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Exploring Web 2.0 Applications as a Mean of Bolstering up
Knowledge Management
Thomas Bebensee, Remko Helms and Marco Spruit
Utrecht University, Netherlands
[email protected]
[email protected]
[email protected]
Abstract: Web 2.0 applications aim at improving the interaction between users. Web 2.0 principles overlap with
characteristics of knowledge management (KM) or could be applied to reshape KM practices. Applying Web 2.0
applications to KM has the potential to improve the sharing and creation of knowledge. However, little research has
been conducted in this area. This research aims at identifying Web 2.0 applications for bolstering up organizations’
KM practices. An additional aspect addressed is how Web 2.0 applications for KM can be categorized and how they
match different aspects of the KM strategy of an organization. The research examines the suitability of Web 2.0
applications in KM by conducting exploratory case studies in two student-run organizations, which are an interesting
research subject because their members are considered most open towards new technologies. The case studies aim
at exploring which Web 2.0 applications are in place. Based on the findings we propose a framework for categorizing
Web 2.0 applications for KM. The findings indicate that Web 2.0 applications may enhance KM and may even initiate
a new era of KM. Moreover, the article provides a discussion of a number of Web 2.0 applications and proposes a
way of categorizing these applications. The proposed framework allows assessing the use of Web 2.0 applications
for KM and can be used as an orientation for the introduction of Web 2.0 applications in organizational KM. The
research contributes to the general understanding of how Web 2.0 applications can be used in KM. The proposed
framework for categorizing Web 2.0 applications provides an orientation for organizations that want to use these
applications for bolstering up their KM practices.
Keywords: Web 2.0, collective intelligence, user-generated content, social computing, knowledge management, KM
2.0
1. Introduction
Today, an increasing amount of organizations recognize the importance of their workforces’ knowledge
as assets leveraging competitive advantage. This development gave rise to the emergence of knowledge
management (KM). The KM discipline describes how knowledge-intensive organizations can develop a
strategy and design an approach to manage the creation, sharing and application of knowledge in order
to perform better and reach their overall strategic goals (Dalkir 2005).
With the dot-com crash in 2001, a new era of the World Wide Web began, which is often referred to as
Web 2.0 (O'Reilly 2007). Since then organizations have begun to adopt Web 2.0 applications and
techniques such as wikis and social networking for leveraging and improving their core processes (Chui
et al. 2009). A systematic search on Google Scholar and other literature databases with different
combinations of the keywords “Web 2.0” and “knowledge management” and some of their synonyms
revealed that little research has been conducted to examine the impact of Web 2.0 on organizational KM
practices. This brings us to our research question:
How can organizations use Web 2.0 applications for managing knowledge and which impact do they
have on KM?
By conducting explorative case studies the research contributes to the general understanding of how
Web 2.0 applications can be used to support or enable KM. The results are captured in a framework of
Web 2.0 applications that organizations can use for bolstering up their KM practices.
The paper is structured as follows. Section 2 gives an introduction to the field of KM and Web 2.0.
Section 3 presents the findings from the case studies. Section discusses the findings and a KM spectrum
for Web 2.0 applications is proposed. Section 5 contains conclusions and indicates areas of further
research.
2. Theoretical background
This section elaborates on relevant aspects of KM, Web 2.0 and the implication of Web 2.0 on
organizations.
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©Academic Publishing International Ltd
Reference this paper as: Bebensee, T, Helms, R and Spruit, M. “Exploring Web 2.0 Applications as a Mean of
Bolstering up Knowledge Management” The Electronic Journal of Knowledge Management Volume 9 Issue 1 (pp19), available online at www.ejkm.com
Electronic Journal of Knowledge Management Volume 9 Issue 1 2011
2.1 Knowledge management
KM is a young but relevant field in today's economy. Jashapara defines it as “the effective learning
process associated with exploring, exploitation and sharing of human knowledge that use the appropriate
technology and cultural environments to enhance an organization’s intellectual capital and performance”
(Jashapara 2004). In many large organizations, knowledge-management projects have been run,
resulting in overall success (Davenport et al. 1999).
However, KM encompasses a variety of different aspects and can be regarded from a number of
perspectives. Binney's (2001) KM Spectrum combines various KM theories, tools and techniques
discussed in literature in one single framework. The six elements of the KM spectrum are:

Transactional KM applications present knowledge to the user in the course of an interaction with a
system.

Analytical KM solutions allow for creating new knowledge from vast amounts of data or information by
providing certain interpretations.

Asset management involves the managing of knowledge assets and making them available to people
when they are needed.

Process-Based KM deals with the codification and improvement of processes in order to come up
with „engineered assets’. This often involves using methodologies stemming from other disciplines
such as Total Quality Management.

Developmental KM aims at improving and developing the competencies or capabilities of an
organization’s knowledge workers including both tacit and explicit knowledge.

Innovation and creation KM fosters an environment in which knowledge workers, preferably with
different backgrounds, can come together to create new knowledge.
In the following we use Binney’s framework for analyzing KM in two organizations.
2.2 Web 2.0
A glance at Google’s search history shows an increasing interest for the term “Web 2.0” since its
emergence in the early 2000s. This shows the term’s popularity but what does it actually stand for? In a
2006 report Musser and O'Reilly speak of it as “a set of economic, social, and technology trends that
collectively form the basis for the next generation of the Internet”. However, some people argue that Web
2.0 is merely a meaningless marketing buzzword (Brodkin 2007). It seems necessary to further illuminate
it and its context in order to come up with a definition of the concept.
In 2004, the term gained popularity when O’Reilly Media and MediaLive initiated the first Web 2.0
conference (O'Reilly 2007). O'Reilly and others (Hoegg et al. 2006; McAfee 2006; Vossen & Hagemann
2007) came up with a number of general principles describing the properties of Web 2.0. Knol, Spruit and
Scheper (2008) compared the principles proposed by different authors and proposed a generic set of
Web 2.0 principles (they refer to them as Social Computing principles) that are depicted by the nine
circles in Figure 1.
Knol et al. (2008) point out that the four principles in the bottom of Figure 1 are technically oriented and
provide the fundament for the five socially oriented principles in the top. We argue that the phenomenon
of Web 2.0, i.e. what you can see about it, can be mainly related to the socially oriented principles that
are enabled by a set of Web 2.0 Technologies. Therefore, we propose the following definitions based on
the Web 2.0 principles:
Web 2.0 is the reorientation of the Web that promotes unbounded interaction, collaboration
and participation of people. It is characterized by the emergence of a large amount of
content generated by a collective of Internet users. It harnesses networking effects and
leverages the long tail.
Web 2.0 Technologies are technologies that transform the Web into a platform spanning all
connected devices. They enable the creation of web-services and applications, constructed
from lightweight models, and can be used intuitively.
Some examples of Web 2.0 Technologies are AJAX and lightweight scripting languages like PHP, Perl,
Python and Ruby (Andersen 2007).
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Unbounded
Collaboration
Blogs
Polling
Usergenerated
content
Collective
Inteligence
Social
Bookmarking
Wikis
Technically
Oriented Principles
Applications
Socially Oriented
Principles
Thomas Bebensee et al.
Micro Blogging
Enabling
Services
Leverage the
Long Tail
Shared
Workspaces
Commenting
Social
Bookmarking
Media Sharing
Customer SelfService
Network
Effects
Data Mash-Up
Open
Platform
Tagging
User Tracking
Leightweight
Models
Rating
Intuitive
Usability
Figure 1: Web 2.0 principles (adopted from Knol et al., 2008) and popular applications
By reviewing literature (Chui et al. 2009; Andersen 2007; Knol 2008) we identified a number of common,
but certainly not all, Web 2.0 applications, services and techniques (in the following only referred to as
Web 2.0 applications). They are depicted in the middle layer of Figure 1. We added “Micro-Blogging” (e.g.
Twitter) as application since we think that this considerably new trend can be valuable for KM as
explained later.
2.3 Enterprise 2.0
Technology adoption type
Applying Web 2.0 principles on companies is widely referred to as Enterprise 2.0 (McAfee 2006;
Tredinnick 2006; Levy 2009). Levy reviewed literature dealing with Enterprise 2.0 and proposes a matrix
(Figure 2) that structures Enterprise 2.0 according to two dimensions: the type of technology used and
the type of user that is being addressed.
Applications &
tools
Knowledge
Management
System
infrastructure
Marketing
Technology Enhancement
Internal
External
User Orientation
Figure 2: Enterprise 2.0 segments (adapted from Levy, 2009)
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The “technology adoption type” dimension distinguishes between two types of adoption: Web 2.0 system
infrastructure (developing in lightweight models, using AJAX etc.), which can be related to the
technological aspect of Web 2.0 as introduced in the previous section; and secondly Web 2.0
applications and tools (using wikis, blogs, tagging etc.), which stem from the phenomenon aspect of Web
2.0.
The “user orientation” dimension distinguishes between the use of these technologies with an internal (by
and for the organization) and an external focus (facing customers, suppliers and other external
stakeholders). As suggested by the matrix in Figure 2, KM enabled by Web 2.0 principles is one specific
aspect of Enterprise 2.0 that encompasses an internal focus together with adoption of Web 2.0
applications and tools.
This raises the question which Web 2.0 applications have an impact on KM. Are they just an
enhancement of KM practices by a number of fancy tools or do they pave the way for of new kind of KM,
a KM 2.0? By conducting case studies in two student-run organizations why attempt to answer this
question.
3. Cases studies
Due to the exploratory nature of the research question case study research (CSR) was chosen as the
principal research method. CSR is a research method that is applicable in situations where a number of
variables are to be observed in a real life context and where this observation cannot simply be limited to
an analysis of data points (Yin 2008: 18). It can involve both qualitative and quantitative evidence and is
especially applicable to real-life situations that are too complex for survey and experimental research (Yin
2008: 19).
In order to explore how Web 2.0 can be used for KM we studied two student organizations. The analysis
was divided into three steps:

1. Analyze the KM function using Binney’s KM spectrum;

2. Determine which technology, especially in regards to Web 2.0, is used to support specific elements
of the KM spectrum;

3. Provide recommendations regarding the potential of Web 2.0 applications for KM.
A recent study published by Pew Research Institute shows that the largest group of people using the
Internet, in fact, consists of people born between 1977 and 1990 (Jones & Fox 2009). In a 2009 article on
Web 2.0’s implications on KM, Levy proposes to use the young generation as pioneers of Web 2.0 in
organizations to leverage KM practices. Obviously, the generation of today’s students is the most active
group of Internet users and thus most familiar with the new technologies of Web 2.0. We therefore think
that student-run organizations are an interesting subject for researching the implications of Web 2.0 on
KM practices.
The case studies involved a number of semi-structured interviews with key personnel and a review of IS
fragments of AIESEC in Germany and MARKET TEAM, which are two of Germany’s largest student-run
organizations. Prior to carrying out research we developed a case study protocol that described field
procedures and the principal questions to be answered.
Both organizations are non-profit organizations (NPOs) and are run by student volunteers on the local
level and students working fulltime on the national level. In general, people change position every year
which makes knowledge retention a key challenge. As in the NPO domain in general, knowledge in the
two organizations can be classified into accounting / administrative, managerial / organizational, teaching
/ training, fund raising / public relation management / marketing, operational and miscellaneous
knowledge (Lettieri et al. 2004).
Both organizations are at different stages of adopting Web 2.0 technologies to enhance their KM
practices. Due to their different size and scope (national vs. international) they also differ considerably in
regard to their KM needs as indicated by Hume & Hume (2008).
3.1 MARKET TEAM
MARKET TEAM e.V. (in the following MT), solely operating in Germany, aims at providing students
insights into the business world by organizing events like workshops, trainings and symposia with
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Thomas Bebensee et al.
companies. The organization has around 1000 members in 23 chapters (Market Team 2010). KM aims at
supporting day to day operations of the organization, which mainly consist of running various projects on
both the local and the national level. In general, KM takes place on the local level. There is no knowledge
sharing between different chapters. At the moment the organization runs an initiative that aims at
improving knowledge sharing between local chapters to build on synergy effect, i.e. re-use knowledge in
different parts of the organization.
We analyzed MT’s KM function using Binney’s (2001) KM spectrum and identified the aspects shown in
the upper part of Figure 3. Below we listed the web applications used to support these KM aspects.
 Help Desk
Applications
Analytical
 Customer
Relationship
Management
(CRM)
Web 2.0
Applications
KM Applications
Transactional
Asset
Management
 Document
Management
 Knowledge
Reporsitories
 Content
Management
Process
 Best practises
 Quality
Management
 Process
Automation
 Media Wiki
 Dropbox
Innovation and
Creation
Developmental





Skills Development
Staff Competencies
Learning
Teaching
Training






Communities
Collaboration
Discussion Forums
Networking
Virtual Teams
Multi-disciplined
Teams




Media Wiki
StudiVZ
Mindmeister
Google
Spreadsheets
 Google Docs
Figure 3: KM and Web 2.0 applications used for KM by MT
In the past ten years MT has been using a custom developed web platform for fostering communication
between the national board and the chapters, for administering member data, for exchanging information
and experiences about completed projects and for storing information about partner companies. Since
the platform is mainly designed for unilateral communication from national to local level, the organization
is currently evaluating how it can be replaced by a more interactive platform leveraging Web 2.0
technologies.
Some local chapters use wiki platforms based on MediaWiki for facilitating project management. In
general, information and experience report from previous projects and manuals how to run a project are
retrieved from the national web platform and the local platform is used mainly for facilitating
communication and collaboration between the members of project teams. In addition they may guide
project teams through the process of running a project.
Besides physical meetings, communication mainly takes place through emails but also through StudiVZ,
a large German social networking platform. These channels are therefore the main mean of exchange
ideas and contributing to innovation.
Skill development and training solely takes place in physical meetings and apart from providing manuals
and explicit information on the national web platform, no specific web technology is used for this aspect of
KM.
Following the general trend, members have started using free Web 2.0 tools for collaborating and sharing
files with each other. Dropbox is mainly used for sharing and storing documents online. Google Docs and
Spreadsheets and Mindmeister, an online mind map tool, are used for collaboration and idea generation.
These tools were not specifically introduced by the organization, but just appeared to be useful and very
often already known by members from personal use.
3.2 AIESEC Germany
AIESEC has over 45,000 members globally (AIESEC International 2009), whereof more than 2,500 are
from 47 chapters in Germany. The organization aims at developing tomorrow’s socially responsible
leaders by running an integrated leadership development program and providing coordinating internships
at its partner companies around the world (AIESEC International 2009). Due to its size and international
scope AIESEC’s KM is directed at leveraging economies of scale by providing one single web platform
connecting members from around the world. In accordance with Hume and Hume (2008) KM in general
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can be considered operationally and strategically mature and KM structures try to capture both explicit
and tacit knowledge. A key challenge of AIESEC’s KM is to find the best KM approach that fits all the
different cultures and national branches’ needs (size differs significantly reaching from a few dozen to
thousands of members in some countries). Therefore, KM programs are mainly run on the national level,
although making it available to the global network is also a concern.
In 2007, the national executive board of AIESEC Germany decided to foster the vision of a “member
driven organization”, i.e. a bottom-up organization that benefits from the contribution of every single
member. In order to achieve this from a KM perspective steps have been taken to adopt Web 2.0
applications such as wikis to enable every member to contribute to the organizational knowledge base.
Since then the organization has adopted a number of Web 2.0 applications to improve collaboration and
knowledge sharing between its members. The upper part of Figure 4 provides an overview of different
KM aspects in AIESEC Germany and the bottom part shows Web 2.0 applications used for supporting
these aspects.
 Help Desk
Applications
Web 2.0 Applications
KM Applications
Transactional
Asset
Management
Analytical
Process
 Customer
Relationship
Management
(CRM)
 Business
Intelligence
 Document
Management
 Knowledge
Repositories
 Content
Management
 Best practises
 Quality
Management
 Process
Automation





 Google Analytics
 Google Forms
 Tagging






 Brandkore
 Google
Presentation
 Slide Share
 Google Video
 WizIQ
 Teamviewer
 Meetgreen
Web Portal
OpenCMS
Google Video
Youtube
Flickr
Wikis
Innovation and
Creation
Developmental
Skills Development
Staff Competencies
Learning
Teaching
Training






Communities
Collaboration
Discussion Forums
Networking
Virtual Teams
Multi-disciplined
Teams
 Google
Spreadsheet
 Google Docs
 Google Calendar
 Mind42
 Goggle Mail
 Google Talk
 Skype
 Facebook
 Blogspot
 Twitter
 WIkis
Figure 4: KM and Web 2.0 applications used for KM by AIESEC Germany
AIESEC’s global web platform contains a wiki module in which every user can create wiki pages. Two
years ago, AIESEC Germany has switched from a Lotus Domino powered knowledge base to providing
knowledge assets in these wiki pages. Information in AIESEC’s global web platform is searchable
through an advanced search function based on tags and elaborated filters. These wikis are used for
storing information such as manuals, contain processes documentations and are used for collaborative
idea generation (e.g. virtual brainstorming sessions). Even though wikis should enable everybody to
contribute content or enrich other people’s contributions, only a limited number of members have actually
been doing it and most of them are nationally active. Since there were some problems with the usability
of the platform when it was launched, an interviewee supposed that the problem might be related to that.
AIESEC recently started using Google Apps, a bundle of collaborative web applications. Its word
processing module and its spreadsheets module are mainly used for documentation (e.g. minutes) and
idea generation (e.g. brainstorming). The presentation module is used for virtual education and the video
module is used to distribute education videos. A module that allows for creating forms that is used for
creating surveys amongst members. In addition, for improving interaction and information exchange
between the members a webmail application and a built-in instant messaging client that is identical with
Google’s consumer product Gmail is used. According to an interviewee the acceptance of Google Apps
was significantly facilitated by its intuitive interface and the fact that users already knew the applications
from personal use.
In order to streamline their marketing material creation, which needs to be customized for each chapter,
AIESEC uses Brandkore, a web-based marketing automation tool. Consequently, members do not need
to be familiar with using complicated graphic suits anymore
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In order to facilitate the development and learning of its members AIESEC uses a number of e-learning
applications such as the platform WizIQ and Teamviewer in combination with web-controlled telephone
conferencing tools such as Meetgreen. The organization is currently evaluating the use of web-based
video conferencing tools such as Netviewer that allow multiple users to see and interact with each other.
In order to keep members up to date a news module and a classifieds module in the global web platform
of AIESEC are used. In addition, a public Google Calendar is used to inform members about upcoming
events. Although some communication channels such as Facebook and Twitter are intended for
communication with external stakeholders, members have started using them for internal
communications and collaboration amongst each other as well.
4. Discussion
The two case studies show that Web 2.0 applications can be used for KM. When we look at Binney’s KM
spectrum and the Web 2.0 applications matched with the respective elements (see Figure 3 and 4), we
notice that apparently not all elements of the spectrum are associated with Web 2.0 applications.
We used the findings from the case studies to derive a number of generic Web 2.0 applications (as those
in Figure 1) and mapped them to the KM spectrum. The result is shown in Figure 5.
Supporting
Principles
Web 2.0
Applications
Transactional
Analytical





Polling
Tagging
Social Networking
Ratings
Social
Bookmarking
Asset
Management
 Wikis
 Media Sharing
 Blogging
Collective Intelligence
Process
Innovation and
Creation
Developmental
 Social Networking
 Shared
Workspaces
 Media Sharing
 Podcasts





