay, Dell, etc. and the major airlines and hotel operators.
Positive recommendations from relatives and friends tend to reinforce this pattern. In view of the above
discussion about trust issues, it is relevant to note that e-retailers that could follow eBay’s example and use
customer feedback to substantiate the seller’s trustworthiness would be able to alleviate Saudi buyers’
customary lack of trust. Similarly, the use of PayPal for online payments can help build customer trust,
because it acts as a third party between the seller and the buyer, thus helping to resolve problems that might
arise.
Examination of the bottom rows of Table 3 reveals interesting contrasts and similarities between
respondents with and without online purchase experiences. For example, it can be seen clearly that whilst
IN1 (lack of experience in buying online) is a major inhibitor to respondents who have not bought online (it
is selected by 59.0% of them, ranked 2) it is of little relevance to respondents who have done so, especially to
those who have bought from overseas vendors only (10.6%). Yet as far as the issues of trust in Saudi eretailers (IN2, IN4, IN6, and IN10) and the missing presence of government regulations and supervision
(IN9) the various categories of respondents give very similar ratings. These similarities serve to reinforce a
general conclusion that has emerged from our analysis: trust in Saudi e-retailers (or the lack of it) is probably
the most important factor affecting current and potential Saudi customers. From this, it is reasonable to draw
the implication that the government can play, if it so wishes, a key role in regulating, supervising, and
facilitating e-retail in Saudi Arabia. The critical question, then, becomes whether there are valid justifications
for the government to take such an interventionist role in normal commerce, as opposed to the cases of egovernment and e-learning which involve public services or “social” goods. Such a question must be left to
future research.
5. CONCLUSION
This paper has investigated the issues that positively and negatively influence customers to purchase from
online retailers in Saudi Arabia. The study comes up with a list of factors that influence the decision of Saudi
customers to purchase from online retailers in Saudi Arabia ranked according their rating. The main finding
of this study clearly demonstrates that the most serious inhibitor tend to be related to a lack of trust. It also
appears that in the minds of many Saudi customers, a lack of clear government regulations and legislations
on e-commerce may have been a key contributor to this general lack of trust and experience (chosen by
53.4% of respondents, ranked 2). On the other hand, the top two enablers of Saudi online purchases are both
measures with the potential to alleviate the trust/experience issues identified above as key inhibitors: EN8
(the presence of a physical shop as well as an online shopfront) is selected by 65% of the respondents (ranked
1) and EN6 (government support, supervision and control of e-commerce) is selected by 58% (ranked 2).
In conclusion, trust in Saudi e-retailers (or the lack of it) is probably the most important factor affecting
current and potential Saudi customers. From this, it is reasonable to draw the implication that the government
can play, if it so wishes, a key role in regulating, supervising, and facilitating e-retail in Saudi Arabia. The
critical question, then, becomes whether there are valid justifications for the government to take such an
interventionist role in normal commerce, as opposed to the cases of e-government and e-learning which
involve public services or “social” goods. Such a question must be left to future research.
This study is limited in terms of the sample size. However, the data collection still ongoing and by the end
of the study the sample is expected to reach 700 participants. This study is still in progress. We will, in due
course, be able to report all the factors that positively and negatively affect e-retailing growth in Saudi Arabia
and gaining the information from all involved parties (i.e. retailers, customers and government) in this field
in order to contribute to e-commerce development in general and the diffusion of online retailing in particular
in Saudi Arabia.
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161
Short Papers
IADIS International Conference e-Commerce 2011
THE DETERMINANTS OF ONLINE HOTEL
RESERVATION
Hulisi Öğüt
Department of Business Administration,
TOBB University of Economics and Technology, Ankara, Turkey
ABSTRACT
In this paper, we identify the determinant of online hotel reservation using data from one of the biggest online hotel
booking website. We find that online customer rating significantly affects the hotel reservation while the star rating does
not increase popularity of the hotels. Furthermore, increase in prices leads to decrease in sales as we expected. Regression
result allows us to quantify the relationship between these variables and online reservation as well. The managerial
implication of these results is that hotels should strive to please customer as their future revenue depends on the
satisfaction of past users. This study also guides hotel management to forecast their sales based on online rating and other
features of hotel.
KEYWORDS
Internet Customer Reviews and Ratings; Online Hotel Booking; Online Hotel Price; Service Quality Metrics
1. INTRODUCTION
Consumers increasingly use e-commerce sites for purchasing many products and services and internet
becomes preferred sales channel for many industries. Travel industry is one of the first and successful
industries to use Internet for this purpose and studies show that online travel sales keep growing. With a 16%
share, hotel accommodation is the second largest sales item after air travel among online travel sales and
revenue generated through online hotel booking increases (Marcussen 2007). Recent studies show that travel
reviews are increasingly becoming an important factor in hotel selection by travelers. As indicated by Milan
(2007), millions of travelers log on daily to Travel websites like Tripadvisor.com and experience web content
through hotel generated photos, written text and hotel reviews by past customers. Milan (2007) indicates that
84% of people visiting a Travel website hosting consumer generated content have their hotel choices affected
by what they see and online hotel shoppers find reviews and hotel and room photos much more convincing
than other features of hotels.
The studies mentioned above show that online hotel shopping and online reviews are becoming
increasingly important for both hotel consumers and hotel management. However, researcher analyzed the
different aspect of online reviews in particular sectors, the impact of online reviews are not fully explored in
online hotel booking setting. One exception to this is the study of Öğüt and Taş (2011). In their paper, they
modeled and estimated the effect of online customer rating and other features of hotel on the demand and
price of hotel rooms. However, one of the limitations of their study is the unavailability of hotel reservation
data. For this purpose, they use the number of reviews as a proxy for sales data. Thus, the validity of the price
elasticity and other coefficient of their model in their study are subject to further verification since coefficient
calculation are not based on real sales data. Recently, this website publishes the online booking data in real
data in the form of last reserved booking hotels in real time. Thus, we collected these data and investigate
how online review and other features of hotels affects the hotel’s online reservation based on real sales data
in this paper. By controlling hotel star, our analysis shows that hotels increase (decrease) their sales if they
have higher (lower) online review scores. However, increase in star rating does not increase the online
booking of hotels. We also find that price increase leads to decreases in sales as it is expected. Regression
result allows us to quantify the relationship between these variables and sales data as well. We also compare
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the research of Öğüt and Taş (2011) and our paper and find that the use of the number of reviews as a proxy
for sales data overestimate the coefficient of customer rating and elasticity of prices
The remainder of the paper is organized as following. In section 2, relevant studies in hotels and online
customer reviews literatures are summarized. We describe our data in Section 3 and model is analyzed in
Section 4. The paper is concluded in Section 5.
2. LITERATURE REVIEW
Online reviews are extensively studied in many of the e-commerce application and the results of these papers
find that information asymmetry between seller and buyer has been mitigated by online customer reviews.
This observation is valid especially for experience goods as their assessment of quality are difficult prior to
purchase. Among these studies, Chevaliear and Mayzlin (2006) examine the effect of consumer reviews on
relative sales of books on Amazon.com and BarnesandNoble.com and they show that customer
communication on the internet has an important impact on customer behavior. They find that an
improvement in a book's reviews leads to an increase in relative sales at that site. Duan et al. (2008) and Liu
(2006) find that sales performance and review volume in the movie industry are positive correlated. Pavlou
and Dimoka(2006) show that seller who received higher rating can sell their product with a higher price in
the online auction sites.
Recently, researchers investigate the impact of online reviews on consumer’s hotel selection decision.
Among them, Vermeulen and Seeger (2009) conduct an experimental study and conclude that exposure to
online reviews increases hotel consideration in consumers. By using survey methodology, Dickinger and
Mazanec (2008) show that recommendations of friends and online reviews are the most two important
drivers of online hotel booking. Our paper is different from these papers in two respects. First, while these
researches analyze mainly how customer’s hotel selection decision is affected by online reviews, we quantify
the impact of online reviews on the sales of hotel rooms. Another difference is that while other two studies
use experimental and survey data, we used real historic data extracted from an online hotel booking website
in real time.
3. BACKGROUND
The price of hotel is one of the most important criteria for the selection of hotels as it represents the actual
cost to customer. This is especially true when two hotels have the same features except their price. Thus, we
expected that the low price is preferred high price if everything is being equal. Consequently, we hypothesize
that
H1: All else being constant, hotels with higher price have lower sales.
The offering of hotels to the customer can be classified as service delivery. Some of the characteristic of
service delivery are that customer contact is high, output is intangible and evaluation of the service can be
done only after delivery of service (Stevenson, 2007). Thus, customer takes into account many features of the
hotel in order to decreases risk of hotel decision. As the most frequently mentioned quality features, star
rating of the hotel plays important role in the customer decision and studies show that every one out of two
customer consider star the most important attribute in the selection process (Callan, 1998). Therefore, we
expect that
H2: All else being constant, hotels with higher star have higher sales.
However, star attribute did not measure some subjective quality dimensions such as how nice hotel staff,
cleanness of hotel room and value for money. For this reason, most people choose hotels based on
recommendation of friend and earlier studies shows that word of mouth is one of the important factors in
hotel selection process (Dickinger and Mazanec 2008). Online reviews is considered as the counterpart of the
word of mouth in the cyber world and recent studies found that online reviews play important role in the
customer decision process (Dickinger and Mazanec 2008, Vermeulen and Seeger 2009). As a quality
measure, online reviews complement star features and higher online reviews can increases popularity of the
hotel. For these reasons, we expect that hotels with higher online reviews charge premium over other hotels
and we hypothesize that,
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H3: All else being equal, hotels with higher online rating score have higher sales.
4. DATA
Our data come from is one of the biggest online hotel booking sites. After customers enter the location,
check-in and check-out date, available hotels are listed in this website. In these listing, it is possible to obtain
information about price, star, address, map and average customer review score of the hotels. If specific
hotel’s web site is clicked, customer can get further information about pictures, facilities, hotel policies and
individual review scores and comments of previous customers. Individual review score is calculated in the
following way. First, customers rate hotel quality in terms of hotel staff, services/facilities, cleanness of hotel
room, comfort and value for money. The score in these dimensions can be poor, fair, good or excellent and
counts for 1, 2, 3 and 4 points respectively. All these points are added and divided by 2 for the final
individual score. Information about hotels’ region in Paris and London is obtained from web site’s
classification. Since some hotels do not have price for single room, we used the price of standard double
room as the dependent variable. Data collection period lasts almost two and a half months in 2010. Table I
shows the descriptive statistics of the variables used in our study.
Table 1. Descriptive Statistics.
Mean
Median
Minimum
Maximum
Standard
Deviation
Number of
Observation
Paris
Number of Hotel
Booking
182.32
131
1
1331
167.01
970
Room Price Per Night
150.5
139
43
600
63.039
970
Hotel Star
2.8876
3
1
5
0.76207
970
Number of Rooms
58.508
39
9
1025
82.649
970
Customer Rating
7.5174
7.6
5.3
9.4
0.68947
970
London
Number of Hotel
Booking
268.44
174
6
5114
341.19
668
Room Price Per Night
116.97
99.99
38
581.62
59.289
668
Hotel Star
3.0853
3
0
5
1.2367
668
Number of Rooms
103.85
54
3
1054
132.95
668
Customer Rating
7.2921
7.4
4.2
9.3
0.95144
668
5. EMPRICAL MODELS AND ESTIMATION RESULTS
We used following model to find the relationship between the demand for hotels and their components:
N-1
ln(Sales)i = β0+β11ln(Price)i +β21Customer Ratingi + β31Star+
∑βk,DRegionDummyi +εi (1)
i β41ln(Size)+
i
k=1
We use log transformation of sales and price rather than sales and price levels for two reasons. First, it is
possible for us to compute elasticity of independent variables with respect to sales per room. Second, when
we use log transformation of sales and price, the relationship is closer to linear. Since we expect that hotels
with higher number of rooms have higher number of sales, we control size effect by including the number of
hotel room as an independent variable.
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Table 2. The regression result of the determinants of online hotel reservations in London.
Explanatory
Variable
constant
(1)
(2)
(3)
(4)
8.857**
(0.3598)
-1.189**
(0.08484)
8.732**
(0.3595)
-1.391**
(0.1054)
0.1586**
(0.04970)
0.4314**
(0.03704)
0.4090**
(0.03745)
8.836**
(0.4549)
-1.417**
(0.1249)
0.1552**
(0.05056)
0.01626
(0.04351)
0.4058**
(0.03841)
Number of
Observation
668
668
668
9.643**
(0.5555)
-1.5953**
(0.1361)
0.2224**
(0.05253)
0.02347
(0.04441)
0.4237**
(0.04000)
15 out of 42
dummies are
significant
668
Adjusted R2
0.2599
0.2700
0.2690
0.3131
log(Price)
Rating
Star
log(Rooms)
Regional
Dummies
Table 3. The regression result of the determinant of online hotel reservations in Paris.
Explanatory
Variable
Constant
log(Price)
(1)
(2)
(3)
(4)
7.326**
(0.3823)
-0.7583**
(0.07396)
6.813**
(0.3944)
-1.001**
(0.09020)
5.717**
(0.5103)
-0.7060**
(0.1256)
6.2055**
(0.5707)
-0.7145**
(0.1377)
0.2329**
(0.05055)
0.2418**
(0.05035)
0.2357**
(0.0516)
0.3175**
(0.04463)
-0.2051**
(0.06104)
0.3611**
(0.04624)
-0.2076**
(0.06198)
0.3386**
(0.04843)
Rating
Star
log(Size)
0.3277**
(0.04503)
Regional
Dummies
Number of
Observation
971
971
971
10 out of 20
dummies are
significant
971
Adjusted R2
0.1249
0.1428
0.1518
0.1708
We estimate the coefficients of the regression equation using OLS and Table II and III display the
regression results of equation (1) when the dependent variable is the demand for London and Paris hotels
respectively. Robust standard errors are displayed in parentheses below the coefficient estimates. One star
next to the standard errors denotes that the coefficient is significant at 5%. Two stars denote that the
coefficient is significant at 1%.
The significance of the coefficient of price variable tests the hypothesis 1. Table II and III show that, for
all of the regression specifications with different sets of explanatory variables, the coefficient of price
variable is significant at 1% and the sign of the coefficient is negative. The coefficient of price variable can
be interpreted as price elasticity as both the dependent variable(sales) and independent variable is in the log
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form. For this reason, 1% increase in the price level decreases the sales ranging from 1.18% to 1.59% in
London and ranging from 1.18% to 1.59% in Paris. Thus, the regression results validate our first hypothesis
by showing that as the price of the hotel increases, the sales of that hotel decreases.
We have also found that the coefficient of star rating is not statistically different than zero for London
hotels while the coefficient of star rating is significant at 1% significance level with a negative sign for Paris
hotels. Thus, increase in the star rating does not increase the sales of hotel rooms even after price variable is
controlled. For this reason, our second hypothesis is not supported.
Our third hypothesis asks the question of “Does increase in review scores increase the sales of hotel
rooms?” In order to confirm this hypothesis, we have to find that the coefficient of online customer rating
should be significant and sign of the coefficient should be positive. As our regression results show, our third
hypothesis for both London and Paris hotels are also supported.
6. CONCLUSION
In this paper, we collected online booking data and investigate how online review and other features of hotels
affects the hotel’s online reservation based on real sales data in this paper. By controlling hotel star price and
location information, our analysis shows that hotels increase (decrease) their sales if they have higher (lower)
online review scores. However, increase in star rating does not increase the online booking of hotels.
Furthermore, increase in price leads to decreases in online reservation. We also quantify the relationship
between independent variables (price, customer rating and star) and dependent variable (sales data) using
OLS regression method. In addition, we compare the study of Öğüt and Taş (2011) and our paper and find
that the use of the number of reviews rather than real sales data overestimate the coefficient of customer
rating and elasticity of price. The managerial implication of these results is that hotels should strive to please
customer as their future revenue depends on the satisfaction of past users. This study also guides hotel
management to forecast their sales based on online rating, price and other features of hotel.
REFERENCES
Callan R.(1998).Attributional Analysis of Customer’s hotel Selection Criteria by U.K. Grading Scheme Theories.
Journal of Travel Reseach, 36(3), 20-34.
Chevalier, J. A., & Mayzlin, D. (2006). The effect of word of mouth on sales: online book reviews. Journal of Marketing
Research, 43(3), 345–354.
Dickinger, A. & Mazanec, J. (2008): Consumers’ Preferred Criteria for Hotel Online Booking. In: Information and
Communication Technologies in Tourism, O’Connor, Höpken, Gretzel (Eds.), 244-254.
Duan, W., Gu B. & Whinston A.B. (2008). Do online reviews matter? — An empirical investigation of panel data,
Decision Support Systems, 45 (4), 1007-1016.
Liu, Y. (2006). Word-of-mouth for movies: Its dynamics and impact on box office receipts?, Journal of Marketing,
70(3), 74–89.
Marcussen C. (2008), Trends in European Internet Distribution - of Travel and Tourism Services. <
http://www.crt.dk/UK/staff/chm/trends.htm >. Accessed 23.01.2011.
Milan, R. (2007), Travel reviews - consumers are changing your brand and reputation online.
<http://www.travelindustrywire.com/article29359>. Accessed 23.01.2011.
Öğüt, H. & Taş B.K.O. (2011). The Influence of Internet Customer Reviews on the Online Sales and Prices in Hotel
Industry,Service Industries Journal, in press.
Pavlou, P. A. & Dimoka A. (2006). The Nature and Role of Feedback Text Comments in Online Marketplaces:
Implications for Trust Building, Price Premiums, and Seller Differentiation. Information Systems Research, 17(4),
391-412.
Stefansky W. (1972). Rejecting Outliers in Factorial Designs, Technometrics, 14, 469-479.
Stevenson W. J.(2007). Operations Management(9th edition). McGraw-Hill.
Vermeulen, I. E. & Seegers D.(2009). Tried and tested: The impact of online hotel reviews on consumer consideration.
Tourism Management, 30, 23-127.
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CONSUMER BEHAVIORS IN REVENUE MANAGEMENT
W.R.T AUCTION THEORY
Mariam Shafqat1 and Zeeshan Khawar Malik2
1
MBIT - Final Year
Assistant Professor
Institute of Business & Information Technology
University of the Punjab, Lahore, Pakistan
2
ABSTRACT
In this research, the effects of consumer behaviors, are implied on the auction business model for the optimal utilization
of revenues and ultimately to seeks consumer satisfaction. The research identifies the significant factors that pose a strong
impact on the auction mechanism and thus increases the consumer satisfaction. With the advancement of technology and
infrastructure, the Online Auction plays an important role in the terms of diversity of auctioning services, pricing
strategies and defining bidding rules. The research is descriptive in nature as various statistical analyses were performed
to study the effects of consumer behaviors in terms of managing their revenues effectively. The research also highlights
the current scenario of auctioning mechanism in the public and private companies indicating the growth rate of the
auction business. There are several Online Auction Portals providing C2C and B2B business opportunities to conduct eauctions. However these portals need effective improvement in terms of security and overall mechanism. Online auction
model is an effective strategy to rejuvenate the current scenario of Auction Business trends in the market.
KEYWORDS
Auction, Consumer Behaviors, Revenue Management, Bidding, Procurement, PPRA
1. INTRODUCTION
Consumer theory invokes the study of human behaviors in term of psychological and economical patterns
that drives the demand in the market. The Consumer behavior models seeks to identity the variables that
effects the decision making in terms of pricing, purchasing power, personal preferences and various
psychological needs. In the recent years, Business analysts have formulate the techniques to channelize the
consumer behavior models to forecast the market trends in order to improve the decision capabilities to set
the prices and as well as managing the revenues. Researchers go beyond the traditional theories and analysis
to seek out the variables that are difficult to measure such as heuristic as of cognitive biases as well as market
inefficiencies as the non traditional forms of behaviors. In the modern era, online auctioning has become
more widespread than ever. This generates even more exciting challenges for the researchers to understand
the consumer behaviors in auction markets. Auction theory is rich in modeling bidding and seller behaviors
in terms of revenue management. Online auctioning sites such as “Ebay, Amazon, eBid, UBid, CQ, Google
GBuy, Adword, Bidder Network, USAuctions” etc. are some of the examples of market leaders in electronic
auctioning. Auctioning sites such as “Ebay” allows customer to choose between two different methods of
bidding i.e. Single Item Auction shares both characteristic of English Auctions and a hybrid combination of
First Price and Second Price Bid Auctions.
1.1 Procurement System in Pakistan
Auction falls under the category of procurement process. Procurement system is an electronic system refers
to e-procurement, is used to manage purchasing and selling activities of the business backed by ERP system
or accountancy software. The main objective of procurement system is the advance planning and scheduling
for buying/selling of goods and services in a cost effective way. Similarly an online procurement is the
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platform for buyers to access the supplier’s offerings. For many years before the advent of the standardized
procedures and regulations for procurement, there was no check and balance for providing these services in
the public sector. As a result “PPRA” Ordinance was passed by the Govt. in 2002, and formed Public
Procurement Authority in 2004 to regulate the procedure of tendering system in Pakistan. The aim for
developing such system was to introduce the standardize procedures, rules for biding and a transparent
procurement system for the public sector organizations. These rules are applied to all procurement agencies
at federal and providential level. “PPRA” provides the services of managing, improving, governing,
transparency, accountability and quality system for public procurement. “PPRA” has the set of pre-defined
set of rules and regulations for the effective bidding mechanism for both tendering and auctioning of the
goods and services in Public sector.
Figure1. Conventional Mechanism of Auction System in Public Sector of Pakistan
1.2 Internet Auctions
Besides the manual system of auctioning in Pakistan, there are some online portals based upon B2B, B2C
and C2C business models. The web portals like “PakistanAuctions, Neelamghar.pk, Bidspk.com,
TenderServiceOnline.com, hafeezcenter.pk, cmall.com, Apnicari.com, and ShopHive” etc. are some of the
current existing examples in Pakistan. However, despite the presence on online auction, there is low % of
participants available on these systems. This is due to negative impression on the security and transparency
of the system, neither these portals provide the proper bidding rules/strategies. Online auction technology
provides several benefits as compared to the traditional auction. Internet auctions provide convenience to
break free from geographical boundaries to place their bids electronically.