Wikis
Micro blogging
Blogs
Social Networking
Shared
Workspaces
Unbounded Collaboration
Network Effects
Network Effects
User Generated Content
Leverage the Long Tail
User Generated Content
Leverage the Long Tail
Figure 5: Web 2.0 principles mapped to the KM spectrum
We added some applications (italic font type in Figure 5) to the ones that we found in the case studies
since we found some evidence in literature that they can be used for KM. Hideo and Shinichi (2007)
describe how communication data generated from Web 2.0 applications such as social networking
platforms can be used to create new knowledge. Chui et al. (2009) note that data from social
bookmarking and ratings can be used for creating additional information. Anderson (2007) describes how
podcasts can be used for educational purposes. We did not derive a generic Web 2.0 application from
Brandkore that we identified in the AIESEC case because we think that is an applications that mainly
builds on the technological enhancement aspect of Web 2.0 and cannot be related to any socially
oriented Web 2.0 principle.
In a second step we used the mapping of Web 2.0 applications to associate the socially oriented Web 2.0
principles with the elements of the KM spectrum.
“Collective Intelligence” refers to the fact that a large collective can create more content than a small
number of experts (Knol et al. 2008) and that intelligence can be derived from data created by a large
number of users (Anderson 2007: 41). This applies to analytical KM and asset management. Analytical
KM applications may create information from large amounts of user data such as social bookmarking and
ratings. Wikis, as an asset management tool, also rely on this principle because their content may be
created by large numbers of users whereof everyone just contributes a small amount.
“Network Effects” refer to services that get better, the more people use them (Knol et al. 2008). This
applies to basically all analytical KM applications that we identified. Also the content of wikis and other
asset management applications benefits from network effects. Finally, also network effects are also
relevant to social networking and micro blogging that are related to innovation and creation KM.
“User Generated Content” refers to the large amount of content that is generated by users (Knol et al.
2008). This content may be stored in asset management applications such as wikis, blogs or media
sharing platforms. The fact that users generate content also leads to an increased creation of ideas and
innovation. However, it should be noted that quality of content might become an issue in comparison with
traditional KM approaches where content is mainly generated by a small number of experts. Apart from
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that there might be a risk of a low user participation in content creation (Tredinnick 2006). This issue is
clearly linked to organizational culture. Consequently, only certain types of organizations may benefit
from user generated content. Tredinnick (2006) suggests that especially dynamic organization in a fast
changing environment and built on a high degree of innovation may benefit from this aspect of Web 2.0.
“Leverage the long tail”, i.e. the exploration of niches (Knol et al. 2008), applied to micro blogging and
social networking services may be beneficial for knowledge creation in such a way that users may
exchange snippets of information that they would otherwise not have known about. These micro
messages may lead to creation of new ideas and innovations. In addition, we think that analytical KM
might also benefit from the long tail in such a way that the interaction of users can be used as an
additional source for data mining as suggested by Hideo and Shinichi (2007).
“Unbounded collaboration” refers to a form of collaboration that is independent from place and time, i.e.
time differences and different locations do not matter anymore. It enables creativity processes that were
not possible before. Furthermore, this novel kind of collaboration might also lead to cost and time savings
because travel might be reduced. This also has an impact on training and education because e-learning
and virtual conferencing applications may be used.
This discussion shows that Web 2.0 applications may be beneficial to four elements of Binney’s (2001)
KM spectrum, i.e. analytical KM, asset management, developmental KM and innovation and creation.
Although transactional and process-oriented KM does not seem to benefit from Web 2.0 applications, it
may benefit from enhancing technology by adopting technical principles. For instance, the AIESEC case
suggests that intuitiveness is a key enabler for the acceptance of a new technology.
In the case of AIESEC we have also found out that there does not seem to be such a clear differentiation
between internal and external use of Web 2.0 applications as proposed by Levy (2009) (see Figure 2)
because organizational members communicate about internal subjects in open channels, e.g. social
networking sites. This overlap of internal and external communication might become a real problem for
the organization by decreasing the attractiveness of public relation campaigns and by making confidential
information available to public. We assume that one possible reason for this blend of communication
could be that organizational members do not find the communication channels that they desire to use
inside the organizations. By introducing and fostering internal social networking platforms organizations
may mitigate this issue.
5. Conclusions
The research question, as proposed in section 1, states:
How can organizations use Web 2.0 applications for managing knowledge and which impact
do they have on KM?
We conducted exploratory case study research in two study-run organizations to explore in how they use
Web 2.0 applications for different aspects of their KM strategy. Based on the findings we were able to
identify which aspects of KM, as described in Binney’s (2001) KM spectrum, benefit from Web 2.0
applications. As a last step we created a generic KM spectrum for Web 2.0 applications.
The research suggests that analytical KM, asset management, developmental KM and innovation &
creation may benefit from the adoption of Web 2.0 applications. Depending on the organizational culture
these applications may even lead to a novel kind of KM. This new approach to KM would not just benefit
from a technology enhancement of the existing applications, but also lead to a new understanding of KM
that is based on user contributions, a novel way of unbounded collaboration and leveraging the long tail
of user interaction data. In our opinion, it would therefore be appropriate to refer to this as KM 2.0.
The findings in this research are based on two case studies. To expand external validity of the findings
research should be extended by replicating the case study in different types of organizations. It would be
interesting to have a look at other types of non-profit organizations and for-profit organizations and
examine if there are considerable differences in term of KM and the impact of Web 2.0 applications. The
framework proposed in Figure 6 can be used for providing recommendations to organizations that intent
adopting Web 2.0 applications for bolstering up KM. Therefore, the applicability as a tool for providing
recommendations should also be tested.
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As we observed a low participation in wikis in one of the cases (AIESEC) and no knowledge sharing
between different chapters of the other organization (MT), we suppose that organizational culture and
structure have a major effect on the effectiveness of adopting Web 2.0 applications for KM. Further
research should therefore investigate the influence of organizational culture and other factors on the
effectiveness of adopting Web 2.0 applications for KM.
References
AIESEC International (2009) "Welcome to AIESEC International", [online],
http://www.aiesec.org/cms/aiesec/AI/students/index.html.
Andersen, P. (2007) What is Web 2.0?: ideas, technologies and implications for education, JISC, London.
Binney, D., (2001) "The knowledge management spectrum-understanding the KM landscape", Journal of Knowledge
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Inter-Generational Learning Dynamics in Universities
Constantin Bratianu, Adriana Agapie, Ivona Orzea and Simona Agoston
Academy of Economic Studies of Bucharest, Romania
[email protected]
[email protected]
Abstract: Inter-generational learning is an open process people of all ages can learn from each other in a stimulating
context. It is a complex process of knowledge sharing that overcomes age and cultural barriers. Inter-generational
learning is more specific for those organizations where people group together in age layers or strata. Universities are
such kind of layered or nested organizations. The purpose of this paper is to present some results of our research in
the field of inter-generational learning and knowledge sharing in universities. This topic is important because a
university is by its own nature a nested knowledge organization, due to a continuous flow of students and the bottomup regeneration of the faculty staff. Knowledge creation and knowledge loss are intertwined processes, and both of
them are strongly influenced by the age scale. A university is a multilayered knowledge organization, where the inner
most layers are represented by older professors who concentrate the fundamental structures of knowledge, and the
outer layers are represented by students in their different learning cycles. In this paper we are interested in assessing
the choices done by the academic staff, in the context of the determinant criterions and trade-offs in intergenerational learning. This had been done in the framework of Analytic Hierarchic Processes (AHP). We thought that
this is a proper tool since it mainly belongs to the field of decision-making with the possibility to determine vectors of
priorities for the individuals participating in the decisions under study.
Keywords: learning dynamics, university, knowledge sharing, knowledge creation, analytic hierarchy process
1. Introduction
Universities are social institutions with long life cycle. The venerable Bologna University dates from 1088,
and the famous Oxford University dates from 1187. Main activities associated with those days
universities were collecting knowledge, preserving it and passing it on. Creating new knowledge was not
a part of university’s mission. A professor was mostly a scholar and not a researcher. Learning was a
process based mostly on transferring knowledge from one generation toward the other. In 1809, Wilhelm
von Humboldt established the Berlin University, based on a new paradigm. According to his vision, a
university should approach knowledge scientifically. It should produce knowledge, not only to re-produce
it (Harayama, 1997, p.9). Today, the research universities integrate perfectly knowledge generation with
knowledge dissemination. Knowledge production and learning processes at individual and organizational
levels transform the university into a knowledge intensive organization, which fits excellently with the new
requirements of the knowledge society. Moreover, they may become learning organizations if double-loop
learning and organizational integrators are well developed (Armstrong & Foley, 2003; Bratianu, 2007;
Bratianu, 2008; Ortenblad, 2001; Stewart, 2001).
Learning is a knowledge intensive process at both individual and organizational level. It is a strong
nonlinear process that integrates several activities: perception, knowledge acquiring, dynamics of tacit
and explicit knowledge, dynamics of cognitive and emotional knowledge, structuring and re-structuring
through a continuous dynamics, knowledge storage, knowledge removal from the memory, and
knowledge creation through a conscious effort (Bratianu, 2009; Bratianu & Orzea, 2009; Fauconnier &
Turner, 2002; Pinker, 2007; Lakoff & Johnson, 1999; Nonaka & Takeuchi, 1995). Inter-generational
learning (IGL) is a specific process of knowledge transfer from one generation toward another generation,
focusing more on tacit knowledge and competences that require experience and skills. The transfer is
always done from people of higher level of knowledge toward people of lower level of knowledge, in
concordance with the law of entropy (Bratianu, 2010). In the same time, IGL stimulates reciprocal
learning relationships between different generations and helps to develop social capital and social
cohesion. IGL became in the last years an important issue in Europe due to population ageing and
knowledge loss from organizations with the old employees retirement. IGL stimulates creativity and
innovation by melting down barriers between generations. IGL becomes a dynamic capability (Teece,
2009) especially of those organizations where individuals group themselves in age layers or strata.
Universities are such organizations and IGL is a natural process. A university is by its own nature a
nested Ba since in any department there are several age layers represented by professors, associated
professors, lecturers and assistants. In such a context, it is interesting how knowledge sharing is
configured according to priorities given by professors to different academic strategies and activities. The
concept of Ba has been developed by Nonaka and Takeuchi: “The essence of Ba is the contexts and the
meanings that are shared and created through interactions which occur at a specific time and in a
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Reference this paper as: Bratianu, C, Agapie, A, Orzea, I and Agoston, S. “Inter-Generational Learning Dynamics in
Universities” The Electronic Journal of Knowledge Management Volume 9 Issue 1 (pp10-18), available online at
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Electronic Journal of Knowledge Management Volume 9 Issue 1 2011
specific space, rather than a space itself. Ba also means relationships of those who are at the specific
time and the specific space” (Nonaka & Takeuchi, 2007, p.23).
The purpose of this paper is to investigate the dynamics of IGL by using the mathematical model of the
Analytic Hierarchy Process (AHP), in the Romanian university environment (Harker & Vargas, 1987;
Liang et al., 2008; Saaty, 1994). This topic is important because a university is by its own nature a nested
knowledge organization, due to a continuous flow of students and of the bottom-up regeneration of the
faculty staff. Knowledge creation and knowledge transfer are intertwined processes, and both of them are
strongly influenced by the age scale. A university is a multi-layered knowledge organization, where the
inner most layers are represented by older professors who concentrate the fundamental structures of
knowledge, and the outer layers are represented by students in their different learning cycles. Although
the AHP method belongs to the rational approach of the decision making process, the way in which we
structure the field of interests and motivation of the faculty staff in the analysis of IGL involves also the
non-rational approach based on emotions, trust and transparency. As Tomé and Kianto remarked, “In
sum, knowledge sharing and transfer are fundamentally based on interpersonal issues. It doesn’t seem
that all of those could be completely explained by purely rational calculations. At the present stage of our
research we would think that emotions and soft issues like trust are at least as important as rationality in
the processes of knowledge sharing and knowledge transfer” (Tomé & Kianto, 2009, p.480).
2. Inter-generational learning in knowledge economies
The problem of IGL is generally summed up in the framework of asymmetric information. The additions of
elements from psychology into economics of information lead to the consideration of the some explicit
details in this particular problem of asymmetric information. Among these, the most important seem to be
the incentive salience conflict (conventionally, a conflict between the relative weight in utility attached to
tempting versus no tempting goods), the temporal horizon conflict (born from the importance attached to
distant events versus temporally close one) and the asymmetric information conflict (a conflict between
the information available in different areas subsumed to the research region).The latest developments in
neuroeconomics conduced to models of brain as a hierarchical organization (Brocas & Carrilo , 2008) in
which, in order to model temporal and informational conflicts an individual is split into an
impulsive/myopic agent and a cognitive/forward looking principal. Yet, this dichotomy between impulsive
(through temporal horizon conflict and asymmetric information conflict) and reflexive behavior (expressed
through incentive salience conflict) - a long term object of neuroeconomics research (Thaler &
Shafrin,1981, Shafrin & Thaler, 1988, Lowenstein,1996) - has been also present in the framework of
organization theory as the dichotomy between relative ability and absolute ability. Effects of competition
in educational institutions regarded as organizations highlighted particular adverse effects in reliance on
relative abilities (also referred in this framework as relative performance) instead of absolute abilities
(expressed through the measurement of performance against objective standards).Thus, it was found
that (Wang & Yang, 2003) in competitive learning game, limited rewards lead to an “ability game”,
therefore competition among students no longer motivates increased effort. On the other hand, there is a
flow of literature devoted to behavioral analysis of the impact of ageing on decision making at the level of
firms challenging mostly negative stereotypes (like seniors are less flexible and willing to change, less
willing to learn but more reliable and determined than juniors, with a lower adaptability to change). These
generalities were splinted into attitude concerning cooperation in teams, attitudes concerning competition
and attitudes toward innovation and studied through experiments in laboratories. In this line, there are
results (Hamilton, Jack, Nickerson & Owan 2003) that show that cooperation is a learned trait and that
the insight developed over a more elderly person’s lifetime may be particular useful in providing a good
example for younger workers to emulate.
In addressing the problem of ageing versus IGL in the framework of education institutions as
organizations - like Academy of Economic Studies of Bucharest is - this paper is going to evaluate
perceptions of the academic staff toward the attitudes of cooperation in teams, competition and
innovation, dimensions that are highly relevant for the success of modern organizations. Opinion about
attitude of cooperation in team is supposed to offer a measure for the individual’s intangible temporal
horizon conflict, opinion about attitude on competition - in a learning environment - is offering a measure
on the asymmetric information conflict of the individual, since he has to be competitive and up to date in
his field, while opinion on innovation is seen as an indicator of the salience conflict. The importance of
each of these attitudes is going to be evaluated under particular alternatives and also weighted from the
point of view of tradeoffs allowed in some situations. Priority vectors for each of these three attitudes and
alternatives will be determined for every member of the academic staff who participated in this research
through the completion of a certain specially designed survey. This will show how the main actors in the
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Constantin Bratianu et al.
intergenerational transfer of knowledge see themselves or equivalent, what are their priorities in these
three main attitudes.
IGL in universities is most intensive through the doctoral programs that contain both research and
studies, and research grants. The highest quoted professors (obligatory PhD supervisors) are involved
through doctoral school in transmitting the most important information to the students and also the state
of art of performing research. These activities are all done in a coherent perspective of cooperation.
Knowledge sharing and knowledge creation are the main components of the knowledge dynamics
process that is focused on IGL. The decision of including a professor in this activity is looking at three
professional criterions: grants, papers and books. In evaluating accomplishments with respect of these
alternatives, some tradeoffs regarding different levels of quality are elaborated by the Romanian Ministry
of Education and by the Universities’ boards over a few sets of criteria. So, on one hand, in considering
the decision to choose in between different members to teach in doctoral school programs, the Board of
University is looking whether some obligatory criterions are compelled. On the other hand, a particular
professor,(senior lecturer, lecturer) can choose his own level of effort in fulfilling these criterions, given
the previously mentioned available tradeoffs regarding different levels of quality (these will be presented
in more detail in the next section).The choice a particular professor is taking - in a complex interplay of its
own interior conflicts and the exterior imposed criterions - is shaping its current teaching activities and
therefore future outcomes.
3. Using AHP for evaluating IGL in the Academy of Economic Studies of
Bucharest
3.1 Structuring the general field of motivation
In order to provide the reader with some background concerning the particular determinants for attitudes
toward cooperation, competition and innovation in a Romanian University like Academy of Economic
Studies of Bucharest is, in the following it will be described in short the determinants of the promotion
process that is currently at place. This is strictly connected with the flow of transfer of knowledge since if
one has to fulfill some criterions it is also true the backward assertion, namely that the value of a person
is the sum of the fulfilled criterions. And this value is very concretely expressed through its wage-a
tangible, measurable variable and also through some intangible aspects, like its determinant participation
in doctoral school or supervision of Master dissertations-main channels in IGL in the considered
framework. Academic staff in Academy of Economic Studies of Bucharest is professionally evaluated
according to its participation in scientific grants (G), number of scientific papers (P) and books (B) and
manuals. For being promoted to the next level (assistant, lecturer, senior lecturer, professor, and
professor-PhD adviser) the cumulated scores for the previous three alternatives need to surpass some
general “cutoff values” established by the Romanian Ministry of Education and Research and each
University’s board.
For example, for someone to apply for a promotion from the position of a senior lecturer to the position of
a professor, four main criterions are considered. The first one regards its teaching activities, relations with
colleagues inside its Department, evaluations form the students and the number of manuals edited in its
specialization. The second one is looking at research activities measured through the number of grants.
A minimal number of two is required with the mention that the candidate had to be director in at least an
international one. The third criterion is looking also at research activities measured through the number of
scientific papers published in prestigious international journals. Five to seven scientific articles are
required and out of these at least four have to be published in ISI quoted journals or indexed in reference
international data bases. Also a minimal number of two books is required, published in selected
publishing companies; the candidate has to be the first author for at least one of these. The last criterion
looks at the so called “professional prestige” which subsumes any other activities like international
recognition given by participation at professional associations, membership in editorial boards,
distinctions and awards.
Apart of this four criterions, there are also available some tradeoffs for the set of criteria looking at the
quality of the grants, papers and books. For instance, being director in an international research grant is
considered to be equivalent to being director for two years in a national research grant. Publication of a
scientific paper in an ISI quoted journal is quoted equal with the publication of four scientific papers in B+
national journals while publication of an article in a journal quoted in international scientific databases is
quoted equal with three B+ papers. These criterions have also some eliminatory specifications elaborated
by each particular University. For instance, in the particular case of the Academy of Economic Studies of
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Bucharest, any scientific grant which is not run through the institution is not taken into consideration. So,
the particular staffs applying for a promotion can for instance fulfills the Ministry’s criterions yet not fulfill
the Academy of Economic Studies of Bucharest internal ones. Given the range of alternatives available
for a university professor, his attitude toward competition can be ranked differently whether he chooses to
apply for an international grant - with all the risks - or go for all the national competitions and don’t bother
to go internationally, or whether he is deciding to put a lot of effort into submitting a paper to an
international journal instead to take the easy way to publish a larger number of papers into national B+
journals. The difference between cooperation and competition from IGL perspective means also the
impact of the process. In any cooperation the IGL process is developed on an open basis and with a
larger impact due to fewer barriers in knowledge sharing.
A professor’s attitude toward innovation can be different if he chooses to spend time to develop a new
theory or new empirical methods of estimations and be competitive at an international level or he decides
that it is better from his personal point of view to add several smaller improvements in its professional
career. His choices are also affecting the message transmitted mostly to his younger clleagues. After all,
it matters if a professor is sending the message “you need to be the best” – and for this, take my example
- or the message: ”satisficing is a pretty good heuristic” (Bendor, Kumar & Siegel, 2009).This common
sense observation is supported by mathematical models of satisficing which explicitly represents agent’s
aspirations and which explores both single-player and multi-player contexts. In this view satisficing has a
signature performance profile in two contexts: it can induce optimal long-run behavior in one class of
problems but not in complimentary class and it generates behavior that is sensible but not optimal. In this
paper we are interested in assessing the choices done by the academic staff, in the context of the above
presented range of criterions and trade-offs. This had been done in the framework of Analytic Hierarchic
Processes (AHP). We thought that this is a proper tool since it mainly belongs to the field of decisionmaking with the possibility to determine vectors of priorities for the individuals participating in the
decisions under study and also there is the possibility to determine individual numerical scales-since
verbal interpretations can differ from one person to another (Liang, Wang, Hua & Zhang, 2008). A second
reason for this approach is that the latest developments in neuroeconomics proved that asymmetry of
information in learning can be modeled at an individual’s scale also in terms of an hierarchic organization
(Brocas & Carrilo, 2008) .
3.2 Determining individuals vectors of priorities
The framework constructed for analysis includes a hierarchy with the three criterions at top: attitude
toward cooperation (C1), attitude toward competition (C2) and attitude toward innovation (C3) and three
specific alternatives located further down the hierarchy: grants (G) ,papers (P) and books (B) .This AHP
structure is illustrated in figure 1. The bottom level of this hierarchy contains possible options according to
the relative importance of the factors involved in the three previous alternatives .The analytical process
includes making judgments on pairs of elements throughout the hierarchy, one level at a time beginning
at the top, based on the respondent’s knowledge and according to theirs perceived relative importance of
the factors involved. The most heavily weighted alternative outcome in the bottom level is the most likely
one. A survey designed according with these principles was electronically distributed among the
academic staff in the Academy of Economic Studies of Bucharest. In order to understand how this was
processed, a short presentation of the way in which the questions were posed in this survey and
processed thereafter will follow. Numerical results and interpretations will be presented in the next
section.
3.2.1 Presentation of the survey with a sample of responses
In the following it will be presented the general form of the survey considered and one example of answer
will be indicated in square brackets, immediately after the question. In the next subsection it will be
showed how the answers were processed.
In the first page were asked general information about the position of the respondent in the Academy of
Economic Studies of Bucharest: the academic status (professor-PhD supervisor, professor, senior
lecturer, lecturer, assistant or PhD student), the Department and the affiliation to a certain Faculty. The
second page was devoted to the determination of the priority vectors of the three chosen criterions in
determining the quality of the transfer of knowledge. This was done through the formulation of questions
in comparative terms, as shown below:
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IGL
Cooperation
(C1)
Competition
(C2)
Innovation
(C3)
Grants
(G)
Papers
(P)
Books
(B)
Figure 1: The AHP structure
1. Please, indicate on a scale from 1 to 9 (1-indifferent, 9-full agreement)to what extent you agree with
the next assertion: ”In the framework of intergenerational transfer of knowledge, attitude toward
cooperation (C1)(with PhD students, colleagues in your Department ,or from other departments of the
University) is more important than attitude toward competition (C2). ” [5]
2. Please, indicate on a scale from 1 to 9 (1-indifferent, 9-full agreement) to what extent you agree with
the next assertion:”In the framework of intergenerational transfer of knowledge, attitude toward
competition (C2) is more important than attitude toward innovation (C3) (like for instance developing a
new economic theory, new empirical methods of estimation, proposals of international grants or
promoting and implementing institutional changes).” [8]
3. Please, indicate on a scale from 1 to 9 (1-indifferent, 9-full agreement) to what extent you agree with
the next assertion:”In the framework of intergenerational transfer of knowledge, attitude toward
cooperation (C1) is more important than attitude toward innovation (C3).” [6]
The third page was devoted to the determination of the priority vectors of the alternatives (grants, papers,
books) taking into consideration the criterions in the above level of hierarchy. Questions were formulated
as follows:
4. With respect to the problem of inter generational transfer of knowledge, from the point of view of the
attitude toward cooperation please indicate, on a scale from 1 to 9 (1-indifferent, 9-full agreement) to
what extent you agree with the next three assertions:

4a. Participating in research grants (G) is more important than writing scientific papers (P). [4]

4b. Writing scientific papers (P) is more important than writing books or manuals(B). [4]

4c. Participating in research grants (G) is more important than writing books or manuals (B). [3]
5. With respect to the problem of inter generational transfer of knowledge, from the point of view of the
attitude toward competition please indicate, on a scale from 1 to 9 (1-indifferent, 9-full agreement) to what
extent you agree with the next three assertions:

5a. Participating in research grants (G) is more important than writing scientific papers (P). [4]

5b. Writing scientific papers (P) is more important than writing books or manuals(B). [3]
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
5c. Participating in research grants (G) is more important than writing books or manuals (B). [2]
6. With respect to the problem of inter generational transfer of knowledge, from the point of view of the
attitude toward innovation please indicate, on a scale from 1 to 9 (1-indifferent, 9-full agreement) to what
extent you agree with the next three assertions:

6a. Participating in research grants (G) is more important than writing scientific papers (P). [2]

6b. Writing scientific papers (P) is more important than writing books or manuals(B). [3]

6c. Participating in research grants (G) is more important than writing books or manuals (B). [4]
The forth and the last page was devoted to determining the priority vectors for the alternative schemes of
equivalence regarding the alternatives in the above level of the hierarchy.
7. With respect to research grants, please indicate, on a scale from 1 to 9 (1-indifferent, 9-full agreement)
to what extent you agree with the next assertions:

7a. Other professional objectives are more important than participation as a director or member in
CNCSIS (national) research grants. [8]

7b. Is more important to participate as a director or as a member on a CNCSIS (national research
grant) than elaborating/or making efforts to become a member in international research grants. [3]

7c. Other professional objectives are more important than to participate as a director or as a member
on a CNCSIS (national research grant) than elaborating/or making efforts to become a member in
international research grants. [5]
8. With respect to scientific papers, please indicate, on a scale from 1 to 9 (1-indifferent, 9-full agreement)
to what extent you agree with the next assertions:

8a It is more important to write a large number of articles publishable in national B+ journals than
writing papers publishable in national ISI journals. [5]

8b. It is more important to write few papers publishable in national ISI journals than taking the risk of
submitting a paper to an international ISI quoted journal. [4]