The portal doesn’t only provide the flexibility to the buyer, but it also facilitates the seller, as it will be a
lot easier to find the potential buyers. The major problem is regarding the security of the online portal, since
currently the websites are not secured enough for the bidders to place their bids. The websites doesn’t
facilitate the participants to pay for the bidding items; instead the dialog box appears to contact the seller/
buyer via message. However users have negative impression on such websites as there are heavily chances of
frauds, so usually hesitate to provide their personal information on the websites regarding their credit card
information. Evidentially this is a fact that internet frauds are a common practice especially in Pakistan.
However, to mitigate such frauds; websites do subscribe third party services.
2. HYPOTHESIS
H0: There is no relationship between the variables i.e. consumer behavior, revenue management and
consumer satisfaction.
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H1: Modeling Consumer Behaviors in Auction theory will help managing revenues effectively and thus
leads to consumer satisfaction.
The main purpose of the research is to identify the key factors that affect consumer behaviors while
managing their revenues in an auction platform. Consumer behaviors play important role to identity key
elements to manage the revenues effectively while keeping the high satisfaction in an e-auction business
model. Despite the advancement of technologies and infrastructure, the auction business lacks attention and
awareness to improve the current system. There is the huge investment opportunity to the investors to
provide effective online portals to flourish trade activities in the country such as e-Bay and Amazon. So, the
research techniques and methodologies are designed and structured in a way to seek the objectivity of the
hypothesis.
3. LITERATURE REVIEW
Traditionally, auction has been used a B2B medium for selling of old scrap in the public sector, now-a-days,
B2C trend has diversified the auctioning model and trend of selling products in the consumer market.
However electronic exchanges and advancement of information technology has revived the trend of trading
items (Bajri, Hortascsu, Ghose, & Telang, 2004). Sometimes, it may happen that consumers may resale their
products rapidly with the best researched prices either at the highest prices or the best least price (Halstead &
Becherer, 2003). There is a huge impact of one resale of goods on the selling of secondary items. That is
why in US, annual sales through reselling of items have been doubled as compared to traditional selling of
items. (Dykema &hermann, 1999). Past researches have shown that consumer resale behavior may found in
different phases, it may be termed as consumer disposition behavior (Hanson & Harrlyland, 1980). However
various studies struggle to prove the true measures of auction items, whereas, in the recent researchers has
emphasized on the literature of the online auctioned items. (Ariely & Simonson, 2003). In 1982, researchers
formulated a general model in which each bidders response acts as a confidential signal to some specific
object’s value, i.e. it may be in the form of some appraisal, that may be accessible to the seller but not for the
respective bidders. (Milegrom & Weber, 1982).
Internet auction has provoked the new dimensions to review the bidding mechanism and how customers
behave in the particular bidding strategies. Amazon and e-Bay offers the customer the second price auctions
where bidders submit their reservation price and the maximum price to bid for them by proxy. The trend of
trading products using second price auction has lead rise to a tremendous growth in the revenues of
auctioneers from the last minute bidding snipping. (Roth & Ockenfels, 2000). The transaction cost, pricing
etc. effects consumer’s motives in buying and selling products from internet via auction. The interactive
bidding behaviors of the consumers are often determinants of their perceptions and attitudes toward the
products. (Lai, Shih, Chiang, & Chen, 2010). The implementation of secured online auction application
requires the system to be backed by an ERP system, which a secured authenticated user access, software
applications to make the system effective. Various auction methods should be placed to promote the online
auctioning of products and services. (Kumar & Fledman, Internet Auctions).
4. RESEARCH METHODOLOGY
The purpose of the research is to determine the consumer behavior
patterns in managing the revenues with respect to auction theory.
Since auctioning is maintained at micro level in Pakistan, there is
no as such platform for electronic auctioning. Reason thereby is
the lack of standardize system with proper platform for customer
to engage in such activity neither the available systems are secured
enough for the consumers to take an effective decision that helps
in optimizing their revenues. In relevance to such problems this
research is conducted to gather the relevant pool of data for further
analysis. The research methodology is descriptive in nature so data
is collected via Questionnaire technique, Survey will be conducted
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Figure 2. Sample Segmentation
IADIS International Conference e-Commerce 2011
from the targeted audience that includes people from different private & public sector organizations and
consumers of auction system. This research is based upon cross sectional studies, due to the time constraint
this is method is selected. The unit of analysis for designing the survey questionnaire was segmented in two
sets i.e. the middle level managers from the purchase or procurement department of the organization and the
consumers. One is the service provider and other is user of the auction system. The data was collected in a
conventional way and with the use of online survey tool i.e. “Questionpro.com”. In the convectional way; the
Questionnaire was personally handed over to the respondents, as the speed of data collection is moderate and
respondents can fill out without any ambiguity. Close ended questions are mostly selected. The segmentation
is as follows in the figure
5. RESEARCH FINDING
The research finding illustrates the data being statistically tested for the significance of the hypothesis;
various tests were applied to measure the significance, in order to find the significance between the
relationships the Pearson Correlation test was applied. The results with statistical evidence will signify the
hypothesis and the interpretation to support the association of relations. The hypothesis is based upon trivariate as the main objective of the hypothesis is to determine the relationship among three variables i.e.
consumer behaviors, revenue management, and consumer satisfaction. H0= r =0.00: There is no relationship,
association and magnitude among the variables i.e. Consumer Behaviors, Revenue Management and
Consumer Satisfaction.H1 ≠ r = 0.00: There exists a positive relationship among the variables i.e. Consumer
Behaviors, Revenue Management and Consumer Satisfaction. With the increase impact of Consumer
behaviors the revenue management increase and thus Consumer Satisfaction increases as well.
Figure 3. Correlation Matrix
Figure 4. Scatter Plotting
The above correlation matrix shows that there is strong positive relationship between CB and RM by
+.480 correlation, weak positive relationship between RM and CS by +.311correlation and very weak
positive relationship between CB and CS by +.198correlation among variables significant at 0.01 level. This
shows the dependency pattern among the variables CB>RM>CS as shown below:
CB has a strong impact on RM as compared to CS
RM has strong impact on CS as compared to CB
CB and CS are less likely poses an impact on each other
6. CONCLUSION
Online auction is one of the industry’s business models that are widely represented via online portal. With the
advancement in the technology and infrastructure, auction business is revived and various initiatives are
already taken to improve the current scenario. The slight modification in the auction business rules has a
strong impact on the consumer behaviors and thus in the expected revenues and overall satisfaction of the
consumers. Therefore business logics should be designed in accordance consumer behavior patterns for
attaining the optimum revenues at both sides (seller and bidder).
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Figure 5. Current e-Auction Mechanism
Figure 6. Business Integration
Figure 7. Recommended Model
The effective auction business model should be constructed in such a way that it reduces the gap between
seller and buyers on a single platform linked by networks of suppliers and retailers, secured by ESCROW
services, engaged with TCS services for tracking and for authenticity website should be linked with NADRA
(detecting NIC from DB) and PTA (detecting mobile numbers) to provide regulatory assistance. For the ease
of services, Consumers participated in online portals should be provided with the support applications on
their mobile sets such as ibid an application developed by “Mobilink” for its Blackberry users. The
awareness of such portals should be created in order to get a better response from the consumers.
The Reverse auction is very favorable business strategy in the industry, various telecommunication
companies such as “Mobilink”, Telenor and even Radio one “fm91” has used such strategy to earn revenues.
This strategy should be adopted on the online auction business model, both seller and website upon agreed
ratio can earn commission and generating more pool of customers. This highlights that, consumer behaviors
should be taken into account while developing the effective online auction model to attain the prospect
consumers for the optimization of revenues and to revitalize the emerging trends of auction business in the
market.
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Nowlis, S. M., & Simoson, I. (1997). Attribute Task Compatibility as a Determinant of Consumer Preception Rversals.
Journal of Marketing Research , 205-218.
Roth, A. E., & Ockenfels, A. (2000). Last Minute Bidding and Rules for Ending Second Price Auction. Evidence from Ebay and Amazon Auction on Internet , 11.
Adomavicius, G., Curley, S. P., & Gupta, A. (n.d.). User Preceptions in Continuous Combinatorial Auction. Effect of
Information Feedback, 20.
Ariely, D., & Simonson, I. (2003). Buying, Bidding, Playing or Competition? Value Assesment and Decision Dynamics
in Online Journals .
Beam, Segev, & Reiley, L. (1999). The future of e-markets:Multi-Dimensional market mechanism. Journals of
Economics, 142.
Becherer, R. C., & Halestead, D. (2004). Charcteristics and internet marketing strategiesog online auction sellers. Internet
Marketing and Advertisment.
Bhattachriya, A. (2009). Using 'Smart' Pricing to increase prices and the Consumer Satisfaction.
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IMPACT OF VALUE PROPOSITION OF E-COMMERCE BY
FIRMS ON CUSTOMERS’ ADOPTABILITY
Aitzaz Ali1 and Zeeshan Khawar Malik2
1
MBIT Student, 2Assistant Professor
Institute of Business & Information Technology, University of the Punjab
Lahore, Pakistan
ABSTRACT
This document covers different aspects of perception about E-commerce in Pakistan in the current scenario. The research
involves the assessment of perceptions of working professional in various organizations regarding E-commerce value
propositions and also the perceptions and attitude of general public to adopt E-commerce practices in Pakistan. Different
statistical approaches are used to measure the potential of E-commerce implementation and adoption in Pakistan and it is
inferred from the findings that, E-commerce value propositions with respect to different dimensions can increase the
adoptability of E-commerce and online trading by their customers. There are few concerns at both ends, which can hinder
the common practice of online trading. The plausible implications and challenges are identified and recommendations are
made accordingly.
KEYWORDS
E-commerce, Electronic Commerce, Adoption, Pakistan
1. INTRODUCTION
The rapid increase of information technology and blending of various communication technologies has
virtually created an impact on business processes. E-commerce represents an innovative mode of conducting
business transactions, that may include buying & selling, or exchange of products, services, and information
between different parties through information exchange networks like the Internet, intranet, and extranet.
According to Dou & Chou (2002), “E-commerce provides the business world with functions like electronic
delivery of information, products, services, or payments; automation of business transactions and workflow;
reduction in service costs while improving the quality of goods and increasing the speed of service delivery;
and the use of online services. Furthermore, E-commerce is rapidly reshaping the marketing domain and
many of its traditional practices, such as business-to-business transactions.”
In today’s world of hard-hitting competition, technology-driven firms are looking to engage a successful
E-commerce strategy that can make people to adopt the online mode of buying. According to Chatterjee,
Grewal & Sambamurthy (2002), “The potential of the Internet and web technologies is globally
acknowledged. While some firms have benefited by adopting E-commerce, others have not been successful.”
Organizations always look to create value for themselves in terms of high profits, perpetual growth and
unprecedented market share. E-commerce can play an integral part in this regard.
E-commerce is altering the business processes and consequently it is shifting the organizational structure.
E-commerce is becoming the only option for many organizations, as businesses become more fascinated in
expanding their operations online. In doing so, they need to assess whether E-commerce can bring drastic
change in their business processes. How can this change bring out value for themselves in terms of growth,
revenue, flexibility, cost-effectiveness and most important of all, how will their customers perceive it.
According to Litter and Hudson (2004), “The development of e-commerce requires a series of essential
activities in technical infrastructure, legal and regulatory issues, awareness, training and education, private
sector protection, and government supports to provide conditions for economic players such as consumers
and businesses to play a key role in the application of E-commerce.” Revenue generation through this
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effective sales channel, Cost savings, Flexibility and increased business process efficiencies are other
considerable potential impacts of E-commerce which have been recognized by main industry players.
This kind of research work has been done in the past but has never been done in perspective of Pakistan.
The reason for choosing this topic is to assess the perception of the working professionals regarding Ecommerce being beneficial for a company and also to assess the perception of consumers about their
adoption of E-commerce. The idea is to see whether if a company is proposing value of E-commerce for
itself to devise a successful E-commerce strategy, then how much it can pursue the customer to adopt it.
In a research by Abbasi (2007), “Popularity of using the ICT tools in economy is appropriate to business
environment such as political stability, tax regulations and openness to trade and investment. Another
prerequisite for the expansion of e-commerce is traders and consumers' adoption along with social and
cultural infrastructure such as high-skilled labor and electronic literacy. Legal and political environment
including the Internet regulations, new businesses, facilitating, protecting private and intellectual properties,
investment and government support of technology infrastructure are all essential for development and
promotion of e-commerce.”
In developed countries, organizations have developed successful E-commerce strategies to attract
customers. However, most of the under-developed countries have been unable to create awareness among
organizations regarding E-commerce. According to Swami and Seleka (2005), “Developing countries face
the lack of infrastructure, economic and social-political framework for the development of e-commerce.
However, some developing countries have initiated strategies to achieve an appropriate level of E-commerce
development.”
Pakistan has been facing the same problem in this regard. According to a research by Kemal (1998) on Ecommerce implementations by exporters for international trade, “One of the major reasons for stagnation of
Pakistani exports has been the failure to explore new markets and to diversify their exports. E-commerce, by
providing easy access to product specification and prices can be instrumental to increasing their share in
international trade. While the electronic commerce is on the rise in the world and it provides vast
opportunities to Pakistan to diversify its export products and destinations, it has made very little use of the
electronic commerce. Therefore, the financial, legal, and market issues still unresolved in this regard need to
be addressed on an urgent basis.”
Another reason for Organizations hesitancy to implement E-commerce is the lack of knowledge and trust
of the management. In a research by Mirchandani and Motwani (2001), “Their findings reveal that the
relevant adoption included enthusiasm of the top management, compatibility of the e-commerce with the
work of the company, perception about the relative advantage being gained from the e-commerce, and
knowledge of the computers by the employees.”
According to Wong (2003), “The most common of the perceived barriers for not adopting e-commerce
were security and cost, followed by lack of readiness on customer's as well as supplier's end.” “Researchers
(Ho & Wu, 1999; Liang & Huang, 1998; Lohse & Spiller, 1998; Kim et al., 2001; Muthitacharoen, 1999)
tested different service factors concerning online shopping attitudes and behavior, including customer
communication channels, ease of vendor contact, response to customer needs, accessibility of sales people,
reliability of the purchasing process, timeliness of orders, availability of personalized services, ease of return
and refunds, fraud, delivery (speed and tracking), transaction costs, peripheral costs, and promotion.”
2. RESEARCH FINDINGS
2.1 Research Methodology
The purpose of my research was to assess the perception of working professionals about E-commerce
implementation and what do they think about its value proposition dimensions. Also to get an insight of
educated people, who know how to use internet, about the impact that firms creates when it offers Ecommerce services and if it makes them go for online trading.
For this purpose, I decided to take 2 surveys. First, survey was taken from professionals working in
different firms in Pakistan to check their perception regarding E-commerce value propositions and secondly,
from the general public to assess their preferences regarding adoption of E-commerce.
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After preparing questionnaires, I made contacts with 100 working professionals from various
organizations in Lahore to get the questionnaires for Value proposition filled.. The concentration was to have
responses from Top level as well as Middle level management in 50-50 ratio.
Then, Questionnaire for Adoption of E-commerce was also distributed to people. These respondents
included students and working professionals. Surveys were distributed according to 50-50 ratio of gender.
2.2 Research Findings
The research findings demonstrate the data being statistically tested for the significance of the hypothesis.
Various tests were applied in order to find the significance between the two variables. Pearson Correlation
Test and Regression Analysis were applied. The results with statistical evidence will signify the hypothesis
and the interpretation to support the association of relations.
H0 = There is no relationship between Value proposition of E-commerce and adoptability by customers.
H1 = There is relationship between Value proposition of E-commerce and adoptability by customers.
Table 1. Correlation between Variables
Value Proposition
of E-commerce
Adoption
by Customers
1
.264**
Value Proposition of
E-commerce
Pearson Correlation
N
100
100
Adoption by Customers
Pearson Correlation
.264**
1
Sig. (2-tailed)
.008
N
100
Sig. (2-tailed)
.008
100
** Correlation is significant at the 0.01 level (2-tailed).
The relationship is significant but its intensity is somewhat weak. From the value in the Table 1, it is seen
that Value proposition of E-commerce by firms is moderately related to the adoption by Customers. Thus, H1
is accepted i.e. there is relationship between Value proposition of E-commerce and adoptability by
customers.
The dimensions of E-commerce value propositions like revenue generation, flexibility, convenience,
proper implementation of security modules for data safety and integrity, awareness programs for marketing
of its E-commerce website can somewhat impact of the adoptability of this unique mode of online buying
and selling.
To check the intensity of this impact, Regression analysis of the two variables has been done.
Linear Regression Equation:
Y= a + b (X)
Y=Dependent Variable= Adoptability by Customer
a = intercept = 2.544
b = slope = 0.331
X = Independent Variable = Mean of Value proposition of E-commerce by Firms
Calculation:
Y = a + b(X)
Y = 2.544 + 0.331 (3.94)
Y = 3.84
Regression Equation gives out a value of 3.84 Adoptability by Customers (Dependent Variable) with
respect to certain Standard Deviation. It shows that, as far as Adoption of E-commerce by customers is
concerned, Value proposition of E-commerce by firms keeps a weak hold on the adoption by customers and
the results are inclined towards an agreeable opinion.
The scatter plot in the Figure 1 below shows that there is a positive relationship between the two
variables. It can be inferred that these variables have a weak positive relation as there are many outliers but
the curve line has enough dots adjacent to it to be recognized as weak positive relation.
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Figure 1. Scatter Plot between variables
3. CONCLUSION
The sample which was used in the Executives survey included companies mostly from the Lahore region and
a few from Islamabad. This might lead to an unclear view about the whole population and this sample cannot
be a suitable representative of the whole country.
It was a difficult task to contact professionals in different organizations and make sure that they fill out
the questionnaire for the purpose of research. Executives were approached formally and through professional
social networking site, LinkedIn. In both samples, for Executives and for General Public, some people who
knew Internet usage but did not have knowledge of E-commerce and its importance, so I had to elaborate for
them as well before they could fill out the questionnaire.
The Internet and the global information infrastructure are fast gaining worldwide prominence because the
private sector is driving it. E-commerce is somewhat neglected in Pakistan by the companies. The decision
makers in the companies do not perceive it as a necessity and they might just not think of it as important.
However a lot of top level employees consider E-commerce a very good strategy in terms of business.
The study concluded that there is a tendency for E-commerce to flourish and grow in Pakistan.
Companies deem it as a prospective domain in terms of growth. Employees consider website existence
valuable for a company. It can become an effective sales channel to capture market share as well as identify
unexplored markets. The value E-commerce offer to the business can be perpetual provided that adoptions to
technology changes are kept intact. This might entail revenue generation through a cost cutting and time
efficient sales channel. The flexibility it offers in terms of positive infrastructure change through bridging
communication gaps between the key stakeholders, i.e. customers, business partners, etc.
As people are more inclined towards the use of technology now-a-days, businesses can greatly benefit
from it. The survey from customers implied that people find the online mode of trading very convenient in
terms of time and effort saving. This convenience can be in terms of ubiquity, easy access to information,
availability of the products or services on one click, variety for consumers, price transparency, etc. Also its
time-effectiveness, through rapid search of products and services and ordering and shipment through one
click, it surely can be one of the most time saving modes of shopping.
It is also observed from the study that Companies are somewhat concerned about factors regarding Ecommerce that were identified as hindrance in implementing E-commerce. It was found that technology
illiteracy is a big block in E-commerce. It will take a lot of time in increasing the literacy rate of the country
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and more time will be required to give awareness to the people about the E-Commerce. Also that the
companies and customers are pretty much concerned about the security of the transactional data, the personal
information of the customers and bank or credit card details, low PC and internet penetration, people prefer
to use traditional ways of business enjoying personal contacts and mode of payments. Another major
concern is government’s support regarding E-commerce practices. Apart from that, customers also keep in
mind the market reputation and trustworthiness of the E-commerce portals of the companies. The
Government should provide a safe and secure environment; both businesses and consumers must be assured
of security and safety in cyberspace transactions. For this purpose, proper implementation of cyber laws must
be done. There should be a legal framework devised for its growth and proper implementation.
It can be inferred from the research findings that, people in Pakistan are slowly getting aware of the fact
that business on the internet is less costly and are more beneficial. It can be said that as long as companies
and businesses are implementing E-commerce and proposing value for themselves through E-commerce, it
can also make the people to go for this electronic mode of payments. People will embrace E-commerce by
desire or by force as more and more companies are looking to propose value through E-commerce.
REFERENCES
Abbasi, A (2007), E-Commerce Development in Iran, Information Technology Policy Program, College of Engineering,
Seoul National University, Seoul, Korea, Retrieved from http://www.webology.ir/2007/v4n4/a49.html
Chatterjee, D., Grewal, R., & Sambamurthy, V. (2002). "Shaping up for E-Commerce: Institutional Enablers of the
Organizational Assimilation of Web Technologies." MIS Quarterly, 26(2), 65-89.
Ho, C., & Wu, W. (1999), Antecedents of consumer satisfaction on the Internet: an empirical study of online shopping,.
Proceedings of the 32nd Hawaii International Conference on System Sciencesm,
Iqbal, A. (2009), Future of E-commerce in Pakistan, EzineArticles.com Expert Author, Retrieved from
http://ezinearticles.com/?Future-of-E-Commerce-in-Pakistan&id=1974082.
Kemal, A. R., (1998) Electronic commerce and international trade of Pakistan, Retrieved from
http://findarticles.com/p/articles/mi_6788/is_4_37/ai_n28724652/
Kim, D., Song, Y., Braynov, S., & Rao, H. (2001). A B-to-C trust model for on-line exchange. In Proceedings of
Americas Conference on Information Systems, paper 153
Littler, K. & Hudson, R.. (2004), The impact of depolarization on e-commerce development in the distribution of
regulated financial products. International Journal of Information Management, 24(4), 283-293
Liang, T., & Huang, J. (1998). An empirical study on consumer acceptance of products in electronic markets: a
transaction cost model. Decision Support Systems, 24(4), 29-43.
Lohse, G. L., & Spiller, P. (1998). Electronic shopping,. Communications of ACM 41(7), 81-87.
Mirchandani, A. A., Motwani, J., (2001) Understanding small business electronic commerce adoption: an empirical
analysis. Journal of Computer Information Systems, 70-73
Ranganathan, C & Ganapathy, S. (2002). Key dimensions of business-to-consumer web sites. Information &
Management 39, 465-475.
Swami, B. & Seleka, G.G. (2005), Problems, prospects and development of e-commerce- case study of South African
development communities, IADIS International Conference E-Commerce, 379-384.
Wong, P. (2003), Global and National factors affecting e-commerce diffusion in Singapore. The Information Society, 19,
19-32,
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CYBERCRIMES AND THE BRAZILILIAN ATTEMPT TO
DEVELOP LEGISLATION
Maria Eugênia Finkelstein
Bachelor of Law at the University of São Paulo; Master in Commercial Law at Pontifícia Universidade Católica de São
Paulo; PHD in Commercial Law at the Law School of the University of São Paulo, Professor at the Law School of
Pontifícia Universidade Católica de São Paulo and FAAP, Coordinator of the Post-Graduation specialization course in
Corporate Law at Fundação Getúlio Vargas. Visiting Professor at Instituto de Empresa de Madrid
ABSTRACT
The purpose of this text is to briefly analyze the impact of the commercial exploitation of the internet and the
development of a new way to perpetrate crimes, usually denominated cybercimes. It considers the importance of the
development of specific legal texts as well as analyses the development of such matter in Brazil.
KEYWORDS
Internet, cybercrimes, legislation, Brazil
1. INTRODUCTION
It can be said, without doubt, that e-commerce is in full expansion worldwide. According to Internet World
Statsi there are currently 1,966,514,816 Internet users worldwide, and every one of them is a potential
consumer of products and services offered therein. It is estimated that in Brazil, there are approximately 70
million users, a fact that certainly deserves attention from legislators, jurists, and judges. Of course not only
the Internet has developed. Sectors such as media and manufacturing have also experienced an amazing
development and caused impact on society. The essential differences between information technology and
the other areas of knowledge are contemporaneity, transnationality, dynamics of the computer revolution, and
socialization of informationii. However, due to the novelty of this issue, there is a notorious lacking of
satisfactory regulation, which in simple terms means that the cyber phenomenon has an influence on the
mind of man, but man is not sure how to solve many of the conflicts that may arise from its use.
Thus, the digital era represents a revolution in society. The economic activity, as we know it today, is
known to have begun with the so-called Industrial Revolution (Huberman, L.,1986, p. 55), occurred in the
18th century in England. This boom in economic activity brought about some negative consequences, as the
result of the lack of regulation to stop the disordered growth. Now, it seems clear that man was not prepared
to identify the consequences of the growth and development of industrial activity, and it is also seems clear
that man currently cannot notice all changes generated by the digital era and electronic culture. We might be
experiencing a true information technology revolution, or a post-industrial revolution.
Despite the fact that a new way to perpetrate crime was being developed by the usage of computer
technology, it has to be stressed that property was still being physically stolen, individuals were still at risk of
personal assault and sexual harassments were still happening. However, it cannot be denied that the Internet
has created new means of committing crimes, which started to be denominated by the media as cybercrimes,
an expression that although is highly accepted by the public in general, does not always encounters a
correspondence at the legal texts.
Several countries began to regulate these new fields of Law, and other fields need to be resized, such as
Criminal Law, which began to regulate, for example, consumer crimes, crimes against economic activity,
crimes against the economic system, etc. Similarly, Brazil has regulated such areas, but with a certain delay
in relation to social expectations. Now, however, with this new digital revolution, Brazil faces new needs for
urgent changes.
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Any way, it is uncontroversial that the new phenomenon of cybercrimes need to be studied by the entire
academic community. And so this is true that many congresses, seminars, workshops and journals are
dedicated to the study of such a theme. After all, a criminal, hidden by the anonymity the Web provides, may
feel even more encouraged to commit crimes of this kind. Although it is believed that the personal computer
virus first appeared in the 80’s, it is to be mentioned that the world community only notice their existence
after the famous case of the Melissa virus, which, in 1999, infected millions of computersiii. However, after
2001, it is to be noticed that the conduct of cybercriminals changed dramatically. In 2001 the United States
Department of Justice defined computer crimes as “any violation of criminal law that involved the knowledge
of computer technology for its perpetration, investigation or prosecution”. So, cybercrimes apply for the
following conducts: digital piracy, cyberstalking, e.mail piracy, theft of digital information (which leads to
identity theft and bank fraud) and many other conducts some of them yet to be created.
Absolutely nobody is free from this new kind of crime. Microsoft itself, one of the world’s largest
companies, has suffered criminal cyberattacksiv.
2. THE NEED FOR REGULATION
The commercial use of the Internet, in 1993, gave rise to criminal practices, using means previously
unknown. Even nowadays, tracking the agents that use the Internet is very hard and need specific trainings.
It is a fact, however, that Cybercrimes “require the adoption of new, cybercrime specific laws because the
conduct involved in the commission of and/or the ‘ harms’ inflicted by target cybercrimes do not fit into
traditional criminal law” (BRENNER, S., 2010, p. 73). A 2001 case perfectly illustrates this claim. In such
year the computers of two casinos were accessed by hackers and the poker and video slot machine were
altered. For just a few hours, gamers at those casinos gained almost 2 million dollars. The firs impediment
for the characterization of such conduct as theft was the fact that they did not profit with their conduct. The
second, obviously, was the fact that this conduct was not theft, since the hackers did not took possession of
the casino machinery. The same applies to fraud, since there was no benefit for the hackers. So, if not theft
or fraud, what would this conduct characterize? The answer is that the hackers shall be prosecuted under the
federal computer crime statute. However, it is to be mentioned that such hackers were never identified. This
simple example demonstrates that sometimes, the conduct perpetrated by the usage of computers in any case
cannot be considered as a regular crime known before the internet (BRENNER, S., 2010, p. 73). Spams are
another example for the necessity of the creation of specific legislation.
3. THE BRAZILIAN SITUATION
Brazil is considered one of the leading country in electronic criminal activityv. Unfortunately, however, as it
will be seen further on, there are not even specific laws to inhibit such practice. On top of that, the police is
not sufficiently equipped yetvi. Many are the types of attack reported on a daily basisvii.
The possibility of third parties accessing personal passwords or electronic signatures may be disastrous.
The attempt to regulate electronic signatures through Presidential Order No. 2.200/01 is an indication of the
awareness that the disordered growth of e-commerce leads to conflicts, which have already been settled by
many Courts in Brazil. Undoubtedly there is an increasing concern with making data transmission on the
Internet safer, for example by using the encryption technique. However, legal principles such as “nullen
crimen sine legeviii” have benefited hackers, who, living in a lawless environment, hide in the anonymity
and commit crimes (such as intellectual property infringement) without suffering any penalties.
The issue of the need for regulation on cybercrimes is controversial, since there are two different
positions regarding the regulation of the Internet. On one hand, some consider the cyberspace as a separate
territory calling for a separate jurisdiction. This is the point of view supported by Lorenzetti (2000, p. 227), a
member of the Argentinean Supreme Court. Others (L. Bochurberg, 1999, p. 221) believe the Internet should
be self-regulated in the way it is designed.
In the Brazilian legal system, laws are based on territorial principles, which conflicts with the
transnational character of the Internet. There are already domestic laws, though none of them of a penal
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nature, regarding the Internet, but their effects are limited to the jurisdiction covered by the Brazilian
sovereignty only. In a global context, it is necessary that Law and Information Technology facilitate
negotiations between the nations, based on cross-cultural standards which are adequate to juridical
rationalism.
Thus, the global character of the Internet and the international possibilities of cybercrimes are points to be
considered. Due to this character, any legislative change should be implemented by several countries,
alternatively international efforts designed to harmonize practices should be promoted. The greatest mistake
we could make would be to attempt to solve problems created by the Internet thinking individually and
regionally, without considering an international context. After all, the Internet is not an issue of purely local
scope, but globalix, due to the transnational nature of the Internet. For this reason, it is once more clear that
law will have to adapt to the new social digital context of the world-wide computer network to face the
challenge of the transnationality of cyberspace.
Accordingly, the first steps seem to be have been taken by means of the standardization of laws supported
by international institutions such as UNCITRAL, OECD, and the European Communityx. These
international attempts end up being felt nationallyxi. Many countries regulated this issue nationallyxii. Let us
take Brazil as an example. There are various legislative bills on cybercrimes in progressxiii. Some of them
are based on laws of other countries.
4. CYBER CRIMES
The difficulty in studying computer crimes begins with defining them (LICKS, O. B.; ARAÚJO JR, J. M.,
1994, pp 90-95).However, we believe that, in almost all definitions we have found, the Internet is put as the
means of consecution, and not itself as a new conduct (MARTÍN, R. M. M., 2001, p. 22). Notwithstanding,
new laws designed to prevent judges from resorting to extensive methods of interpretation to convict a
criminal act are welcome. Besides, this is the position adopted by the United Nations Organizations
(GOODMAN, M. and BRENNER, S., 2004).
We are contrary to those who believe that the computer society brought about new legal assets that need
new criminal concepts to protect them (SERRA, C. and STRANO, M., 1997, p. 21). What would those new
assets be? Information was already protected, as well as privacy. Property and financial damages caused by
digital attacks are the same as those protected from traditional attacks. Illegal copies of software have always
been protectedxiv. Information too, through copyrights.
It is true that society has changed a lot in its form of relationship. In the past, those who did not have any
criminal tendency can now hide behind the anonymity offered by the Web and attempt criminal conducts,
which undoubtedly is a very serious issue. It is evident that the Web makes it easier for potential offenders to
violate the law without major conscience crises. The growth in the occurrences of cybercrimes evidences
such statement, such as the conducts of Cybertrespass (WALL, D., 2004, p. 3) or hackering/cracking, Cyber
deception/ thefts (WALL, D., 2004, p. 4) and Cyberpiracy (WALL, D., 2004, p. 5). Only concerning fraud, a
crime that exploded in the cyberspace, many specific types deserve mention.
Notwithstanding, the fact that the Web facilitates the occurrence of criminal conducts alonexv deserves
special attention from legislators because the Internet is world-famous as a lawless land, and unfortunately
impunity occurs more often with virtual crimes, among other reasons, because of the difficulty of tracking
their perpetrators.
Thus, our view is that the criminal legislation does not really need to be changed, but the same cannot be
said of the procedural legislation, the creation of a more specialized and prepared police force, or the need for
acceptance of electronic documents as evidence. Impunity must be fought! And if new laws facilitate
punishment, then we are totally favorable to them.
REFERENCES
BOCHURBERG, L., Internet et Commerce Électronique, Paris: Dalloz, 1999.
BRENNER, Susan W., Cybercrime: criminal threats from cyberspace. California: Greenwood, 2010.
GHOSH, Sumit; TURRINI, Elliot. Cybercrimes: A Multidisciplinary Analysis, Berlin-Heildelberg: Springer, 2010.
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GOODMAN, M. and BRENNER, S. The Emerging Consensus on Criminal Conduct in Cyberspace at
http://www.lawtechjournal.com on February 3, 2004.
HUBERMAN, L. História da riqueza do homem. 21st ed. Rio de Janeiro: Guanabara, 1986.
LICKS, O. B.; ARAÚJO JR, J. M., Aspectos Penais dos Crimes Informáticos no Brasil, Revista do Ministério Público
do Rio Grande do Sul, Porto Alegre, N. 33, 1994
LORENZETTI, R. L. Comercio Electrónico, Buenos Aires: Abeledo Perrot, 2000.
MARTÍN, R. M. M. Delicuencia Informatica y Derecho Penal, Madrid: Edisofer, 2001.
SERRA, C. and STRANO, M. Nuove Frontier della Criminalitá – La Criminalitá Tecnologica – Milano: Giuffrè, 1997.
WALL, D. Crime and the internet: Cybercrimes and Cyberfears, New York: Routledge, 2004.
i
Internet World Stats 2010, http://www.internet worldstats.com/stats.htm in March, 2011.
Interview with Umberto Eco in the magazine Veja Digital of December 2000, page 11. “For the first time, mankind has an enormous
amount of information available to him at a low cost. In the past, this information was costly, involved buying books, exploring
libraries. Now, from the middle of Africa, if you are connected, you may have access to Latin philosophical texts. It is quite a change.”
iii
The main difficulty in such investigation was to define the amount of damages caused, as, by that time, the penalty was somewhat
correlate to damage caused or intended. So, the damage was amounted between 77 million dollars and 350 million dollars. By the end
of the investigation and due to the plea of guilty provided by the criminal himself the damage was amounted in 80 million dollars and
David Smith, the creator of the Melissa virus was sentenced to 20-month imprisonment. GHOSH, Sumit; TURRINI, Elliot.
Cybercrimes: A Multidisciplinary Analysis, Berlin-Heildelberg: Springer, 2010, p. 3
iv
Employee Richard Gregg was arrested on the charge of unlawfully marketing 5,436 programs from the company, with a total property
loss of US$ 17 million.
v
To see a graphic, please consult http://www.cert.br/stats/incidentes/
vi
the Attorney General’s Office of the State of Rio de Janeiro has the so-called Electronic Investigation coordinated by attorney Romero
Lyra. In the same state, there is also a Police Office specialized in Computer Crime Enforcement.
vii
to see a graphic, please consult http://www.cert.br/stats/incidentes/.
ii
x
The European Union set a directive recommending how the authorities should act in case of computer crimes. The project website is
www.ctose.org.
xi
European Community - Convention on Cybercrime on November 23, 2001, in Budapest, set guidelines recommending that evidence
of the occurrence of cybercrimes should be accepted in court to increase punishment of this type of crime
Argentina - Argentina has approved the so called “The Data Protection Act” which includes punishment to specific kinds of
unauthorized access (hacking); Australia- There is a Federal Legislation called The Cybercrime Act 2001, which amends the law
relating to computer offences, and for other purposes. The following offences are set forth: unauthorized modification of data to cause
impairment; unauthorized impairment of data held in a computer disk and other means of data storage; possession or control of data
with intent to commit a computer offence; and producing, supplying or obtaining data with intent to commit a computer offence.;
Austria - There is a specific law called Strafrechtsanderungsgesetz, approved in 2002; Belgium - In November 2000 the Belgian
Parliament adopted new articles in the Criminal Code on computer crime, in effect as from February 13, 2001. The four main problems
of computer forgery, computer fraud, hacking and sabotage were henceforth considered criminal offences; Botswana - The Government
Computer Bureau has been assigned to formulate the National ICT policy. Together with the ICT policy it has been agreed that the ICT
legislation issues should be addressed; Canada - The Canadian Criminal Code suffered amendments to foreseen cybercrimes in 2003;
Chile – Chile has Law Nr. 19.223 on Automated Data Processing Crimes, published on June 7, 1993; China - In 1997 many
Cybercrime issues are covered in laws and regulations that refers to Internet related crimes. The penalties foreseen varies from three to
five years of imprisonment. It is important to stress that only 10% of the telephone lines in China have full Internet access. However,
there is an extensive legislation on this regard. Hong Kong has different regulations regarding cybercrimes conducts, which are dealt by
the Telecommunication Ordinance; Denmark - A Bill on Information Technology crimes was presented to the Danish Parliament on
November 5, 2003. However, some provisions of the current penal Code may be applicable to cybercrimes; France - The Penal Code, in
effect since March 1, 1993 sets forth that attacks on systems for automated data processing are classified as crimes. Penalties vary from
one to three years of imprisonment and fines; Germany - The German Penal Code foresees the crime of data espionage, alteration of
data and computer sabotage. Penalties vary from two to three years of imprisonment and fines. The attempt of the last crime shall be
punished; Greece - Law Nr. 1805/1988 applies to cybercrimes. This law has reformed some dispositions of the Penal Code with regard
to cybercrimes and supplemented others; Hungary - The Hungarian Penal Code foresees the criminal conduct for breaching computer
systems and computer data, compromising or defrauding the integrity of the computer protection system or device; Iceland - The Penal
Code of Iceland foresees that penalties shall apply to persons who unlawfully obtain access to data or programs stored as data; Republic
of Ireland - The Criminal Justice (Theft and Fraud Offences) Act 2001 foresees the Unlawful use of computers as offence. The Criminal
Damages Act 1991 foresee as an offence the unauthorized accessing of data; Israel - Israel approved the Computers Law of 1995..
Penalties vary from three to five years of imprisonmen; Italy - The Italian Penal Code foresees the following as crimes: the unauthorized
access into a computer or telecommunication systems, the illegal possession and diffusion of access codes to computer or
telecommunication systems, the diffusion of programs aimed to damage or to interrupt a computer system. Penalties vary from one to
five years of imprisonment and fines; Japan - In effect from February 3, 2000, the Japanese Law Nr. 128 of 1999 has extensive
provisions regarding cybercrimes such as prohibition of acts of unauthorized computer access, prohibition of acts of facilitating
unauthorized computer access, damage to Documents in Public Use and Damage to Documents in Private Use. Maximum penalty is
five years of imprisonment; Korea - Korea has some dispositions in its Law concerning cybercrimes, such as invalidity of public
documents, destruction of public goods, false preparation or alteration of public electromagnetic records, falsification or alteration of
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private electromagnetic records, violation of secrecy, fraud by the use of computer, etc and destruction and damage of property). Also,
in Korea, the Act on Promotion of Information and Communications Network Utilization and Information;
Malaysia - Malaysia has the Computer Crimes Act of 1997, which specifically deal with cybercrimes; Mexico - The Mexican Penal
Code contains specific dispositions concerning cybercrimes; Netherlands - The Criminal Code of the Netherlands applies to
cybercrimes; Peru - The Penal Code of Peru has a section with provisions regarding cybercrimes; Poland - The Penal Code of Poland
contains dispositions specifically applicable to cybercrimes. The maximum penalty is eight years of imprisonment; Portugal - Since
1991 Portugal has a law designed to inhibit the practice of cybercrimes. It is the so-called Computer Crime Law; Singapore Singapore has a Computer Misuse Act, which foresees the following offences: unauthorized access to computer material, access with
intent to commit or facilitate commission of offence, unauthorized modification of computer material, unauthorized use or interception
of computer service, unauthorized obstruction of use of computer, unauthorized disclosure of access code and enhanced punishment for
offences involving protected computers. The maximum penalty is 20 years of imprisonment; South Africa - South Africa has approved
the Electronic Communications and Transactions Act of July 31 2002 (Act No. 25, 2002) related to cybercrimes, such as unauthorized
access to, interception of or interference with data. The maximum penalty is 5 years of imprisonment; Sweden - The Penal Code of
Sweden has specific dispositions which apply to cybercrimes; Switzerland - The Penal Code of Switzerland foresees the following
offences: unauthorized access to data processing systems and damage to data. The maximum penalty is five years of imprisonment;
United Kingdom - The United Kingdom has the Computer Misuse Act of 1990, which foresees the unauthorized access to computer
material as a criminal offence. The maximum penalty is five years of imprisonment; United States - After the terrorist attacks of
September 11, 2001, the United States began to be seriously concerned about the occurrence of cybercrimes, since the press widely
broadcast that the terrorists used electronic means to plan the terrorist attacks that shocked the world; Thus, the United States is
undoubtedly the country that has stood out the most in passing laws to fight cybercrimes. Remarkable statutes include: - USAPA – USA
Patriotic Act – a statute passed in late 2001 that intends to expedite the arrest and prosecution of those responsible for electronic
invasions. This statute provides that some hacker invasions are treated as terrorist acts and those responsible are subject to extremely
serious penalties. Punishable conducts include the publication of information that could harm the United States and technical
information that could lead to terrorism and even the transmission of other people’s personal information. - FISA – Foreign Intelligence
Surveillance Act – provides the monitoring of special foreign agents acting in the United States and facilitates the intervention of U.S.
authorities in international cases; CSEA – Cybersecurity Enhancement Act – which imposes 10 years of imprisonment as the minimum
sentence for electronic crimes and immediate punishment on anyone who accesses information without permission to do so.
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This principle is a basis of the Brazilian criminal law and means that in case there is no specific law, there is no crime.
xiii
Bill No. 4833/98 by Representative Paulo Paim, defines the crime of broadcasting information that induces or promote discrimination
or prejudice on the basis of race, color, ethnics, religion, or national origin on the Internet or other public access networks; Bill No.
84/99 by Representative Luiz Piauhylino, deals with crimes relating to information technology, applicable penalties, and other
provisions; Bill No. 76/00 by Senator Renan Calheiros, defines and classifies computer crimes; Bill No. 1070/95 by Representative
Ildemar Kussler, deals with crimes relating to the distribution of pornographic material by means of computers; Bill No. 101/99 by
Representative Maria Elvira, deals with child and adolescent sexual exploitation, and imposes four to ten years of imprisonment on the
establishment and user committing sexual exploitation.
xiv
xv
Article 184 of the Brazilian Penal Code, as amended by Law No. 8.635 and the Brazilian Software Law.
And the increasing number of pedophilia cases is no doubt the best example.