8c. It is more important to write a large number of articles publishable in national B+ journals than
taking the risk of submitting a paper to an international ISI quoted journal. [3]
The last question, question 9 asked for the number of participations in national research grants,
conducted through the Academy of Economic Studies of Bucharest, international research grants
conducted through same university, research grants through other institutions, number of papers
published in national ISI journal, number of paper published in international ISI journals with an impact
coefficient less than 1 and number of papers published in international ISI journals with an impact
coefficient greater than 1.
3.2.2 The method of processing one individual’s answers and the interpretation of the results obtained.
Paired comparison judgments in the AHP are applied to pairs of homogeneous elements and
summarized in a matrix of judgments. Scoring is applied to rank the three alternatives in terms of each of
the three criterions considered. Matrix of judgments is determined assuming values equal to one on the
main diagonal and also reversibility of the preferences-so that if C1 is preferred to C2 at a corresponding
absolute value of 5, the C2 will be preferred to C1 at an absolute value of 1/5, which is 0.2.The
corresponding vector of priorities is calculated in an eigenvalue formulation. The solution is obtained by
raising the matrix to a sufficiently large power, then summing over the rows and normalizing to obtain the
priority vector. The process is stopped when the difference between components of the priority vector
obtained at the k-th power and at the (k+1) power is less than some predetermined small value. The
vector of priorities is the derived scale associated with the matrix of comparisons (Saaty,1994). After
setting priorities for the criteria, pair wise comparisons are also made ratings themselves to set priorities
for them under each criterion and dividing each of their priorities by the largest rated intensity to get the
ideal intensity. Finally, alternatives are scored by checking off their respective ratings under each criterion
and summing these ratings for all criteria. This produces a ratio scale score for the alternative. The
scores thus obtained of the alternatives can in the end be normalized by dividing each one by their sum.
For the example considered in the section above, the pair wise comparison matrix is given in Table 1.
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Table 1: The pair wise comparison matrix (attitude to cooperation-C1, competition-C2, and innovation-C3)
Absolute judgments amongst criterions
C1
C2
C3
C1
1
0.2
0.16667
C2
5
1
0.125
C3
6
8
1
The correspondent vector of priorities, calculated as briefly presented above is given by any column in
the above normalized matrix, as presented in Table 2.
Table 2: Vector of priorities for the criterions’ pair wise comparisons
Vector of priorities
C1
C2
C3
C1
0.768293
0.134146
0.097561
C2
0.768293
0.134146
0.097561
C3
0.768293
0.134146
0.097561
The interpretation is that, in the view of the particular person who answered the survey, in the prevalent
attitude determining IGL is cooperation, corresponding to C1, since it has the highest value: 0.768293.
Second, it comes the necessity to be competitive, corresponding to a value of 0.134146 and the last
important would be to be innovative - in the sense presented in the section above, with a value of
0.097561 in the priority vector. Similarly were determined the pair wise matrices of judgments of the three
alternatives (Grants-A1, Papers-A2 Books-A3) with respect to each of the previous three criterions
together with the determined values for the priority vectors .In Table 3. is given the pair wise matrix of
judgments of the three alternatives with respect of Criterion 1(attitude to cooperation) and corresponding
vector of priorities.
Table 3: Pair wise matrix of judgments of the three alternatives with respect of Criterion 1 (attitude to
cooperation) and corresponding vector of priorities
Absolute judgments amongst alternatives A1, A2, A3 with respect to Criterion 1
A1
A2
A3
A1
1
4
3
A2
0.25
1
4
A3
0.3333
0.25
1
Vector of Priorities
A1
A2
A3
A1
0.61898
0.61898
0.61898
A2
0.220113
0.220113
0.220113
A3
0.160907
0.160907
0.160907
4. Discussion and conclusions
The survey was delivered to 4 distinct Departments of the Academy of Economic Studies of Bucharest
and the rate of response was 30%. Out of the received answers, 17.3 % were valid answers. The priority
vector of the criterions considered to influence the IGL was calculated as an average on the individual
vectors of priority-presented in table 1. The weight of the Alternative 1 (Grants) from the point of view of
the attitude to cooperation-Criterion 1 is calculated again as the average over the individual values in the
corresponding priorities vectors, as shown in table 3. Results weighted for all the respondents are
summarized in Table 4.
Table 4: Synthesis in the distributive mode
Distributive Mode
A1
A2
A3
C1
C2
C3
0.693693
0.183968
0.124902
0.604529
0.630678
0.638076
0.246879
0.247676
0.236087
0.155292
0.121646
0.128091
In order to establish the composite or global priorities of the alternatives considered we lay out in a matrix
the local priorities of the alternatives with respect to each criterion and multiply each column of vectors by
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the priority of the corresponding criterion and add across each row, which results in the composite or
global priority vector of the alternatives. Corresponding results are presented in Table 5.
Table 5: Synthesis
Distributive Mode
A1
A2
A3
C1
C2
C3
0.414859
0.136212
0.062385
0.613972
0.169421
0.053493
0.023082
0.247196
0.106569
0.026273
0.012523
0.143
Similarly were determined vectors of priority averaged over all the respondents for the trade-off criterions
with respect of grants and papers , where 1 means-other are more important, 2-is a compromise at a
national level and 3 is going international with respect to the considered alternative. The results are
presented in table 6.
Table 6: Synthesis for the trade-off criterions regarding grants-A1 and papers-A2
Distributive Mode
A1
A2
0.694924
0.645866
0.175785
0.204687
0.129291
0.149447
1
2
3
As a conclusion, from the point of view of the IGL in the Academy of Economic Studies of Bucharest, for
the academic staff the most important appears to be cooperation - with a weight of 0.693693, and the
most preferred channel for cooperation is through national research grants. By looking at the results in
table 5 we see that it also appears that option 1 - doing something else but grants and papers - is most
preferred. So we conclude that this also checks the fact that cooperation in the sense of something else
but grants and papers are preferred channels for IGL. Results are in concordance also with the
organizational culture of our universities, since cooperation has been stimulated much more than
competition during the socialism regime. At the limit, it has been declared that in the state universities
should be no competition since academic life is different than any business on a certain market. Thus, the
rational analysis of IGL involves also the cultural value system developed at the organizational level.
IGL becomes a challenge for the knowledge management and the intellectual capital research due to its
importance in speeding up the knowledge gap between generations, and to its capacity of reducing the
organizational knowledge loss. Our research shows how the AHP method used for the managerial
decision making can be used successfully for determining the vectors of priorities for the possible
strategies and activities to be elaborated and implemented in order to increase the impact of IGL.
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How to Create Relational Capital in Hospital-In-The-Home
Units1
Juan-Gabriel Cegarra-Navarro1, Gabriel Cepeda-Carrion2, Eva Martínez-Caro1 and
Mª Paz Salmador-Sánchez3
1
Universidad Politécnica de Cartagena, Spain
2
Universidad de Sevilla, Spain
3
Universidad Autónoma de Madrid, Spain
[email protected]
[email protected]
[email protected]
[email protected]
Abstract: The Spanish healthcare system has undergone important changes, particularly with respect to the
development of new hospital services. Today, more than ever, the factors that define the nature and structured of the
Spanish healthcare environment (e.g. demand, costs, system deregulation) are undergoing rapid change thus
obliging hospital administrators to develop and implement flexible and adaptive strategies in order to survive in an
increasingly challenging environment facing hospital management. This work examines how the existence of some
learning practices is linked to knowledge transfer and how this component is linked to relational capital. These
relationships are examined through an empirical investigation of 54 doctors and 62 nurses belonging to 44 Hospitalin-the-Home Units. In an applied sense, the findings provide homecare practitioners with identifiable factors, which
enable two learning models (conceptual and operational) and address the relevant issues by changing strategies at
both the individual and organisational levels.
Keywords: hospital-in-the-home units, conceptual learning, operational learning
1. Introduction
The Hospital-in-the-Home Unit (HHU) is an innovation which delivers acute hospital services to
appropriate patients in their own homes (Montalto, 1996). Health care resources are limited, and
therefore the identification of the true expense generators are necessary to be able to optimise resource
use. The World Health Organization stresses that strategies should be drawn up for providing support to
patients and carers at community level in order to avoid costly institutional care (e.g., Montalto, 1996;
Drake et al., 2006). In this regard, the key benefits of HHUS are clear. If the patient stays at home,
hospital admissions decrease, and more importantly, infections are avoided (Planas-Miret et al., 2005). It
has also been recognised that home health care increases patients' quality of life considerably as it eases
their care in the family and prevents risks associated with hospital admissions (Montalto, 1996; Gideon,
et al., 1999). A number of factors may explain the greater satisfaction with treatment at home: In their
own homes, patients are in their familiar environment, their privacy is protected, their sleep less
interrupted, and they can eat their usual food (Cruse and Foord, 1980).
The concept of relational capital concerns the relationships that an organisation develops with its external
agents. Furthermore, the value of an organisation’s relational capital may be considered to be the value
of these relationships. These relationships enable organisations to gain knowledge of customers,
enabling them to develop new products, services or processes which may significantly increase “what
customers gain from the organisation’s products, processes or services” (Chang and Tseng, 2005). In
this study we have considered that relational capital involves the value of the relations that a HHU
maintains with the different agents of its environment (e.g. patients and other practitioners). Traditionally,
relational capital needs to become a stable resource if it is to be translated into greater satisfaction with
home treatment (Brown, 1993). However, there is a growing rate of turnover among doctors, nurses,
and/or knowledge workers who accumulate organisation-specific knowledge that is ultimately lost to the
healthcare system. Therefore, relational capital would have a relatively short half-life due to employee
turnover and the passage of time.
The above provides an illustration that, in order to create relational capital, strengthen patient
relationships and thus positively influence patient satisfaction, a HHU must be flexible in configuring
1
The dates in this research were taken from a research programme supported by Spanish Ministry of Education (REF: ECO20080641-C02-02), entitled: „Science Strategic Knowledge Management in the Sanitary Industry: An Application to Home Care Units’.
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Reference this paper as: Cegarra-Navarro, J, Cepeda-Carrion. G, Martínez-Caro, E and Salmador-Sánchez, M. “How
to Create Relational Capital In Hospital-In-The-Home Units” The Electronic Journal of Knowledge Management
Volume 9 Issue 1 (pp19-27), available online at www.ejkm.com
Electronic Journal of Knowledge Management Volume 9 Issue 1 2011
(combining) knowledge and knowledge structures in a way that is appropriate for delivering value to the
patient (Dixon, 1994). Thus, as Szulanski (1996) noted, in order to overcome the internal barriers of
knowledge transfer, it might be fruitful “to devote resources and managerial attention to develop the
learning capacities of organizational units, foster close relationships between organizational units, and
systematically understand and communicate practices”. In doing so, Jansen et al. (2005) define
“absorptive capacity” as a set of learning processes which are the overall outcome of developments in
the knowledge environment as well as of managerial agency. Kim (1993) further proposes that learning
can be classified as conceptual or operational. While „conceptual learning’ concerns thinking about why
things are how they are or why they are done in the first place, „operational learning’ basically refers to
learning how to do something. The purpose of this paper is to highlight the links among the extent to
which a HHU possesses some conceptual and operational practices and the strengths of its relational
capital from the practitioners’ point of view. The key factors that characterise conceptual learning,
operational learning and relational capital are introduced and discussed in the next section.
2. Contextual framework
About former studies in Relational Capital, the revision of relative literature on intellectual capital allows
us identify multiple researches which refer to this question. One of the first models of measurement and
management that is going beyond of financial indicators, it is the Scorecard Balance (Kaplan and Norton,
1992), that considers, in a perspective much more closed the relationships of the organizations with
customers (in our case patients or carers) in what they named a perspective of clients, in this block some
aims are marked to get them. In this way, focus in clients is referred by Edvinsson and Malone (1997) in
'Navigator of Skandia" as indicators to representative the actual situation of the company. Bontis (1996)
speaks of clients capital and defines it as "the knowledge of distributions channels and relationships with
clients". Brooking (1996) is another author interested in the relationships of the company with clients, but
with vision beyond them, this consultant named market assets as "those which are derived from a
beneficial relationship of the company with market and customers", including product brands, prestige,
distribution channels, image and name of the company, and other types of contracts that give competitive
advantage to the company. In the same line that Brooking (1996), Roos and Roos (1997) extend the
study of company relationships with clients, and this category of intellectual capital is designated as
clients and relationships capital, including in this block at the same time other intellectual capital as:
relationships with suppliers, relationships with partners and relationships with investors. It must be
mentioned Sveiby (1997) contributions, who in his "external structure" included relationships with clients
and suppliers, commercial brands and reputation or image of the company, using for this, three types of
indicators: Growing and innovation, efficiency and stability indicators. About former considerations,
"Relational Capital" is defined as the value of relationships that an organisation maintains with the
environment (Euroforum, 1998). However, among all the agents which a company has relationships, the
most important are customers (patients), because of the direct relation with financial performance and
survival in a long term (Euroforum, 1998). To get Relational Capital, it is necessary the knowledge of
clients. For this reason, in the following epigraph, a relational learning model will be presented, which
every level of learning (individual, group, and organizational) will be studied, changing information and
beginning by explicit knowledge of customer, distributed and used to create Relational Capital.
Transitioning from care services being provided in a hospital setting to their provision in a homecare
setting creates many important challenges (Sanchez & Cegarra, 2008). In a hospital setting the
practitioner mainly focuses on applying physical and psychological assessment skills to the patient in the
structured hospital environment. However, when care services are provided in a homecare setting the
practitioner not only conducts a complete physical and psychological assessment, but also assesses
social, economic, environmental, home safety, and factors relating to the familial situation that may affect
the patient’s care (Humphrey & Milone-Nuzzo, 1996). Clearly another difference between providing care
in a hospital setting and a homecare setting relates the work environment. While in the hospital setting
the patient is always present and everything is familiar and convenient for the practitioner, in the
homecare setting the practitioner is responsible for identifying what has to be done to assure an
appropriate level of care and ensuring that the patient and family are aware of what might be helpful.
Often the family are required to participate in providing care and therefore they have to be actively
involved in the development of a care plan for the patient. This means that the practitioner who provides
care services in a homecare setting must, over time, develop knowledge of the community resources
available both inside and outside the hospital (Cegarra & Cepeda, 2010).
The essence of identifying and sharing efficient practices is to learn from others and to reuse knowledge
and avoid waste. In doing so, the learning process within the organisational context, is a topic which has
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Juan-Gabriel Cegarra-Navarro et al.
been studied mainly within a framework of strict psychology and has not received due attention from
healthcare literature. Thus, Kim (1998) understands absorptive capacity as skills relating to the ability to
learn and solve problems that enable a firm to assimilate and create new knowledge. Zahra and George
(2002) have suggested four dimensions of absorptive capacity, each playing different but complementary
roles in explaining how absorptive capacity can influence innovation performance. The first two
dimensions (i.e. acquisition and assimilation) are in effect what Zahra and George (2002) label potential
absorptive capacity (PACAP) and the other two dimensions (i.e. transformation and exploitation)
constitute realised absorptive capacity (RACAP). Whereas PACAP implies personal internal processes
such as reflection, intuition and interpretation, RACAP reflects the efficiency of leveraging externally
absorbed knowledge.
Literature has not used the same number and nomenclature of absorptive capacity processes. PACAP
and RACAP have also been labelled by other authors as „conceptual and operational learning processes’
e.g., Kim (1992; 1993). Kim (1992) begins with a discussion of the two levels of organizational learningoperational and conceptual (which he also correlates to Argyris & Schön's (1978) single and double loop
learning). Next, Kim outlines how operational learning focuses on resolving procedural issues; while
conceptual learning is most capable of addressing issues that cross functional-areas of process. In Kim’s
terms (1993), operational learning is procedural and rule based, while conceptual learning facilitates
causal reasoning. Kim (1992) also shows how the processes involving the effective and efficient
allocation of resources into valuable and competitive business platforms based on existing knowledge are
ideally suited for operational learning; and that formal or informal meetings, or creating external
communities, as outlined by Jansen et al. (2005), are perfectly designed to conceptual learning.
The above provides an illustration that, although there are many overlaps between conceptual learning
and operational learning, the two constructs are not identical. Conceptual learning starts with activities
involving searching, variation, risk-taking, experimentation and innovation (Kim, 1992; 1993). These
activities lead to the introduction of novel practices by HHU S. In addition, knowledge obtained as a result
of operational activities can be internalized by doctors and nurses who materialize it in the form of
relational trust, common language and confidence (Bontis et al., 2002). The existence of these subprocesses and the extent to which they are implemented testify to the intensity of efforts made toward the
development of HHUS’ internal capabilities and for accessing knowledge from external sources. While
conceptual learning pursues new knowledge and develops new services for patients, operational learning
builds upon current knowledge to meet the needs of existing patients.
The framework shown in Figure 1 integrates the key factors that influence the nature and effectiveness of
the learning context.
Conceptual frame
Causal Reasoning
Interactions with external
agents
Reveal new tendencies and
diverse viewpoints
Self-reflection and flexibility
Conceptual learning
Operational learning
Operational frame
Changes in the organization’s
structure or processes to
improve patient relations
(Relational Capital)
Procedural and rule based
Knowledge structures
Systematized knowledge
Communication
Management style
Figure 1: A framework for development of relational by hospital-in-the-home units
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As shown in Figure 1, conceptual learning is facilitated through organizational structures and factors that
facilitate the exploring of new understandings (e.g. new opportunities to serve patients). Operational
learning, in contrast, is facilitated by organizational structures and factors that provide for the utilization of
experiences and lessons learned (e.g. beliefs, norms, values, procedures, and routines).
Relational capital arises as a result of interaction between a HHU and its external agents (e.g. patients
and carers). Since patients' expectations and demands are dynamic, it is necessary that practitioners pay
close attention to track patient and career demands in products and services and develop their
capabilities to meet those demands quickly (Cegarra and Cepeda, 2010). In this regard, conceptual
processes can be used to respond more quickly to patients demands since information about new
homecare services can be disseminated more quickly (Drake and Bethan, 2006). Equally, patient
relations will benefit from access to the new knowledge necessary to resolve healthcare problems
(Montalto, 1996). The effective utilisation of knowledge further allows appropriate responses to be made
to changes in, for example, carers´ technology structures, or to changes in patient expectations (PlanasMiret et al., 2005). In addition, relational capital can also be supported by operational processes, for
instance organizational design features (e.g. teamwork or cross-department specialist teams) may help
the avoidance of entrenched behaviours and result in the enactment of more appropriate behaviours
(Sanchez and Cegarra, 2008). These issues are explored by testing the following hypotheses:
H1: Conceptual learning practices are positively associated with relational capital
H2: Operational learning practices are positively associated with relational capital
3. Methodology
In order to compare the above hypotheses, HHUS in Spain were considered. The Hospital-in-the-Home
domain was chosen for two main reasons. On one hand, despite patient satisfaction being reported as
being high in Hospital-in-the-Home (Carr-Hill, 1992), evaluation of the causes of high levels of satisfaction
have been underdeveloped. On the other hand, the HHU is an ideal platform to learn, because two or
more individuals (e.g. patients, carers, doctors and nurses) are working together with different resources
and complementary capacities, which are learning facilitator factors (Fenwick, 2007). In practical terms,
this has sown the seed for knowledge to be made available and for HHU members to be actively directed
towards the patient in the form of strategic competence mapping, development and utilisation.
Therefore, the Hospital-in-the-Home sector is an appropriate setting for an investigation of learning
practices and its impact on relational capital. This is mainly because these units provide „face-to-face’
interaction, allowing the exchange of information to be inserted into the social context of the patients,
which by its tacit character is more difficult to imitate. This means constantly searching for new ways to
improve homecare services, developing new offerings and introducing improved working methods, but
they will only occur if practitioners, carers and patients are engaged to share individual expertise and
create organisational knowledge (Montalto, 1996). Consequently, HHU are highly motivated to introduce
relationships with carers and patients to create relational capital and try to systematise the „learning’
process.
We used a list of home care units (65 HHU) provided by the Spanish Homecare Society (SHS) in Spain.
Those units were contacted and asked by the SHS to participate in the study, and 44 agreed. They were
also informed by telephone of the work objectives and they were assured of its strictly scientific and
confidential character as well as the global and anonymous treatment of the data. Finally, prior to the
telephone interviews, a presentation of the study was given in the 8th National Conference on Internal
Medicine held on 18th-21st November 2009 in Valencia, Spain. Surveying took place over a period of two
months, from December 2009 to January 2010. Participants were divided into two categories: HHU
members with nursing backgrounds and HHU members with medical backgrounds. In total, 63 nurse
managers and 63 medical managers were telephoned and invited to participate in the study, and a total
of 119 questionnaires were collected, of which 3 were found to be without an overall satisfaction rating.
Therefore, data analysis was based on 116 valid questionnaires (54 doctors and 62 nurses). The great
majority of respondents were female (62.1 percent) and had medical backgrounds (34.7 percent).
The existence of conditions necessary to support conceptual learning or (CL) were measured using an
adapted version of a scale by Jansen et al. (2005) to measure the construct of „potential absorptive
capacity’. This construct focuses on the generation of new insights, developing the competencies
necessary for doing one’s job, having a sense of pride and ownership in one’s work and being aware of
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Juan-Gabriel Cegarra-Navarro et al.
the critical issues that affect one’s work. The initial measures relating to the existence of operational
learning (OL) initiatives consisted of 4 items adapted from a scale designed by Jansen et al. (2005) to
measure the construct of „realised absorptive capacity’. Consistent with Jansen et al, items that tapped
the operational learning initiatives were interwoven with issues focused on recognising opportunities and
consequences of existing operations, structures, and strategies. The items had 7-point scales ranging
from 1 (high disagreement) to 7 (high agreement). Among the indicators of relational capital or (RC),
factors relating to the existence of satisfied patients (e.g. quick health services, relationship, and
collaboration) are most often used (Chang and Tseng, 2005). In this research, respondents were asked
to indicate the degree in which his(her) reached four objectives (1= strong down and 7= strong up). A
principal factor analysis (with varimax rotation) was carried out on all independent and dependent
variables yielding three factors explaining 71.296 percent of the variance, with factor 1 accounting for just
26.7 percent of the variance. Exploratory factor analysis also allows for an examination of the
unidimensionality and validity of the items. Three distinct factors, reflecting each of the dependent and
independent variables, emerged, as shown in Table 1. This provides good support for the construct
validity of the scales.
In order to assure the research can be generalised, it is important to add control variables to the
regression model in order to ensure that the effects of CL and OL on RC are independent of the Hospitalin-the-Home Units’s focus on RC. In this regard, RC could be strengthened in those situations where
HHU employ relatively young employees in those areas dealing with decision making about the adoption
of new ideas and practices (Nystrom et al., 2002). Younger employees are more likely to adopt
innovations (Brancheau and Wetherbe, 1990), whereas older people may become so rooted in past
practices that a substantial degree of inertia accumulates over time (Becker, 2005). Under this
framework, the date on which each practitioner started in his/her current position might have a different
impact on RC (e.g., older people may have lower levels of uncertainty). Furthermore, Becker (2008)
argues that those with a breadth of knowledge are more likely to be open to forget and change, however,
those with a depth of expertise, particularly in the area requiring change, are more likely to resist
changing. Thus, although doctors and nurses are two natural partners in the HHU team, they also have
very different jobs, very different responsibilities and different school and training requirements.
Therefore, it seems that they may have different perceptions about how to respond to conflicting patient
demands. Thus, in this paper we have included two control variables.

The number of years spent developing the same position. This dimension was measured by a
continuous variable with a minimum value of a few months and a maximum value of seventy-eight
years.

The practitioner’s background may also impact the level of utilisation of each HHU initiative. In our
study, we considered whether (1), the person who answered was a doctor or (2), the person who
answered was a nurse.
Table 1: Rotation factor matrix
a
Table 1: Rotation factor matrix
Factors
Survey items
Conceptual learning
Relational capital
Operational learning
Our unit has frequent interactions with corporate
headquarters to acquire new knowledge
New opportunities to serve our patients are
quickly understood
We quickly analyse and interpret changing new
tendencies in our environment
We quickly analyse and interpret changing market
demands
Employees record and store newly acquired
knowledge for future reference
Our unit quickly recognises the usefulness of new
external knowledge to existing knowledge
Its clearly known how activities within our unit
should be performed
Employees have a common language regarding
our products and services
Quality of services
0.753
0.047
0.155
0.862
0.186
0.298
0.920
0.164
0.152
0.857
0.212
0.172
0.230
0.205
0.687
0.114
0.055
0.869
0.245
0.044
0.803
0.122
0.303
0.749
0.021
0.067
0.354
0.205
0.865
0.853
0.627
0.748
0.130
0.188
0.072
0.143
A more efficient use of resources
Satisfaction of patients
Speed of services to patients
Notes: Extraction method: principal factor analysis; rotation method: varimax with Kaiser normalization; a rotation converged in five
interactions
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4. Results
Before analysing the effects of CL and OL on RC, the relationship between the independent
questionnaire variables needs to be investigated (Peterson, 1994). In doing so, multicolineality tests give
satisfactory results with no VIF over 2 (FIV=1.271) and no tolerance value over 1 (tolerance=0.968). We
can see in Table 2 that the tolerances of all the predictors are higher than the evaluation criteria of 0.01,
and VIF values are not higher than the evaluation criteria of 10 (Stevens, 2002). Therefore, the tolerance
and VIF values are well within normal bounds, suggesting that multicollinearity is not present among
these independent variables. Table 2 also provides an overview of the construct’s means, standard
deviations and correlations.
Table 2: Assessment of the measures
Table 2: Assessment of the measures
Eigenvalue
µ
4.575
1. Age (range 0–28)
0.314
2. Background (Doctor–2:Nurse)
0.072
3. CL (range 1–7)
SD
10.583
7.532
1.534
0.501
5.252
CA
1
Correlation matrix analysed
2
3
4
Collinearity statistics
5
Tolerance
VIF
0.968
1.033
0.949
1.053
0.786
1.273
0.787
1.271
---
---
1.000
0.899
1.179
-0.175c
1.000
-0.049
0.128
1.000
a
1.000
0.392 a
0.024
4. OL (range 1–7)
5.435
1.014
0.818
-0.024
0.133
0.457
0.016
5. RC (range 2.50–7)
5.851
0.870
0.822
-0.111
0.064
0.371 a
1.000
Notes:
a
<0.01; b <0.05; c <0.1
µ = the average score for all of the items included in this measure; S.D. = Standard Deviation; C.A. = Cronbach´s alpha ?
Age: Years in the same position; CL= Conceptual learning; OL= Operational learning; RC= Relational capital
As shown in Table 3, we adopt Baron and Kenny's (1986) three-step hierarchical regression analysis
procedure in this study. In the first model, which we refer to as the control model, only the control
variables are entered into the regression equation (i.e. the number of years spent developing the same
position and the practitioner’s background).In the second model, which we refer to as the CL-model, we
added CL into the regression equation. Finally, in the third model, which we refer to as the OL-model, the
OL-variable is added. A comparison among the three models permits the conclusion that the third model
fits better to the observable data than the first two models shown (the fit statistics for the third model were
2
2
R =0.204; Adj R =0.175; F = 7.066). Table 3 shows that the least supported model (the control model)
implies that the number of years spent developing the same position and the practitioner’s background
have insignificant effect on RC. The addition of the mediation term (Step 2) significantly improved the
results from the control model (p<0.001), and importantly, the previously insignificant relationships
between „the control variables’ and RC (control model) became insignificant. In addition, as shown in the
CL-model, „CL’ has a significant impact on RC (the dependent variable) ( =0.367, p<0.01). Table 3 also
shows that the addition of the mediation term (Step 3) significantly improved the results from Step 2
(p<0.001), and importantly, the previously significant relationship between CL and RC became significant
( =0.246, p<0.05), while the previously significant relationships the control variables’ and RC became
insignificant. Furthermore, Table 3 indicates that the second mediating variable, OL, also has a significant
positive effect on RC ( =0.271, p<0.01). This analysis provides full support for H1: (CLRC), and H2:
(OLRC). The theoretical and managerial implications of the relationships observed across those
constructs are discussed in further detail in the following section.
Table 3: Regression analysis performed for HHU (N=116)
Table 3: Regression analysis performed for HHU (N=116)
Step 1
Years in the same position
Backgrounds
Step 2
Conceptual Learning
Step 3
Operational Learning
R2 =
Adj R2 =
F=
Change in R2 =
Change in F =
Control
model
Conceptual learning
model
Operational learning
model
-0.106 (t= -1.110)
0.035 (t= 0.371)
-0.096 (t= -1.075)
-0.010 (t= -0.010)
-0.098 (t= -1.136)
-0.028 (t= -0.324)
----
0.367 a (t= 4.153)
0.246 b (t= 2.560)
----
----
0.271 a (t= 2.832)
0.014
-0.004
0.782
0.014
0.782
0,146
0,123
6,346 a
0.133
17.248 a
0,204
0,175
7,066 a
0.058
8.020 a
Notes:
a
<0.01; b <0.05
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5. Discussion
The first contribution of this research derives from the presented framework. As shown in Figure 1, the
context in which practitioners are able to learn from patient needs is customised and based on two
frameworks: (1) conceptual; and (2) operational. While conceptual triggers to solve the needs of patients
and carers are the main drivers for learning new critical norms and routines, operational processes such
as norms, procedures and routines are the main enablers to complete a particular task. Developing these
key qualities has strategic importance for any HHU, and offers clear benefits when the right knowledge is
applied to homecare problems with speed and efficiency. The key benefits of the use of this framework
for HHUS are clear; it enables healthcare professionals to identify and replace poor practices and also
avoids the reinvention of the wheel (e.g. by minimising unnecessary work caused by the use of ineffective
methods), reduces costs through better productivity and efficiency (improving services to patients) and
increases profitability (Stefl, 2002; Brakensiek, 2002).
The second contribution of this research derives from the results of the empirical test in the hypotheses.
In this study we have considered three models (one control model and two learning models) to test CL
and OL effects on „RC’ within HHUS. The two learning models tested the „CL-model’ with CL treated as
an intermediate variable between control variables and RC, and against the „OL-model’, including CL and
OL as intermediate variables between control variables and RC.
The least supported model (the control model) implies that the number of years spent developing the
same position and the practitioner’s background do not have any significant effect on the creation of RC.
These results do not confirm the position adopted by Wilson (1988) when he argues that people who
have spent time in the same job are more likely to lose the ability to see the market signals stemming
from patient demands, and they may decide to go solely by their own ways of doing and interpreting
things. A possible explanation would be the fact that HHU members share their tasks in a collaborative
environment. When that happens, older people are more motivated and more willing to make an effort
towards patient demands and they do not confuse experience with believing that they always know better
than anybody how a patient should be helped.
However, as shown in the CL-model and the OL-model, relational capital arises as a result of interaction
between conceptual and operational processes. These results support the suggestion of (Pavia, 2001),
that healthcare organisations need to be effective at collecting and analysing clinical and market
information, screening and organising these information into knowledge useful to decision making.
Therefore, by combining operational structures with personal input from experienced patients and carers
via conceptual processes, the HHU can improve the care for their patients and create RC. A possible
explanation would be the fact that conceptual and operational processes will facilitate healthcare
professionals’ understanding of the content of their medical records and the options for future care.
The best supported model (the OL-model) provides support for CL practices and OL processes being full
mediators of the relationship between control variables (i.e. the number of years spent developing the
same position and the practitioner’s background) and RC. One conclusion that might be drawn from this
result is that CL programmes have to be designed around „OL practices’ to attain any benefit from the
knowledge provided by operational processes such as relational trust, common language and
confidence. Considering this, we suggest that maintaining an appropriate balance between conceptual
and operational processes is critical for RC. HHUS require healthcare providers to cooperate and
communicate with one another. This includes managers, clinicians and all other staff that provide
services to the patient. Through cooperation and communication, the most comprehensive care for the
patients will become more achievable. This view is shared by some authors (e.g. Stefl, 2002; Brakensiek,
2002), who assert that the newest medical and scientific knowledge will be created by clinicians sharing
their knowledge with others both within and across organisations. Thus, we argue that the hospital should
offer tangible rewards to those HHU members who reinforce both the culture and the behaviours needed
for effective knowledge transfer. Otherwise, individuals can become insufficiently motivated and are liable
to act spontaneously, without the support of their superiors.
The third contribution of this research is aimed at documenting the essential features of conceptual and
operational processes, giving pointers to relevant experts in that practice, deducing general guidelines,
diffusing basic information, and using subject matter experts to apply and adapt the practices in a
Hospital-in-the-Home setting. Our findings support that conceptual and operational processes require to
be actively promoted, otherwise, we may end up with technologies and people that are under-used and
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Electronic Journal of Knowledge Management Volume 9 Issue 1 2011
not fulfilling their potential. As Gold et al. (2001) noted, technologies cannot predefine and predict who is
the right person, what is the right time or what constitutes the right information; only individuals can apply
their own experience and contextual understanding to interpret the details and implications of a particular
situation, subsequently determining the appropriate action to take. Therefore, Hospital-in-the-Home
leaders need to reinforce the environment in which practitioners, patients and carers operate and provide
them with the means to survive in the context of the competitive knowledge-based economy. As noted
above, both processes (conceptual and operational) play a key role in identifying services that have been
particularly innovative or effective in meeting specific patient needs. Therefore, they can also encourage
HHU members to share their experience so that others can benefit by using or adapting original ideas to
suit their own circumstances.
The study has some limitations. Any healthcare organisation wishing to implement a learning context
must understand what the patient values about home based care services. Nevertheless, the response to
this issue is complex, since the differential values that patients have can be intangible and
heterogeneous in nature. Furthermore, the management of these elements will be different, depending
on the type of speciality, its structure and the strategy of the unit. Therefore, other factors which have not
been included in this study are also likely to affect conceptual and operational processes. Furthermore,
conducting this type of single case study (an interview-based case study approach) should be understood
foremost as a prelude to further study, i.e. as an exploratory device or a pilot case where issues are
identified rather than hypotheses tested. Taking into account its limitations, a possible research direction
could extend the range of indicators and measures by identifying common measures for patients,
clinicians, staff, managers and board members. Another possible research direction could examine how
patients and clinicians can contribute to conceptual and operational processes. For instance, the patients
can provide information about technologies and standardisation issues. Practitioners can disclose the
problems that they have experienced by using technologies, as well as their countermeasures. Finally,
future quantitative studies including common measures for patients, clinicians, staff, managers and board
members may help improve the rigor of the findings.
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ISSN 1479-4411
SPF 5 and Limitations to Investing in Knowledge
Management
Scott Erickson1 and Helen Rothberg2
1
Ithaca College, Ithaca, USA
2
Marist College, Poughkeepsie, USA
[email protected]
[email protected]
Abstract: This paper will continue our work concerning the strategic management of intellectual capital. Based on
the Rothberg/Erickson SPF framework which balances knowledge development with knowledge protection, we
continue to explore differing circumstances and their impact on IC strategy. The framework differentiates between IC
that needs to be aggressively developed by the firm (or not) and IC that is vulnerable to competitive intelligence
incursion and needs protection (or not). Previously, we have looked at an environment within which substantial
development of IC is necessary in order to be competitive but in which those same knowledge assets are at risk from
competitive efforts to appropriate them (Erickson & Rothberg 2009b). In this paper, we will develop the scenario
wherein aggressive development of IC may not be useful (highly tacit knowledge, difficult to share or apply in other
situations) and little competitive intelligence activity is taking place (SPF 5 in the framework). In particular, we will
characterize the nature of this environment in terms of theory, identify representative firms and industries, and apply
data to the framework. Where appropriate, contrasts with other SPF environments will also be made.
Keywords: knowledge management, intellectual capital, competitive intelligence, SPF framework
1. Background
The field of knowledge management (KM) is founded on the belief that greater development and use of
knowledge assets (or intellectual capital (IC)) will result in competitive advantage (Marr & Schiuma 2001).
Implicit in this view is the idea that more collection, more development, and more leveraging of
knowledge assets through sharing is always for the good. The field of competitive intelligence (CI) also
believes in the power of knowledge assets, specifically those related to the strategy and operations of a
competitor (Andreou & Bontis 2007; Erickson & Rothberg 2000). If a firm can relieve its competitor of
specific knowledge, information, or data, It can better anticipate an counter competitive actions.
Competitive intelligence activities that access and analyse such knowledge from and concerning
competitors is a growing field (ASIS 1999) and is also believed to add to competitive advantage
(Bernhardt 2002; Cappel and Boone 1995).
While similarities exist between the disciplines, there is also a fundamental tension between them as
aggressive knowledge management can lead to vulnerabilities in relation to competitive intelligence.
Specifically, as firms codify their knowledge assets, centralizing them in a database, they are able to
better collect knowledge across the firm and then leverage it by making it accessible throughout the
organization (Grant 1996; Quinn 1992). Further, if it is distributed digitally to the organization and even
the extended network around it, the knowledge can be useful to many more individuals and entities. And
though codification is usually associated with explicit knowledge, genius systems and other methods of
better managing tacit knowledge can also lead to growth in knowledge assets and higher organizational
performance. More knowledge in more hands is viewed as unambiguously good in most KM applications.
Collecting knowledge as much as possible and then spreading it as much as possible is an implicit goal
of the field.
From a competitive intelligence standpoint, however, the same things that provide potential value instill
potential vulnerability (Liebeskind 1996). Collection of the knowledge assets in a central location (or at
least through a centralized system), especially in digital form, available to more and more individuals
throughout the network spells exponentially more opportunities for competitive intelligence infiltration.
Operatives are free to look for the weak point in the network, and that weak point is much more likely to
have access to much more data, information, and knowledge than would be the case if a KM system was
not in place. The result of these two opposing viewpoints is a dilemma. An organization needs to develop
knowledge in order to keep up with competitors doing the same. A failure to develop knowledge to its
fullest extent has the potential to leave a firm at a competitive disadvantage in terms of KM. So there are
definite pressures to develop knowledge assets aggressively. On the other hand, greater development
makes it harder to defend those same assets from competitive incursions. If knowledge does slip into
competitive hands, the firm may again be at a competitive disadvantage, this time in terms of CI This
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Reference this paper as: Erickson, S and Rothberg, H. “SPF 5 and Limitations to Investing in Knowledge
Management” The Electronic Journal of Knowledge Management Volume 9 Issue 1 (pp28-36), available online at
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Electronic Journal of Knowledge Management Volume 9 Issue 1 2011
tension in developing vs. protecting knowledge has been depicted in the following graph (Rothberg &
Erickson 2005). “Capital Management Risk” refers to the risk of not developing knowledge assets
(intellectual capital) to the same degree as competitors. More knowledge development (investment in KM
systems) decreases this risk. Competitive Intelligence Risk has to do with leaving intellectual capital open
to competitive incursions. Less development and sharing reduces this risk, as knowledge assets are then
easier to protect. As shown, these risks move in opposite directions as KM development increases
(“amount of knowledge sharing”). Strategists should assess each and try to determine the optimal level of
knowledge development, the “sweet spot” that minimizes total risk.
Figure 1
Intellectual Capital Risks
Total
Risk
Risk Level
Minimum
Total
Risk
Competitive Intelligence
Risk
Capital Management
Risk
Optimal Level of
Knowledge Sharing
Amount of
Knowledge Sharing
Figure 1: Risk in the SPF fFramework (Rothberg & Erickson 2005)
The work behind the graph (Rothberg & Erickson 2005) suggests that the competitive environment on the
national, industry, and firm level will vary and analysis will help to determine the specific circumstances of
the firm, and how these risks impact it. The curves depicted here are generic. In reality, they could be all
sorts of shapes and in all sorts of locations. The key point is that the very nature of the trade-off suggests
that circumstances differ. In some situations, knowledge development will be much more critical and
there may be little risk of competitive incursion. In other situations, little may be gained from further
knowledge development while the action may lead to unacceptable competitive intelligence risks. The
task of the manager is to determine what those circumstances are, how far to develop knowledge assets,
and how much to invest in protection of the same assets.
2. Conceptual framework and methodology
The Rothberg/Erickson SPF framework that flows from Figure 1 provides different risk scenarios and
some specifics of each. As noted, the curves in the figure could be at all sorts of levels depending on
circumstances, resulting in the optimal risk level being anywhere in the graph. Specifically, the framework
breaks down four basic scenarios, with relative position illustrated in Figure 2:

SPF 45: High KM Risk/High CI Risk

SPF 15: High KM Risk/Low CI Risk

SPF 30: Low KM Risk/High CI Risk

SPF 5: Low KM Risk/Low CI Risk
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©Academic Publishing International Ltd
Scott Erickson and Helen Rothberg
Based on a dataset we have developed, numerical divisions/cutoffs are illustrated for the respective risk
levels. We’ll explain the basis of these shortly. But to first cover the strategic protection factor (SPF)
levels, the conceptual basis is as follows, including KM factors identified in the literature such as type of
intellectual capital (Stewart 1997) and knowledge characteristics (Zander & Kogut 1995):

SPF 45 poses a situation where both KM and CI risk are high. Firms that don’t invest heavily in
knowledge management will likely be left behind by competitors who do and who more productively
employ their knowledge assets. On the other hand, the same knowledge assets are very attractive to
competitors, who pursue them aggressively. The knowledge itself is likely to be explicit, easily shared
both within and without the firm, and easily lifted by the competition. Firms must simultaneously
develop IC in an aggressive manner while also taking careful steps to protect it.

SPF 30 includes low KM risk but high CI risk. Knowledge development may have little impact,
whether because the nature of the knowledge is tacit and not easily transferred, because it is specific
to the original application, or some other circumstance. But competitive intelligence risk is high
because once the results of the application of knowledge are uncovered, they are easy to copy. This
may sound counterintuitive, but it fits situations where there is a creative spark of innovation (hard to
duplicate by others within the organization) but where that innovation can be quickly copied once
incorporated into a product. Innovative investment strategies, for example, may be hard to create but
are easily duplicated once competitors figure them out.

SPF 15 indicates high KM risk and low CI risk. Knowledge assets need to be developed aggressively.
But once developed, they are hard for competitors to co-opt. Typically, there is some other barrier to
competitors copying the originating firm, even if they possess similar knowledge. Wal-Mart, for
example, shares its supply chain knowledge, information, and data throughout the firm and with key
suppliers. Firms looking to compete with them must try to do the same or they will be at a
tremendous knowledge disadvantage (as most are). There is no secret in much of what Wal-Mart
does. But the strategy is hard to copy without Wal-Mart’s strong brand, close relationships with
partners, and massive, expensive information technology systems.