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MULTICHANNEL RETAILING STRATEGIES IN THE
JAPANESE-STYLE DISTRIBUTION SYSTEM: THE CASE
OF KINOKUNIYA’S MULTICHANNEL STRATEGIES
Hyemi Bang
Doctoral Student, Graduate School of Business, Osaka City University, JAPAN
Sugimoto 3-3-138, Sumiyoshi Osaka, 558-8585, Japan
ABSTRACT
The world of retailing in 2010 is a very different place compared with 1999.The advent of the Internet has added another
dimension to the way that merchandise reaches consumers. Integrating this technology with traditional retailing methods
has become the dominant retail model that students of retailing should all be aware of Multi-Channel Retailing identifies
and explains the underlying principles of e-retailing and its relationship with conventional retail methods. Most important,
retailers’wares must be accessible by whatever means customers want – in a retail store, by phone, in a mail order catalog,
from handheld devices, or on the Web. Indeed, a growing segment of shoppers now expects to reach a single retailer
through all possible channels.
The purpose of this paper is to give an overview of what it is about, covering the drivers, benefits, challenges and
organizational changes needed to get there in the Japanese-style distribution system.
KEYWORDS
Multichannel retailing, Japanese-style distribution system, multichannel shopping
1. INTRODUCTION
Multichannel retailing is the set of activities involved in selling merchandise or services to consumers
through more than one channel. Multichannel retailers dominate today’s retail landscape. While there are
many benefits of operating multiple channels, these retailers also face many challenges. Multichannel
retailing is the set of activities involved in selling merchandise or services to consumers through more than
one channel (Levy and Weitz 2009). The adoption of Multichannel Retailing presents numerous implications
to the marketing context, enlarging the complexity of marketing decisions. Retail organizations are facing
many new challenges and opportunities in the multichannel retailing environment. There are also many
questions to be answered by marketing researchers and industry practitioners. If this complexity in making
decisions is proven, will there be advantages in adopting multichannel retailing? The most appealing
approach found in the studies exploits exactly the factors which took the retailers to implement a
multichannel strategy: cost reduction in transactions, reduced growth of demand, competitive strategy and
differentiation, changing in the consumer’s behavior, increase of efficiency in distribution, concentration of
supply e convergence of channels roles (Lason2001;Stone ,Hobbs and Khaleeli2002;Souza and
Serrentino2002;). Especially, There are some special features in the Japanese distribution system. One of the
important features is that to have a multi-stage structure where two or more parties from manufacturer to
retailers are connected vertically. When we consider more specifically the integration among channels, we
discover that there are a still few empiric studies that exploit its synergies in the adoption of a multichannel
retailing strategy (Simons, Steinfield and Bouwman 2002).
As the distribution industry would be influenced the most by the electronic commerce, the impact of
electronic commerce on the distribution industry has been analyzed. The objectives of the research are as
follows; 1) an analysis of impact of electronic commerce on the structure of the distribution industry and on
the transaction pattern, 2) development of competitive strategies to improve the global competitiveness of the
domestic (JAPAN) distribution industry.
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2. CONCEPTUAL BACKGROUND
2.1 Definition of Multichannel Retail Concept
Multichannel retailing can be defined as an opportunity given to the consumer to obtain the same product
from the same retailer by multiple purchase channels. The multichannel marketing strategies attempt to foster
the consumers' behavior to be multichannel (Nicholson, Clarke and Blakemore 2002). Although some authors
identify up to ten kinds of channels (Stone, Hobbs and Khaleeli 2002;), the greatest part of the studies is
focused basically on physical stores, printed catalogues and commercial websites on the internet. To
Eastingwood and Coelho (2003) those companies that obtain part of their sales from 2 different channels, are
classified as having adopted the multichannel system, while those with 100% of sales proceeding from one
channel, adopt the only one channel model
2.2 Motivations for Retailers to Operate Multiple Channels
Ultimately, the search for improved financial performance motivates traditional singlechannel
retailers—store based, catalog, TV home shopping, or Internet-based retailers—to evolve into multichannel
operators. While the decision to sell through additional channels prompts concerns about cannibalization and
negative spillover (Deleersnyder et al. 2002; Falk et al. 2007), research indicates that operating multiple
channels can have a positive effect on financial performance (Geyskens, Gielens, and Dekimpe 2002). Some
sources of the improved financial performance for multichannel retailers are: (1) low-cost access to new
markets, (2)increased customer satisfaction and loyalty, and (3) creation of a strategic advantage.
2.3 Constraints for Expanding to Multichannel
While many retailers have become multichannel operators, some have intentionally shunned this strategy so
far (e.g. Amazon.com). There are three key reasons that have kept these retailers from pursuing multichannel:
(1) consumer access to broadband Internet service, (2) operational difficulties of integration, and (3) costs of
multichannel offering (Zhang et al 2009).
3. RESEARCH METHODOLOGY
3.1 Focus
All the research will be based on bookstores in Japan. The analysis unit will be centered on Japanese
companies of the retail sector that have their business focused on the "books" category and that have
introduced multichannel strategies, which means to say that they use at least two channels for consumers to
acquire their products.
3.2 Contents and Scope of the Research
The analysis has been done based on the classification of electronic commerce as business-to-business,
business-to-consumer and internal electronic commerce within an organization. The empirical investigation
has been limited to the retailers which seem to be influenced most by the wide spread of the electronic
commerce. The contents of the research are as follows;(1)investigation of the current status and issues of the
JAPANESE distribution industry(2)development of architectural framework of electronic commerce by
which the distribution industry may be able to utilize to develop electronic commerce
opportunities(3)analysis of the impact of electronic commerce on the distribution industry influenced by the
electronic market(4)the competitors in the distribution industry through the analysis of the industry structure,
and its implications.
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3.3 Japanese-style Distribution System
There are some special features in the Japanese distribution system. One of the important features is that to
have a multi-stage structure where two or more parties from manufacturer to retailers are connected
vertically.
3.3.1 Retailers
In Japan, there are a large number of retailers, though the majority of them are doing small scale business.
One possible reason is that consumers tend to go shopping frequently but buy little at a time. They not only
live in a small house without enough storage space but also prioritize freshness of products. In response to
this consumers’ behavior, the retailer, too, want to avoid having a large stock. They themselves do not want
expensive inventory cost either. Thus, they place small orders frequently(Tajima and Harada 1997).
3.3.2 Wholesalers
Japan has far more wholesalers than foreign countries have. Since manufacturers were often small scale
producers, each of them was involved in just a part of production process, and the wholesalers bridged many
parts of the process. This is why there are many wholesalers (ESRI 1991). The situation where a large
number of various wholesalers exist suits Japanese small scale retail. Under restrictions of the management
ability of dealings, the wholesalers reduce the number of dealings in distribution process and save dealing
costs (Tajima and Harada 1997).
3.3.3 Policy
The price control system is one of the business practices in which manufacturers determine their products’
retail price. A manufacturer set the resale price by topping up profits each party earns in the process of
distribution. In other words, manufacturers decide how much margin to be paid to wholesale stores or even
retail stores. On this basis, they negotiate for the delivery price to retailers and wholesalers (Miwa &
Nishimura 1991). Although this price setting system can be also found in many countries, what makes
Japanese one unique is that it is practiced extensively. Not only it brings successful branding, which results in
monopolization in market but also it defines the highest price as suggested retail price and the lowest price,
with the returned-goods system and the rebate system. Since the dealings on the basis of this price were used
to be observed, it became a factor of enhancement of resale price maintenance system.
In Japan, the returned-goods system is widely observed from an apparel industry to that of fiber, books,
and medical supplies. For instance, in the United States, goods are hardly returned to manufacturers only
because they remained unsold. But in Japan, the business practice where each contractor conducts continuous
dealings is considered important, and thus the returned-goods system can serve to share a risk of dead stock.
Because of minimization of the risk, retailers such as department stores may take advantage of
returned-goods system to reduce dead stock, and as a result, the system works as sales promotion (Ishihara
and Yahagi 2004).
3.4 Empiric Research
Documents – among the various documents mentioned to collect evidence, newspaper clippings and other
articles published in mass media will be used, including the websites of selected bookstores. The catalogue
will also be added when the company uses it to sell products.
Interviews –is one of the most important sources of case study information. Although it is also the survey
method, the interviews are essential sources of case study information.
The two methods of data collecting (sites and interviews), with the addition of information in newspapers,
magazines and catalogues, will be revised and analyzed together, in a way that the findings of the case study
will be based on the convergence of information derived from different sources, and not from quantitative or
qualitative data separately.
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4. DISCUSSION & CONCLUSIONS
It is generally thought that research on multi-channel retailing needs to be developed more substantially. Like
I have pointed out in this paper, even just the discussion on “multichannel retailing”is difficult to treat as a
simple concept. It is already being discussed by dividing it into several types, but nonetheless because
multi-channel retailing still remains a complicated issue, disseminating it into several patterns will be a
indispensable topic within its related discussions.
Of course, as I have shown, there is a steady emerging amount of research on dividing multi-channel
retailing into several patterns but apparently it is necessary that the current situation of multi-channel
strategies of large scale retailing and small and midsize retailing businesses should be elaborated upon further
using a new framework on how the multi-channel retailing can be properly divided into certain patterns.
Moreover, the biggest issue relating to the multi-channel retailing matter pertains to how we can increase
the synergy between channels and it is in this area that the current amount of literature is still lacking. It is
research on the multi-channel shoppers. I have shown in this paper that the focus on research of
multi-channel retailing has currently shifted from the retailing of providers to the client consumers. In order
to elaborate on the strategies of multi-channel retailing it is absolutely necessary to analyze the consumers
who are the clients and in a way this change can be regarded as a natural course.
REFERENCES
Barsh, Joanna; Crawford Chris,and Grosso(2000). “How e-tailing can rise from the ashes”. McKinsey Quarterly; 3, 98-12
Deleersnyder, Barbara, Inge Geyskens, Katrijn Gielens, and Marnik G. Dekimpe (2002), “How Cannibalistic Is the
Internet Channel? A Study of the Newspaper Industry in the United Kingdom and The Netherlands,” International
Journal of Research in Marketing, 19(December), 337-348.
Doherty, N.F. Ellis-Chadwick, F, and HART, C.A(1999) “Cyber retailing in the UK: the potential of the Internet as a
Retail channel”. International Journal of Retail and Distribution Management, 27(1) 22-39
Falk, Tomas, Jeroen Schepers, Maik Hammerschmidt, and Hans Bauer (2007), “IdentifyingCross-Channel Dissynergies
for Multichannel Service Providers,” Journal of ServiceResearch, 10 (November), 143-160.
Geyskens, Inge, Katrijn Gielens, and Marnik G. Dekimpe (2002), “The Market Valuation ofInternet Channel Additions,”
Journal of Marketing, 66 (2), 102–119.
Levy, Michael and Barton A. Weitz (2009), Retailing Management, 7th Edition. New York,N.Y.: ThMcGraw-Hills/Irwin
Companies, Inc.
Simons,Luuk P.A.; Luuk P.A.; Steinfield,Charles(2002) “Strategic positioning of the Web in a multi-channel market
approach.” Internet Research: Electronic Networking Applications and Policy, 12(4) 339-347
Steinfield C, Bouwman H and Adelaar T (2002b) “The dynamics of click and mortar e-commerce: Opportunities and
management strategies” International Journal of Electronic Commerce, 7(1): 93-119
Stone, M., et al. (2002), “Multichannel customer management: The benefits and challenges.” Journal of Database of
Marketing 10(1): 39-52.
Zhang, Jie and Michel Wedel (2009), “The Effectiveness of Customized Promotions in Onlineand Offline Stores,”
Journal of Marketing Research, 46 (2), 190-206.
Ishihara, T and Yahagi,T(2004.) Nihon no ryutsu 100 nen (100 years ofJapanese distribution), Yuhikaku.
Tajima, Y and Harada,H.(1997) Zeminaru ryutsu nyumon (seminars on the introduction to distribution problem), Nihon
Keizai Shinbun Sha.
Yahagi, T (1996) Gendai ryutsu (Modern distribution), Yuhikaku aruma.
Yahagi, T (2003) Chugoku ajia no kouri (Retail innovation in China and Asia), Nihon Keizai Shinbun Sha.
Yamaoka, Y (1990). Keshohin gyokai (Cosmetic industry), Kyoikusha sinsho.
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DEVELOPING COMMUNICATION PRACTICES BY
COMPUTER AND VIDEO-CONFERENCING SYSTEMS: A
CASE STUDY OF A FINNISH RETAIL BANK
Johanna Ahola and Helena Ahola
University of Oulu, Department of Anthropology and Art Studies, Cultural Anthropology, Pentti Kaiteran katu 1, Oulu,
Finland, Oulu University of Applied Sciences, School of Business and Information Management, Teuvo Pakkalan katu
19, Oulu, Finland
ABSTRACT
Retail banks are on the way towards real-time online banking independent of time and place enabled by the Internet. The
purpose of this paper is to get more understanding on online communication within e-retail banking contexts on issues
such as how to develop communication practices by using computer and video-conferencing systems, and the challenges
met when applying these kinds of tools for internal use in a bank. Insights based on online communication research, and a
case study of the experiences from a bank’s internal project are provided. Computer and video-conferencing systems
offer opportunities to banking business, because online collaborations save time, money and cause less environmental
impact than that of face-to-face meetings. In the case project the challenges were related to communication culture,
network capacity, technologies, and support. The project was, however, well planned and organized to meet these
challenges. Results of the project were encouraging. Although this project was to develop the bank’s internal processes, it
was also a first step in a process towards online real-time retail banking. This case of banking was successful, but it
showed that launching new media needs planning, training and support, and finally it may change culture. More research
is suggested on cultural changes, social media’s role in business use, and also semiotics viewpoints.
KEYWORDS
e-retail banking, online communication, computer and video-conferencing systems, media richness, media syncronicity
1. INTRODUCTION
Retail banks are on the way towards real-time online banking independent of time and place enabled by the
Internet. It is a challenge to provide excellent service and at the same time save costs in a very competitive
situation as retail banks are nowadays. In addition, internal efficiency of the organization is a prerequisite for
success. The purpose of this paper is to get more understanding on online communication within e-retail
banking contexts. In this paper the research questions are the following:
• How a retail bank can develop its communication practices by using computer and video-conferencing
systems?
• What kind of challenges are expected and met when applying these kinds of tools for internal use in a
bank?
These research questions are answered by providing insights based on online communication research,
and an exploratory, authentic case study of the experiences from a bank’s internal project of online
communications. The case is based on data obtained through participant observations and documents during
the year of 2010, when one of the authors was involved in this kind of a project as a development manager in
the bank.
In the research context of retail banking it is vital that communication practices can be developed without
sacrificing service quality and customer satisfaction. Using the internet for banking and customer relationship
management cannot substitute other service channels (Durkin et al. 2008). Multichannel business model for
serving customers has been largely adopted within banking business. Practically all the bank's customers
(97%) display some form of multi-channel behavior according to Cortiñas and Villanueva (2009). When
building trust in e-banking traditional service quality in branches is a necessary condition for the promotion
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of e-banking (Yap, Wong, Loh and Bak 2010).Thus offline and online banking support each other. Internet
banking service quality factors have been discovered in various studies. For example, Rod, Ashill, Shao and
Carruthers (2009) found that even in the absence of face-to-face interactions, reliability, responsiveness,
tangibles and empathy are still important to customers. Also Loonam and O’Loughlin (2008) found that due
to the remote form of the online encounter, many traditional service quality attributes were found to be
important. Despite all efforts to rationalize banking business, still human interaction is crucial in service
business (Herington and Weaven 2009). Also social perspectives have been found important for establishing
and maintaining desired relationships with customers (Park, Chung and Rutherford, 2011).
2. LITERATURE REVIEW
Media differ from each other in their characteristics (see Media Richness Theory by Daft and Lengel, 1986,
and Media Synchronicity Theory by Dennis and Valacich, 1999). Media richness is based on feedback
capability, the communication channels utilized, language variety, and personal focus. The more a medium
incorporates these characteristics, the richer it is (Daft and Lengel, 1986). Generally the richness level is
higher in oral than in written media and in synchronous rather than in asynchronous media. Dennis and
Valacich (1999) suggest that to successfully utilize media to accomplish a task, the most effective media
choices must consider the mix of two basic communication processes required for performing any type of
task. These processes focus on information transmission (conveying information) and information processing
(convergence on shared meaning). For example, face-to-face communications are highly synchronous,
whereas e-mail and e-bulletin-boards are of low synchronicity.
Concerning channels strategy recent research emphasizes the differences in various target groups and
situations. Danaher and Rossiter (2009) compare the traditional channels of television, radio and mail, as well
as the new digital channels of the Internet (e-mail) and cellular phones (SMS). They found that, although email is well established and widely used, the traditional channels of television, radio, newspapers and direct
mail retain their attributes of trust and reliability of information that make them still preferred by consumers.
Business receivers are more accepting of e-mail marketing communications than are consumers.
Nevertheless, face-to-face communication (discussions, seminars, visits to productions sites ) is still often
found to be the best way to communicate within business context (see e.g. Karjaluoto 2010).
Based on experiences of online collaborations in facilitating transdisciplinary sustainable development
research teams through online collaboration Dale, Newman, and Ling (2010) found out that in order for
online collaboration to be successful the employees must be very organized and have strong facilitation
skills. The geographical location of team members is not important, and participation costs are lower, and the
elimination of travel time is significant. In addition, electronic communications technologies can give
marginalized people a voice.
The influence of organizational context (competitive versus cooperative) and introductory meeting
communication medium (face-to-face versus electronic) on the development of trust and collaborative
behaviors of dyads communicating electronically introductory face-to-face interaction plays a more
important role in facilitating the development of trust and collaboration in a computer-mediated environment
when the context is competitive (see Hill, Bartol, Tesluk and Langa 2009). This has to be taken into account
in planning electronic communication.
Management’s role and culture is crucial in launching electronic channels into organizations. Digital
communication methods have changed how employees communicate and interact with their managers.
Mackenzie (2010) argues that traditionally the ways and behaviors of managers had developed and thrived
within face-to-face work environments, but as computer-mediated technologies continue to change the
boundaries of the business community, permit alternative worksites to increase, and the traditional workday
to disappear, the role of the manager has changed. Jackson and Philip (2010) suggest that an
incremental/evolutionary approach with ad-hoc improvisation made to culture and technology over time and
space makes for an effective techno-change solution. In general, worklife is going towards “anytime,
anywhere”. For example, homeworkers are inclined to remain connected to work at “anytime, anywhere” via
mobile phones” irrespective of time or location (Lal and Dwivedi 2010).
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3. A CASE STUDY OF USING COMPUTER AND VIDEOCONFERENCING SYSTEMS
The context for studying online communication tools was a Finnish retail bank. New communication tools
for internal use, such as project work, management and coaching, and sales support, were taken into use in
2010. The central unit of the focal bank offered technical solutions, and acted as a service center for its local
member banks. The bank’s organization is very scattered throughout Finland in terms of their branch offices
and headquarters. Distances between regions, and even distances within a city like Helsinki are fairly long.
The central bank’s service development group launched computer and video-conferencing systems during
the year of 2010. Technology used in this operation consisted of 47 video-conferencing systems for training
and educational purposes, about 670 SharePoint-workspaces for projects and other purposes. Altogether,
about 10000 Ms Office Communicator Server users were involved (messages, voip calls, webinars etc).
The purpose of this project was to improve productivity of knowledge work by making the use of
information, and the ways of interaction more efficient. This was expected to bring immediate cost savings
and more efficient use of knowhow and expertise.
Activities of the project were planned professionally. Interaction and cooperation was promoted by using
new communication tools. Also a new communication strategy was created together by the Information
Management and the Sales Support. Some principles were agreed upon. For example, it was necessary to
make sure that the capacity of data networks for increasing use was sufficient. People were asked to
communicate by their own names (a cultural principle). As to travelling the main principle was that the first
meetings were held face-to-face and the rest online. Microphones and webcams were installed, and bigger
meeting rooms were equipped with computer and video-conferencing systems. Network files were replaced
by virtual workspaces. Further, everyone was to be reachable by instant messenging systems, and internal
calls were made by computers. Recommendations were given concerning the channel for different
communication situations (See Table 1).
Table 1. Recommendations for communication channels
Media/tool
Richness/synchronicity
To be used in
Messinging/ Ms Office
Communicator
Net meeting/Ms Office
Communicator
Video negotiation/HP
and Tandberg
equipment
Virtual workspace/Ms
Sharepoint
Intranet of the bank
low richness/ medium
synchronicity
high richness/ high
synchronicity
high richness/ high
synchronicity
group discussions
Webcasting/
service
from GoodMood
medium richness/ low
synchronicity
medium richness/ low
synchronicity
medium richness/ low
synchronicity
meetings (2-20
persons)
seminars, events
(20-60 persons)
project and group
work
internal
communication
seminars, events,
conferences (over
100 persons)
Support
from
internal
team
internal
team
external
support
internal
team
internal
team
external
support
Instead of
phone call, text message, email
travelling, phone call, text
message
travelling
network disk
e-mail, travelling
e-mail, printed media
travelling
Challenges were expected, one of them being the corporate culture. Management needs understanding of
the nature of knowledge work and the possibilities provided by new technology. There were also many other
issues to discuss on, such as confidence to open communication by one’s own name, network capacity,
installations, tools, and applications. Also previous experiences might reduce the interest in a new way of
working. Adequate support for the way of working online was a critical issue. The tools, training and support
were launched, the principles were put into practice, and technical things were made to work. It was
important to raise the users’ awareness, to motivate them, and to add their enthusiasm at the new way of
working. Information was offered in internal journals. A special day for launching these tools was organized.
Continuous visibility was arranged by posters, and a video trailer was made to raise interest. Support was
available.
Results of the project were encouraging. One example, “Management update event” in spring, 2010,
gathered over 550 participants from 20 districts via computer and video-conferencing systems. The whole
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concept of the event changed due to the new technology. It was possible to have local hosts for the event.
Votes were possible by text messages. Webcasts had been made just in case everything does not work.
Another big national event was “Management forum online” in summer, 2010. In this forum, the central bank
and the managers of the biggest cooperative banks met each other online from their own workplace or
conference room. This forum was very quickly organized, but well planned. Authentic feedback of the forum
was “a good way to bring up current and important issues, cost efficient and easy, adds opportunities to meet
each other more often”. These tools also offered an online meeting place for discussions, materials, and a
communication channel for supporting the organizational change of the central bank. The experiences from
this project made us also think that not only travelling costs can be reduced but also the characteristics of new
media can change communication culture and improve the quality of communication, and thus service
quality.
4. CONCLUSIONS AND DISCUSSION
Based on previous research and literature we can make some conclusions concerning banking business and
online communication. In developing communication practices a retail bank has to take into account the
realities of banking business, the service quality required and keeping its customers satisfied. Using the
internet for banking and customer relationship management cannot substitute other marketing channels.
Human interactions as well as social perspectives have been found important for establishing and maintaining
desired relationships with customers. Face-to-face communication and human interaction play a key role in
building trust.
Another viewpoint is the trend in communication tools and practices, which offer opportunities and
challenges also to banking business. Online collaborations save time, money and cause less environmental
impact than that of face-to-face meetings. They require organizing and strong facilitation skills. The
geographical location is not important, and participation costs are lower, and the elimination of travel time is
significant. Organizational context has to be taken into account in planning electronic communication to
develop of trust and collaborative behaviors. Management’s role and culture is crucial in launching electronic
channels into organizations. Digital communication methods have changed how employees communicate and
interact with their managers.
In the project of online communications tools the challenges were related to communication culture,
network capacity, technologies, and support. The project was well planned and organized to meet these
challenges. Results and experiences of the project were encouraging. The whole concept of the management
event organized has changed due to the new technology. Although this project was to develop the bank’s
internal processes, it was also a first step in a process towards online real-time retail banking. The next step
would be business customers, and finally consumers. Then it would be a key issue to develop communication
practices online without sacrificing service quality and customer satisfaction.
Theories of media richness and media synchronicity suggest that some media are richer and more
efficient than others and preferred by different target groups. Each medium has its advantages, but when to
use it depends on situations and contexts. This case of banking was successful, but showed that launching
new media needs planning, training and support. It may at the end change management culture. Managers are
encouraged to use online tools, but they have to believe in these tools and technologies to be able to sell these
ideas to their organization and finally to their customers.
This paper offered an illustrative example of one bank’s first steps towards virtual working. More
research is needed on cultural changes which may have started to develop and the consequences it has on the
bank’s operations. From communication perspective, besides media richness and synchronicity, it would be
worth studying emerging social media’s role in business use. It would also be useful to study cultural sign
processes, analogy, metaphor, signs and symbols (semiotics) to get more understanding of the new online
communication media.
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A CHOREOGRAPHY LANGUAGE FOR BUSINESS
COLLABORATION: FROM ELECTRONIC
CONTRACTING TO INTER-ORGANIZATIONAL
ENACTMENT
Alex Norta
University of Helsinki, Department of Computer Science
Gustaf Hällströmin katu 2b, FI-00014, Helsinki, Finland
ABSTRACT
Automating business collaboration with means of service-oriented and cloud computing, promises significant efficiency
and effectiveness increases. The development of available choreography languages for automating inter-organizationally
connected business processes, is typically technology driven and focuses less on suitability for business collaboration. A
choreography describes the observable collaboration behavior between two or many business partners. Suitability means
that choreography languages comprise concepts to allow the formulation of real-world business-collaboration scenarios
in many perspectives. On the other hand, a choreography language must be expressive for automated setup and
enactment. Expressiveness means, the constructs of a choreography language have semantic clarity for ensuring uniform
enactment behavior by application systems. To address the gap, the paper applies a method for choreography-language
development with high suitability and expressiveness features for which we use a running example. The presented
choreography language has been applied in case studies with industry, may be totally or partially adopted for
choreographing business collaboration, and the language development approach is replicable for exploring strengths and
weaknesses of other existing choreography languages.
KEYWORDS
Choreography language, inter-organizational, B2B, eSourcing, business process, suitability, expressiveness.
1. INTRODUCTION
With the emergence of new automation paradigms such as service-oriented computing (SOC) and cloud
computing (CC), the way companies collaborate with each other experiences significant changes. SOC
(Allen et al., 2006) comprises the creation of automation logic in the form of web services. In CC
(Antonopoulos and Gillam, 2010), the Internet is used to access web-based applications, web services, and IT
infrastructure as a service. Web services (Alonso et al., 2004) are an important vehicle for enabling
organizations to cooperate with each other by inter-organizationally linking business processes (Norta and
Eshuis, 2010) with choreography languages for the purpose of electronic outsourcing.
With respect to existing choreography languages, the most notable are versions of the Business Process
Execution Language such as AbstractBPEL (Jordan et al., 2007a) and BPEL4Chor (Decker et al., 2007),Web
Services Choreography Description Language (WS-CDL) (Jordan et al., 2007b), Business Process Modeling
Notation (BPMN) (Decker and Barros, 2008; White et al., 2006) Let’s Dance (Zaha et al., 2006), ebXML
BPSS (ebXML Technical Architecture Project Team, 2001) and more recently, the Business Choreography
Language (BCL) (Motal et al., 2009). However, not only existing choreography languages but also other
XML-based languages for SOC have not been adopted by industry as expected. A reason is the approach for
language development that is often driven by politics and technical concerns resulting in suitability and
expressiveness deficiencies. This paper fills this gap with answering the question how to design a
choreography language that comprises concepts and properties relevant for enabling electronic business
collaboration.
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The structure of the paper simultaneously reveals the method we use for the development of eSML and is
as follows. Section 2 presents a business-collaboration model that evolves from case studies in the research
project called CrossWork (Grefen et al., 2009;Mehandjiev and Grefen, 2010), namely eSourcing (Norta,
2007; Norta and Eshuis, 2010; Norta and Grefen, 2007a). In Section 3, the collaboration model is further
explored in a pattern-based way (Norta, 2007; Norta and Grefen, 2007b) with the objective of generating the
essential concepts needed for eSML to gain a high degree of business-collaboration suitability. Next,
assuming the control-flow perspective is dominant for automating business collaborations, we present in
Section 4 how high expressiveness is achieved in eSML, which is essential for, e.g., business-collaboration
verification, or consistent enactment behavior of different application systems. Section 5 presents the highlevel structure and concepts contained in eSML. Finally, Section 6 concludes this paper and discusses future
work.
2. BUSINESS COLLABORATION MODEL
In the EU research project CrossWork (Grefen et al., 2009), observing business collaborations of industry
partners reveals characteristic features. An original equipment manufacturer (OEM) organizes the creation of
value in an in-house business process that is decomposable into different perspectives, e.g., control flow of
tasks, information flow, personnel management, allocation of production resources, and so on.
(a)
(b)
Figure 1. (a) eSourcing in three-level business-process. (b) An overview of an eSML instantiation
Figure 1(a) depicts conceptually a three-level model as part of an eSourcing example (Norta, 2007; Norta
and Eshuis, 2010; Norta and Grefen, 2007a). The three-level model is instrumental for not forcing
collaborating parties into connecting their information infrastructure directly. The processes in Figure 1(a)
depict the control-flow perspective of the eSourcing concept that focuses on structurally harmonizing on an
external level the intra-organizational business processes of a service consuming and one or many service
providing organizations into a business collaboration. Important elements of eSourcing are the support of
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different visibility levels of corporate process details for the collaborating counterpart and flexible
mechanisms for service monitoring and information exchange.
The very top and bottom of Figure 1(a), show the internal levels of the service consumer and provider
where processes are directly enactable by legacy systems, e.g., by workflow management systems. Using
internal levels caters towards a heterogeneous system environment. Furthermore, processes on a conceptual
level are independent from infrastructure and collaboration specifics. In the center of Figure 1(a), the external
level stretches across the respective domains of eSourcing parties where structural process matching takes
place and for which eSML is applicable. Either collaborating counterparties project only interfaces, or parts,
or all of the respective conceptual-level processes to the external level for performing business-process
matching (Norta and Eshuis, 2010). A contractual consensus between collaborating parties comes into
existence when the projected processes are matched externally, i.e., when they are equal. Not projected
process parts remain opaque to the collaborating counterpart. The dashed monitoring arcs (Norta and Grefen,
2007a) in Figure 1(a) that connect the conceptual business processes via the external level into a
configuration, depict monitorability constructs that allow a flexible observation of service-provision progress
for the service consumer.
3. SUITABILITY EXPLORATION
For ensuring that eSML comprises concepts to allow the formulation of real-world business-collaboration in
relevant perspectives like control-flow, data-flow, resources and so on, the case-study findings culminating in
the eSourcing model of Figure 1(a), require more exploration. Contracts are the basis for business
collaboration between organizations and thus, taking pre-existing work about contract automation (Angelov,
2006) into account for the eSML suitability exploration, we pursue a pattern-based method.
In response to Section 2, the foundation of eSML is the XML-based language ECML (Electronic
Contracting Markup Language) (Angelov, 2006). A contract is a legally enforceable agreement, in which two
or more parties commit to certain obligations in return for certain rights (Reinecke et al., 1989). Contracts are
instruments for organizing business collaborations. Electronic contracting aims at using information
technologies to significantly improve the efficiency and effectiveness of paper contracting, allowing
companies to support newly emerging business paradigms, while still being legally protected.
Although ECML permits business-process definitions, it lacks a clear collaboration-model support as
proposed by eSourcing, which we resolve with an extension into eSML. Inheriting concepts from ECML, at
the highest abstraction, a contract in eSML answers three conceptual questions i.e., the Who, Where, and
What question (Angelov, 2006). The Who-answer concerns the actors that participate in the contract
establishment and enactment. The Where-answer specifies the context of a contract, e.g., the legal context,
business context. The What-answer models the exchanged values, rules, and the exchange processes.
The chosen approach for suitability exploration uses an established perspective taxonomy from which we
extract a set of conceptually formulated patterns (Norta, 2007). The patterns are the basis for deducing the
constructs that become part of a suitable choreography language. The pattern summaries below are due to
page limitation but we refer to (Norta and Grefen, 2007a) for detailed pattern specifications and to (Norta,
2007) for collaborating counterparty-interaction patterns during setup.
4. EXPRESSIVENESS EXPLORATION
Semantic clarity for choreography-language constructs, ensures that different application systems create
uniform enactment behavior. For eSML, we consider control-flow in business collaborations as the best
explored perspective based on which the expressiveness may be expanded for other perspectives. We adopt
XRL (eXchangable Routing Language) (Aalst and Kumar, 2003) for realizing semantically clear controlflow, which is contained in the schema definition (Norta, 2007) of eSML for the purpose of specifying the
contractual spheres of a service provider and one or many service consumers.
XRL is an instance-based workflow language that uses XML for the representation of process definitions
and Petri nets for its semantics. The definition of XRL (Aalst and Kumar, 2003) contains as routing elements
a catalog of formalized control-flow patterns (Aalst et al., 2000; Kiepuszewski et al., 2003) that result in
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strong control-flow expressiveness. These routing elements are equipped with Petri-net semantics (Aalst et
al., 2001), namely, every routing element stands for an equivalent workflow net (WF-net) (Aalst, 1997; Aalst,
1998; Ellis and Nutt, 1993) that can be connected with other routing elements into a bigger WF-net. The
syntax of XRL is completely specified in a DTD and schema definition (Aalst and Kumar, 2003; Norta,
2007).
5. REALIZATION IN ESML
After explaining the approach for developing eSML through exploring methodologically the suitability and
expressiveness prerequisites, we show the high-level structure of the business-collaboration language. As
explained earlier, eSML uses parts of the ECML-schema (Angelov, 2006) as a foundation. Figure 1(b)
reflects this fact by considering an entire eSML instance as a contract between collaborating parties and by
structuring the eSML content into the blocks Who, Where, and What, as explained in Section 3. We refer to
(Norta, 2007) for elaborate code examples and detailed models.
The bold typed eSML-definitions in Figure 1(b) are extensions and modifications that are not part of the
ECML foundation. In the Who-block, extensions for eSML are the resource definition and the data definition.
In the What-block, the XRL adoption permits the use of control-flow patterns for business-process definitions
that have semantic clarity. However, extensions have taken place for adopting the conjoinment nodes and for
linking to the resource- and data-definition sections of eSML that are both based on respective pattern
collections (Russell et al., 2004a; Russell et al., 2004b).
The life-cycle-mapping block is for specifying semantic equivalence between, firstly, the lifecycles stages
of the inter-organizationally harmonized business processes, and secondly, for the life-cycle stages of tasks
from the opposing domains. To establish a semantic equivalence relationship, the second part of the mapping
block focuses on the mapping of task labels in the active_node_label_mapping tag. The
monitorability section of Figure 1(b) influences how much of the enactment phase is perceived by the service
consumer. For the complete eSML-schema, examples and evaluations, we refer to a CrossWork case study
(Mehandjiev and Grefen, 2010, Norta, 2007.
6. CONCLUSION
This paper applies a method for developing a choreography language for electronic business collaboration.
eSML results from this method where case study-based suitability and expressiveness exploration ensures the
language comprises essential collaboration concepts with a foundation for semantic clarity. We use a subset
of ECML as a base language for eSML. Assuming that the control-flow perspective in a business
collaboration is best explored, the expressiveness in eSML we address by adopting WF-net based semantics,
which is verifiable with tool support. In an application with industry, eSML demonstrates its ability to
specify elaborate business collaborations better than other industry standards. Limitations for eSML result
from mapping from an external collaboration level with eSML to inhouse conceptual business-process levels
using industry standards.
For future work, we plan to carry out case studies with eSML in research projects about designing cloudcomputing infrastructures for mobile business collaboration. In those studies, we want to address
expressiveness extensions into more business-collaboration perspectives than control-flow and make eSML
suitable for mobile business services.
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Aalst,W. (1997). Verification ofWorkflow Nets. In Az´ema, P. and Balbo, G., editors, Application and Theory of Petri
Nets 1997, volume 1248 of Lecture Notes in Computer Science, pages 407–426. Springer-Verlag, Berlin.
Aalst,W. (1998). The Application of PetriNets toWorkflow Management. The Journal of Circuits, Systems and
Computers, 8(1):21–66.
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Aalst, W., Hofstede, A., Kiepuszewski, B., and Barros, A. Workflow Patterns Home Page.
http://www.workflowpatterns.com.
Aalst, W., Hofstede, A., Kiepuszewski, B., and Barros, A. (2000). Advanced Workflow Patterns. In Etzion, O. and
Scheuermann, P., editors, 7th International Conference on Cooperative Information Systems (CoopIS 2000), volume
1901 of Lecture Notes in Computer Science, pages 18–29. Springer-Verlag, Berlin.
Aalst, W. and Kumar, A. (2003). XML Based Schema Definition for Support of Inter-organizational Workflow.
Information Systems Research, 14(1):23–47.
Aalst, W., Verbeek, H., and Kumar, A. (2001). XRL/-Woflan: Verification of an XML/Petri-net based language for interorganizational workflows (Best paper award). In Altinkemer, K. and Chari, K., editors, Proceedings of the 6th
Informs Conference on Information Systems and Technology (CIST-2001), pages 30–45. Informs, Linthicum, MD.
Allen, P., Higgins, S., McRae, P., and Schlamann, H., editors (2006). Service Orientation: Winning Strategies and Best
Practices. CAMBRIDGE UNIVERSITY PRESS.
Antonopoulos, N. and Gillam, L., editors (2010). Cloud Computing: Principles, Systems and Application. Springer.
Alonso, G., Casati, F., Kuno, H., and Machiraju., V. (2004). Web Services: Concepts, Architectures and Applications.
Springer-Verlag Berlin Heidelberg.
Angelov, S. (2006). Foundations of B2B Electronic Contracting. Dissertation, Technology University Eindhoven,
Faculty of Technology Management, Information Systems Department.
Decker, G. and Barros, A. (2008). Interaction modeling using BPMN. In BPM’07: Proceedings of the 2007 international
conference on Business process management, pages 208–219, Berlin, Heidelberg. Springer-Verlag.
Decker, G., Kopp, O., Leymann, F., and Weske, M. (2007). BPEL4Chor: Extending BPEL for Modeling Choreographies.
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ebXML Technical Architecture Project Team (2001). ebxml technical architecture specification.
Ellis, C. and Nutt, G. (1993). Modelling and Enactment of Workflow Systems. In Marsan, M. A., editor, Application and
Theory of Petri Nets 1993, volume 691 of Lecture Notes in Computer Science, pages 1–16. Springer-Verlag, Berlin.
Grefen, P., Eshuis, R.,Mehandjiev, N., Kouvas, G., andWeichhart, G. (2009). Internet-based support for processoriented
instant virtual enterprises. IEEE Internet Computing, 13(6):65–73.
Jordan, D., Evdemon, J., Alves, A., and Arkin, A. (2007a). Business Process Execution Language for Web-Services 2.0.
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Kiepuszewski, B., Hofstede, A., and Aalst,W. (2003). Fundamentals of Control Flow in Workflows. Acta Informatica,
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Mehandjiev, N. and Grefen, P., editors (2010). Dynamic Business Process Formation for Instant Virtual Enterprises.
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Norta, A. (2007). Exploring Dynamic Inter-Organizational Business Process Collaboration. PhD thesis, Technology
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CHANGES IN CONSUMER ACCEPTANCE OF DIRECT
BANKING IN GERMANY FOLLOWING THE FINANCIAL
CRISES
Dirk Braun1, Jan Kaehler1 and Jürgen Karla2
RWTH Aachen University,Templergraben 64, 52062 Aachen, Germany
1
Chair of Decision Theory and Financial Services
2
Chair of Business Information Systems and Operations Research
ABSTRACT
The traditional foundation of “trust” on which stable and successful business relations are built has been severely
damaged – particularly in the finance industry. Many investors have lost confidence in the individual competence and
integrity of their financial advisors as well as losing their trust in the institution “bank” in general, and are thus seeking
new paths to follow with regard to their financial transactions or their investments. Alternative distribution channels – in
particular that of direct internet banking – have profited from this behaviour. Banks record an increased use of online
banking services, since these allow clients and investors do autonomously implement their banking activities, without the
need of advisors, and potentially in a private environment. This leads to a change in private customer behaviour in the
domain of direct banking.
KEYWORDS
Direct Banking, Trust in financial consultants, investment advisory services, lack of confidence
1. INTRODUCTION
The forces which were unleashed during the global financial crisis have dealt the financial markets heavy
blows – the final economic outcomes of which cannot yet be foreseen. In addition, fundamental social changes with regard to consumer behaviour, values, and relationships between individuals have been precipitated
(Shiller 2008, p. 20). Owing to profound experiences arising from the impact of the financial crisis, long-term
and stable customer relationships are (again) playing an increasingly important role for companies in all the
different areas of the economy. Business relationships tend to be based on substantial trust between the
individuals involved. Yet it is precisely this traditional foundation of “trust” on which stable and successful
relationships are built that has been severely damaged – particularly in the finance industry. Many investors
have lost confidence in the individual competence and integrity of their financial advisors as well as losing
their trust in the institution “bank” in general, and are thus seeking new paths to follow with regard to their
financial transactions or their investments (Sattler 2009, p. 25ff.).
Here, we present the key findings of a study which has examined potential consequences of the observed
changes in the behaviour of private investors. Since many customers have turned away from traditional banking advisory services, we could expect alternative distribution channels – in particular that of direct internet
banking – to have profited from this behaviour. A credible development would thus be an increased use of
online and direct banking services, since these allow clients and investors do autonomously implement their
banking activities, without the need of advisors, and potentially in a private environment, because customers
have lost faith in the expertise of banking experts. Previous publications (up to the end of 2010) on the topic
of the financial crisis have paid little attention to the change in private customer behaviour in the domain of
direct banking. Almost all of the publications which deal with customer behaviour in direct banking appeared
before the financial crisis and thus fail to deal with these specific problems. In order to identify and analyze
the changes in customer relationships, we shall first examine their great significance for the finance industry
(Section 2). In addition, we identify some basic information about the concept of direct banking as a substi-
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tute for traditional banking advisory services (Section 3). Then we present the design and the key results of
the study (Section 4). Finally, we analyze the expected significance for the development of direct banking
and what people expect from their banks (Section 5).
2. THE RELATION BETWEEN CLIENT AND ADVISOR
The literature on the analysis of the client-advisor relationship offers two main frameworks. From Sniezek
and Buckley we have the term “judge-advisor system (JAS)”, which differentiates between the very different
roles of client (judge) and the advisor. The decision process entails three steps: (1) the initial decision by the
client, (2) the advisor providing the recommendation and finally (3) the final decision by the client
(Sniezek/Buckley 1995, p. 159ff.). An alternative approach is that of Jungermann, who provided the “advice
giving and taking” model – known as AG&T. Here, we have a dyadic decision situation, i.e. client and
advisor are both in a decision-making process involving a mutual sharing of information (Jungermann 1999
and Belting 2008, p. 21). The advisor’s recommendation depends decisively on the client’s initial action and
information provision. The client then has to choose whether to accept the advisor’s recommendation or
reject it. The problem in this situation is the double knowledge asymmetry. Since the advisor knows only a
few details of the problem at the onset, at the end of the advisory session, the client is at a disadvantage with
regard to a competent assessment of the quality of the recommendation. The client can only depend on the
advisor’s references or trustworthiness: the risk involved with regard to the outcome of the decision remains
(Currall/Judge 1995, p. 153). Trust is, then, the central aspect for acceptance by a client.
The question arises as to why – in the first place – a client should make an initial decision in favour of
acquiring advice for a later advisory service by sacrificing free time and – in some cases – money, if she or
he is not going to be in a position to assess the quality of the resulting recommendation. The motives for
acquiring advice are complex, so that at this point we can only discuss a few of them which are relevant for
explaining the changes in client attitudes in the wake of the financial crisis. The main aspect is certainly that
of the wish to compensate for a lack of knowhow with the acquisition of advice, or at least to be able to take
other arguments and reasoning into consideration, which would be otherwise overlooked in the decision
making process. Sometimes an advisory service (only) leads to an increased subjective feeling of security. In
addition, people like to consult an advisory service if they are themselves not in a situation to make the
decision – be it due to time, capacity or complexity reasons. Advisors usually specialize in one area and are
methodologically trained so that they can find a problem solution much more quickly and efficiently than
someone who is faced only once with a specific problem. A last but no less important aspect is that people
like to share responsibility in order to avoid having blame apportioned to them later or having to come to
terms with their own wrong decisions (Belting 1998, p. 23 ff. and Heath/Gonzales 1995, p. 305).