SPF 5 suggests low risks on both fronts, KM and CI. Knowledge assets are difficult to develop and
share. They are also difficult for competitors to make much use of, even if they do uncover them.
Given KM basics, these knowledge assets are likely highly tacit and specific to their original uses,
thus hard to communicate and apply in different situations.
CI
Risk
SPF 30
SPF 45
SPF 5
SPF 15
1.0
3.5
KM
Risk
Figure 2: SPF Relationship to KM risk and CI risk
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Electronic Journal of Knowledge Management Volume 9 Issue 1 2011
The original development of the SPF framework provides conceptual, intuitive support for these
categorizations (Rothberg & Erickson 2005). Recent work has moved on to more empirical backing
(Erickson & Rothberg (2009b) reports on data related to SPF 45), as is the case with this paper. Here, we
look specifically at industries and firms falling into the SPF 5 category. We suggested earlier that
knowledge development might be a more strategic decision than is often recognized. In SPF 5, there is
little KM risk, so there is likely little reward for aggressively developing IC, little to be gained from
investing in substantial IT systems for managing knowledge, and little to be gained from trying to share
knowledge throughout an e-network of collaborators. A full-speed ahead approach to KM initiatives, the
default assumption of the field, is likely to be disappointing and a waste of resources. On the other hand,
there is little point in working hard to protect knowledge assets either, as competitors will probably have
just as hard a time trying to apply them in different circumstances. If we can help practicing managers
identify the circumstances characterizing SPF 5, it can aid them in better managing the balance between
knowledge management and knowledge protection. If they can determine conditions when KM
investment is pointless or where knowledge protection is unnecessary, that is a good thing in terms of
strategy and of allocating resources effectively.
In measuring the two risk levels, there are techniques available in the literature. For IC assessment, a
variety of tools exist. Many are bottom-up approaches, looking to individually measure the components of
intellectual capital, usually human capital, structural capital, and relational capital. While useful in the right
kind of study, this type of analysis begs for a broader measure, one that can be used across a large
number of firms at an aggregate level. Numerous possibilities are available, including Tobin’s q (Tan,
Plowman & Hancock 2007). Here, we use a variation on Tobin’s q as it is a metric with a long history and
robust characteristics. We calculated the ratio of market capitalization to physical assets, a common
measure of intangible assets which can also be taken as a rough measure of intellectual capital. We did
this for a large sample of firms, comprised of the Fortune 500 and a number of other firms drawn from our
second metric, the SCIP membership database. SCIP is the Society for Competitive Intelligence
Professionals. The membership, by firm and by industry average, is a rough indicator of competitive
intelligence activity. A couple SCIP members can be indicative of substantial CI differences as higher
level SCIP members often supervise a sizable staff (who are not members). The database consists of
almost 600 firms, including the financial figures necessary for Tobin’s q and SCIP membership levels.
The database covers the years 1993-1996, providing a perspective on practice at the time (and enough
time passed to allow SCIP to share its membership lists). For the two categories, the respective average
for the database ran around 3.5 for Tobin’s q (a ratio of market capitalization to physical assets of 3.5)
and 1.0 for average SCIP membership. This provided an easy and natural place to divide the four SPF
categories, though this is a first pass and adjustments could be made in the future based on additional
analysis.
3. Results
Tables 1, 2, and 3 present the industries and firms in the database falling into SPF 5, with KM Risk
(Tobin’s q) under 3.5 and CI Risk (SCIP membership) under 1.0. We included only industries with at least
three representative firms so no single firm could overly skew the industry rating (though in cleaning the
data, a couple of firms were dropped, resulting in some smaller industry numbers). Industries are
identified by 2 or 3-digit SIC number, depending on common characteristics and number of apparently
similar firms. We split the results into three tables to make them easier to view in the this paper.
Industries are arranged according to level of KM Risk, from high to low.
Table 1: SPF 5 Industries and Firms, KM Risk > 2.50
Industry (firms)
KM Risk
26: Paper & Allied Products
Champion International
Chesapeake
Westvaco
Weyerheuser
Sunoco Products
WR Grace
Avery Dennison
Nashua
Union Camp
James River
Kimberly Clark
3.24
1.04
1.82
1.34
2.10
2.78
2.04
3.90
1.33
1.75
1.02
4.66
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KM Risk
Range
14.10
CI Risk
0.98
0.75
0.00
1.50
2.00
0.25
1.75
2.00
0.75
0.25
2.25
0.00
CI Risk
Range
2.25
©Academic Publishing International Ltd
Scott Erickson and Helen Rothberg
Tambrands
Industry (firms)
15.12
KM Risk
362-5: Appliances, Electronics
Emerson Electronic
Eaton
Ault
Whirlpool
General Electric
AMP
Hubbell
Lamson & Sessions
Thomas Industries
Sony
358-9: Refrigeration, Industrial Parts
Tennant
Applied Power
Parker Hannifan
Flow International
29: Petroleum Refining
Amoco
DuPont
Mapco
Mobil
Pennzoil
Petro Canada
Phillips
Tosco
Unocal
Lubrizol
50: Wholesale: Durables
Compucon Systems
Tech Data
Avnet
WW Granger
Kaman
3.11
3.84
2.13
1.11
2.20
3.87
3.51
0.55
4.42
1.27
8.21
2.70
2.47
3.65
2.12
2.55
2.53
2.28
3.71
2.88
2.21
2.49
0.65
2.99
3.10
2.49
2.45
2.51
3.18
3.60
1.64
3.18
0.93
KM Risk
Range
7.66
1.53
3.06
2.67
0.25
CI Risk
0.59
1.00
0.75
0.00
1.75
0.50
0.25
0.75
0.00
0.00
0.50
0.63
1.00
0.25
1.00
0.25
0.63
1.25
0.50
0.25
1.25
1.25
0.75
0.25
0.00
0.75
0.00
0.35
0.25
0.00
0.50
0.50
0.50
CI Risk
Range
1.75
0.75
1.25
0.50
Table 2: SPF 5 industries and firms, 2.00—2.50
Industry (firms)
KM Risk
KM Risk
Range
CI Risk
CI Risk
Range
632: Accident, Health Insurance
AFLAC
Cigna
Pacific Health Care
Physicians Health Care
2.48
2.43
1.13
3.43
2.94
2.30
0.88
1.50
1.50
0.25
0.25
1.25
22: Textile Mill Production
Albany International
Sara Lee
Dexter
2.33
2.29
3.18
1.53
1.65
0.92
0.00
1.50
0.00
1.50
51: Wholesale: NonDurables
Bergen Brunwig
Chronmed
Moore Medical
Supervalu
2.28
2.27
3.65
1.70
1.51
2.14
0.52
0.50
0.00
0.25
1.25
1.25
871: Engineering, Architecture
Comarco
Jacobs Engineering
National Technical Systems
Stone & Webster
2.24
3.24
3.18
1.37
1.19
1.87
0.65
0.75
1.00
0.50
0.50
0.50
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Table 3: SPF 5 industries and firms, <2.00
Industry (firms)
KM Risk
KM Risk
Range
CI Risk
CI Risk
Range
24: Lumber & Wood Products
MacMillan Bloedel
Georgia Pacific
Fleetwood Enterprises
1.74
0.87
2.47
1.86
1.60
0.50
0.25
1.00
0.25
0.75
671: Holding Offices
Banc One
Bankers Trust
Chase Manhattan
Chemical Bank
Citicorp
Comerica
Corestates Financial
First Chicago
First Commerce
First Security
First Union
Fleet Financial
JP Morgan
Mellon Bank
Nationsbank
NBD Bancorp
PNC Bank
1.71
2.78
1.44
0.80
0.80
1.93
1.97
3.38
0.85
1.69
1.83
1.80
1.64
1.60
1.79
1.73
1.19
1.91
2.58
0.81
0.75
1.00
1.00
0.50
0.50
0.75
1.00
0.75
0.25
0.75
1.25
0.50
0.00
0.75
1.25
1.50
1.25
1.50
33: Primary Metal Industries
LTV
Weirton Steel
Phelps Dodge
Alcan
Alcoa
Reynolds Metals
Brush Wellman
Kennametal
1.70
1.26
3.06
1.73
0.92
1.63
1.54
1.54
1.95
3.14
0.91
0.25
1.25
1.50
1.25
0.75
2.00
0.25
0.00
2.00
72: Personal Services
Angelica
Healthcare Services Group
Unifirst
1.64
1.16
1.40
2.37
1.21
0.83
0.50
1.00
1.00
0.50
45: Air Transportation
Continental Airlines
KLM Royal Dutch Airlines
FedEx
1.37
1.53
0.61
1.96
1.35
0.25
0.00
0.00
0.75
0.75
40: Railroad Transportation
Canadian Pacific
Norfolk Southern
1.02
0.42
1.62
1.20
0.63
0.75
0.50
0.25
These data are also presented graphically, in Figure 3 , illustrating their position in the southwest
quadrant from Figure 2.
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CI
Risk
1.0
72
671
33
22
26
372
632
871
358-9
362-5
29
24
51
40
45
50
0
KM
3.5 Risk
0
Figure 3: SPF 5 Industries
4. Discussion
So what can we say about the results? Initially, even within the category we have termed SPF 5, there is
great variety both across and within industries. Industries at the top of the KM Risk measure, such as
paper (3.24) and electronics and appliances (3.11) clearly have at least some firms for whom knowledge
development is of some importance. Not the same level as in some other industries (pharmaceuticals, for
example, has a average ratio of 5.54 by this measure), but KM initiatives should not be totally ignored. At
the bottom, however, are industries in which there is apparently very little new under the sun, such as air
transportation (1.37) and railroads (1.02). While the Tobin’s q measure will be affected by industries with
substantial physical capital, as that measure makes up the denominator, these results suggest that there
is very little in these industries of value from a knowledge perspective. The companies, throughout the
industry, are worth very little beyond their physical assets.
There are differences in the CI Risk measure as well, though not as pronounced. But some industries
show very little interest in what competitors are doing (air transportation, 0.25; wholesaling, durables,
0.35) while others are a bit more curious (paper, 0.98; textiles, 0.92) though again not rising to levels we
see in higher SPF industries. Though the level varies, there is generally not much interest in investing in
a competitive intelligence operation (or a need to defend against one).
But SIC categories can also hide differences between firms essentially in the same industry (and some
firms prove difficult to assign to a single SIC when they span many businesses). Even though all the
paper firms fall into SIC 26, for example, Tambrands and even Kimberly Clark are in very different
businesses than firms like Westvaco and Union Camp. They also have very different competitors, facing
up against Procter & Gamble, for example, rather than the other firms within the SIC designation. Even
ignoring such differences, however, there are marked variations in both KM and CI level within industries.
One of the key things we believe our strategic focus and methodology add to KM theory is a way for
practicing managers to assess their situation vis a vis KM and CI. Going back to the paper industry, if one
looks just at firms that focus on basic paper products, there are still differences. And if one is competing
in that in that industry, it’s important to note the relative KM success of an Avery Dennison (3.90) vs.
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James River (1.02). Avery Dennison has developed knowledge assets to some degree. To compete
effectively with them, another paper firm may need to up its game in terms of KM systems, even if it
doesn’t warrant the resources necessary in other industries. The SPF approach clarifies what is standard
for an industry, what is outstanding performance, and what is lagging. It demonstrates that superior
performance is found in a ratio of 3-4 while something in the area of 2 is competitive with most other
firms. Similar judgments can be made about industry averages and necessary investment in CI
operations.
Are there any similarities that allow us to explain why these industries and firms are in the SPF 5
category? What it appears we have here are a number of old-line industries where there is apparently
little new knowledge of value. Our assumptions coming into this analysis were that industries in this
category would probably revolve around individual creativity, genius, or craftsmanship that would be
difficult to duplicate (hence no need to capture and share throughout the organization). That really isn’t
seen in the data, though the firms that compete on such a basis may not be of such a size to fall into our
database.
Rather, what we see are old-line manufacturing or processing industries, often based on natural
resources. In addition, we see basic services such as wholesaling, insurance, and engineering wherein
little is hidden and there is little of real value added through what we consider typical knowledge assets
(improving proprietary processes and such). The basics are the basics, and individual contributions
through learning or innovation are muted. And if knowledge isn’t overly valuable for the originating firm,
there is little value for competitors either.
These ideas square well with previous theory concerning KM and CI. The conceptual basis of the SPF
framework suggested that environmental factors on the national, industry, and firm level could affect a
firm’s need to develop and protect knowledge assets (Rothberg & Erickson 2005). At the national level,
for example, regulation can impact the circumstances under which knowledge is employed. Here, there
are a number of regulated industries (transportation, natural resources, financial services) that may not
have incentives to innovate or find new processes. Or regulation may require or encourage sharing of
knowledge across industries, again affecting if and how knowledge is developed or protected.
Similarly, factors at the industry level such as industry life cycle stage (just about every industry in this
study is quite mature) or degree of competitive rivalry could make a difference. The nature of the
knowledge employed in the industry (tacit or explicit, complex or not, specific/sticky or not) can also have
an effect. Generally, knowledge that is tacit, complex, and sticky is harder to develop but not particularly
hard to protect, though whether that is what is going on in this case would require deeper analysis and
more data.
As noted earlier in this paper, the point of this type of analysis is precisely to identify when the
circumstances are right to pursue knowledge development and when not. To identify when aggressive
competitive intelligence is appropriate as well as robust CI defences. While these measures are not yet
developed enough to trust at the margins, the results are robust enough provide compelling guidance at
the extremes. Those industries and firms with markedly low KM risk and CI risk numbers clearly have
little knowledge of value about them and should take care in devoting assets to knowledge initiatives.
5. Conclusions
Our intention is to continue to develop this analysis, with different parts of the framework and with ever
more in-depth data. Initial results are promising in terms of identifying high-risk industries and firms and
low-risk industries and firms, in all areas. As we continue this work, we continue to gain a better
understanding of the circumstances within which knowledge assets are managed.
With such an understanding, management of IC can become more strategic. By knowing conditions n
their industry, managers can gauge the opportunities and threats present in decisions regarding
investment in KM systems, including both development and protection. As a result, KM can be pursued
aggressively when circumstances call for it. Alternatively, when investment may do little good, managers
can forgo both the expense and disappointment of unwise pursuit of knowledge development.
Acknowledgement
The authors gratefully acknowledge the cooperation of the Society of Competitive Intelligence
Professionals which provided data used in this study.
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Scott Erickson and Helen Rothberg
References
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Rothberg, H.N. and Erickson, G.S. (2005) From Knowledge to Intelligence: Creating Competitive Advantage in the
Next Economy, Elsevier Butterworth-Heinemann, Woburn, MA.
Stewart, T.A. (1997) Intellectual Capital:The New Wealth of Organizations, Doubleday, New York.
Tan, H.P., Plowman, D. & Hancock, P. (2007) “Intellectual Capital and Financial Returns of Companies”, Journal of
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A Problem-Solving Typology of Service Business
Paavo Ritala1, Tatiana Andreeva2, Miia Kosonen1 and Kirsimarja Blomqvist1
1
Lappeenranta University of Technology, Finland
2
St. Petersburg State University, Russia
[email protected]
[email protected]
[email protected]
[email protected]
Abstract: In this study, we sketch a “problem-based perspective” of the service business, following the latest
theoretical developments in the field of the knowledge-based view of the firm and the related problem-solving
perspective. In particular, we approach services as “problems to be solved” for and with the customer. Our paper
outlines a framework in which the knowledge processes regarding service delivery are conceptualized on two axes:
1) the intensity of knowledge sharing and co-creation of services between the provider and the customer and 2) the
nature of the problem-solving process regarding the service delivery. Based on the developed conceptual framework,
we provide implications concerning the organizing of various types of services in terms of the different problemsolving processes they require. Furthermore, after identifying the distinctive problem-solving processes with the help
of the typology, theoretical and practical implications for service and knowledge management are discussed.
Keywords: services, service business, knowledge, co-creation, problem solving, typology
1. Introduction
The service sector has shown a significant increase in importance, and it has become the dominant
driver of economic growth in many economies over the last decades (Andersen et al., 2000). Services –
rather than products – are often in the core of the business models of contemporary organizations
(Hurmelinna-Laukkanen and Ritala, 2010). Consequently, research on services has gained increasing
attention within recent years to understand the factors of competitiveness in this field. The basic
assumption behind this stream of research is that services differ from products in many important
aspects. In particular, services are seen as extremely heterogeneous and often intangible processes,
which most often involve and depend on specialized human labor. In fact, specific challenges and best
practices of managing so-called “knowledge-intensive services” have received increasing interest (e.g.,
Tether and Hipp, 2002; Freel, 2006). It has also been widely suggested that knowledge-intensive service
firms generate value and contribute to growth in the contemporary economy more than other types of
services (e.g. Andersen et al., 2000).
The knowledge-intensive nature of many high-value services calls for effective knowledge management
in this field. However, since services are extremely heterogeneous, it is difficult to formulate generic
management guidelines or best practices for service business-related knowledge management. For
instance, Oliva and Kallenberg (2003) note how the transition from products to services causes major
concern in terms of how to replicate HR and knowledge management capabilities in service provision. In
any case, human resources and the related knowledge assets are seen as especially valuable in serviceoriented firms (Kianto et al., 2009). Thus, the underlying challenge of service management in general is
to pursue effective combination and integration of individual and organizational-level knowledge in order
to create new value through service solutions (e.g. Chesbrough and Spohrer, 2006).
To address this issue, we propose a pragmatic conceptualization on the nature of the service business
(in B2C and B2B contexts) which we call a ”problem-solving perspective of the service business”. In this
task, we utilize the knowledge-based view of the firm (Grant, 1996; Spender, 1996), as well as the
recently established problem-solving perspective of a firm (Nickerson and Zenger, 2004; Nickerson et al.,
2007, Heiman et al. 2009). The problem-solving perspective views the organization as a problem-solving
entity, where the role of the organization is to solve valuable problems and utilize various knowledge
processes to organize for this task. In accordance with the problem-based perspective we analyze
knowledge processes in services simultaneously from the customer and provider perspectives, showing
that services can be seen as problems to be solved and where the process involves different levels of
knowledge sharing and creation. Even though earlier conceptualizations of the knowledge intensity of
service providers and customers exist (see e.g. Hauknes, 1999), the problem-solving perspective allows
a more in-depth as well as pragmatic analysis in terms of understanding the knowledge processes
involved in service provision.
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Reference this paper as: Ritala, P, Andreeva, T, Kosonen, M and Blomqvist, K. “A Problem-Solving Typology of
Service Business” The Electronic Journal of Knowledge Management Volume 9 Issue 1 (pp37-45), available online at
www.ejkm.com
Electronic Journal of Knowledge Management Volume 9 Issue 1 2011
The main contribution of our study is twofold. First, we elaborate a knowledge process-based view on
services and analyze problem-solving issues. The framework enables a useful theoretical and practical
categorization of all types of services based on the different levels and types of their knowledge intensity.
In this, we distinctively identify the role of customers and providers in solving the service-related
“problems”, which helps to analyze the value and provision of a service from a value co-creation
perspective. Second, we formulate theoretical and managerial implications for different types of services,
utilizing the proposed framework as a basis for these implications. In addition, the typology proposed in
this study is helpful for future research in suggesting that all services can be viewed from a problemsolving viewpoint, taking into account the variation in the intensity of co-creation as well as the level of
routinization.
The study is structured as follows. In the next section, a problem-solving perspective of service business
is briefly formulated. Then, a problem-solving typology of service business is sketched with the help of a
two-by-two matrix. Finally, we discuss and summarize the proposed framework with the help of practical
examples from different service industries. To conclude, we propose concrete implications for practice, as
well as further avenues for research.
2. Problem-solving perspective of service business
Services are by nature something that help customers to solve their specific problems. Thus, by
consciously adopting the customer’s problem as the object of inquiry in theory development, the nature of
services is intuitively taken into account throughout the analysis. In this section, we formulate very simple
foundations to a view what we call a “problem-solving perspective of service business”. Our aim is to
adopt the problem as the unit of analysis, and analyze service business from the co-creation perspective
where such problems are solved in collaboration with the customer and provider of the service.
2.1 Problem-solving perspective of a firm
Why do firms exist and how do they organize to create value? These questions are fundamental ones in
organization theory, and have been approached from many perspectives, including transaction (Coase,
1937; Williamson, 1985), evolutionary (Nelson and Winter, 1982), resource and capability (Penrose,
1959; Barney, 1991; Teece et al., 1997; Teece, 2007), and knowledge (Kogut and Zander, 1992; Grant,
1996; Spender, 1996) perspectives.
The problem-solving perspective of a firm (Nickerson and Zenger, 2004; Nickerson et al., 2007) departs
from the other theories of a firm in that it takes the problem as the unit of analysis. The perspective
fundamentally builds on the knowledge-based view of the firm (Kogut and Zander, 1992; Conner and
Prahalad, 1996; Grant, 1996) and also contributes to the recent discussion around the “knowledge
governance” approach (Foss, 2007; Foss et al. 2010; Heiman et al., 2009). From this perspective, any
individual organization is seen as a problem-solving entity. The “problem” is understood in a broad sense,
including any type of issue or activity that can create value (or is valuable) if a valuable solution can be
found. Therefore, successful organizations are those that are able to identify and solve problems that
eventually bring unique competitive value in the eyes of the organization’s customers. In other words, the
more valuable the problem identified and the more valuable the solution found to such a problem (in the
eyes of the customer), the more value is created in the end.
In a more practical sense, the problem-solving perspective helps to understand the nature of problems
the organization encounters and identifies which problem-solving methods (i.e. organizational knowledge
processes) are most applicable. This is the viewpoint which is used in this study to categorize different
types of services according to the problem-solving processes involved, and to develop theoretical and
practical implications based on this.
2.2 Services as problems to be solved
The problem-solving perspective has been used to describe the identification and solving of problems
inside an individual organization (Nickerson and Zenger, 2004; Nickerson et al., 2007), we extend the
logic to cover the customer/provider interface in order to describe the service business through this
perspective. We claim that services can fundamentally be seen as “problems to be solved”. A service is
often a specific benefit that the customer obtains, for example, in terms of convenience, time saving,
physical transformation, or a value adding function for customers’ possessions (for a review, see e.g.
Cook et al., 1999; Lovelock, 1983). All these can be viewed as different types of problems. For example,
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the customer can seek a solution for a broken car (solution = repair), monetary assets that are in
redundant use (solution = financial advice, e.g. wealth management), transportation (solution = a bus
service/taxi), or uncertainty over the target market’s needs (solution = market research/consulting
advice). All these examples include the logic that there is a problem which has been identified, and that
providing a solution to it creates value.
As the services by their very nature involve intense cooperation between a client and a provider,
problem-solving processes in services can be delineated in two categories: 1) service co-creation with
the customer and the related knowledge sharing and 2) the nature of the service-providing process. First,
the co-creation perspective suggests that the customers are the fundamental initiators (more or less
consciously) of the problems (or the issue around which they have a problem that they have not specified
yet) to which they seek solutions. In this task, there are varying levels of knowledge sharing (and cocreation) required between the customer and the provider in interactively identifying the exact problem to
be solved. Second, the nature of the service-providing process suggests that the service provider solves
the problem for (and with) the customer through certain problem-solving processes. Again, there are
varying levels of knowledge requirements in such processes.
In the following sections, we first discuss the co-creation of services and related knowledge sharing and
secondly the nature of service provision in terms of different problem-solving processes.
3. Problem-solving typology of services
3.1 Co-creation intensity
Customers are viewed here as individuals or institutions seeking solutions to their problems in
collaboration with service providers. This requires various types and levels of knowledge sharing.
Especially in cases where knowledge sharing requires complex and intense interaction between the
provider and the customer, customers become the “co-creators” of services (e.g. Sawhney and Prandelli,
2000). The co-creation perspective on services implies that value is created in collaboration with
customers (and with other organizations in the overall value network). Indeed, a better understanding of
the customers’ role and developing methods for motivating customer involvement in co-creation
processes is needed within the service science (Ostrom et al., 2010). For instance, Bettencourt et al.
(2002) note how customers must perform effectively and take an active role when co-creating services.
They should openly communicate useful and timely information, and take responsibility for maintaining
the relationship itself and problems that arise. The complex and customized nature of interactions makes
problems and adjustments unavoidable. Thus, it is essential for customers to communicate potential
bottlenecks on time, provoke questions, and provide constructive feedback (Bettencourt et al., 2002).
Prior research focusing on customer relationships within knowledge-based services distinguishes
between transactional and co-operational relationships (Sivula et al., 2001, O’Farrel and Moffat, 1991,
Miles, 2005). In transactional relationships, the customer typically knows a solution to the problem in
question and the relationship is dominated by market efficiency. In contrast, in cooperative relationships
the customer does not know how to solve the problem beforehand. In line with the co-creation
perspective, solutions to problems are developed in the relational exchange of knowledge and skills
between the service provider and customer.
Based on the aforementioned issues, two basic modes of knowledge sharing and co-creation relevant for
service-related problem solving can be roughly divided into “low” and “high” categories. First, some
services require only few in-depth knowledge inputs from the customer, and related to this, low levels of
co-creation regarding the service. In such cases, problem identification is a process where the customer
has a problem (= a service need) which is repeated over and over again, to the extent that the
identification of the problem is basically similar each time the problem occurs. Services that are used
frequently in a similar manner, such as transportation, grocery store shopping, or car repair are situated
within this category. In some cases, the customer has a problem which is repeated from time to time and
is thus of familiar nature, but there is some variation over the specific customer need involved each time
the service is requested.
Second, certain services require service creation-related knowledge to be exchanged between the
customer and provider. In these instances, the problem is identified and solved in an intense co-creation
process between the provider and the customer. Oftentimes in these situations, the customer has a
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time, individualized services, which often include contingencies over the time, place, and other contextual
issues related to the service. In other words, knowledge exchange is mostly situational, rather than
generic. For example, services provided by the fire brigade are most likely to be unique for the customer
and to involve unforeseen elements related to the environment where the service is needed. On the other
hand, co-creation can only concern a certain part or element of the service, while other parts are similar
for all types of customers.
3.2 Nature of the problem-solving process
As the services are viewed as problems to be solved in our perspective, the nature of service provision is
discussed here as different types of problem-solving processes. The nature of the problem-solving (i.e.
service-providing) process fundamentally causes variation in the provider’s need to create and utilize
unique, service-specific knowledge during the process (from the provider’s viewpoint). The various types
of problem-solving processes of the service provider can be examined from the perspective of
routinization in these processes.
In general, a distinction between different types of organizational activities in terms of their routinization
can be found in the existing literature in the manufacturing context (see e.g. Lillrank, 2003). In the service
context, Tether et al. (2001) have distinguished firms’ service outputs as either standardized, partially
customized, or bespoke (individualized). Following these sources, and by integrating the problem-solving
perspective into the discussion, we distinguish between the different types of service providing processes
based on their nature in terms of problem solving between the polar types of “routinized” and
“unstructured” problem solving. Routinized processes are based on the repetition of existing ways of
identifying and solving problems, whereas unstructured processes relate to unique, highly customized
and often one-time ways of identifying and solving problems. In the business practice context, all the
problem-solving processes are eventually situated somewhere on a continuum between fully routinized
and completely unstructured processes. For the sake of simplification, we discuss both extremes
separately in this study.
First, routinized problem solving is a process where the service is delivered as a standard offering where
very little or no customization is involved (unless there is a crisis in the delivery process). Often,
routinized problem solving can be (almost) completely automated or standardized. In the process of
delivering these kinds of services, there is usually no need to create unique knowledge from the
perspective of the provider. Second, unstructured problem solving is a process where the service is
delivered in a unique way, involving none or only few pre-existing structures. In these instances, the
service provider is required to create new knowledge because the problems often range beyond the preexisting knowledge base of the organization.
Between these two extremes, there are naturally many “shades of gray”. However, most of the services
can be identified as belonging to one of these categories. These two types of problem solving, coupled
with the co-creation intensity discussed in the earlier section, are put together to propose a typology in
the following.
3.3 Typology and implications
In Figure 1, a two-by-two matrix is presented where the co-creation intensity of the service, as well as the
nature of the service-providing process are illustrated. As discussed throughout the last two sections,
these two axes determine the nature of problem solving in services from both the customer and provider
perspective. According to the model, services can be categorized according to the need for knowledge
sharing between the customer and the service provider in determining the service (i.e. co-creation
intensity), and according to the nature of the service and the related problem-solving process.
The lower left corner illustrates the logic of standard offerings. In such services, customer knowledge
inputs in the co-creation process are low, and very little knowledge sharing is required. In addition,
problem solving is a routine process, where services are delivered each time in a quite similar manner.
Examples of these types of services include car wash or railroad transportation, which are practically predetermined in terms of their delivery process.
The upper left corner identifies a type of service that we label add-on offerings. The difference with the
purely standard service offerings is that in these types of services, customer knowledge inputs are rather
high, and they are utilized in the co-creation of the service. Still, problem solving is a routine process,
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where the service is offered efficiently to address various types of customers’ problems. This type of
problem solving sometimes also allows the mass customization of services, where the customer has the
possibility to affect the contents of the offering, although the service delivery is routinized. Google, for
instance, pursues to offer access to any type of information the customer is seeking in a way that can be
scaled to cover all the possible customers possessing an internet connection. In a B2B setting, firms
offering market research services often have highly routinized ways to solve the customer’s problem (i.e.
framing of the search, conducting and reporting a survey etc.), but provide the customer with the
possibility to co-create the offering in terms of its target and eventual contents.
Co-creation
intensity
high
Add-on
offerings
Tailored
offerings
low
Standard
offerings
Specific
offerings
Nature of service and
related problemheterogenous, solving process
unstructured
homogeneous,
routinized
Figure 1: A problem-solving typology of service business
The lower right corner shows the area of specific offerings. In these types of services, co-creation
intensity with the customer is low, while problems need to be solved in an unstructured manner, yet with
some reliance on the existing service offerings or platforms. Rajala and Westerlund (2008) suggest that
these types of services are especially challenging in terms of business profitability, since the offering can
typically be only partially finished due to the pursuit to serve the needs of many different customers.
Furthermore, they suggest that these types of services are most common in subcontracting with semifinished products such as (software) subcontractors. Examples of these types of services are typically
more common in B2B settings, where providing integrative components and service platforms are quite
commonplace in the ICT industry or factory process maintenance services, for example.
Finally, the upper right corner identifies tailored offerings. In these services, customer knowledge inputs
for the co-creation process are particularly high, providing input in the individualized service delivery. In
addition, problem solving in these instances is a highly unstructured process, where the service is tailored
every time to meet the unique, often one-time customer needs. Thus, problems are solved with only a
very thin pre-existing knowledge framework, which makes it possible to come up with creative and
customer-centric solutions. These types of creative service offerings are quite commonplace in the
contemporary economy. A good example of such activity is interior design, where each case is different
depending on the context and customized customer needs. Further examples involve unique and onetime service activities, where each identified customer problem is solved in a unique way. Examples
include creative R&D services, and consulting projects concerning the client’s specific emergent problem.
4. Discussion
In this study, we proposed a framework where we described services as problems to be solved, involving
1) different levels of co-creation between the service provider and the customer and 2) different types of
problem-solving processes (routine or unstructured). Based on these axes, we suggested a framework of
problem-solving types in services, which provides a more in-depth view on approaching different types of
services and their knowledge-intensity than the pre-existing formulations. Table 1 below summarizes the
implications and provides practical examples.
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Table 1: Summary of the typology and practical examples
Standard offering
Nature of the
problem-solving
process
Knowledge
requirements in
service co-creation
Mostly routine, rigid
Almost no customer
knowledge required
Add-on
offering
Mostly routine, yet
allowing
customization
Basic knowledge on
customer
preferences
required
Specific
offering
Mostly unstructured
Tailored
offering
Unstructured
Low requirements
for customer
knowledge, but high
requirements for
service-specific
knowledge
High requirements
for customer
preferences and
service-specific
knowledge
Examples from
B2C markets
Car services
Car wash
Car maintenance
service
Car repair
Race car design
Banking services
Opening a bank
account
Bank loan
Wealth
management
Loan re-negotiation
Health services
Examples from
B2B markets
Taking temperature
Eyesight check
Mending fractures
Marketing
consulting
Market
report
Market
research
Future trends
research
Market strategy
consulting
Factory
maintenance
services
Supply of spare
parts
Supply of customer
process-specific
spare parts
Unexpected process
break down
maintenance
service
Customer core
process reengineering
Mental health
4.1 Theoretical implications
Our study provides important implications to the literature on organizing services. While comparable
frameworks have been crafted about services or offerings (e.g. Haukness, 1999; Rajala and Westerlund,
2008), the typology provided in this article takes two knowledge-related categories into account in a
unique way. Firstly, we elaborated a problem-solving based view on services, which has been greatly
lacking in the literature. Secondly, we approached problem-solving not as a passive, firm-initiated
process, but more as interaction between service providers and customers, thus incorporating the service
co-creation perspective (e.g. Bettencourt et al., 2002) and illustrating the types of knowledge needed for
mutual problem identification and solving.
Based on the framework different types of services can be studied empirically for a more thorough
understanding of the axes and different classes in the typology. Our perspective provides a useful point
of departure for studying the organizing of efficient and effective problem-solving processes in
organizations delivering different types of services. Also, our typology may serve as a foundation for the
comparison and re-interpretation of prior research on best management practices in the services sector,
and, through this, for building a more comprehensive theory of management of services.
4.2 Practical implications
Our study leads to important managerial implications for building sustainable competitive advantage in
service industries. The service offering of most firms can be seen to consist of a variety of services
requiring different type and level of knowledge sharing with the customer, and differing types of problemsolving processes from the service provider. Taking this into account, the relevance for service providers
is to optimize the appropriate knowledge processes and co-creation activities to suit their service offering.
In addressing this issue, our typology can provide a valuable tool for practitioners to analyze their
services portfolio in line with types and levels of problem-solving processes.
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For example, it can be expected that most of the relatively more routine service-providing processes with
various knowledge inputs from the customer can be automated and sold over the Internet. When the
service provider is able to provide services in this way, while taking into account also the individual
customer preferences (the upper left corner in Figure 1), the “sweet spot” of service providing can be
reached generating maximal customer value with routinized (and thus sufficiently inexpensive) problemsolving processes. Of course, not all services can be delivered in such a way. Thus, it is important for
managers in service firms to identify the customer needs and the underlying problem-solving processes
in their organizations in order to maximize customer value while still operating efficiently organizationwise.
In order to provide practical guidelines for practitioners, the proposed typology needs to be linked with
strategies and operational issues of firms. For example, our typology could help managers operating in
the service business to make informed choices regarding their overall knowledge management strategy.
The extant literature suggests that knowledge management efforts bring value to the organization only if
they constitute a coherent strategy (Blumentritt, Johnston, 1999). Two widely discussed knowledge
strategies are codification versus personalization or tacitness (Hansen et al., 1999; Schulz, Jobe, 2001;
Haesli, Boxall, 2005).Our typology suggests that organizations that represent the left part of the matrix
may benefit more from adopting the codification knowledge management strategy, since the customer
preferences and related problem-solving are quite homogeneous in these types of services. On the other
hand, organizations from the right part of the matrix may opt for the personalization strategy because
customer preferences are more heterogeneous and vague.
4.3 Limitations and further research directions
The main limitation of this study is naturally its conceptual nature. Thus, further research could empirically
investigate services in the four suggested categories. The differences between offerings/firms situated in
these categories could be tested in terms of profitability, size, industry, and so on. Case-based studies
focusing on the service portfolio of a certain firm could also be beneficial for the empirical application of
the framework. In this context, further study of the management practices (including human resource
management and knowledge management practices) in organizations of the four suggested categories
could be very informative for service practitioners.
In addition, the typology presented here could benefit from further theoretical and conceptual
development. For instance, the difference of and interaction between customer and provider possessed
knowledge could be analyzed in a more profound manner, as the value of services is fundamentally cocreated between these actors. Also, while they are analyzed within the same framework in this study, the
two distinct phases of problem identification and problem solving could be analyzed separately, as they
may consist (at least partially) of different types of interaction between the actors involved.
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Trust-Building Mechanisms for the Provision of KnowledgeIntensive Business Services
Enrico Scarso and Ettore Bolisani
DTG - University of Padua, Vicenza, Italy
[email protected]
[email protected]
Abstract: The term knowledge-intensive business services (KIBS) indicates private companies whose job consists of
collecting, generating, analysing, and distributing knowledge with the purpose of delivering customized services to
satisfy client’s needs. KIBS firms rely on highly educated professionals, and supply knowledge resources or other
knowledge-based services that clients are unable or unwilling to develop by themselves. The provision of KIBS
entails a bilateral exchange of knowledge between the service provider and the end user along with the entire supply
cycle. In this process, not only KIBS firms supply clients with precious elements of technical and applicative
knowledge, but also client firms provide KIBS with pieces of knowledge that are necessary for designing a successful
solution. As is well underlined in the literature, trust is an essential ingredient of client-provider knowledge
exchanges, so that KIBS companies have deal with it properly. This is not simple, since trust has several dimensions
that rely on different trust-building mechanisms. In light of this, the paper aims to analyse the different forms of trust
and the related trust-building mechanisms that come into play during the delivery of a knowledge-intensive service.
This is done by discussing the findings of a multiple case-study of a particular group of KIBS, i.e. computer service
companies located in the Northeast of Italy. Specifically, the study: a) offers a knowledge-oriented description of the
interactions that take place during the service delivery process between client and KIBS firms; b) analyses the role
played by the different forms of trust, as antecedents and consequences of each interaction; c) makes some remarks
about the trust building mechanisms that a KIBS company can exploit, and the resulting management implications.
Keywords: KIBS; knowledge interactions; trust-building mechanisms; computer services; case study
1. Introduction
The term knowledge-intensive business services (KIBS) was introduced by Miles et al. (1995) to indicate
private companies whose job consists of collecting, generating, analysing, and distributing knowledge
with the purpose of delivering customised services and solutions that client firms are not able or willing to
develop by themselves. KIBS companies rely on highly educated professionals, experts on specific
technical disciplines or functional domains, and supply knowledge resources or other knowledge-based
services to clients. They work in different sectors such as business and management consulting,
marketing and advertising, labour recruitment, legal activities, accounting and auditing services, research
and development, architectural and engineering activities, computer and related services, technical
testing and analysis. KIBS companies are usually subdivided into two broad categories, referred as PKIBS (pure professional KIBS) and T-KIBS (technology-based KIBS), which include the additional
category of C-KIBS (computer and software-related services) indicated by Martinez-Fernandez et al.
(2004). The latter is the object of our investigation.
KIBS companies have been the centre of the interest of many research works in recent years, especially
for two reasons. Firstly the sector has been one of the main sources of job creation in Europe; secondly
its development is closely linked to the technological progress and economic growth of a country (Pro
Inno Europe, 2009). In particular, KIBS firms are deemed to be a crucial component of the regional
innovation system where they are located, since they act as key producers and diffusers of new
knowledge (Doloreux et al., 2008; Rodríguex and Camacho, 2009). In point of fact, KIBS are not only
innovators by themselves (Ojanen, 2007), but they also support and promote the innovation activities of
other industries (Miozzo and Grimshaw, 2006). Since they “shuttle” between various business clients,
KIBS can carry new ideas, technologies and best practices from one firm to another, thus becoming a
“vehicle” for the transmission of innovative knowledge (Smedlund and Toivonen, 2007).
According to Strambach (2008) three core features denote the KIBS sector: a) knowledge is both their
key production factor and the kind of “goods” they sell; b) the delivering of knowledge-intensive services
generally requires an in-depth interaction between supplier and client, so that they become co-producers
of supplied services and are involved in mutual learning processes (Bettencourt et al., 2002); and c) all
KIBS firms perform an activity of consulting in the form of a process of problem solving, in which they
adapt their expertise and knowledge to the specific problem of individual client. To sum up, the provision
of knowledge-intensive services entails a bilateral exchange of knowledge between the involved actors
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Reference this paper as: Scarso, E and Bolisani, E. “Trust-Building Mechanisms for the Provision of KnowledgeIntensive Business Services” The Electronic Journal of Knowledge Management Volume 9 Issue 1 (pp46-56),
available online at www.ejkm.com
Electronic Journal of Knowledge Management Volume 9 Issue 1 2011
along with the entire supplying process - from problem formulation, to delivery of solutions and ongoing
after-sales support (Miles, 2005). During this process, not only KIBS companies provide clients with
precious elements of knowledge (for instance how to implement a specific application, how to re-engineer
a process, how to use a new technology), but also client firms provide KIBS with pieces of knowledge
that are necessary for designing, developing and delivering a successful service solution.
Such cognitive interaction requires a trustworthy environment to be effectively accomplished, since both
parties must be ready to exchange sensible information and knowledge (Bagdoniene and Jakstaite,
2009). This is the reason why although trust is an essential ingredient of many economic transactions, it
is even more crucial in the delivering of knowledge-intensive services (Weterings and Boschma, 2009),
so that it can be considered a key element of marketing strategies of KIBS companies. Accordingly, KIBS
companies need to implement mechanisms that allow them to establish and enforce trustworthy
relationships with clients. The point here is that not only trust is a multidimensional concept that entails
various aspects, but also the kind of trust that comes into play and its role may vary according to the type
of service provided as well as to the nature and the stage of development of the client-provider
relationship. Hence, KIBS companies have to be aware of the different kinds of trust-building
mechanisms they can exploit, as well as of when and how to employ them properly.
In light of this the paper intends to analyse the different mechanisms of trust-building that a KIBS firm can
exploit during the provision of a service. In particular it aims to outline and discuss their distinctive
features and application fields. This is done by illustrating the findings of a multiple case-study of a
particular pool of KIBS firms, i.e. computer service companies located in the Northeast of Italy. In
particular the study: a) offers a knowledge-oriented description of the interactions that take place during
the service delivery process between client and KIBS firm; b) analyses the role played by the different
forms of trust, as antecedents and consequences of each interaction; c) makes some remarks about the
trust building mechanisms that a KIBS company can make use of, and the resulting management
implications.
The paper is articulated as follows. In the next section we discuss the nature of the business relationships
and cognitive interactions that occur between KIBS providers and clients. Section three analyse the role
of played by trust in the cognitive interactions that characterise the delivery of a knowledge-intensive
service, and the related trust-building mechanisms. Section four gives some information about the
empirical investigation, and section five summarises its main findings. The last section offers some
concluding remarks about the managerial implications that can be derived from the study, and its limits.
2. Business relationships and cognitive interactions between KIBS companies
and clients
In order to understand the role played by trust during the provision of a knowledge-intensive service, and
investigate the trust-building mechanisms that KIBS firms can use to sustain their business activities, it is
necessary to go into the topic of business relationships and knowledge exchanges among KIBS
companies and clients.
It is widely agreed that interactions between customer and service provider are perhaps the most
distinctive feature of service delivery processes (Kuusisto, 2008). This is particularly the case of
knowledge-intensive services where service provider and customer may engage in a long process of
working together. Especially in the initial stage, namely when the business relationship starts, the players
need to achieve a mutual understanding of the situation. Such interactions involve a continuous
exchange of information and knowledge that spans the whole delivery process, from the initial formulation
of the problem by the client, to the delivery and implementation of the solution and the after-sale support
(Figure 1), and strongly relies on the existence of reciprocal trust.
It is worth noting that clients can be involved in the production of business services in many ways. This
means that the points of contact during the service delivery process, as well as the kind and depth of the
interaction (Päällysaho, 2008), can vary depending on: a) the degree of customisation of the delivered
service, and b) the nature and development stages of the business relationship.
Firstly it must be recalled that not all services are produced and/or delivered by means of an active
participation of clients. Concerning this, Kuusisto (2008) affirms that clients can assume four different
roles in services production (i.e. consuming, co-performer, co-creator, and co-designer) which require an
increasing involvement. For example, the supply of a standard software package looks like a simple
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Enrico Scarso and Ettore Bolisani
service consumption and does not involve the customer directly with the provider, while the delivery of a
personalised application can be regarded as a co-creation or co-design process, which requires an
effective contribution by the end-user. Al things considered the role played by the client is strictly
connected with the nature and the evolution of its relationship with the provider.
Figure 1: Cognitive interaction between KIBS and clients (from: Martinez-Fernandez and Miles, 2006)
Concerning the former, Miles (2003) identifies three main types of relationship, as follows:

Sparring relationships, when the content of the service is negotiated between provider and client,
communication as roughly being equal in status, knowledge and competence;

Jobbing relationships, which involve less interaction and require the provider to perform a specialist
and technical task, clearly defined by the client;

Sales relationships, which imply (more) standardised services that can be designed before the
transaction.
As regards the evolution of the relationship, Bagdoniene and Jakstaite (2009) distinguish four typical
development stages, which characterise the different degree of maturity of the relationship itself:

Pre-relationship stage. During this stage the client is looking for a service provider that could assist
him/her to find a solution. So everything that could help to evaluate potential service provider and
choose an acceptable one is useful;

Exploratory stage. At this stage the first contact with potential provider is established and the
relationship started. Clearly the two parties are still “distant”, since they have limited mutual
experience and knowledge;

Developing stage. This stage is denoted by the fact that both sides have increased their reciprocal
knowledge, thus developing a common understanding of problems and opportunities. The provider
expects the client has good awareness of offered services, willing to continue the relationship and
recommend the used services to other firms; at the same time the client expects that the provider
improve the quality of services, is more transparent, and the like;
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
Stable stage. This stage characterises long term partnerships, where the two parties are accustomed
to each other way of thinking and action. Reciprocal knowledge is at the top as well as the shared
understanding of business.
The nature and length of the relationship is also affected by the fact that KIBS services/products are
highly intangible, and this produces information asymmetry leading to clients being unable to fully
evaluate the quality of service delivered. According to de Bandt (1995, quoted by Miles, 2003) five types
of “information deficit” may concern the clients of KIBS providers:

It can be hard to establish the KIBS’ competence and experience in dealing with relevant problems;

The client may not be able to accurately assess the kind or level of skills required to deal with specific
problems it faces, nor to match these to the KIBS’ offerings;

The highly specific and complex nature of the service can make it hard to reach an agreement on the
specific services to be rendered, or on the criteria for assessing their quality;

Estimation of the effort required by the KIBS in supplying the service can be difficult;

The impact and effectiveness of the service provided by the KIBS may be affected by many factors
(some due to clients, some to unpredictable external circumstances), and consequently it is hard to
determine the KIBS’ responsibility in case of arising problems.
Generally speaking, the presence of relevant asymmetries favours the establishment of long-term
relationships between provider and client that are based on bilateral knowledge exchanges and mutual
trust (Bagdoniene and Jakstaite, 2009).
From what above said, it results that opportunities and needs for knowledge exchange vary in
accordance with the different types of relationship at stake. In particular, while sales relationships offer
little scope for cognitive interactions, sparring and jobbing relationships have potential for co-production
and dissemination of new knowledge, and call for more reciprocal commitment. Furthermore, the content
and the depth of the interactions vary along with the development stages of the relationship. In particular,
while initially the parties need to develop a minimal mutual acquaintance and hence have to share a lot of
information, later they have reached a common understanding of the business situation which makes the
issue of knowledge exchange less critical.
To sum up, the kind of trust and trust-building mechanism that come into play vary in accordance to the
kind of knowledge exchanges performed by provider and client, which are, in turn, affected by two
important elements, namely: a) the different activity or task performed during a specific project, and b) the
development stage of the provider-client relationship, i.e. its maturity. In the next section the different
trust-building mechanisms that are at work in provider-client interactions are analysed in relation to their
different effectiveness in the various possible situations.
3. Trust-building mechanisms
The role played by trust in knowledge interactions has been deeply analysed by the KM literature. In
particular, it is commonly agreed that trust is a necessary condition to persuade people to share
knowledge, particularly the tacit components (Ford, 2003). This is especially the case of interactions that
involve different organisations, for instance in the context of inter-firms alliances or business networks
(Panteli and Sockalingam, 2005; Becerra et al., 2008).
Before analysing the different mechanisms that KIBS companies can employ to create a trustworthy
environment, it is necessary to recall what is intended by trust. Conceptualisations and explanations of
the meaning of trust proliferate in current literature, so that a common definition of the term can’t be
found, as is well testified by the recent review made by Castaldo et al. (2010). A formal and often cited
definition is that proposed by Gambetta (2000), who defines trust as the subjective probability with which
a player agent assesses that another agent or group of agents will perform a particular action. In
accordance with this view, when we say that we trust someone or that someone is trustworthy, we mean
that the probability that he will perform an action that is beneficial or at least not detrimental to us is high
enough for us to consider engaging in some form of cooperation with him.
Despite the lack of a shared definition, it seems to be ascertained that trust is a multidimensional concept
consisting of several dimensions such as (Blomqvist, 1997; Şengün, 2010): dependability/reliability
(confidence, loyalty, respect), honesty, competence, mutual orientation (altruism, congruence,
motivation), and friendliness (acceptance, benevolence and liking). This means that trust involves many
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subjective components, linked to how the individual perceives the reality in which he operates and the
actions of the parties he interacts with. Thus the establishment of a trustworthy environment is based on
a mix of “rational” assessments and social-psychological perceptions that are vague and hard to manage.
In other words, as the real life experience shows, to create a trustworthy environment economic players
can resort to different trust-building mechanisms, that can be classified as follows (Ford, 2003; Panteli
and Sockalingam, 2005):

Institution-based mechanisms, based on warranty, certification, safety nets, or other formal
structures;

Deterrence-based mechanisms, derived from the presence of costly sanctions for opportunistic
behaviours;

Calculus-based mechanisms, grounded on the rewards that come from pursuing and preserving a
relationship, and fear of punishment for the violation of trust;

Knowledge-based mechanisms, relying on the information about involved parties, which also
develops thanks to repeated interactions. The assumption is that the more information is available
about someone, the more easy is to predict his actions;

Identification-based mechanisms, characterised by mutual understanding (i.e. empathy and a sharing
of common values) among parties to the point that each can effectively act in favour of the others;

Personality-based mechanisms, emerging from reciprocally sensitive, thoughtful and concerned
relationships.
Given that the different types/dimensions of trust are not mutually exclusive, trust can rely on several
mechanisms. The question is that these mechanisms can be more or less suitable depending on the type
of cognitive interaction and business relationship that involves the two parties. For example, as stated by
Roberts (2003), the type of trust needed for transferring tacit knowledge is different from the one required
for codified knowledge. The former case (indicated as “hard trust”) implies that the participants trust in a
set of formal institutions (e.g. contracts, IPR regime, laws) that can facilitate the validation and protection
of knowledge, while the latter case (denoted as “soft trust”) is based on the existence of common social
context, mutual understanding and long term relationships.
4. Empirical survey
In the following pages we illustrate and discuss the findings of an exploratory study aiming to examine the
trust-building mechanisms that small local computer services usually resort to during the service delivery
process. Given its exploratory aim, the research was carried out using a case-study methodology (Yin,
2003). Such approach, in fact, well fits the nature of the study and the complexity of the phenomenon
under investigation (Leedy and Ormrod, 2005). The analysis focused on the delivery of customised
services, developed through a project-based approach. In point of that, the study especially considered
sparring relationships (see section two), where cognitive interactions (and, consequently, trust-building
mechanisms) are more significant and relevant than in other types of provider-client relationship.
As said, the investigation regards how different trust-building mechanisms come into play in the different
steps of a delivery process, and in relation to the maturity stages of the provider-client relationship. The
aim is to point out the distinctive features of the various mechanisms, and their application domain. The
questions addressed are as follows: what dimensions of trust come into play in the various steps of the
service delivery process? What are the reasons for that? What type of trust-building mechanisms can be
used in those steps? How the stage of development of the business relationship affects the kinds of trust
involved and the relevant trust-building mechanisms?
A multi-case study methodology seems particularly useful to address these questions, because it allows
to find regularities in the information collected and to classify variations and diverging cases or situations.
Specifically, the survey involved 21 small firms (Table 1) in the Northeast of Italy (Veneto Region). The
sample was mainly identified with the help of a local industry association.
The collection of information consisted of an in-depth semi-structured interview with executives and
managers, and was based on a framework that was previously tested by means of a “pilot interview” with
two company managers, which allowed adjusting it especially as regards language and terms used. For
instance, concepts such as “trust” or “knowledge transfer” (that may have a clear definition for
researchers but may be misunderstood by managers) were paraphrased into terms that are more
understandable in business, or are indirect manifestations of them. Each interview aimed to examine how
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the single company is able to generate economic value through the processes of external acquisition,
internal processing (creation/elaboration, storage and retrieval) and finally transfer the knowledge needed
to supply computer services to clients. Although each interview was flexible and open (meaning that it
was possible to collect specific details in each case), the use of a common framework made the
comparison between different situations easier, and allowed to highlight similar patterns.
To increase the validity of the analysis, information gathered though the survey was integrated with other
elements coming from multiple sources (Yin, 2003), such as company documents, web sites, industry
literature, and data collected by means of additional interviews with special observers and informed
experts (clients or suppliers of the sampled firms, public agencies, and trade associations). The research
was mainly conducted in 2008 and partly 2009. Further details about the empirical investigation that are
not explained here for lack of room, can be asked to the authors directly.
Table 1: An outline of the cases examined (disguised names for reason of confidentiality)
Company
Specialisation
Main markets
Size
A
B
C
D
E
F
G
H
IT Infrastructure
ERP
ERP
ERP; Business Intelligence
IT Infrastructure
IT Infrastructure
ERP
Test and measuring systems
SMEs
Retailing, Manufacturing
SMEs, Beverage
Manufacturing SMEs
Finance; Insurance
SMEs
Manufacturing SMEs
Manufacturing; Laboratories
7
50
60
110
50
20
100
22
I
Network management
Large enterprises; Public org.
53
J
K
L
M
N
O
P
Q
R
S
T
U
Software applications
Security; Business Intelligence
IT Infrastructure
Services; Connectivity
ERP; Consulting
ERP
MIS
Information Systems
ERP; MIS
ERP
BPR
Consulting
Large manufacturing firms
Manufacturing firms
PA; Medium enterprises
PA; Private companies
Manufacturing SMEs
Manufacturing
Finance
SMEs; Retailing; Hospitality
Large Distributors
Manufacturing SMEs
Large distributors
Public org.; Large firms
40
26
30
60
10
250
273
140
70
50
15
9
First of all, we have to recall some features of the investigated firms that are important for our aims. The
sampled companies provide highly personalised solutions developed through sparring relations. The core
of their business is the capability to identify and analyse the problems of clients, and to find the proper
solution. This makes knowledge exchanges with clients vital. These are, in fact, the final users of the
services as well as the source of new knowledge that providers can use for future services. Although
each provider makes use of specific working procedures, they usually follow some typical steps when
developing and delivering a new service to a client. These steps are as follows: a) first contacts with the
customer; b) preliminary analysis and requirement identification; c) feasibility study and formulation of an
offer; d) negotiation, sign of the contract; e) technical development, release, test, and implementation;
and finally f) post-sale assistance. Every step involves several cognitive interactions with the client, where
trust can play a crucial role. For a provider, the duration of the relationship with clients is on average quite
long (cases of loss of clients are rare).
5. Empirical evidence: trust-building mechanisms in the different steps of a
computer service delivery process
In this section the different trust-building mechanisms that the surveyed companies usually adopt during
the different steps of a service delivery project are illustrated and discussed. In addition, for each step of
the project, the case of low maturity of provider-client relationship (i.e. with “new clients”) is contrasted
with the case of high maturity (i.e. with “old clients”).
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5.1 First contact with customer
First contacts are extremely critical especially when new business relationships are established, in that
very often computer services will not have other chances to introduce themselves to potential clients.
Even though technical reputation and “certifications” (i.e. official partnerships with a global technology
vendor, memberships of an industry association) still represent a good “visit card”, word-of-mouth
suggestions coming from satisfied clients continue to play a significant role. First contacts are generally a
responsibility of the provider’s commercial staff.
Once the prospective client has been identified and contacted, the situation changes. The provider
describes its offer in more detail, and the client provides some information about its interests. Generally
speaking, this is a moment of mutual acquaintance between the two parties, and the success of this
reciprocal exchange of knowledge can deeply influence the continuation of the business relationship.
Very often customers are approached by showing a demo of the product/service that illustrates its main
functions. Usually, the provider’s technical team incorporates just standard elements of knowledge into
this demo, and leaves the rest to direct explanations that are supplied by interacting with the client’s
buying team. Sometimes, the demo is configured using preliminary information about the specific
requirements of the customer, collected by the sales force during preliminary contacts. In many cases,
this step can go a long way especially with the most cautious new customers.
As said, institution-based mechanisms (i.e. all kinds of public and private certifications) can be useful
here, especially during the first contact with prospective customers. However, knowledge-based
mechanisms take the lion share, given the crucial role played by the reputation created by positive
information passed by word-of-mouth.
The situation is different in the case of old clients, with which a stable relationship has already been
established. On the whole, the preliminary step is skipped, since the two parties have been accustomed
to the other way of working and thinking. This means that identification-based mechanisms are at work.
5.2 Preliminary analysis, requirement identification
After the prospective client has confirmed to be interested in the proposal, the service delivery process
keeps on with the analysis of the specific issues at stake and the identification of the service
requirements as more precisely as possible. Only the full understanding of the client’s problems allows
the provider to propose a complete and satisfying solution: hence in this phase client’s contribution and
active collaboration is decisive. Our investigation confirmed that such attitude prevails with old “longlasting” clients. Problems can arise with clients lacking some minimal technical knowledge, which may
found it difficult to appreciate the value of the proposed solution. Sometimes there may even be a
“hostile” behaviour, for two main reasons: first, when the proposed technical solution has organisational
impacts that can raise internal conflicts and negatively affect the project realisation; second, when the
client’s IT staff prefers a different technological standard or platform from the one suggested by the
provider.
The preliminary phase may be long especially with new clients, since many interactions and knowledge
exchanges are necessary to arrive to a satisfactory definition of requirements. Again, things are easier
with old clients, since the provider knows their business processes, and clients are more disposed to
assume a cooperative behaviour. Competence and willingness to collaborate on the client’s side are vital
for the success and the quality of the delivered service. In case of high-tech services, there may be the
need to develop trustworthy relationships with the client’s IT technical staff, given the influence that these
people exert on the buying decision as well on the project implementation.
This is the reason why during this phase the capability to cultivate personal relationships is critical, and
the willingness to collaborate by single individuals is essential. Especially in the case of a new
relationship (where the relationship is still at an exploratory stage) the provider’s staff has to be not only
expert of the technical field but also capable of understanding the client staff’s attitudes and behaviours.
Excellent communication abilities and some elements of psychology clearly help. This is why
identification-based trust and/or personality-based mechanisms are important here, both with new and
old clients.
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5.3 Feasibility study, formulation of an offer
The preliminary analysis provides inputs for the subsequent feasibility study that to goes into the
technical aspects thoroughly. Such inputs are formalised into a document on which the two parties agree,
and is fundamental for developing the offer, which consists of a technical part and an economic part,
each of which can be articulated in several papers. A key aspect of this phase concerns how price is
fixed. Two are the more diffused approaches:

Upon final balance, i.e. on the basis of the effective use of some factors (especially manpower)
whose unit price is contractually fixed;

Turnkey (fixed price), i.e. when the economic aspects are all established ex-ante.
The surveyed companies affirmed that, in recent years, clients increasingly prefer the second option. This
tends to transfer the risk of the business to the provider, especially in case of new relationships. In fact, it
has to be noted that the execution of the project can start only after the contract has been signed. But
before that moment the provider has had to show and transfer a pool of technical and managerial
knowledge to the client about the ideas of the possible service, with no economic return. These ideas
could be used by the client to compare the provider’s proposal with those of competitors. The client can
also try to use them on its own, without the provider’s help. For the provider this is especially risky in the
case of new clients: calculus-based mechanisms (concerning estimation of the risks and opportunities to
engage in a new project) come into play here.
The same mechanism is at work when the provider considers it useful to cooperate with a particular client
for jointly developing an innovative solution. In this circumstance, the provider often bears part of the
project costs in order to encourage the client’s participation in the project.
5.4 Negotiation, sign of contract
This step is characterised by the fact that the provider must be able to communicate the economic value
of the proposal to the client which, in turn, has to understand and appraise it and possibly formulate
counterproposals. Typically, supplier-client communication occurs through a combination of direct faceto-face interactions and transfers of contractual agreements. Again, communication is easier with “old
clients” that are experienced with the provider’s proposals. The choice of the contract format varies from
case to case, typically in accordance with the size of the client. In general, bigger and organized clients
use their own contractual formats and require the provider to follow them; the opposite occurs with
smaller customers.
In principle, the resort to contracts implies that deterrence-based mechanisms are working. Instead, other
forms of mechanisms prevail, for instance those based on calculus of mutual convenience or, even more
important, those based on reciprocal knowledge of parties, especially with reference to the more
intangible (and hence difficult to define) aspects of a contract. Indeed, the investigated companies
consider a contract a “working tool” or a necessary act rather that a real warranty against the possible
opportunistic behaviour of counterparts. Actually, the complex nature of the delivered services requires
flexibility by both parties: cases of misunderstandings, requests of changes, delays and similar needs are
usually faced by coming to an arrangement instead of taking legal steps. Sometimes, to be sure of having
a “real time” validation of their job, the provider requests that an internal referent is designated, who has
the responsibility for the project on the client’s side and acts as interface with the provider’s project team.
The selection of the delegate is critical, because it can influence the level of trust between the parties. To
sum up, in this phase there is prevalent use of identification-based and personality-based mechanisms,
especially in case of old clients.
5.5 Technical development: Release, test, and implementation
This activity is largely accomplished by the surveyed companies internally, and does not involve many
interactions with the client. Sometimes, the project schedule is shared with the client who can therefore
control the progress of the work closely. This is a knowledge-based mechanism that increases the level
of trust between the parties.
The project ends with the installation, test and implementation of the application/system at the customer’s
offices. In many cases, the client’s workforce has to be trained to use the new application. This is another
crucial point especially for the more customised solutions, whose functioning is difficult and complex to
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learn, and cannot be done only through written handbooks. Hence the training of the client’s employees
concludes the knowledge transfer.
During the installation, the provider may need to be allowed to access the information system and
database of the client. Consequently, it may come into possession and manipulate crucial information.
While strict contractual agreements (i.e. deterrence-based mechanisms) may be of use with new clients,
with old clients they are of less use than knowledge-based and identification-based mechanisms that
derive from previous co-operative work.
Lastly, it is worth remembering that a successful project represents the best way to satisfy the client
needs and to improve the provider’s reputation. This also sets the ground for a continuous business
relationship, and represents a good visit card for new clients.
5.6 Post-sale assistance
In principle this step may or may not be specified in the contract, but the continuous management of the
customers’ base represents, for many providers, a substantial part of their business. Nurturing
relationships provides opportunities for acquiring new orders and upgrading the offer. Almost all the
surveyed firms are very committed in cultivating the relations with their main clients, as testified by the
periodical visits that their commercial staffs usually do. Such visits are denoted by mutual exchanges of
knowledge concerning, on the one hand, the recent technical advancements and the provider’s new
applications and, on the other hand, the last news about the client and its business. Other ways to
“cultivate” customer relationships are newsletters, workshops, Internet portals, and other indirect
channels. Whatever it is, this “customer care” activity puts into action identification-based mechanisms,
whose exploitation benefits from the proximity between providers and clients.
6. Conclusion
The empirical investigation confirms that the delivery of a knowledge-intensive service, as in the case of
computer services, is a complex and articulated process that consists of a sequence of cognitive
interactions by which the involved actors increase their knowledge about the problem and the ways to
deal with it.
Trust proves to be an essential ingredient of the different steps of a project, and the establishment of a
trustworthy environment is directly associated to the intense knowledge exchanges that are necessary.
As the study shows, several forms of trust come into play in this process. The awareness of that is
particularly important for managers of KIBS companies, and the selection of the appropriate mechanism
of trust-building becomes particular critical.
In point of this, the survey confirms that the role played by the different mechanisms changes both with
the step of the delivery process, and in accordance with the maturity of the provider-client business
relationship. This is illustrated in Table 2 where the main outcomes of the analysis is summarised.
In any case, it is notable that soft forms of trust seem to prevail on hard forms. Actually, even though
computer services imply technicalities and formal methods, codified knowledge assumes a minor role
than informal or tacit components. Consequently, more than on formal trust-building mechanisms (e.g.
contracts, certifications, laws), trust is based on the establishment of personal relationships even among
individual employees of the two parties, and this increases the likelihood that provider-client relationships
will last long. There is, however, a difference between old and new clients. While with new clients there is
some room for hard trust-building mechanisms, with old clients the soft forms that involve empathy and
mutual understanding (i.e. identification-based or personality-based mechanisms) are prevalent.
The prevalence of soft mechanisms raises an evident risk: while a trustworthy atmosphere takes a long
time to be created, it may take a very short time to break it. Just one mistake or misbehaviour can destroy
a reputation created in several years of fruitful cooperation. Furthermore, thanks to the word of mouth
communication process, a disappointed client matters much more than a satisfied one.
The findings of our investigation allow to draw some managerial implications for marketing and human
resource management strategies of KIBS.
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Table 2: Use of trust-building mechanisms in relation to the different steps of a service project and to the
different relationship maturity
Type of mechanism
Institution-based
Deterrence-based
Calculus-based
Knowledge-based
Identification-based
Personality-based
Project phase
Old clients (mature relationships)
New clients (new relationships)
First contact
Negotiation; tech development
Feasibility
Feasibility; negotiation
Tech development
First-contact; tech development
Preliminary analysis; negotiation; tech
Preliminary analysis; post-sale
development; post sale
Preliminary analysis; negotiation
Preliminary analysis
As far as the former are concerned, providers need to develop marketing initiatives that allows to employ
the proper trust-building mechanisms in the different steps of a service delivery project. This involves
taking care of personal relations and assuming a transparent behaviour with the client. It also implies
having updated information about the business situation of client. The use of Customer Relationship
Management approaches and tools can support such activity. Also, specialising on specific markets or
customer needs (this is particularly the case of many computer services companies) can allow providers
to reach a deeper understanding of the client’s needs, which reinforces the positive effects of
identification-based trust-building mechanisms.
Furthermore, empirical findings show that employees need to have not only technical competencies (i.e.
those strictly related to the delivered service), but also relational capabilities and skills. This is not always
simple: for instance, in case of T-KIBS companies (as computer services providers), the technical
background of many employees can be a limitation. In any case, the physical, “social” and cultural
proximities between clients and providers may be of help here.
The main limitation of this study is that the findings are not easily generalisable to the entire KIBS sector,
since they concern only a particular industry, whose knowledge base can be described as synthetic
(Weterings and Ponds, 2009), i.e. denoted by the application or novel combination of existing knowledge,
by low levels or R&D, and by an orientation to solving customers’ problems. In the computer services
sector, learning by doing, practical skills and tacit knowledge are crucial and generally lead to incremental
innovations. Things may change when KIBS companies with an analytic knowledge base are considered,
i.e. those characterised by a strong reliance on scientific inputs and codified knowledge (e.g., the life
science industry). Here, knowledge generation processes are more rational and systematic, and
outcomes are often documented. Hence, there is the need to extend the analysis to other KIBS sectors,
especially with the aim to investigate how the different kinds of knowledge exchanged in a KIBS-client
interaction may affect the role played by trust and trust-building mechanisms.
Acknowledgements
The authors are grateful to Kirsimarja Blomqvist for her useful comments during a preliminary
presentation of this work at the European Conference on Knowledge Management.
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The LIFE Technique – Creating a Personal Work Profile
Peter Sharp
Regent’s College, London, UK
[email protected]
Abstract: This paper focuses on the question: how can a personal work profile be created most easily and effectively
for people considering their future? A personal work profile is a detailed description of the skills a person would like to
use and characteristics of a work environment they would like to experience. This is valuable for all people of working
age because it helps them find, or move towards, work which suits them best. This is tremendously important in
Knowledge Management (KM). This is because when the an individual’s knowledge and skills are matched well with
the work they conduct, there is a high level of job satisfaction, motivation and performance. Therefore, if there is a
good match, employees and organisations benefit enormously. The paper categorises and critically examines
literature relevant to the research question and explains why the new Look Into your FuturE (LIFE) technique („the
LIFE Technique’) was designed, what is new about it, how it works and how it has been road tested, reflected upon
and improved. The primary data strongly suggests that the stages of the Technique are useful and easy to do, and
that it is a valuable initiative that should be developed and applied further in the future.
Keywords: storytelling, personal knowledge and skills, work profile
1. Introduction
The question that this research focused on was: how can a personal work profile be created most easily
and effectively for people considering their future? There are many reasons why this is such an important
question. If a good personal work profile is created easily and effectively it enables the individual and the
organisation to get a good match between the work the organisation needs to do and the most suitable
employee to do it. When this is done the employee normally experiences increased job satisfaction. This
is important because if job satisfaction is low, companies lose core employees, work productivity suffers
and organisations fail to work effectively (Wan, 2007). A poor match between skills and work roles also
means that the implementation of core strategic functions can suffer (Prahalad and Hamel 1990), that
skill gaps can develop in an economy (e.g. Mohamud et al. 2006), and there is a loss of good employees.
This is a significant waste that can lead to the disintegration of organisations (Sveiby 1997; Larsen and
Myers 1999; Bolles 2006). Therefore, processes that effectively answer the research question should
help prevent these things happening and lead to positive outcomes for individuals, organisations and
economies.
2. Literary context
In this research „knowledge’ refers to the subject area that a person wants to work in (e.g. marketing),
and a „skill’ refers to anything that a person can do. So any verb relevant to a person is a personal skill
they have (Bolles 2006).
There are a number of different approaches to developing profiles to help people plan their future work.
Some approaches regard individuals as completely malleable to the requirements of the organisation.
Therefore, they create profiles [job descriptions] for employees to fit in to. Other approaches encourage
employees to take complete ownership of their own career path. Some approaches fall between these
two extremes. Table 1 summarises a selection of them.
Table 1: Approaches to profiling for future work
Approach
Aim of the Approach
Summary of how it
works
Degree of Individual
Ownership
1
Personal Story
Telling (Clare 2003)*
To openly think
about life and what
next.
Very high
2
Personal Flower
Profile (Bolles
2006)*
To produce a
personal flower
profile.
To reflect openly on
life and through
open discussion
think about
important questions
related to career
path.
Use the techniques
Bolles (2006)
advises to make up
the flower profile.
Very High
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Electronic Journal of Knowledge Management Volume 9 Issue 1 2011
Approach
Aim of the Approach
Summary of how it
works
Degree of Individual
Ownership
3
360 degree
feedback (e.g.
McCarthy and
Garavan 1999)
To assist in
setting career
goals.
Normally High
4
Career and
Development
workshops (e.g.
Stevens 1996)*
To plan next
career steps.
5
Career
Counselling (e.g.
Baruch 1999)*
To help clarify
future career
paths for
individuals.
6
Myers-Briggs
Personality Test
(e.g. Tagger and
Parkinson 2007)
To produce a
Myers-Briggs
Type Inventory
(MBTI).
7
Psychometric
Tests (e.g.
Melamed and
Jackson 1995)
8
Continual
Professional
Development
(CPD) and
Personal
Coaching (e.g.
Eales-White
2002)*
Training to do job
that is prescribed
by the
organisation.
To produce
personality
profiles and
occupational
interest
inventories.
To help clarify
future career
paths of
individuals.
To conduct 360
degree feedback
to develop a
character profile
to help set career
goals.
Reflection time,
self assessment
and exploration
and draft profile
options.
Meeting between
career counsellor
and an individual
to generate
profile.
Complete a
questionnaire on
personal
characteristics to
create profile.
Apply personality
questionnaires to
create profile.
Usually a mixture
of meetings with
personal coach
and work within a
CPD structure of
an organisation.
Mixture of
individual and
organisation.
9
To train
Training based on
employees in the
job requirement.
skills required to
do the job
described by the
organisation.
* With these approaches, usually a number of steps are applied in combination.
Normally high.
Normally high.
Depends on who
implements the
test and how the
profile is used.
Depends on who
implements the
test and how
profile is used.
Low
Some approaches do not tap in to the personal skills and character of individuals. For example some
companies may write job descriptions and train individuals to do those jobs but ignore the skills the
individuals may have. Techniques 3 to 8 in Table 1 are usually conducted within organisations and
introduce a framework. The framework may be the CPD structure of the organisation or it may be the
design of the technique itself. Arguably this is a problem because it can stifle participants in eliciting their
own personal skills (Stevens 1996; Bolles 2006). The approaches referred to in rows 1 and 2 of Table 1
seek to address this problem by putting a heavy emphasis on individuals shaping their own profile. The
author believes these approaches are preferable for addressing the research question in this paper
because they place emphasis on the individual tailoring their own profiles or plans. This gives them
ownership of the process and the outcome and tends to reflect their character most closely.
Clare (2003) takes a loose approach to telling personal stories and focuses on asking questions. The
weakness with this is that there is may be an endless series of questions that are asked and a personal
plan may only be loosely articulated. Bolles (2006) focuses on the construction of the flower profile based
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Peter Sharp
on a series of techniques to fill each petal. One of the problems with this approach is that it takes
considerable time to apply the techniques he provides and the techniques themselves can be
constraining. For example he has charts which list categories of skills which an individual can choose
from but the lists are not exhaustive and impose a structure that limit the participant and are very time
consuming to complete.
The LIFE Technique is designed to improve on these approaches. The idea is to use the story-telling
approach as a starting point and produce a personal flower profile. However, the idea is to produce the
profile using a different approach to Bolles (2006) so that less time is used and a personal set of skills is
created that stems from the very words of individuals who do the technique. To do this, the LIFE
Technique makes use of qualitative pattern recognition techniques (Miles and Huberman 1984) and the
principle of traceability from the MaKE model (Sharp 2004) (see Stage 2 in Section 3 below). The LIFE
Technique is also designed to be a relatively simple process that is useful but also relatively easy to do.
3. Design of LIFE technique
The purpose of the process is to facilitate the identification and articulation of a personal work profile as
easily and effectively as possible. Three cycles of action learning research were implemented (see
Section 4). This section explains the design of the LIFE Technique in these cycles. The „participant’ is the
person whose profile is created. The participant is assisted by a person who is referred to as the
„facilitator’. Appendix 1 includes templates relevant to each stage.
The aim of the LIFE Technique is to help a participant to articulate their own personal work profile. The
participant can be any person who is thinking about their future work life whether employed or not. Each
stage should be implemented by the participant working with a facilitator. He/she could be anyone who
understands how to implement the LIFE Technique. The original design had three stages. A fourth stage
was introduced in cycle 2 of the action learning research based on feedback received from cycle 1 (see
Section 5). The aim and process for each stage is given below.
Stage 1: Tell Personal Stories
Aim
Stages 1 and 2 are to identify the „real’ skills an individual has and enjoys using. Stage 1 involves
obtaining a record of three personal success stories for stage 2.
Process
The participant thinks back over his/her life and tells stories of three personal achievements. The value of
storytelling is that it taps in to the personality of the participant and comes very naturally to people (Clare
2003; Denning 2006). The facilitator listens and records on paper what the participant did to accomplish
the achievement. The participant is encouraged to tell each story in detail so the richness of their
character is expressed. After this, the participant is asked to say how he/she thinks the achievements can
be measured in terms of success. This is so the participant thinks about the personal value they attach to
their achievements. This helps participants to think about the positive side of what they have done so far
in their lives. It also helps participants to reflect on how they measure success.
Outcome
A record of the stories of personal achievements which can be put in a template (see Appendix 1).
Stage 2: Prioritise Skills
Aim
To prioritise 6 skills the participant enjoys and is good at using and put them in a list.
Process
The facilitator highlights the verbs that were written in each of the personal story accounts. He/she lists
them. The participant looks at the list and highlights the top 6 things that they like doing and think they
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are good at. The participant puts them in priority order in a new list (see right hand side of form for Stage
2 – see Appendix 1). This is built up from what the participant said in Stage 1. The idea is that the skills
that are identified can be traced back to the original personal stories of achievement in Stage 1. Having
done this, the participant should add a noun to each verb that is appropriate to specify more specifically
what they enjoy doing and /or think they are good at. For example, if „organising’ was a verb in the top 6,
the participant should add a noun (e.g. „organising information’) to make it more specific.
Outcome
Record of prioritised list of 6 skills the participant enjoys and is good at using listed in a template (see
Appendix 1).
Stage 3 : Create Flower Profile
Aim
To create a complete personal flower profile.
Process
The facilitator should write the 6 prioritised skills in the centre of the flower diagram and then help the
participant to complete all the elements (petals) of the flower (see Appendix 1). This stage is to make
sure the participant thinks about the other elements of a work environment that reflect their personal
preferences.
Outcome
A personal work profile in a flower picture which provides a clear picture of the personal skills, knowledge
and working environment which the participant thinks will suit him/her in their future working life.
Stage 4 : Draft Profile Statement
Aim
To produce a personal statement in a few sentences that clearly describes what skills the participant
enjoys using, in what places and with what type of people.
Process
The participant uses the information in his/her personal flower profile to write these sentences and hone
the statement as appropriate.
Outcome
Personal profile statement in the template (see Appendix 1).
The novelty of the LIFE Technique is not in the use of the flower concept or the emphasis on identifying
personal skills. This has been designed, published and used world wide (Bolles 2006). What is new is
the:

Design of a technique which combines personal storytelling with the identification of key personal
skills;

Use of simple qualitative data techniques to highlight and prioritise key skills (in Stage 2) in a way
that traces back to the personal achievement stories in Stage 1;

Order of the stages and;

The face-to-face nature of the Technique designed to be completed in one sitting of no more than 90
minutes.
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4. Action learning research design and implementation
This section explains and justifies the design and implementation of the action learning research
methodology.
4.1 Design of action learning research
The author describes the methodology as action learning research because there are significant
elements of the methodology that are like action research and other elements that are similar to double
loop learning methodology. The characteristics of the research methodology used in this research are
described and explained in light of characteristics of action research and double loop learning. There are
a number of characteristics of action research:

It aims to increase understanding of an immediate social situation.

It simultaneously assists in practical problem solving and expands knowledge.

It is performed collaboratively.

It is primarily applicable for understanding change processes in social systems.
(Hult and Lennung, 1980; Baskerville, 1999; Reason and Bradbury, 2001)
Many, would also add that:

It has an iterative nature;

It involves the participation of the researcher; and

It has an action and change orientation (i.e. active change of the environment in which the practical
application takes place).
Argyris and Schon (1996) articulate double loop learning within organisations in similar terms. They
emphasise the importance of addressing a problem in an organisation by actions that lead to
consequences that are reflected upon in light of the problem. The reflection in double-loop learning
includes reflecting on whether the original assumptions and problem were well founded and whether they
should be altered (Argyris and Schon 1996). Virtually all these characteristics align with the methodology
for this research. However, there are a few fundamental differences. This research is primarily designed
to work with individuals and examine in particular the LIFE Technique process - not specific change
processes within and for organisations. Also, this methodology does not seek to change the environment
of an organisation except to the extent of the effect of the LIFE Technique on the participants that may
work in an organisation. Figure 1 illustrates the structure of the action learning research cycles that were
used. For each cycle of research each of these stages would be implemented.
Figure 1: Action learning research loop (adapted from Baskerville, 1999 and Susman and Evered, 1978)
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The plan was that for each cycle of research the LIFE Technique would be used by a sample of
participants who were considering their future work preferences. Then feedback would be obtained on
the process. This feedback would be described, summarised, evaluated and learnt from before shaping
the next cycle of research.
To obtain feedback, the author used a questionnaire that was given to each participant (see Appendix 2).
The questionnaire was designed to elicit responses about two things on each stage.

1. How helpful the LIFE Technique is for participants in planning their future.

2. How easy it is to complete.
Likert-scale options are followed by an „Any Other Comments’ section so participants could freely
expound their opinions on these themes.
These themes are of fundamental importance to this research. The practical helpfulness of the Technique
is important to gauge because the research is designed to produce a concept that is practically valuable
for people’s lives. The second theme is also very important. If something is valuable but very difficult to
do it means that the concept is potentially of little value to a wide community of people. So it was
important in the questionnaire to prompt participants to give feedback in these areas.
For each section, space was given for „Any Other Comments’ and finally, an open question at the end of
the questionnaire was to elicit helpful comments to improve the design as appropriate. This gave
participants space to add comments to clarify their likert-scale answers and give suggestions that may
help improve the process or confirm its value. The questionnaire was relatively short to maximise the
chances of getting feedback from each participant.
4.2 Implementation of action research
In cycle 1, the author attempted to implement the Technique and obtain questionnaire feedback from 15
participants who fitted the criteria. Two could not meet him and therefore it was implemented with 13.
One participant went through the stages of the Technique but did not fill in the questionnaire. There was
a considerable range of participants in terms of age, nationality and employment status. The ages ranged
between 18 and 64 years old. The 13 participants were from 7 different nations. Employment status
varied but all were considering their future plans. One was an apprentice. The author applied the LIFE
Technique with each individual.
In the first cycle the researcher would implement the LIFE Technique himself and reflect on the
questionnaire feedback in light of his own experience in the action learning research and make any
improvements that may be required for the next cycle.
A couple of adjustments were made between cycle 1 and 2. The author designed pro formas that were
used in cycle 2 and Stage 4 was added and an equivalent section in the questionnaire. These
adjustments were made to improve the Technique based on the criteria for the design and reflection and
feedback from cycle 1.
In cycle 2, the author attempted to implement the Technique with a minimum of 20 Masters students in a
group context, pairing students up to implement the LIFE Technique as described above. It was
implemented with 24. There was a considerable range of participants in terms of nationality. The
participants came from 19 different nations and ages ranged between 22 and 32 years old. The MA
students were in a Business and Management faculty in an International Postgraduate Business School
in London. It was applied in the first 3 weeks of their Masters course.
In cycle 3, the author attempted to implement the LIFE Technique with 33 Masters students in a group
context and an alumni student, pairing students up as described above. It was implemented with all 33
individuals. There was a considerable range of participants in terms of nationality. The participants came
from 18 different nations and ages ranged between 21 and 41 years old. The MA students were in a
Business and Management faculty in an International Postgraduate Business School in London. It was
applied in the first week of their Masters course.
No adjustments were made between the implementation in cycle 2 and 3.
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Peter Sharp
Virtually every participant completed a questionnaire and provided feedback.
5. Presentation and analysis of primary data
The primary data will be presented and discussed in four parts. This is:

1. Feedback from cycle 1;

2. Feedback from cycle 2;

3. Feedback from cycle 3 and;

4. The overall pattern from all the cycles.
5.1 Cycle 1
A summary of the likert-scale primary data from cycle 1 is provided in Appendix 3. 12 questionnaires
were completed. The numerical data shows that 10 of the 12 agreed or strongly agreed in finding stage 1
helpful for planning their future. Not so many found it easy to do. 7 out of 12 found it easy to do and 4
disagreed that with the statement that it was easy to do. A similar pattern occurred with feedback on
Stage 2 and arguably with Stage 3, except with Stage 3 there were a 2 who strongly felt it did not help
them plan their future and 3 who neither agreed nor disagreed that it was easy to do.
The qualitative feedback for cycle 1 is shown in Appendix 3. The qualitative data for each stage was
limited. Only 2 people provided qualitative feedback for Stages 1 and 2. One commented that it was
interesting that the words that were used reflected their personality. Another said that Stage 1 helped
build confidence about oneself “looking back at positive events.” [Participant 1]. Stage 3 attracted far
more other comments. 5 made comments and virtually all of them stated how helpful it was to articulate
the vision in picture and written form of „what I want and need’ [Participant 6]. One participant [11]
suggested why he found it useful but not easy to do. This may reflect what others thought: “This is a great
exercise to do but something I could not have done easily on my own…”
The last question attracted 7 comments. 3 said it would be helpful to have something to look to the next
level, examples or lists of jobs that identify what may be available that matches their profile. One said pro
formas would help. Another, suggested a personal Strengths, Weakness, Opportunities and Threats
stage. The others made positive comments and suggested widening its application or giving more time to
the LIFE Technique.
5.2 Cycle 2
A summary of the likert-scale primary data is provided in Appendix 4. 24 questionnaires were completed.
The numerical data shows that 18 of the 24 either agreed or strongly agreed that they found stage 1
helpful for planning their future. Only one strongly agreed with this statement. Not so many found it easy
to do. 14 out of 24 found it easy to do and 10 did not. A similar pattern of feedback occurred for Stages 2,
3 and 4. In each case, more participants agreed or strongly agree that they found the stage helpful than
those who found it easy to do. This was a similar pattern to Stage 1 feedback, except more found Stages
2, 3 and 4 easier to do.
The qualitative feedback for Cycle 2 is shown in Appendix 4. Only 2 comments were provided for all the
stages. One comment reiterated how useful stage 1 was and the other comment referred to Stage 4 and
how much easier it is to do this stage, having completed the other stages.
11 comments were provided in answer to the final question. 4 comments expressed how useful,
enjoyable or effective the process was in putting „thoughts in to words.” [Participant 19]. Various
suggestions were made to improve the LIFE Technique.

Examples of lists of jobs that identify what may be available that matches personal profiles

Create a personal Strengths, Weaknesses, Opportunities and Threats matrix

More time to be given to the process

More reflection time between stages

Diversify questions

Remove repetition from the process
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
Adopt a questionnaire pattern like a belbin test for the process
5.3 Cycle 3
A summary of the likert-scale primary data is provided in Appendix 5. 34 questionnaires were completed.
The numerical data shows that 28 of the 34 either agreed or strongly agreed that they found stage 1
helpful for planning their future. 7 strongly agreed with this statement. 29 found it easy to do. A similar
pattern occurred with feedback for Stages 2, 3 and 4. However, for Part 3, Creating the Flower profile,
more participants strongly agreed (as opposed to just agreeing) that they found this helpful for future
planning and easy to do.
The qualitative feedback for cycle 3 is shown in Appendix 5. Only a total of 11 comments were provided
for the stages. These comments referred to clarification of the process, potential for development of
thinking based on outcomes from the process, and the usefulness of some of the outcomes.
12 comments were provided in answer to the final question. Four comments were very positive about the
whole process with nothing „on mind that could improve this process’ [Participant 16] or „it’s perfect’
[Participants 23 and 25] and one said „I think the process is efficient’ [Participant 6]. Two participants
were not sure and other comments suggested ways to improve the process:

More time to think over questions

More focus on careers people may want to do

Make it a bit more „grown up’!