Until now, the above mentioned arguments have led to a continuous increase in the call for advisory
services in the finance industry because the relevant topics have become increasingly complex due to the
legal and fiscal frameworks and an expanding range of financial products. Customers, on the other hand,
have less time to address these issues with the required intensity. Banks and their financial advisors enjoyed
for their part a high status in society. All of these conditions, however, were shaken to the core by the
financial crisis, as were the belief in the competence and quality of the advisors and the general confidence in
banks and in the financial system. Apart from real-life experiences, this attitude is linked to negative future
expectations (Akerlof/Shiller 2009, p. 31ff.). Many clients have come to the conclusion that financial
advisory services cannot offer them a reliable return because banks are looking after their own interests first
and the advisors are no more competent than they themselves are. On account of a lack of confidence,
customers do not make use of advisory services and prefer to rely on their own decisions (only).
3. DIRECT BANKING AS POSSIBLE SUBSTITUTE FOR TRADITIONAL
FINANCIAL ADVISORY SERVICES
The term “direct banking” (DB) covers all systematic activities involved in the provision of banking services
via direct communication channels without any intermediaries. The main medium used is modern telecommunications (internet, telephone/mobile phone, fax etc.) DB belongs, then, to the domain of e-commerce, and
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primarily targets private households. Its distribution channels are regarded as independent channels for specific market development and as fully fledged alternatives rather than as supplementary means of communication that support traditional distribution channels. Customer and bank communicate with each other by utilizing impersonal media. The direct selling of banking products and services is foremost. Since DB disposes
with intermediate selling or in-house stages, it can be seen as a “puristic” form of banking. When clients
make use of a product or service, they are not on a banking institution’s premises and exploit – to a much
greater degree than with branch-banking – the temporal and spatial availability of products and services. The
customer is always the one who takes the initiative.
The distribution channel “direct banking” has three main properties which distinguish it from traditional
banking: (1) it is cheaper, because the bank rewards its clients for their deliberate foregoing of their right to
intensive, personal advisory services. (2) it is fast because pro-cessing time is – on account of the direct
distribution channel – quicker than with traditional banking. (3) it is simple, so that customers can manage
their own banking activities with little problem (Raabe 2008, p. 9).
We will not provide a detailed differentiation between the individual direct banking products and services
with regard to their distribution or range. Instead, we shall only provide a basic differentiation between tradition banking products, such as account-managing, payments and simple product deals (e.g. fixed- interest
investments). It should also be noted here that the amount of products on offer has increased considerably,
and will presumably continue to increase on account of the increasing demand, so that DB will be used in
more and more areas. DB products and services have met with increased consumer acceptance in broad areas
of the population on account of the daily use of modern media in people’s professional and private lives, and
also a reduction of customer loyalty coupled with a willingness to switch banks in the wake of changes in
public opinion stemming from the scandals, misselling and financial crises of the last 15 years (Jung 2005, p.
68, Raabe 2008, p. 19ff. and Schmeisser/Fuchs 2008, p. 133ff.).
4. CHANGINGS IN THE USEAGE AND ACCEPTANCE OF DIRECT
BANKING FOLLOWING THE FINANCIAL CRISIS
In the above, we have already identified general changes in the framework conditions and customer requirements with regard to the expected development of DB. We have also observed that confidence and trust are
key for the acceptance of financial advisory services by private customers, and that traditional banking
advisory services are (at least currently) losing their importance and many customers are searching for new
paths for procuring information and investing their money. In the following, we will look at the design of our
survey and its results, which provide information on the concrete impacts of the financial crisis on the
behaviour of private DB customers in Germany.
4.1 Design of the Survey
In the summer of 2010, 458 persons aged between 18 and 60 received an online questionnaire asking them
about their current individual banking behaviour in comparison to their behaviour in 2007, (i.e. before the
outbreak of the financial crisis). 67% of the respondents were men, 33% women. Most of them were aged
between 18 and 25 (60%) and 26 to 35 (33%). Most of them were students (60%) and employed/self
employed (30%). Their customer relationships with German banks correspond roughly with the market
shares of the institutions in the German retail banking segment. Although the share of males, students and
young customers is above average with regard to the German population as a whole, the sample can still be
seen as valid because it corresponds closely to the average figures of DB users on the one hand. On the other
hand, when we examine the results of the individual groups, only the group of employed/self-employed
diverges from the total group, and this group is presented and elucidated separately here.
In particular, our questions targeted the following aspects (in 2007 and in 2010, respectively):
• General usage of banking products and services (regardless of type of distribution channel)
• Specific usage of banking products and services via direct banking (differentiating between banking and
brokerage) and changes in the intensity of usage
• Reasons for using banking products and services via direct banking
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In addition, there were also questions regarding the impact of the financial crisis on bank relationships
with regard to:
• Loss of confidence in banks
• Changes in the belief in advisor competence
• Customer loyalty and willingness to switch banks
• Changes in the procuring of information and in decision making processes.
4.2 Essential Findings
First, we present the results with regard to changes in consumer behaviour during the financial crisis, before
looking at the reasons. We can see various differences in the consumer behaviour of the respondents. Whilst
telephone banking is still used by 13% of them, online banking and direct brokerage have grown considerably by 5% and 6%, respectively. The general usage of direct banking products and services has increased by
6%: 90% of the respondents use DB products and services.
before the financial crisis
currently
13%
13%
Telephone banking
83%
88%
Internet banking
8%
Direct brokerage
14%
16%
None of these
10%
Figure 1. Consumer behaviour with regard to direct banking (complete sample)
However, these results do not enable us to ascertain whether the changes over the last few years were
caused by the financial crisis, or at least influenced by it. In order to be able to evaluate the results in more
detail, the respondents were required to state their reasons for direct banking both before and after the
financial crisis.
before the financial crisis
Financial crisis-related
3%
11%
33%
Cost saving
40%
44%
49%
55%
Control
Other
85%
89%
83%
86%
Time saving
Disaffection with advisory services
currently
4%
9%
18%
12%
complete sample
63%
47%
58%
4%
19%
16%
10%
employees/self employed
Figure 2. Reasons behind the usage of direct banking
One important result is that dissatisfaction with advisory services and the status of “control” has risen by
5%, respectively, as figure 2 shows. However, it would appear that more general trends – such as saving time
and costs – have just as much influence if not more as the financial crisis. The group of employees/self
employed focuses more on the aspects of “control” and “time saving”. With regard to “costs”, this can be
explained – in contrast with the students – by the fact that students can normally make use of free or greatly
reduced offers and tariffs, which banks do not make available to people who are employed/self employed.
With regard to the greater importance of “control”, the reason behind this already provides a clue to later
results. 11% of the employed/self employed group stated that the financial crisis had an impact on their usage
of direct banking.
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Also, questions were formulated which would reveal a potential loss of client confidence in their house
bank and a potential lost of confidence in the competence of the banking advisors stemming from the
financial crisis. The results of these questions show big differences between the groups of students and
employed/self employed. This can be explained by the fact that only about 20% of the surveyed students had
their own financial advisor at their bank and that as they also had less money available for investment, they
were not likely to encounter a loss of trust or confidence in a bank or financial advisor. With regard to the
concrete impact of the financial crisis on consumer behaviour in direct banking, the group of employed/self
employed respondents is, then, more suitable for analysis. In the following figure 3, we show the results of
those questions regarding a general loss of confidence and trust during the course of the financial crisis and
the consequences which the respondents have drawn from it all. About a third of them state that they have
lost confidence in their house banks. This figure reflects the deep impact of the financial crisis on private
investors: 13% of respondents who have lost confidence switched to other banks. A further 29% became
customers of another bank in addition to their house bank.
yes
no
29%
Lack of confidence arising from financial crisis
Switching of another bank owing to lack of confidence
customer at additional bank
71%
13%
58%
29%
Figure 3. Lack of confidence and consequences arising from the financial crisis (employees/self employed)
The lost of confidence in advisors is particularly visible in the securities business, which is very adviceintensive, particularly as big changes have been made to the classic process of securities orders in branches
and per direct brokerage. The amount of employed and self-employed private customers taking advantage of
fee-free advice services has dropped by almost a third, and advisory services in branch banks, which are –
unlike direct brokerage – not free of charge – have dropped by almost a half. The percentage of users of
direct brokerage, on the other hand, has almost doubled. These figures reflect the changed consumer
behaviour with the wish to have control and to save costs, on the one hand, and the impression that advisory
services are not likely to be of much use, on the other.
before the financial crisis
12%
Implementing transactions in securities via direct brokerage
Usage of advisory services via direct banking
Implementation of transactions in securities via branch bank
Usage of advisory services in branch bank
5%
current
26%
9%
39%
20%
30%
42%
Figure 4. Impact of the financial crisis to the usage of securities advisory services and direct brokerage (e./s. e.)
5. CONCLUSION
The financial crisis has had a positive impact on the usage of direct banking. The evaluation of the empirical
survey, taking all participants into consideration, the largest group of which was that of students (ca. 60% of
458 respondents), did not immediately lead to a decisive correlation between the outbreak of the financial
crisis and the increased usage of direct banking. In contrast, the differentiated evaluation of the group of
employed/self employed (approx. 30% of the respondents) confirmed the positive impact of the financial
crisis on direct banking. The financial crisis has led to a loss of confidence of a lot of customers in the
advisory actors and the banks themselves. 11% of the surveyed employed/self employed stated that the
financial crisis had led to their increased usage of direct banking. The assumption, on which this survey was
based, that is, that there could be a correlation between the financial crisis and the increased usage of direct
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banking, was confirmed. Apart from general reasons, such as cost savings, in particular a greater desire for
control and a lower estimation or a loss of confidence in the advisory services of banks can be mentioned.
The framework conditions of the financial industry have been permanently and unquestionably changed.
A lot of customers and investors feel let down by their banks and the actors there. Classical values, such as a
feeling of responsibility and trust, have come back into the focus of a lot of investors following the outbreak
of the crisis. Furthermore, the banking market is becoming more transparent and competition is increasing.
The binding of a customer to a house bank and its network of branches or individual advisors continues to
diminish because the range of products and services is so extensive and hard to distinguish between for most
private customers, and alternatives such as direct banking are becoming increasingly competitive. These
changed framework conditions have led to a general change in consumer demand for products and services.
Additionally, the increasing development of the internet as a distribution channel will allow direct banking in
e-commerce to increase in the future. For example, 28% of all the persons surveyed said that they intended in
future to only use direct brokerage. There is, of course, also the opportunity of using mobile banking for banking transactions. Web-enabled mobile phones, such as Apple’s iPhone, allow customers unlimited temporal
and spatial access to the online banking portals of the respective banks. Any further developing of this
technology can consequently have a positive impact on the usage of direct banking. A core area of banking –
investment advisory services – came under great criticism from the media and from experts. This empirical
survey has shown that a lot of customers are dissatisfied with the advisory services available and are seeking
alternatives. The banks are responding to the drop in the call for their advisory services by focusing on
quality again. The greatest challenge to the banks will – in the future – be that of binding customers to them.
The results of this study have shown that this can only happen if the ranges of products and services become
very transparent with regard to the reasons for their being recommended and to the costs involved – quite
independent of the distribution channel – thus meeting the increased consumer need for “control”.
REFERENCES
Akerlof, G. A., Shiller, R. J., 2009. Animal Spirits. How human psychology drives the economy and why it matters for
global capitalism. Princeton University Press, Princeton, New Jersey, USA.
Belting, J., 2008. Kontrolle ist gut, Vertrauen ist besser: die Bedeutung von Vertrauen in Beratungssituationen am
Beispiel der Anlageberatung. VDM Verlag Dr. Müller, Saarbrücken, Germany.
Currall, S.C., Judge, T.A., 1995. Measuring trust between organizational boundary role persons. In: Organizational
Behavior and Human Decision Processes, 64, pp 151-170.
Heath, C., Gonzalez, R., 1995. Interaction with others increases decision confidence but not decision quality: Evidence
against information collection views of interactive decision making. In: Organizational Behavior and Human
Decision Processes, 61, pp 305-326.
Jung, C., 2005. Online Banking: Der Zuwachs ist ungebrochen. In: Die Bank, Vol. 11, p 68.
Jungermann, H., 1999, Advice giving and taking. Proceedings of the 32nd Hawaii International Conference on System
Sciences. Maui, Hawaii: Institute of Electrical and Electronics Engineers, Inc. (IEEE).
Raabe, M., 2008. Innovatives Bankmarketing – Erfolgsstrategien im Direct Banking, Universität Kassel, Germany.
Sattler, N. C., 2009. Finanzkrise – Ihre Entstehung und bisherige Folgen sowie mögliche weitere Auswirkungen und
Zukunftsperspektiven für den deutschen Finanzmarkt, AVM Verlag, München, Germany.
Schmeisser, W., Fuchs, C., 2008. Zum Wandel der Finanzdienstleistungsbranche durch innovative Dienstleistungen von
Non- und Nearbanks. In: Zum Wandel der Finanzdienstleistungsmärkte – dargestellt anhand ausgewählter
Bankinstrumente und Finanzdienstleistungsinnovationen, Rainer Hampp Verlag, München, Germany.
Shiller, R. J., 2008. The Subprime Solution: How Today's Global Financial Crisis Happened, and What to Do about It.
Princeton University Press, Princeton, New Jersey, USA.
Sniezek, J.A., Buckley, T., 1995. Cueing and cognitive conflict in judge-advisor decision making. In: Organizational
Behavior and Human Decision Processes, 62, pp 159-174.
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Reflection Papers
IADIS International Conference e-Commerce 2011
IMPACT OF E-GOVERNMENT ON THE PRIVATE
SECTOR AND THE ROLE OF PRIVATE SECTOR IN THE
E-GOVERNMENT INITIATIVES
Hussain Kassem Wasly1 and Dr. Ali AlSoufi2
1
Asia e University, Saudi Arabia, Jubail
2
University of Bahrain, Bahrain
ABSTRACT
Recently, there have been large investments in the field of e-Government (e-Gov) in all parts of the world including and
specifically in GCC countries. However, little is known about the impact of investments in e-Gov, due in part to the lack
of guidance evaluation, and the absence of appropriate measurement tool for the impact of e-Gov on the private sector, as
well as the lack of effective management to resolve or eliminate the barriers to e-Gov which led to the failure or delay of
many projects, especially in developing countries and third world countries. This paper is primarily concerned in
determining the impact of e-Gov on the private sector (PS) in Saudi Arabia (SA) and the role of PS in supporting,
promoting and consuming e-Gov services. The paper takes SA as a case study due to a huge investment on its e-Gov
program that named Yasser to identify the challenges, barriers and opportunities of implementing the G2B services.
Despite such investments, SA PS is still in its early adoption of e-Gov services and resistance to it is very much
noticeable. A combination of Modified Technology Acceptance Model (TAM) and DeLone and McLean's of IS success
will be utilized as a research model, and e-Gov Economics Project (eGEP) measurement framework to measure “net
benefits” for G2B services. The result will help Yasser decision makers to recognize the critical factors that are
responsible for G2B success. On the other hand, it will enable them to measure the impact for e-Gov on the private
sector. Furthermore, it will benefit the private sector to better utilize the e-Gov services while positively contributing to
improvement and enhancement of e-Gov program.
KEYWORDS
E-Government, G2B, eGEP Measurement Framework, TAM
1.
INTRODUCTION
The financial and economic crisis beginning in 2008 has forced government and private sector as well to
focus on how to maximize saving costs and providing good services. Countries spend millions and even
billions on IT and e-Gov programs, for example in 2009; the US government is expected to spend more than
$71 billion on IT, with an estimated 10 percent of it related to e-Gov which means around 7.1 billion for eGov. E-Government (e-Gov) refers to the use of information and communication technologies, particularly
the Internet, to deliver government information and services (ANOA, 2006). E-Gov can create significant
benefits for citizens, businesses, and governments around the world. Nowadays, countries spend millions and
even billions on IT and e-Gov programs, for example in 2009; the US government is expected to spend more
than $71 billion on IT, with an estimated 10 percent of it related to e-Gov which means around 7.1 billion for
e-Gov. (2009 Federal IT Budget; Federal Enterprise Architecture taxonomy for 2008 budget; McKinsey
Estimates). In 2010; the SA government spends more than $3 billion on ICT. $800 million for e-Gov
program. According to Yasser the vision for Saudi Arabia's e-Gov initiative was detailed by determining ten
objectives to be achieved by the end of 2010. Those objectives are as the following: 1) Provide the top
priority services (150) at world class level of quality electronically.2) Deliver services in a seamless and user
friendly way and at highest standards of security. 3) Make services available to everyone in the Kingdom
and allow 24/7 access from cities as well as countryside and even outside the country. 4) Realize 75%
adoption rate with respect to the number of users. 6) Ensure 80% user satisfaction rating for all services
provided electronically. 6) Deliver all possible official intra-governmental communication in a paperless
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way. 7) Ensure accessibility of all information needed across government agencies and storage of
information with as little redundancy as possible. 8) Purchase all goods and services above a reasonable
value threshold thought e-procurement. 9) Contribute to establishment of information society in the Kingdom
thought spreading information, knowledge and use of e-services. 10) Help improve use of country’s assets
and resources by increasing society's productivity in private, business and public sector. So, there have been
large investments in the field of IT and e-Gov in all parts of the world. However, little is known about the
impact of investments in e-Gov, due to lack of guidance evaluation, and the absence of appropriate
measurement tool for the impact of e-Gov on the private sector, as well as the lack of effective management
to resolve or eliminate the barriers to e-Gov which led to the failure or delay of many projects, especially in
developing countries and third world countries. Many government projects are failing for various reasons.
These include unclear business cases, misaligned accountability and incentive structure, insufficient
management or technical expertise by external service providers, poor project management discipline,
inadequate performance management practices and tracking systems, ineffective governance, and uncertain
budget environments (Gartner, 2006). According to the UN's 2010 e-Gov readiness index, SA got 58 which
doesn’t reflect the huge investment and Yasser initiatives.
Government to business (G2B) impacts many areas like satisfaction / willingness to remain using, time
saving / cost reduction, integration with the existing business processes, trust, security, expenditure & labor
invested (Huang & Chu & Hsiao, 2009). e-Gov investments could easily be recovered if Governments are
able to do impact assessments from first stage and measuring the impact their e-Gov services. According to
Chang-hak Choi Korea (2010) South Korea invested $80 million to implement e-Procurement, as a result it
was able to do savings in 2009 amount of $3.2 billion, which means South Korea recovered the cost in 10
days. Many factors affect positive G2B impact and one of them is e-Gov barriers. The barriers to e-Gov
project team have identified seven key categories of barriers that can block or constrain progress on e-Gov as
the following: 1) Leadership failures 2) Financial inhibitors 3) Digital divides & choices 4) Poor coordination
5) Workplace and organizational inflexibility 6) Lack of trust and 7) Poor technical design. These were
derived from a wide review of relevant literature and research relating to e-Gov, augmented by an analysis of
the experience and knowledge of the project's partners, including growing feedback from stakeholders
obtained from the expert group and project workshops (European Commission’s eEurope, 2005). Also no
clear or good measurement framework is another factor that affects positive G2B impact. Therefore, many
countries have a national measurement Frameworks to identify the benefits and returns of investments of eGov services, each one measuring from different angles. Heeks (2006) mentions some of the well known
national measurements methodologies, and one of them is eGEP measurement framework developed by the
European Commission (2006) on the basis of a review of MAREVA (A Method of Analysis and Value
Enhancement) developed by the French.
2.
RESEARCH OBJECTIVES
Since the study is primarily concerned in determining the impact of e-Gov on the private sector of SA, the
focus will be on finding out the success of implementing and measuring e-Gov services in the country, in
meeting the demands of the business and economic development. The following research objectives will be
recognized by this study to identify the impacts behind e-Gov on the Private sector:
1. To find out ways in which e-Gov services (G2B) benefits can be realized and increased.
2. To identify the challenges and barriers that hander PS benefits for e-Gov services.
3. To identify PS role in supporting e-Gov initiatives.
4. To determine private sector awareness about e-Gov benefits.
5. To study and find gaps/issues in the policies of the SA government on their e-Gov programs.
6. To measuring success and net benefits of G2B services.
3.
RESEARCH METHODOLOGY AND MEASURMENT FRAMWORK.
Impact assessment (IA) is a set of logical steps which helps the Commission to do this. It is a process that
prepares evidence for political decision-makers on the advantages and disadvantages of possible policy
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options by assessing their potential impact (European commission, 2011). IA will be carried out before any
political initiatives are taken to an advanced stage for coming SA G2B initiatives. The case study strategy
will adopt for this study because it allows for an analysis of the impact of G2B on PS and what is the role of
business sectors to support the e-Gov initiatives. A case study approach enables better exploration of the
organizational context and processes through the use of interviews, surveys, document review and
observations. This is an applied research that will employ the descriptive approach to gather information
about the present existing condition. The purpose of employing this method is to describe the nature of a
situation, as it exists at the time of the study and to explore the causes of particular phenomena. The research
will be in two phases:
• Qualitative methods permitted a flexible and iterative approach.
• Quantitative research method will be used since this research intends to find sound evidence. And from
this type of research a survey instrument will be used in the form of interviews and questionnaires.
In order to provide a general and comprehensive definition of IS success that covers different perspectives
of evaluating information systems. Motivated by DeLone and McLean’s call for further development and
validation of their model, many researchers have attempted to extend the original model. Ten years after the
publication of their first model and based on the evaluation of the many contributions to it, DeLone and
McLean proposed an updated IS success model (DeLone & McLean 2002, 2003). TAM has been widely
used in research and empirically proven to be suitable for testing acceptance of any technology by various
user groups in different organizations (Liu, & Chen, 2009). The research uses an extension of DeLone and
McLean's model of IS success, TAM by including efficiency, governance / democracy, and effectiveness
from eGEP and the output for them is Net Benefits / Organizational Impact / Industrial Impact. Figure 1
shows a research model to measuring e-Gov success and its impact on PS.
Figure 1. Research Model to Measuring e-Government Success and Impacts
Figure 2. Adapted from eGovernment Economics Project, Measurement Framework Final Version, May 2006
eGEP framework is the selected tool to measuring net benefits. Figure 2 shows eGEP model that built
around the three value drivers of efficiency, democracy -good governance-, and effectiveness and elaborated
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in such a way as to produce a multidimensional assessment of the public value potentially generated by eGov, not limited to just the strictly quantitative financial impact, but also fully including more qualitative
impacts (RSO SPA and Luiss Management, 2006).
4.
CONCLUSION
The study research will find out and measure the impact of e-Gov on PS and the role of private sector in
supporting and using e-Gov services in Saudi Arabia. Additionally, it will illustrate the problems and
obstacles facing e-Gov and their impact on the parties. The study is extremely significant to the government
and organizations in SA, since they are looking for increased productivity and reduced costs by implementing
e-Gov programs. Needless to say here those both of Saudi government and private sector are doing huge
investment in acquiring the latest technology. This study will be most helpful to the government officials, IT
experts, economist and businesses in Saudi Arabia. The result of the study will provide information regarding
the current situation of e-Gov in SA. The findings of this particular research endeavor will likewise promote
awareness among government and PS. A secondary benefit of the study could be that having identified the
role of private sector in supporting and improving e-Gov services. This study will be in SA only and won’t
cover all G2B services regionally or at international levels.
REFERENCES
Australian National Audit Office (ANAO), 2006. Measuring the Efficiency and Effectiveness of E-Government. Audit
Report No. 26 2004-2005, Canberra.
Chang-hak Choi, 2010. How to Cooperate with Korea in e-Government, Retrieved Jan 10, 2010 from
http://www.consulmatica.com/cumbre/archivos/Chang-hak%20Choi%20Corea.ppt.
DeLone, W.H., and McLean, E.R. 2004. Measuring E-Commerce Success: Applying the DeLone & McLean Information
Systems Success Model, International Journal of Electronic Commerce (9:1), Fall, pp 31-47.
European commission, 2011. Impact Assessment, Retrieved Jan 25, 2011 from
http://ec.europa.eu/governance/impact/index_en.htm.
European commission, 2005. Breaking Barriers to eGovernment, Retrieved Feb 12, 2011 from
http://www.egovbarriers.org/?view=inventory
Gartner Report (2006). What every government IT professional should know about earned value management, Retrieved
April 11, 2011 from http://www.gartner.com/resources/136900/136921/what_every_government_it_pr
o_136921.pdf
Heeks, R., 2006. Understanding and measuring eGovernment: International benchmarking studies. Manchester, UK:
University
of
Manchester.
Retrieved
February
15,
2010
from
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Huang & Chu & Hsiao, 2009. E-Governance Impact – Framework and Assessment G2B, Retrieved Feb 12, 2011 from
http://www.teg.org.tw/common/dl.jsp?f=%2Fseminar%2F42%2FPanel+3_Panelist_Dr.+Nai-Yi+Hsiao.pdf.
Jason Baumgarten & Michael Chui, 2009. E-government 2.0, Retrieved February 23, 2010, from
http://www.mckinsey.com/clientservice/publicsector/pdf/TG_MoG_Issue4_egov.pdf
Liu, H., & Chen, L., 2009. Are travel agents in Taiwan ready for computer technology?. International Journal of
Organizational Innovation (Online), 2(2), 222-231. Retrieved December 28, 2010, from ABI/INFORM Global.
Document ID: 1923289821.
Mark Saunders, Adrian Thornhill, and Philip Lewis, 2003. Research Methods for Business Students, Pearson Education
Limited , Harlow, England.
Ministry of Management Services (MoMS), 2004. Annual Service Plan report, British Columbia, Retrieved Sep, 10,2009
from http://www.bcbudget.gov.bc.ca/Annual_Reports/2004_2005/mser/mser.pdf
RSO SPA and Luiss Management for the eGovernment Unit, 2006. Project (eGEP) Measurement Framework Final
Version, General Directorate Information Society and Media of the European Commission, eGovernment
Economics., Retrieved Feb 10,2011 from http://ec.europa.eu/governance/impact/index_en.htm.
Yasser Program for eGovernment, 2011. SA eGovernment initiatives, Retrieved Feb 10, 2011 from
http://www.yesser.gov.sa/en/Pages/default.aspx
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REFLECTIONS ON PRIVACY IN NEW LOCATION BASED
SERVICES IN SOCIAL NETWORKS
A. Paniza-Fullana, M. Payeras-Capellà, M. Mut-Puigserver and A. Isern-Deyà
University of the Balearic Islands, Carretera de Valldemossa Km. 7, 5 07122 Palma, Spain
ABSTRACT
The paper presents a reflection about the concerns related with privacy that arise in the use of location based services.
The harvesting of location data can be very useful in e-commerce operations, as in advertising, and recently the use of
location data has been extended to social networks. However, the management of simple or aggregated location data
arises several problems related with privacy. In this paper we focus on the problems that can appear when location data is
used in social networks and we present a list with all the problems we have detected. The legislation related with privacy
are explained and applied to each of the detected problems.
KEYWORDS
Location Based Services, Privacy, Legislation, Social networks, Advertising
1. INTRODUCTION TO LOCATION BASED SERVICES
The brand new mobile devices are capable to access data networks and they are also able to execute complex
applications. Furthermore, these devices implement location systems like GPS or others based on location
techniques like GSM or Wi-Fi. The combination of both capabilities can be useful to build new ubiquitous
applications based on user location. These applications provide to service customers valuable information
related to their location.
Location-based services (LBS) are a kind of service offered to the users of mobile devices that provide
added value information related to the context where the users are located. LBS include different kinds of ecommerce applications, like touristic services offering information about the surrounding area of the user,
general social networks like Twitter, mobile social networks like Foursquare or some Google applications.
These applications gather private information of the user. With the aim to use properly (according to the
legislation) this sensible information, the applications often include a question to the user: “Does he allow the
use by the application of his location data?” However, if the user does not allow the use of the location data
then the service will be disabled. It would be interesting to include to the LBS the mechanisms that will allow
both the protection of the user privacy and the use of the applications.
These applications can use both the momentary location of the user and the trail or itinerary of all his
locations that could be used to generate a location profile of the user in order to know his usual movements.
The applications that use the trail of the users have more privacy requirements.
2. PRIVACY IN LOCATION BASED SERVICES
From the security viewpoint, it is clear that the use of private data opens many debates related to users
security because either providers or observers should not have access to both user identity and his location.
For this reason, techniques to ensure the secure use of these applications are required.
Location Based Services can be classified in three types, depending of the anonymity requirements [Liu]:
• Anonymous. The user can be fully anonymous, because the service does not need any type of
identification nor pseudonym. An example could be a service of meteorological alerts for the city where the
user is located.
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• Identified. It only can work if the user provides his true identity. An example could be an application to
alert about a broken protective order by an assailant.
• Pseudonym based. The user does not show his true identity but he only shows a pseudonym. For
example, a dating application, where it is not mandatory to show the real identity although other personal
data could be shared, like age or sex.
Several protocols designed to access to LBS are focused in the protection of the privacy of both users and
queries. Some of them use obfuscation algorithms to hide the exact user location [Gedik, Gruteser], while
others try to allow private requests using a technique called PIR [Ghinita].
3. LEGISLATION ON PRIVACY AND LOCATION-BASED SERVICES
Location data are regulated in the article 9 of the Directive 2002/58/EC of the European Parliament and of
the Council of 12 July 2002 concerning the processing of personal data and the protection of privacy in the
electronic communications sector (Directive on privacy and electronic communications). The Whereas 35 of
this Directive establishes about that question that: “…digital mobile networks may have the capacity to
process location data which are more precise than is necessary for the transmission of communications and
which are used for the provision of value added services… The processing of such data should only be
allowed where subscribers have given their consent. Even in cases where subscribers have given their
consent, they should have a simple means to temporarily deny the processing of location data”.
The requirements to use the location data by the service provider are:
• Location data relating to users or subscribers of public communications networks or publicly available
electronic communications services can be processed when they are anonymous or with the consent of the
users or subscribers.
• This data can only be processed to the extent and for the duration necessary for the provision of a value
added service.
• Service providers must inform the users or subscribers, prior to obtaining their consent, of the type of
location data other than traffic data which will be processed, of the purposes and duration of processing and
whether the data will be transmitted to a third party for the purpose of providing the value added service.
• Besides, users or subscribers shall be given the possibility to withdraw their consent for the processing
of location data other than traffic data at any time.
• The user or subscriber must continue to have the possibility, using simple means and free of charge, of
temporarily refusing the processing of such data for each connection to the network or for each transmission
of a communication.
In the same way the Spanish Telecommunications Act (Act 32/2003, November 3rd) in the article 38.3 says:
location data can only be processed when it is anonymous or if the provider has the consent of the user or
subscriber. Location data can only be processed to the extent and for the duration necessary for the provision
of a value added service and with prior information about the purposes and duration of processing and for the
added value service that will be provided1.
In the guide of “Best Practices and Guidelines for Location-Based Services” of the wireless association2
we can find some guidelines in the same way as the European or Spanish regulation:
• LBS providers must inform users about how their location data will be used, disclosed and protected so
that a user can make an informed decision whether or not to use the LBS or authorize disclosure.
• Once a user has chosen to use a LBS, or authorized the disclosure of location information, he should be
able to choose when or whether location information can be disclosed to third parties and should have the
ability to revoke such authorization.
• LBS providers must inform users about how their location data will be used, disclosed and protected.
• LBS Providers may use written, electronic or oral notice so long as LBS users have an opportunity to be
fully informed of the LBS Provider’s information practices. Any notice must be provided in plain language
and be understandable. It must not be misleading, and if combined with other terms or conditions, the LBS
portion must be conspicuous.
1
2
Vid. Spanish Agency of Protection Data Act 160/2004 about safety measures of data location files.
http://files.ctia.org/pdf/CTIA_LBS_BestPracticesandGuidelines_04_08.p
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4. DETECTED PROBLEMS IN NEW LBS: SOCIAL NETWORKS
Recently, new LBS have appeared. Among them there are services that include location data in social
networks. As a result the location data is not only revealed to a service provider but to a set of people that
usually include contacts in the social network. Facebook Places, Foursquare, Yelp , Google Latitude and
Gowalla are examples of social networks using location. These services enable users to ‘check into’ locations
they visit using a mobile device. Then the users can share their current location and/or the places they have
checked into. The following are concerns or problems related to privacy when these services are used:
1. A first concern is related with who will be able to see this information. Almost all services include
privacy configuration tools to set who has access to the location information. Social networks allow users to
classify other users as friends or contacts. Usually users use this tag to mark real friends and also to mark
other kind of users, as colleagues, neighbors and even unknown people who share with them some kind of
hobby. It is usual that the default configuration of the service allows the access to the location information to
all the contacts of the user, so a lot of people will share this sensible information. This default parameter must
be discussed.
Some legal problems can be debated: essentially the fact that the configuration of the service is not
equivalent to the consent of the users. In the case of the configuration of the browser, the Opinion 1/2009 on
the proposals amending Directive 2002/58/EC on privacy and electronic communications (e-Privacy
Directive) establishes that: “Most browsers use default settings that do not allow the users to be informed
about any tentative storage or access to their terminal equipment. Therefore, default browser settings should
be “privacy friendly” but cannot be a means to collect free, specific and informed consent of the users, as
required in Article 2 (h) of the Data Protection Directive”. As in the browsers, the default configuration of
social networks services should be protective of the user’s privacy.
2. Location information can be used for advertising purposes. As an example, Facebook Places Deals [1]
it’s a service in where a commerce offers promotions or gifts to users if they check into their places. If a user
disables the option to share his location he will lose the access to these opportunities and he will not have
access to any promotions offered by a business if their promotions are based on group offers. As a result,
users are coerced to share their location data. From a legal point of view some questions arise: is it an abusive
term of the contract? It is the same that sometimes occurs with the cookies, if you reject the cookies
sometimes you cannot entry in a web page.
3. Some social networks also allow friends to check another user into a place. This feature can be enabled
and disabled but the configuration tool must be easy and has to have enough options. Enabling this feature
means that friends can tag you and ‘check’ you into a Place. After that, the checked user will get a
notification to say a friend has tagged him. The user will be able to remove the tag just as he can with other
kind of tags like photo tags, but a user will appear placed, or falsely placed, until he removes the tag. From
the legal point of view, the form of the consent is very important. Prior of this consent the user should be
informed of the type of location data other than traffic data which will be processed, of the purposes and
duration of processing and whether the data will be transmitted to a third party for the purpose of providing
the service. It is necessary too in the case where the consent is in the ‘general terms’ of the contract. In this
case some legal aspects arise: is it enough the consent of the user in a “general terms” of a contract?3
The revocation of consent is also important: LBS providers must allow the users to revoke their prior
consent to disclose location information to all or specified third parties. Special legal problem appears with
the consent of minors. A lot of users of social networks are minors and cannot give their consent to the
service provider to use their location data, but in practice it is very difficult to control and stop.
4. If an account is compromised (e.g. as a result of phishing) not only his own location but also the
location of his friends will be compromised including the actual location and the historial of visited places.
Moreover, providers are able to keep records of location data and even share them, so this concern can be
related with the cession of data by the social network providers to third parties.
Some legal problems arise: Who can use this location data? What happen if a third person (e.g. “a friend
of a friend” in the social networks) uses my location data? Service providers need the consent of the users to
send the location data to third parties (e.g. for marketing purposes)
3
As an example, in the Privacy Policy of Gowalla: “In order to use the mobile features of the Gowalla Service, you must consent to: (a)
the use of your phone’s location to provide Gowalla to you, including the display and disclosure of that location information to your
Gowalla friends and within your geo-tagged messages and content… ».
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5. If somebody can know your location he also knows where you are not. That is, you let everyone know
you’re gone, you’re not home, but similarly everyone can know you are not at the office or at the school.
6. There are a lot of applications, websites, games… that use location data as a parameter. Normally the
applications ask users its permission to use location data, but a negative answer will lead to the impossibility
to use them. In some social networks, the access from the applications to location data is defined by the
privacy profile. It is important to know which is the default setting for this kind of access.
7. A lot of people state that they are concerned about the exposure of their location data (see
internet2go.net for statistics). Do these people really know and understand that they are sharing location
information? Do they know who can access this information or how to change the privacy profile? An opt-in
approach would be better? Really the rules establish an opt-in system to use location data: it can only be used
in the case where this data is used in an anonymous way or with the consent of the user. Without this consent
it is not possible to use the location data in a legal form (article 9 Directive on privacy and electronic
communications, Spain, article 38 General Telecommunications Act)4. A wrong way to use location data is
the case of Apple: two people present a claim in U.S.A. against Apple because it seems that they use software
included in the Apple operating system file that sent to the creators location data of the mobile devices of the
users without their knowledge of it [mundo]. At the moment, we don’t know which use of these location data
is doing Apple. Similarly, Android has been also criticized for the harvesting of location data.
8. The inclusion of places like home, friend’s home and so on can be dangerous not only for user’s
privacy but also for personal safety.
5. CONCLUSION
As a result of the application of the legislation related with privacy to a new location based service (social
networks) some conclusions can be listed. There are several points where the services fail to fulfill the
legislation, or, at least, its fulfillment is arguable. The most conflictive points are the default configuration of
the social networks service, the use and cession of collected data, the role of minor users, the use of data by
applications and the personal safety. Also, the applications ask for the users' permission to use their location
or they offer possibility to disable the option of sharing the location. However, if a user doesn't share her
location, the service is denied to the user instead of offering the service with some restrictions (e.g. timerestrictions). This kind of politic tends to break the user's privacy. Once the problems are detected the next
step is how to deal with these problems. Future directions of our work will be to develop a framework for
evaluating social networks services in terms of privacy and propose mechanisms to protect privacy.
REFERENCES
B. Gedik and L. Liu. A Customizable k-Anonymity Model for Protecting Location Privacy. In ICDCS, p. 620–629, 2004.
G. Ghinita, P. Kalnis, A. Khoshgozaran, C. Shahabi, and K.-L. Tan. Private queries in location based services:
anonymizers are not necessary. Proceedings of the 2008 ACM SIGMOD int. conf. on Management of data, pages
121–132, 2008. ACM.
M. Gruteser and D. Grunwald. Anonymous Usage of Location-Based Services Through Spatial and Temporal Cloaking.
In MobiSys ’03: Proceedings of the 1st int. conf. on Mobile systems, applications and services, p. 31–42, 2003. ACM.
L. Liu. Privacy and location anonymization in Location-Based Services. SIGSPATIAL, Vol 1, Issue 2, p. 15-22, 2009.
El
Mundo.
Denuncian
a
Apple
por
el
sistema
de
rastreo
en
sus
dispositivos.
http://www.elmundo.es/elmundo/2011/04/26/navegante/1303783744.html
4
In USA, Telecommunications Act of 1996 includes protections for “Customer Proprietary Network Information,” (CPNI) a complex
term used to encompass calling records, including the numbers called, numbers received, and new types of information collection, such
as location of the user. The Federal Communications Commission recently restricted disclosure of CPNI; carriers must now obtain opt-in
consent from customers (Comparative Study on different approaches on to new privacy challenges in particular in the light of
technological developments. Editor Douwe Korff; United States of America by Chris Hoofnagle. May, 2010).
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UTILIZING THE COMMUNICATION-TECHNOLOGY TO
MINIMIZE THE FINANCIAL NEGATIVE INFLUENCE IN
THE SUPPLY CHAIN
Ming-Yaun Hsieh1, Wen-Yaun Wu2, Chaang-Yuan Kung3 and Ya-Ling Wu1
1
2
Assistant Professor, Department of International Business, National of Taichung of Education
Associated Professor, Department of Distribution Management, National Chin-Yu University of Technology
3
Professor, Department of International Business, National of Taichung of Education
ABSTRACT
In the modern economic era of lower profits, financial risk has been in the supply chain management for quite some time;
however, only a few assessable measurements of financial negative influence are considered. Hence, in order to
comprehensively cross-analyze the influence of multiple financial criteria for minimizing the financial risk in supply
chain, the Analytical Network Process (ANP) model is utilizing to improve the selection of best potential supplier in
supply chain management from financial consideration perspective by selecting and evaluating key financial assessment
criteria through brainstorming, focus group, the Delphi method and nominal group technique. Subsequently, the specific
characteristics of the Analytical Network Process (ANP) model is not only to establish pairwise compared matrix but also
to further calculate the priority vector weights (eigenvector) of each assessable characteristic, criteria and attribute.
Additionally, in the content, the analytical hierarchical relations are definitely expressed in four levels including between
each characteristic of supply chain, criterion and attribute. Moreover, based on the empirical analysis, the enterprises are
able to choose the best potential suppliers through this research in order to minimize financial negative influence from a
financial perspective. Finally, some suggestions for managers and researchers are inductively formed to further the best
development of operation strategy of supply chain management by utilizing the development of the communicationtechnology to diminish financial negative influence and risk.
KEYWORDS
Supply Chain Management (SCM), Communication-technology (CT), Analytical Network Process (ANP)
1. INTRODUCTION
Essentially, there are two significant ideas in Supply Chain Management (“SCM”). One is “The Supply
Chain (“SC”) encompasses all activities associated with the flow and transformation of goods from the raw
materials stage (extraction), through to the end user, as well as the associated information flows. Material and
information flow both up and down the SC.” (Chen et al, 2004) and another one is that SCM is the systemic,
strategic coordination of the traditional business functions and the tactics across these business functions
within a particular company and across businesses within the SC, for the purposes of improving the longterm performance of the individual companies and the SC as a whole. However, the fundamental ideal of
SCM depends on compressing the total cost of manufacture, inventory and delivery in order to reach the best
profits for the enterprises after the orders has been given to the enterprises. SCM is not able to effectively
handle two crucial problems for enterprises: cash-flow stress without orders and account receivable stress
with slow client-payment. In the boom period between the 1990 and 2008, the global economy has been in a
rapid growing status due to the steady development of the economy of Mainland China. Taiwan’s proximity
to Mainland China has resulted in Taiwan being depended on the expose processing and international-trade
to develop its economy. In the last 20 years, more and more of Taiwan’s enterprises have started to invest in
China which has caused a high depended relationship between enterprises in Taiwan and China. The purpose
of this research is to utilize the hierarchically analytical approach and the analytical network process
(“ANP”) approach in order to measure the key elements and assessable criteria for reducing financial
negative influence under SCM for the enterprises to minimize the finance and managerial negative influence.
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2. BODY OF PAPER
Saaty (1996) addressed the most major different point between AHP and ANP is that, based on the original
assumption, AHP is not able to directly evaluate each assessable criterion by hierarchical relations but that,
on the contrary, ANP can be utilized to dispose of direct interdependence relationships and inter-influence
between each criteria and criteria at the same or different level through conducting the “supermatrix”. (1)
Financial Evaluation: revenue growth (“RG”) and gross margin ROI (GM-ROI). (2) Sale Review: sale
forecast accuracy (“SFA”) and days of inventory sales (“DOIS”). (3) Inventory System: inventory turns
(“IT”), obsolete inventory (“OI”) and inventory accuracy (“IA”). (4) Delivery Status: warehouse operations
cost as a percentage of sales (“WOCSP”) and outbound freight cost as a percentage of sales (“OFCOSP”) in
this criterion. (5) Customer Service: on time shipment (“OTS”), percentage of returned good (“PRG”) and
order fill rate (“OFR”). (6) Suppliers’ offer: percentage of on time supplier delivery (“POTSD”), percentage
of supplier delivered material defects (“PSDMD”), percentage of total direct material that do not require
inspection (“PTDMDNRI”), percentage of total material value purchased using a web-based system
(“PTDMVP-W”), percentage of total material value purchases using a EDI transactions (“PTDMVP-EDI”)
and percentage of total material inventory managed by suppliers (“PTMIMS”).
2.1 Figures and Tables
The selection of suppliers with best potential communication-technology in supply chain
Attributes of
each subcriterion
Enterprise’s high-speed operation demand
Financial Evaluation
Criteria of
assessment
Selected
Candidate of
Suppliers
RG
GM-ROI
Value-adding transformation
Supply information channel
Sale Review
Inventory System
Delivery Status
Customer’s Service
SFA
DOIS
IT
OI
IA
WOCSP
OFCOSP
OTS
PRG
OFR
Supplier 1 (without enterprise’s
domain.) (SWTED)
Suppliers 2 with the enterprise’s internal
domain and social networking (SWEIDSN)
Suppliers’ offer
POTSD
PSDMD
PTDMDNRI
PTDMVP-W
PTDMVP-EDI
PTMIMS
Suppliers 3 (with the enterprise’s internal and
external domain and social networking)
(SWEIEDSN)
Figure 1. Relationship for characteristic, criteria, sub-criteria and selected candidates
Table 1. Strategic comparative index of the three measurements
(Financial Evaluation/ Sale Review/ Inventory System/
Delivery Status/ Suppliers’ offer/ Customer Service)
Accounting comparative index
Supplier 1 (SWTED) Suppliers 2 (SWEIDSN) Suppliers 3 (SWEIEDSN)
0.137
0.6414
0.2749
3. CONCLUSION
There are a plethora of researches in SCM surrounded the major fundamental idea of the cost-down under the
development of the communication-techology. However, the measurement and diminishment of financial
negative influence of selection suppliers in SCM is not discussed in detail in the research field. The reason is
the relationship between enterprise and suppliers overall emphasize on the high-speed establishment of
internal domain during the enterprises selects the cooperative suppliers because suppliers growing will
definitely assist the enterprise to grow. Consequently, the highest result of the evaluated score of comparative
index of 0.6414 is Suppliers 2 (SWEIDSN). The ANP model is used not only to clearly establish
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comprehensively hierarchical relations between each assessable criterion but also to assist the decision-maker
to select the best potential supplier 2 with the enterprise’s internal domain and social networking
(“SWEIDSN”) with low financial negative influence through the academic Delphi method and expert’s
survey. In the content, there are six main assessable criteria including three financial assessable factors
(financial evaluation, sale review and inventory system), two SCM assessable factors (delivery status and
suppliers’ offer) and one customer-service assessable factors (customer service).
REFERENCES
Davis, T. 1993. Effective Supply chain management,” Sloan Management Review. vol. 34 no. 4, pp.35-46.
Harland, C. M. 2006. Supply Chain Management: Relationship, Chains, Networks. British Journal of Management, vol.
7, Special Issue, pp.63-S80.
Lambert, Douglas M., and Martha C. Cooper. 2002. Issues in Supply Chain Management. Industrial Marketing
Management, vol.29, pp.65-83.
Li Xiao Cheng. 2009. Gong Ying Lian Feng Xian De Cai Wu Guan Dian. Accounting Research Monthly, vol. 285, pp.6667.
Education: Analytical network Process Approach,” International Journal of Manpower, vol.25 no.7, pp.643-655.
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INFRASTRUCTURE MODEL FOR ASSURANCE OF
AUTHENTICATION DATA EXCHANGE FORMAT
Ahmed Tallat1, Hiroshi Yasuda1 and Kilho Shin2
1
Tokyo Denki University
2
University of Hyogo
ABSTRACT
Conventionally service providers have to manage their own authentication systems individually and independently
without interoperation among them. Lack of the interoperability causes serious problems. By clarifying the requirements
for the interoperability, we propose an authentication infrastructure model, where independent players made up of a
service provider, identity provider and authentication agent cooperate and communicate with one another.
KEYWORDS
Authentication, interoperability, identity provider, password.
1. INTRODUCTION
Authentication is building block for security. Conventionally Service Providers (SPs) provided authentication
functionality independently without any interoperability among them and it caused serious problems to SPs
and users alike; SPs have to duplicate financial investment for registration and authentication system, and
users have to repeat authentication steps in order to access services. To address these problems PKI and SSO
were created to meet the needs of SPs and users alike. However, they aim at different things; SSO
authenticates users whose results can be shared among variety of SPs, and PKI realizes interoperability of
authentication in open environment where SPs can evaluate authentication results from even unknown
entities.
Thus as solution for combining both merits of SSO and PKI, in order to share authentication results in
open environment (like a variety of media, the Internet, diverse operating systems, mobile systems and
smartcard etc.), we propose an authentication infrastructure model, where an identity provider (IdP),
authentication agent (AA) and service provider (SP) cooperate and communicate with each other.
2. RELATED WORK AND EVALUATIONS
PKI [1] [2] works on a basis of Certificate issued and signed by a Certificate Authority (CA) in order to bind
a public key to a subject. The subject creates Certificate Signing Request (CSR) signed by a private key and
submits it with the corresponding public key to CA that creates digitally signed certificate after validating the
subject. The CA also issues certification revocation list and status checking services. Once the certificate is
verified by the CA`s self-signed certificate, others believe that public key belongs to the subject because of
trustworthiness of CA. The trustworthy level of CA depends on its certification policy (CP) and certification
practice statement (CPS), which specifies how certificate services are provided.
In conventional SSO, to access a service server (SS), first users` ID/password are managed by centralized
authentication server (AS) that establishes secure communication channel with other multiple SSs in order to
share the users’ authentication results. Once users authenticate themselves to the AS and access to other
services, behind the scene their data is transferred from the AS to SSs. From the users’ perspective, they get
directly accessed to other services without being prompted for authentication at each of them. Thus, SSO
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improves security by eliminating phishing and identity theft opportunities as well as reducing the risk of
individual identity management. Kerberos [5], SAML2.0 [4] etc realize SSO functionality.
However, PKI, unlike SSO, requires individual authentication, not aimed at sharing authentication results
among SPs, whereas SSO works on Circle of Trust that cannot be assumed in open environment where SPs
may receive authentication results issued from unknown entities.
We assume authentication infrastructure from the points of Sharing authentication result, Open
Environment, Player Independence functions views.
Table 1. Evaluation of selected frameworks and protocols
Conditions
Sharing authenticated result
Open Environment
Player Independence
No
Yes
Yes
Yes
No
No
Yes(partly)
Yes(partly)
Yes(partly)
frameworks
PKI
Kerberos
SAML
1. Sharing authentication result reduces multiple authentication procedures and it is most preferred
function for users and SPs alike.
2. Reaching out Open Environment necessitates the need of evaluating authentication result even issued
from unknown entities.
3. Gaining independence of players is beneficial of economic and security perspectives, because players
concentrate on particular investments, and it limits specific tasks of processing users’ data.
3. AUTHENTICATION INFRASTRUCTURE MODEL
In response to the limitations of PKI and SSO, we propose a model that provides the merits of SSO and PKI
simultaneously and it consists of registration phase, authentication phase and authorization phase (Figure 1).
Figure 1. Authentication infrastructure model
3.1 Protocol
An independent enterprise playing the role AA`s functionality is most crucial of creating authentication
infrastructure in open environment. To relieve the duplicated investments made by SPs individually, AA
bears a huge financial investment of distributing unified interface to authenticate users by means of token,
which can be private key, password, smartcard, fingerprint etc. Currently the main reason for a lack of
authentication infrastructure is that SPs maintain their authentication systems by themselves, which
constitutes significant financial burdens. We can realize AA`s functionality from the ATMs example, which
are found in convenience stores run by an independent entity bridging between multiple SPs and users.
• Registration phase
In the phase, IdP performs registration procedures of users applying for identities based on its policy and it
results in activation of Token and reference data (e.g. fingerprint & templates, private key & public key etc).
Generally IdP does this via the following steps.
Identification: during which the IdP verifies the real-world identity of the applicant.
Custody: during which the IdP stores the verified applicant information safely against environmental,
physical and cryptographic threats so that the repudiation of user registration can be prevented.
Activation: during which the IdP by creating references activates token to be bound to the applicant.
• Authentication phase
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In this phase, users access AA’s interface and creates proof data from their token. Upon receiving proof
data (e.g. password, digital signature, biometrics scanned image etc), AA verifies it by reference data received
from IdP or sends it to IdP for verification. As the result, Endorsement is created as authentication results
covering all necessary information involved of its generation. Furthermore, AA digitally signs Endorsement
with its private key and issues it to authenticated users with certificate that contains corresponding public key.
• Authorization phase
In authorization phase, users present Endorsement and certificate to SPs who verify them in terms of
security and trust levels before providing requested service; SPs at least confirm the trustworthiness of
issuers, whether the alleged security levels of the Endorsement meet SPs` requirements which also includes
the data is fresh and is not a target of any tempering.
3.2 The Solutions by this Research
In the following we describe how the conditions in section 2 are met by our proposed infrastructure model.
• To meet the 1st condition
In our model, IdP and AA cooperate with each other to perform user registration and authentication,
whose results called Endorsement is shared among a large indefinite number of SPs. SPs evaluate the
Endorsement in order to provide users with requested services. Thus SPs must be provided with sufficient
information involved in creation of the Endorsement for its evaluation. Therefore, we have clarified both
threats and counter-measures for phases defined in our model and retrieved necessary information to be
included in the Endorsement. Upon receiving it, SPs verify its security levels [3] and decide its acceptance by
referring to SPs` security policy. We have also defined XML schema [6] to encode the data.
• To meet the 2nd condition
Security level of endorsement alone cannot make the assurance of authentication data exchange possible in
the open environment, unless SPs have reasons to believe that IdPs and AAs are trustworthy. Thus, we deploy
auditing scheme by taking advantage PKI and digital signature scheme with some extensions, where a Trusted
Third Party not only binds public key to AA but also guarantees the trustworthiness of IdP/AA by auditing
them in terms of practicability of their alleged policies.
• To meet the 3rd condition
Unlike conventional framework, PKI enables SPs to entrust registration to CA, whereas SSO enables SPs
to entrust registration and authentication to IdP. But SPs still independently maintain authentication systems
that require big financial investment to distribute and operate them (e.g. biometric authentication). Thus, in
our model IdP, AA and SP work independently, and SPs can determine the acceptance of Endorsement by
entrusting registration and authentication to independent players, the IdP and AA respectively.
4. CONCLUSION
We outlined problems from both users and providers` perspectives in conventional authentication systems
implemented independently without interoperability. Further, we analyzed PKI and SSO aimed at addressing
these problems, and found their interoperability is limited in scope. Thus by clarifying the requirements for
the interoperability, we proposed authentication infrastructural model. Next we plan to develop prototypes of
the SP, IdP and AA systems that cooperate with each other based on the XML-encoded data.
REFERENCES
[1] “Internet X.509 Public Key Infrastructure Certificate and Certificate Revocation List (CRL) Profile”, RFC 5280.
[2] “ Internet X.509 Public Key Infrastructure: Certification Path Building”, RFC 4158.
[3] NIST, Electronic Authentication Guideline, NIST Special Publication 800-63 Version 1.0.2.
[4] OASIS, Security Assertion Markup Language (SAML) V2.0, 2007.
[5] RFC: 4120 The Kerberos Network Authentication Service (V5).
[6] XML Schema Part 0: Primer Second Edition, W3C Recommendation.
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IADIS International Conference e-Commerce 2011
RESEARCH ON USING E-TECHNOLOGY AND
E-ACTIVITIES WITHIN BUSINESSES
Roman Malo
Department of Informatics, Faculty of Business and Economics, Mendel University in Brno
Zemědělská 1, 613 00 Brno, Czech Republic
ABSTRACT
The research on e-technology, e-activities and their impact to business innovations is a one of the part of our research
activities that are being solved. E-technology and its expansion create a basic platform for using e-activities in various
businesses, but a lot of problem should be considered.
In fact, there are crucial problems with e-activities and e-technology benefits recognizing and with simple measuring etechnology maturity within business. That is why our research activities are focused on determining general models of etechnology and e-activities utilization within various types of businesses above all.
We guess, this is the possible way how to support business progress and how to enable the comparison of individual
businesses if we need to analyze their e-technology level.
This poster paper summarizes context, outlets and the last state of our work-in-progress in described domain.
KEYWORDS
E-technology, e-activities, research on e-technology, businesses
1. INTRODUCTION
1.1 E-technology
A comprehensive and generally accepted definitions of the term e-technology (or e-technologies) and the
term e-activities are not available. However, various authors understand both terms in a different way. We
agree with the claim of Tassabehji, Wallace and Cornelius (2007) and thus e-technology in our research is
understood as a new and continuously evolving platform from that an organization can exploit new
opportunities. This is also usually accepted claim.
In fact, e-technology can be viewed as a complex of technical and communication means together with
software applications enabling support of the electronic services and activities especially on the web and
mobile platform. In this way e-technology creates necessary technical environment for implementing eactivities within business.
E-technology must be today considered as dominant actors forming a current state of business
applications mostly based upon the web platform. The main moment of e-technology application is already
traceable for a long time, its utilization helps to communication, business support or supply/demand
relationship management.
1.2 E-activities
E-activities are electronic activities more or less substituting traditional activities. We formally define eactivity as a triple C, S, E where C is content matter, S subject supported by e-activity and E is e-technology.
For an example:
• E-commerce as the important e-activity enables buying and selling products online (usually through
Internet),
• a group of potential customers represents main subject of e-commerce and
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• a platform (e-technology) is usually any kind of e-shop software. (Malo, 2010)
The relation between e-activities and e-technology is quite strong. With respect of massive expansion of
activities as e-commerce, e-payments and others, the e-technology implementation represents a progressive
way of business innovations and new platform for increasing the business effectiveness and competitiveness.
An optimal selection of e-activities within individual business subjects in the enterprise environment is
basic precondition for enterprise progress from e-technology utilization’s point of view and a warranty of
effective applying electronic tools.
2. OUTLETS OF THE RESEARCH
As Piccinelli and Stammers (2001) state – the distance between business models and information technology
(IT) is shortening and aggressive business models impose new requirements on IT. Conversely, absorbing
new technology opens new challenges that request a redefinition of current business models and their
periodical changes in cycles according to businesses changes, market progress or new opportunities
(Osterwalder, 2004).
In fact, there are relations within business models, e-technology and e-activities. A lot of enterprise
business models include common and also less common e-activities. We would like to formalize how various
businesses implement new technology to be able to operate selected e-activities responding to their business
model.
That is why our work, which is still in progress, is focused on problems of e-technology implementation
within businesses, expansion of e-activities and their influence to the business model. We would like to
prepare a complex overview of e-technology used within various types of businesses and analyze and define
typical models of using e-activities. We presupposed that results should help to clearly detect advantages of
various types of businesses and eliminate common barriers of adoption.
Our research consists of two related phases (Malo, 2010):
1. Analysis of current state within the area of e-technology implementation in businesses. This analysis is
used as an outlet for a definition of typical models of using e-technology and e-activities and their support. A
set of pieces of knowledge coming from survey involves:
• the identification of basic problems of e-technology implementation and
• the classification of typical e-activities used and supported by various types (groups) of businesses.
2. The second phase covers a qualitative study of gained results from the phase one. All activities are
addressed to finding relevant criteria for comparing the state of e-technology using in various businesses and
defining basic methodic approach for support e-technology and accepting e-activities as a part of business
model.
3. CURRENT AND FUTURE WORK
The main e-activities covered by our research are e-commerce (including e-procurement), e-marketing, elearning, e-management and e-government and very interesting facts and questions could be in given
domains.
We have surveyed various businesses and first results show us innovative thinking of the most of them.
We can for example state that e-marketing is considered to be the most important e-activity or e-learning is
understood as a tool for increasing productivity.
On the other hand there are factors affecting positive possibilities. The most important factors are an
ignorance and low acquaintance of enterprise subjects with opportunities and possible benefits offered by etechnology; relatively high variance in e-technology possibilities and their utilization; an insufficient
methodic apparatus to quantify benefits and high level of heterogeneity of available software systems and
components. In fact, it is not clear for businesses how to recognize a potential for progress support hidden in
the using e-technology and e-activities. Simply, managements, that usually make a decision about etechnology implementation, have only ambiguous, low-determined and inexact ideas and knowledge about
possibilities. The process of implementing e-technology suffers from entire lack of suitable sources of
information and model case studies.
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IADIS International Conference e-Commerce 2011
Thus, we are preparing recommendations how to compare the level of using e-technology and e-activities
within various types of businesses and clearly answer a few questions as how is it possible to measure and
compare level of using e-technology or e-activities or when is it possible to claim that business has optimal
level of used e-technology or any deficiencies existing in this context.
Because a lot of various types of businesses with a different level of using e-technology and e-activity
support can be found in the business environment, there are also differences in characteristics of these
businesses as size, sector, organization and many others. That is why the comparison based upon simple eactivities or e-technology matching is not relevant, results would be misleading.
Described fact is the main reason why we are working on preparing a group of general models for various
types of businesses (micro, small, medium and large) from various lines and branches. These models are
being defined according to our surveys and in future each business will be able to process self-comparison
with relevant general model.
The web application that is being developed within our research activities too will represent the special
tool for base automated comparison and the source for information about business e-technology. We hope
this application would help businesses to recognize the importance of e-technology and e-activities and their
support.
4. CONCLUSIONS
One of current priorities within businesses is an effort to increase efficiency and expand own business
territories. E-technology and e-activities are understood by specialists as one of alternatives how to support it.
There are various barriers to e-technology adoption and also various needs from different types of businesses.
Our research focuses this state and tries to support and improve given situation.
We guess our research and final results will be available at the end of 2011. Although our work is
primarily limited to Czech Republic, we expect that result will be applicable also to other comparable
countries taking current state and historical consequences into account.
Our work is a kind of contribution to exploring the current state and the importance of economic
informatics and its impact to business efficiency and progress. That is why results of the research are and will
be also applied as a part of special courses at our faculty aiming e-technology domain.
ACKNOWLEDGEMENT
This research is supported by Czech Science Foundation, project 402/09/P271.
REFERENCES
Malo, R.: E-activities Based Business Model: The Case for E-technology Implementation. In Proceedings of the IADIS
International Conference on e-Commerce. Freiburg: IADIS Press, 2010, p. 173–176. ISBN 978-972-8939-24-3.
Osterwalder, A.: The Business Model Ontology – A Proposition in a Design Science Approach [online]. Lausanne:
Licencié en Sciences Politiques de l'Université de Lausanne, 2004. [cited 2010-03-28]. Available from
<http://www.hec.unil.ch/aosterwa/PhD/Osterwalder_PhD_BM_Ontology.pdf>.
Piccinelli, G. Stammers, E. From E-Processes to E-Networks: an E-Service-oriented aproach [online]. 2001, [cit. 201101-24]. Dostupné z <http://www.research.ibm.com/people/b/bth/OOWS2001/piccinelli.pdf>.
Tassabehji, R. et al. 2007. E-technology and the emergent e-environment: Implications for organizational form and
function. The Journal of High Technology Management Research, Volume 18, Issue 1, p. 15–30.
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AUTHOR INDEX
Ahola, H. ........................................................189
Ahola, J...........................................................189
Aïmeur, E. ........................................................59
Al fawwaz, B..................................................114
Al nawayseh, M..............................................114
AlGhamdi, R. .................................................153
Ali, A..............................................................175
Al-khaffaf, M..................................................107
AlQifari, R........................................................19
AlSoufi, A. ............................................... 11, 207
Balachandran, W. ...........................................114
Bang, H...........................................................185
Berg, J.............................................................129
Braun, D. ........................................................199
Carrillo, J..........................................................35
Chang, C.........................................................145
Chen, L. ..........................................................145
Chiang, M. .....................................................145
Colbaugh, R................................................51, 67
Delgado, B........................................................35
Dolák, R. ............................................................3
Drew, S...........................................................153
Fan, Q. ..............................................................27
Finkelstein, M. ...............................................180
Garbarino, H.....................................................35
Glass, K. .....................................................51, 67
Griffiths, G. ....................................................121
He, T.................................................................75
Hettich, M.........................................................91
Hsieh, M. ........................................................217
Isern-Deyà, A. ................................................211
Jang, S. .............................................................99
Kaehler, J........................................................199
Karla, J. ..........................................................199
Keretho, S.......................................................129
Kung, C. .........................................................217
Lee, D. ..............................................................99
Lin, H. ........................................................43, 75
Löffler, C..........................................................91
Malik, Z.................................................. 170, 175
Malo, R. .........................................................223
Martins, F. ......................................................137
Mut-Puigserver, M. ........................................211
Nguyen, A. .....................................................153
Nguyen, J........................................................153
Norta, A.......................................................... 194
Öğüt, H........................................................... 165
Paniza-Fullana, A........................................... 211
Park, H. ............................................................ 99
Payeras-Capellà, M. ....................................... 211
Pruksasri, P. ................................................... 129
Rezaei, N........................................................ 121
Shafqat, M...................................................... 170
Shin, K. .......................................................... 220
Slaninová, K....................................................... 3
Sowaileh, A...................................................... 11
Suchánek, P........................................................ 3
Tallat, A. ........................................................ 220
Torres, A. ....................................................... 137
Touré, F............................................................ 59
Wang, Y.M....................................................... 75
Wang, Y.S........................................................ 75
Wasly, H. ....................................................... 207
Watjatrakul, B. ................................................. 83
Wu, S................................................................ 75
Wu, W. ........................................................... 217
Wu, Y............................................................. 217
Yang, C. ......................................................... 145
Yasuda, H....................................................... 220
Yen, C. ........................................................... 145
Ykhlef, M......................................................... 19