Make it less formal
5.4 Summary of trends from primary data and future areas for research
Broadly, participants agreed that the stages were helpful in planning their futures and easy to do, which is
reflected in the average likert responses of 2.6 or less for all primary data collected. This included Stage
4 in cycles 2 and 3 and the overall feedback suggests that Stage 4 was a helpful addition. Within this
broad pattern it is noticeable that participants in cycle 2 generally agreed that each stage was useful to a
greater extent than they found it easy to do, although in cycle 3 there was some deviation from this trend
with as many if not more participants finding each stage as easy to do as it was useful. This is not easy to
explain because there were no adjustments in the Technique between cycle 2 and 3. The feedback also
suggested that there were other benefits that came from implementing the Technique like the value of
seeing words that reflect participants’ personality, the value of visual representation, and the usefulness
of the Technique for reflection and looking to the future.
In answer to the last question on the questionnaire, helpful comments were given to improve the LIFE
Technique (see Sections 5.2 and 5.3). These suggestions need to be carefully considered in terms of
benefits that they may bring. There were a range of suggestions. Some participants suggested using
more time for the process. However, this can be done outside the time devoted to completing the
Technique. However, this may not be practical for those who are busy at work and it would go against
one of the design aims of the Technique (see Section 3). However, the other suggestions are worth
considering for future cycles of application of the LIFE Technique and provide opportunities for future
areas of research. Also, some participants were not sure at the usefulness of this Technique immediately
after completing it. This is probably because they want to reflect on it after they have used the outcomes
from the Technique. Another future area of research is to obtain feedback on the LIFE Technique from
the participants in this research after more time has elapsed.
6. Conclusion
This research suggests that it is valuable to produce personally tailored knowledge and skills profiles to
help individuals plan their future. The LIFE Technique is a significant contribution in this area because
most participants find each stage useful for planning their future area of work and easy to do. However, to
say this with more certainty, the feedback from immediately after conducting the Technique may need to
be buttressed by future research from the participants after more time has elapsed. However, this
research strongly suggests the LIFE Technique is worth doing for anyone who is considering their future
and that it will help them plan and take the next steps in their work life strategy.
Note about this Paper
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Peter Sharp
This paper publishes research that develops and extends work published at the European Conference of
Knowledge Management 2010 (Sharp 2010).
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Sharp, P.J. (2010) The LIFE Technique – Creation of Personal Knowledge and Skills Profiles for Future Planning, in
th
Proceedings of European Conference on Knowledge Management (ECKM 2010), 11 European Conference on
nd
rd
Knowledge Management, Universidade Lusiada de Vila Nova Famalicao, Famalicao, Portugal, 2 – 3
September 2010, pp 921-932.
Susman, G. and Evered, R. (1978) An Assessment of the Scientific Merits of Action Research, Administrative
Science Quarterly, 23 (4), 582-603.
Stevens, P. (1996) What Works and What Does Not in Career Development Programmes, Career Development
International, Vol. 1, No. 1, pp. 11-18.
Sveiby, K.E. (1997) The New Organizational Wealth: Managing and Measuring Knowledge-Based Assets, BerrettKoehler Publishers Inc., ISBN: 1-57675-014-0.
Taggar, S. and Parkinson, J. (2007) Personality Tests in Accounting Research, Journal of Human Resource Costing
and Accounting, Vol. 11, No. 2, pp. 122-151.
Wan, H. L., (2007) Human Capital Development Policies: enhancing employees’ satisfaction, Journal of Industrial
Training, Vol. 31, No. 4, pp 297-322.
7. Appendix 1: Templates for stages of LIFE technique
[the templates have been reduced in size for this paper]
STAGE 1
Work Placement Module- MA in Global Management
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Name of Student who has achieved the things (below):
Achievement
What (s)he did
How does (s)he
measure success
1.
2.
3.
STAGE 2
Complete list of skills
Verbs ending in „ing’
List the top 6 in order of preference
which skills do you really enjoy using?
AND which do you think you are best at?
1.
2.
3.
4.
5.
6.
Favourite
Subjects
Interests/
Salary
and
Level
of
Responsibility
Favourite
People
Environment
Favourite
Skills
Type and Size
of Organisation
/
Anything
Else?
Geography
Location
/
Favourite
Values
Favourite
Working
Conditions
STAGE 3 Your Flower
(adapted from Bolles 2006)
2006)
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STAGE 4
Skills for Work- MA in Global Management
Name of Student ………………………………………………………………
Personal Statement
Produce a Personal Statement that combines elements of your flower to describe
what you enjoy doing
in what subject areas
in what places
with what type of people
8. Appendix 2: Questionnaire design [condensed in format for paper]
Questionnaire for LIFE project
Introduction
You completed a life story exercise of some of your achievements which was recorded. From this,
a list of your skills were extracted before and prioritized before a flower profile of a projected
future work environment was created for you. For the purposes of this questionnaire this is called
your LIFE project.
Informed Consent
[standard informed consent paragraphs]
Name of Participant
Nationality
Age
Job / Occupation [if applicable]
Telephone Number
E-mail
Date
Questionnaire
Section 1 – Questions about the Three Components of the LIFE project technique
Likert scale feedback
Please rate the statements below by ticking the appropriate box.
The numbers refer to the following scale:
1 = STRONGLY AGREE
2 = AGREE
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3 = DISAGREE
4 = STRONGLY DISAGREE
Part 1 of LIFE project technique - Telling My Story of Three of My Life Achievements
1. I found this helpful for planning my future.
1
2
3
4
Neither agree or
disagree
3
4
Neither agree or
disagree
2. I found this easy to do.
1
2
Any Other Comments
Part 2 of LIFE project technique - Listing and Prioritising My Core Skills from My Life
Achievement Stories
3. I found this helpful for planning my future.
1
2
3
4
Neither agree or
disagree
2
3
4
Neither agree or
disagree
4. I found this easy to do.
1
Any Other Comments
Part 3 of LIFE project technique - Creating My Flower Profile
5. I found this helpful for planning my future.
1
2
3
4
Neither agree or
disagree
2
3
4
Neither agree or
disagree
6. I found this easy to do.
1
Any Other Comments
7. What, if anything, do you think could be done to improve this process?
Many thanks for your feedback.
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9. Appendix 3: Summary of Likert-scale primary data from cycle 1
LIFE Project
Technique
Total 1
(Strongly
Agree)
Total 2
(Agree)
Total 3
(Disagree)
Total 4
(Strongly
Disagree)
Neither
Non
responses
Total
completed
Total (Likert
aggregate)
Average of
Likert
responses
Cycle 1
Listing and
Prioritising
Core Skills
Stage 3
component
Creating
Flower Profile
Q2. I found
this easy to
do
2
Stage 2
component
Q3. I found
it helpful
for
planning
my future
7
Q4. I found
this easy to
do
1
Q5. I found
it helpful for
planning
my future
5
Q6. I found
this easy to
do
2
6
5
4
6
4
6
2
4
1
4
0
0
0
0
0
1
2
0
0
0
1
0
0
0
1
0
0
1
3
1
12
12
12
12
11
11
22
24
18
29
21
22
1.8
2.0
1.5
2.6
1.9
2.0
Stage 1
component
Telling Story
Q1. I found it
helpful for
planning my
future
4
Qualitative Primary Data from Cycle 1
Stage 1
It was very helpful in discerning and building confidence about oneself and looking back at positive events.
Stage 2
It was quite a challenging idea and may have been easier if one was allowed to confer with friends and get
alternative opinions
Interesting to identify the words that I use often without realising and how those words represent significant part of
my personality.
Stage 3
It offered a visual representation to give one an idea of the possibilities that are available.
I knew that there are certain things or aspects that are important in my life, but those things were scattered around
in my head. This exercise helped me organise, clarify and prioritise those things.
The process made me aware of the direction that suits me the most and additionally that I would enjoy doing.
I find these techniques very useful as it makes me reflect and helps to realise what I want and need to improve in
my future career.
This is a great exercise to do but not something I could have done easily on my own. Also makes your brain ache
so helpful to be pushed through it vs doing it on your own.
What if anything, could be done to improve the process?
I think the whole class was really helpful. The only thing I think that should be changed is to not have the class as
an extra class but rather have it as part of the course. I also think it graduation for the students takin the class
should be at the same time as everyone else. I personally really liked the class and would recommend it to
everyone. If we had maybe a week of intense course for this class for the whole of the MA global management
class…it will benefit everyone. The only thing that put me off is the graduation date.
Maybe leave a list of occupations that people of the same attributes are involved in?
Examples for each section, so one can see that what they are writing is not degrading or being big headed but just
yourself. Reflection is very important for how someone views themselves and the their life path.
Some reflection done prior to the meeting via personal research. Identifying strengths and weaknesses,
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opportunities and threats, through feedback from other people and analytical tools. Updating a CV prior to the
session.
A greater emphasis on what jobs are out there, as I don't really know what I want to do, and maybe there are
options I have never thought of.
More lessons would be perfect. I enjoyed the course a lot.
If some of the time spent with individuals not with the group.
Printed pro formas to enable the interviewer to record information easier.
To early to say as I have not delved back into yet – an option would be suggestions to how to take it to the next
level i.e. so these are the kinds of things you could do.
10. Appendix 4: Summary of Likert-scale primary data from cycle 2
LIFE
Project
Techniqu
e
Total 1
(Strongly
Agree)
Total 2
(Agree)
Total 3
(Disagree
)
Total 4
(Strongly
disagree)
Neither
Non
response
s
Total
complete
d
Total
(Likert
aggregate
)
Average
of Likert
response
s
Stage 1
Q1. I
found it
helpful
for
planning
my future
6
Cycle 2
Telling
Story
Q2. I
found
this easy
to do
7
Stage 2
Q3. I
found it
helpful
for
planning
my future
6
12
7
4
Listing
and
Prioritisin
g Core
Skills
Q4. I
found
this easy
to do
5
Stage 3
Q5. I
found it
helpful
for
planning
my future
8
11
9
8
6
1
2
1
0
Creatin
g
Flower
Profile
Creatin
g
Person
al
Profile
stateme
nt
Q6. I
found
this
easy to
do
8
Stage 4
Q7. I
found it
helpful
for
planning
my future
8
11
7
8
9
7
4
7
6
7
0
3
1
2
1
3
1
0
1
0
0
0
0
0
0
0
1
0
0
0
24
24
24
24
24
24
24
24
46
53
46
56
46
51
46
56
2.0
2.2
2.0
2.3
1.9
2.1
2
2.3
Q8. I
found
this
easy to
do
5
Qualitative Primary Data from Cycle 2
Stage 1
The activity is very useful and helpful to think about the future.
Stage 2
No comments provided.
Stage 3
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No comments provided.
Stage 4
With the other parts this is much easier because now you know what you want.
What if anything, could be done to improve the process?
To improve this process I think it should be only in the mornings or afternoons so we will have more time to settle
things.
having more work in groups of 4-6 people
I guess it was really interesting and quite enjoyable
Provide more specific options
This process is very good. It will help me in doing business and when talking with people.
I believe this process is quite effective in making one think about their desires but I believe you can add more
questionnaire pattern e.g. belbin test.
Add other features difference and diversify the questions because most of the questionnaires are almost the same.
Thank you!
Other questions can be added to questions, because some questions are repetitive.
Very useful for putting thoughts into words.
Practicing.
11. Appendix 5: Summary of Likert-scale primary data from cycle 3
Total 1
Total 2
Total 3
Total 4
Neither
Non
responses
Total
completed
Total
(Likert
aggregate)
Average of
Likert
responses
LIFE
Project
Technique
Cycle 3
Part 1
component
Telling
Story
Part 2
Listing and
Part 3
Creating
Part 4
Creating
component Prioritising component Flower component Personal
Core Skills
Profile
Profile
statemen
t
Q1. I found Q2. I found Q3. I found Q4. I found Q5. I found
Q6. I
Q7. I found
Q8. I
it helpful this easy to it helpful this easy to it helpful
found
it helpful
found
for
do
for
do
for
this easy
for
this easy
planning
planning
planning
to do
planning
to do
my future
my future
my future
my future
7
8
7
7
14
13
8
11
21
21
17
21
15
18
19
21
4
4
5
5
3
3
5
2
0
0
0
1
0
0
0
0
2
1
5
0
1
1
2
0
0
0
0
0
0
0
0
0
34
34
34
34
34
34
34
34
61
62
56
68
56
61
61
59
1.8
1.8
1.7
2.0
1.7
1.8
1.8
1.7
Qualitative Primary Data from Cycle 3
Stage 1
I did not see the purpose of 'measures of success' as they were not used later on.
this is quite hard to think of because somehow, the things I have done do not come across as great achievements.
I found it a great ice breaker being a new student, however I already know what I want to do so I didn't necessarily
discover anything new. I do, however, feel more confident.
Stage 2
It was very illuminating as to what my life was about.
This exercise helped me put things in perspective for me.
Stage 3
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There are many possible permutations that happened when you drew the flower and they were not explored and
are possible avenues.
This reminded me of values I had forgotten. Things that used to be important to me but have been left behind after
my disenchanting experience in the workplace.
Again- helped put it all in to perspective and ignited my determination.
Stage 4
I needed to reinterpret the statement myself to turn it in to practical advice.
This personal exercise still comes across as a difficult one even if I have done this before.
It was nice to see it all plainly stated on paper.
What if anything, could be done to improve the process?
Don't Know Yet.
I maybe think we should have more time to think over the questions, so we could come up with more helpful
information. But I think the activities in themselves are really good.
Yes?
I think this process is efficient.
Looking more at careers people want to do and looking at how the results of this exercise compare to that.
Give the students more time to think about what they write down. Maybe send the forms home with the students and
collect them the next day?!
I don't have anything on mind that could improve this process. It is well organised. It helped planning my future step
by step. Before this process I had no idea what to do, but now, I am getting new ideas. I am getting to know what to
do.
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The Changing Role of Knowledge in Companies: How to
Improve Business Performance Through Knowledge
Gaby Neumann1 and Eduardo Tomé2
1
Technical University of Applied Sciences Wildau, Germany
2
Universidade Lusíada de Famalicão, Portugal
[email protected]
[email protected]
Abstract: Knowledge is widely accepted as strategic resource in companies, but its developmental potential is often
not well exploited. Amongst others this is caused by the wide variety of knowledge management concepts, methods
and tools challenging company management in selecting the appropriate measure for the specific company situation
and developmental goal. Furthermore, knowledge is directly linked to people and knowledge-based interventions
therefore cannot be successful without reaching the company’s employees and getting them involved in any change
processes. Against this background the paper discusses the changing role of knowledge in companies and
investigates how knowledge-based change processes in companies need to be launched and run. Based upon this a
methodological framework is proposed in order to help companies in identifying their needs for change and
purposefully intervening in their processes and eventually to lend them a hand in managing their human resources,
selecting technology or changing the organisation. Conclusions open up the view towards future research still
required for achieving the goal of methodologically grounded managerial support and guidelines on how to best
intervene in company knowledge.
Keywords: change processes, knowledge-based development, knowledge management maturity, sensitivity
modelling
1. Introduction
Nowadays economic survival is vital. For that companies or organizations need to have one of three
assets: knowledge, cheap labour, natural resources. Out of these three, knowledge is with no doubt the
only one that can be maintained in the long run. Therefore knowledge is the source for competitive
advantage in the long run. It is a key resource and crucial field of investment in today’s business
organisations. However, companies and organizations have a massive difficulty to account and evaluate
their investment in knowledge (Meritum, 2002; Bornemann and Alwert, 2007). In particular, problems in
strategically and effectively using this resource consist in: (i) how to specify, summarize, visualize the
current state of knowledge; (ii) how to comfortably provide access to scattered and ill-structured
information on the current state of knowledge; (iii) how to define, understand, visualize the impact of
knowledge on organizational performance; (iv) how to assess and evaluate strategies and activities for
purposefully intervening in organizations by means of knowledge.
Furthermore knowledge is not a static resource, but knowledge dynamics is the more important side of
the analysis (Kianto, 2008). This happens because not only the economic environment is changing very
fast nowadays due to globalisation, but also because investment is by itself linked to change and to
dynamics. Especially, the question of how to best make use of knowledge as a resource still remains
insufficiently answered. To overcome this, knowledge management (KM) needs to be seen as a
supporting service addressing a company’s personnel, organisation and IT basis at the same time. Any
knowledge management activity and investment into knowledge must aim to purposefully intervene in a
company’s business processes. For this, companies require comprehensive knowledge and in-depth
understanding on how to implement KM methods in a customized way. In order to provide companies
with respective information and eventually lend them a hand in managing their human resources,
selecting technology or changing the organisational structure, the role of knowledge in business
organisations needs to be investigated and assessed further.
Against this background the paper discusses requirements for and structure of knowledge-based change
processes in general (Section 2), reviews related works with regard to concepts and theories (Section 3),
defines the background of knowledge-based change processes and companies (Section 4) and presents
the methodological framework for unlocking developmental potential of knowledge (Section 5).
Conceptual discussions are completed by a summary and concluding remarks in Section 6 which also
open up the view towards future research still required for achieving the goal of methodologically
grounded managerial support and guidelines on how to best intervene in company knowledge.
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Reference this paper as: Neumann, G and Tomé, E. “The Changing Role of Knowledge in Companies:
How to Improve Business Performance Through Knowledge” The Electronic Journal of Knowledge
Management Volume 9 Issue 1 (pp57-72), available online at www.ejkm.com
Electronic Journal of Knowledge Management Volume 9 Issue 1 2011
2. Knowledge-based change processes
We base our research on the general assumption that there are direct and indirect interactions between
knowledge, economic growth and social well-being which can be investigated at two different levels (see
Figure 1).
Figure 1: Knowledge as enablers in change processes
Concerning the levels of economy or social well-being any development comes from change processes
the drivers of which can be knowledge, but also other societal influences like environment protection or
certain technological advancements. Although those change processes are of complex nature with
several drivers being active at the same time we focus on identifying, describing and investigating those
change process that are initiated and driven by knowledge. Consequently, the specification on how to
achieve a certain development from a current level of economy or social well-being to a particular target
level of economy and social well-being through a knowledge-related change process forms the target
function. For solving this target function and purposefully interacting through knowledge, it is necessary to
understand how those knowledge-related change processes have to be designed.
In general, knowledge-related change processes consist of a series of knowledge-related activities that
contribute to transferring a current knowledge maturity to a target one. Those activities directly depend on
a set of knowledge-related enablers covering the three dimensions of knowledge management, i.e.
individual, technological and organisational aspects. Those enablers again are influenced by a number of
political enablers which form the general framework for a successful intervention through knowledge.
Therefore, the methodological approach of the research foresees the specification of suitable sets of
knowledge-maturity indicators. Furthermore, valid impact models are needed to run systematic
simulations for understanding the impact of knowledge on company performance on one hand and for
deriving guidelines on what kind of action should be made in order to support further development of the
knowledge maturity of a company.
With this, understanding of the changing role of knowledge in relation to growth, employment and
competitiveness as well as the implications of different types of knowledge for the economy should
significantly be improved. Based upon this, case-based and company-specific assessment of the
potential value of a certain investment into knowledge and for deriving specific suggestions and
recommendations for increasing the company’s level of knowledge management maturity should become
possible. Furthermore, the development of quantitative and qualitative methodological approaches is
promoted and the formulation and implementation of relevant policies for the knowledge market are
supported.
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3. Related works
3.1 Concepts
Knowledge is not an easy scientific concept even if science revolves around it. In our opinion it is
important to distinguish between data, information and knowledge, meaning that information is organized
data and knowledge is understood information (Maurer 1998). As a consequence, both information and
knowledge require the intervention of economic agents, and are valuable economically. Also as a
consequence information and knowledge should be evaluated and accounted for because they have an
immense potential impact in the companies’ value (Edvinson and Malone 1997). In this context it was
well understood that the cycle of knowledge should be studied (Nonaka and Takeuchi 1995). However,
all the previous analysis is very much linked to management, or even accountancy. And, when we
analyse knowledge we have to confront and solve economic problems. Knowledge has to be seen as a
resource; it has to be seen as a stock for which there is investment, from which results derive and about
which there is a market.
A market is a place, virtual or local in which transactions take place. Goods and services have markets;
sob knowledge must have a market also. In our opinion if we want to analyse the situation about
knowledge correctly, it is not only necessary to define the level of the asset, but also to scrutinize the
elements of its market namely supply, demand, equilibrium, price, quantity, need, main agents, role of the
State, investment, stock, flow and returns. On what concerns the returns basic economic theory would
say that the most important outcomes are wages and employment for workers, profits, productivity for
companies, exports and income for countries and regions (Becker 1993, Ashton and Green 1996). We
may admit that the augmentation of knowledge is itself a return of the investment in knowledge. However,
recent studies assume that it is impossible to define the effect precise knowledge has in organizations,
and therefore “knowledge productivity” has to be defined as the volume of innovation that is derived from
the investment in knowledge, that innovation being divided in incremental innovation or radical innovation
(Stam 2007): It is in this context that change may be addressed, because change may result from
innovation and therefore may be considered as a return from the investment in knowledge.
3.2 Theories
The Economic theories on knowledge state some very basic ideas about the knowledge market, namely
the following:

A market on knowledge exists in which individuals and organizations sell and buy knowledge.

Individuals and private entities should invest if they derive a positive outcome from that investment
(Becker 1993).

However, the public intervention in the market is also defendable because of market imperfections
and equity reasons (Tomé 2004).

Most of the analysis is made for companies but in a regional or macroeconomic scope knowledge is
assumed to have positive influences that should imply public policies (Bonfour and Edvinson 2005).

The market of knowledge may be competitive, but some authors have recently suggested that
imperfect competition and oligopoly exist. This lack of competitiveness would be a consequence of
increasing returns to scale in the knowledge investment (Stam 2010).

The analysis of the economic effects of knowledge is usually perceived in a static way but
“comparative static”.

However it is also important to put the theories in a dynamic perspective trying to come to terms with
the consequences that the evolution in the knowledge base have in the evolution of organizations or
regions.
It is the dynamic aspect we will develop in this paper.
Companies may be characterized by the way they manage knowledge in different levels of maturity
(Khatiban et al. 2010). In initial stages, knowledge is barely managed, and is not seen as an important
factor in the company; investment in knowledge is rather weak. In the second stage, knowledge is
already recognized as an important asset, but actions in relation to it are still incipient. In a third stage,
knowledge becomes the most important organizational assets and the organizational policies effectively
are made around knowledge; in this stage investments in knowledge are big and the rewards for those
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investments are also big. Quite interestingly, for regions and countries the same levels of maturity
regarding knowledge also may be observed (Aubert 2005). In this case first we have low equilibriums
regarding knowledge, when the country is poor and not developed, investments in knowledge are weak
and knowledge is not a priority. Secondly we have middle equilibriums, when countries begin to emerge,
investments became very important, policies are defined and the knowledge levels increase and so do
the returns. Finally we reach the maturity stage, which exists in developed countries, in which
investments are high, knowledge is the object of important public policies and the rewards from the
investment are considerable. In that context, innovation should be the way of changing from a low level of
maturity to a high level of maturity, for organizations or regions. Innovation may be social, or technical,
and may be radical or incremental (Stam 2007).
Knowledge investments are a part of human and intangible investments. In the last decades those
investments have been evaluated by a number of perspectives, namely social policy, Human resource
economics, management / accountability, and human resource development experts. It is in this arena
that both KM experts and Intellectual Capital studies make their analysis. Table 1 summarizes those six
perspectives. It is very important to notice that they are complementary and that we consider that KM
analysers must be aware of all the different perspectives when studying knowledge.
Table 1: Knowledge studies put in societal perspective
Perspective
User
Problem
Variables
Assessment Methods
Social Policy
Public good
Expenses, number of
supported persons
Wages, employment,
productivity, exports
Progress reports
HRD science
Public
administrator
Human
Resource
Economist
Private
Manager
Traditional
Accountant
HRD expert
Intellectual
Capital
New
Accountants
Impacts on the
organization
Knowledge
Management
Knowledge
Manager
Impacts on the
organization
HR Economics
Management /
Accountability
Impacts on
society or
organizations.
Impact on the
organization
Impact for the
agents involved
Profits
Control Group
Input Output Methods
Supply and demand methods
Return for investment
Competences,
Interviews,
learning, behaviour,
Questionnaire,
company outcomes.
Participant – Observer
Market value minus
Balanced Scorecard:
book value
Finances, Structural Capital,
Social Capital, Human
Capital. Market value versus
Book value.
Knowledge
Knowledge sharing, transfer,
creation, dynamics, learning
and unlearning
3.3 Approaches
Specification of a company’s knowledge management maturity helps in determining both the current
attitude towards knowledge and state-of-knowledge in the company and a company-specific strategy for
implementing knowledge-related activities in order to improve company performance. Knowledge
management maturity models provide a staged framework to initiate a step-by-step change within an
organization based upon its current level of knowledge management maturity. In literature a number of
knowledge management maturity models can be found (see Kochikar 2000, Langen and Ehms 2002,
Joslin 2005). They usually originate from maturity models in software engineering and support companies
in self-assessing their knowledge management maturity by answering questionnaires. Answers specify
certain observable capabilities with regard to people, process and technology from which the current
maturity level is derived. Kochikar (2000), for example, elaborates the following five levels of knowledge
management maturity:

Level 1 – Default. “Knowledge, we’ve got plenty of – what we need is to work hard.”

Level 2 – Reactive. “We need to leverage all our knowledge, but we’re too busy to do that.”

Level 3 – Aware. “At least we’ve made a beginning in managing our knowledge.”
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
Level 4 – Convinced. “We’ve reached where we are by managing our knowledge well, and we intend
to keep it that way.”

Level 5 – Sharing. “We’re sharing knowledge across the organization, and are proud of it.”
Minonne and Turner (2009) propose a two-dimensional model for explaining the degree of progression in
the development and implementation of a KM strategy. Here, one axis is used to ascertain the level of
implementation and the other to pinpoint the degree to which implementation is managed, in other words
the level of control. This way, again five stages of implementation and control maturity are defined.
Problems in applying those models result from the pure qualitative design of the questionnaires and
characteristics of maturity levels or stages which gives a lot of room for individual (mis-)interpretation and
sometimes makes it difficult to the companies to identify the correct maturity level. Here, quantitative
measures, e.g. key performance indicators, and a comparative approach might be of help both of which
can be achieved from applying benchmarking methodology.
4. The background of knowledge-based change processes in companies
Any KM activity needs to influence company processes in a targeted and positive way with regard to
economic efficiency and sustainability. Whereas the first focuses on using the organisational knowledge
base for creating and maintaining highly-productive company processes and structures, the latter is
oriented towards ensuring efficient and effective production and service provision and capacity for
innovation. With this the company is able to offer new products or services and safeguard or even
improve its position at the market. Therefore any knowledge-based company development forms a
comprehensive change process that needs to be lead by the company’s management and where it is
essential to take along the company’s employees. Exactly this kind of a challenge is in focus of change
management. Change management is a structured approach to shifting/transitioning individuals, teams,
and organizations from a current state to a desired future state. It is an organizational process aimed at
empowering employees to accept and embrace changes in their current business environment (Hiatt and
Creasey 2010). In general those changes might include anything from strategic company development to
personal development of employees, but – as explained above - in this paper we focus on changes only
which result from unlocking, gaining, developing and using knowledge as strategic resource.
Change management processes consist of four phases: preparation, diagnosis, intervention and post
processing. The preparation phase aims to define the framework of change, to draft the process of
change and to setup the structure of the change project. Diagnosis focuses on the definition of current
and target situations and with this on the identification and specification of all problems to be solved.
From this, needs for intervention and intended changes are derived. The phase of intervention wants to
achieve changes by planning suitable measures and procedures, evaluating their potential impacts and
finally launching them in the company. Their success is evaluated in the phase of post processing in
order to identify the degree of target achievement and eventually still existing needs for further actions.
Furthermore, findings and experiences (e.g. in the form of lessons learned) are to be derived from critical
reflection and structured documentation of the change process. Here, knowledge management plays a
major role as controlling and monitoring method for directing the change process. On the other hand
knowledge management – or more concrete the intervention into company processes and structures by
use of the knowledge resource – itself might become an activity in the change process. Those
knowledge-based change processes can be seen as a specific version of the general problem solving
process.
Any problem solving process is usually initiated by recognising a certain situation or behaviour as not
satisfying (anymore) and eventually having a clear vision of how it should be ideally or even knowing
what needs to be done to improve situation or change behaviour. In companies those processes typically
aim at improving certain performance parameters like throughput, service level, time of delivery etc.,
improving the cost-benefit ratio of the company as a whole or of a particular product, service, process, or
department, and maintaining or extending the company’s position at the market. The success,
effectiveness and efficiency of any company development depends on how well the company knows its
situation, how clearly and correctly it specifies problems and potential for improvements including their
sources and drivers, and how purposefully and efficiently it selects and applies methods for solving
problems and changing situation or behaviour. Here, knowledge and experience play a major role as
problem-solving in a company context needs to be always knowledge-based and nowadays even more
and more knowledge-focussed. Due to the complexity of today’s problems and processes in a company
and because of the multi-facet appearance of, view on and benefit from applying the concept of
knowledge, companies face the challenge to really manage, operate and understand knowledge as a
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strategic resource. Therefore a methodological framework is proposed in order to help companies in
identifying their needs for change and purposefully intervening in their processes and eventually to lend
them a hand in managing their human resources, selecting technology or changing the organisation.
5. Methodological framework for unlocking the developmental potential of
knowledge
5.1 How to help companies in identifying their needs for change
Pre-condition for any purposeful intervention in a company is a comprehensive understanding of
company processes, its position at the market and its role within a network (or chain) of companies.
Whereas this is usually given, companies quite often lack the ability to really see behind symptoms (in
terms of observations or measures) and identify problems causing those symptoms and drivers enabling
or hindering further development into the target direction. With this the true reason for a certain process
result or company behaviour remains hidden or is found accidentally only. On this basis it is difficult or
even impossible to correctly identify the needs for any change in the company in terms of both deficits
and options.
Consequently, the process of knowledge-based and knowledge-focused intervention in a company needs
to begin with specifying the company (the organization), i.e. the problem(s) to be solved and the context
as well as environment it is (they are) located in. This includes information about the company
environment, IT systems already used for any kind of knowledge management, the current state-ofimplementation of knowledge management, the eventually planned or available investment volume,
preferences with regard to KM activities or tools and the problem to be solved:

The environment refers to the focus (single company or entire supply chain), company size,
educational level of employees, company function, industrial sector, country or region etc. This is of
relevance to the selection process, because KM activities, methods and tools appropriate for a small
company may differ from those recommended for larger companies. For example, tools such as
social software or internal networking opportunities are less important in small companies, since the
employees easily have direct contact to each other.

Existing IT systems can be used for or adjusted to KM needs. This eventually makes it easier and
faster to implement further tools or launch new activities.

The current state-of-implementation of KM gives information on the methods already implemented,
activities and procedures already integrated into company life, tools already used. Further
knowledge-based or knowledge-focused company development should directly build upon those
existent, established and accepted activities, methods and tools, i.e. it is based on the company’s
current attitude towards knowledge and the knowledge culture already alive in the organisation.
Possible interventions then could, for example, extend (upgrade) tools or take into consideration
coherences between certain tools, methods and activities.

The planned investment volume and the user preferences narrow down the range of KM activities,
methods and tools to choose from in order to achieve highest possible acceptance of any changes to
be implemented with both company management and company employees.

The problem to be solved is one of the most important factors in recommending developmental steps
as any intervention in the company must contribute to overcome the problem. This is the critical
success factor; its evaluation requires a sound basis in terms of measures or processes.
For providing that information and in order to ensure their completeness and comparability the company
manager (or user) should be supported by a self-reporting template, a structured questionnaire or even
an easy-handling software tool based on selection dialogues or decision trees. In contrast to any paperbased tool an IT solution here might even get the user involved in an interactive mode (similar to an
interview-based information retrieval) when it provides supporting functionality enabling the user either to
directly enter requested data (if known and specified already) or to elaborate them step-by-step (if the
user is inexperienced or available information are still ill-structured).
KM (software) tools, for example, which are already implemented (used) could be identified via a set of
questions asking for knowledge-related activities and methods instead of tools. Those questions could
focus on training activities, research and development, networking opportunities or the like which are not
solely used for the purpose (or in the name) of KM and therefore may not be associated with it in
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common terms. In combination with information on already existent IT systems this should allow in
concluding on KM tools already in place.
This approach of indirect questions has already been applied in a questionnaire-based KM impact study
(Neumann and Tomé 2005). Here, the questionnaire comprised five groups of questions addressed to
different responsible managers in a company:

The first group aimed at specifying the main company characteristics. Furthermore, in order to
account for the dynamic of the firm, we asked if the company had recently incurred in some
substantial change. These questions were to be answered by the top manager of the unit to which
the data were related to.

The second group should give a clue on the logistics manager’s opinion about the role of knowledge
in the company. Questions specifically dealt with the importance and dynamics of knowledge, the role
of knowledge management with regard to the logistics processes or services, and whether or not
Intellectual Capital (IC) Reports are produced.

The third group asked the human resources (HR) manager to qualitatively assess specific
investments into knowledge made in certain year fully relying on the good faith of the respondents.
For this a detailed grid of 16 items was used that describe different ways of investing into knowledge
(without investments into KM systems and IT infrastructure).

The fourth group used the same grid and scaling as before to ask for the HR manager’s opinion
about the importance of providing employees with access to the 16 types of investments into
knowledge.

The fifth group was based on a grid of 32 company performance indicators related to economic
factors, human relations within the company, customer relationship, operations within the company,
personnel, production process, and strategy. To define the evolution of the company from before the
investment into knowledge to after the investment, the unit’s (company’s) top manager was asked for
classifying the respective company situations.
Whereas responses to the first four groups of questions give a clue on the company’s current attitude
towards knowledge (in correspondence with the KM maturity levels as mentioned in the Section 3.3),
(qualitative) specification of performance indicators in relation to KM interventions should allow
concluding on the impact certain KM activities had/have on company processes. With this the latter
already lays the basis for purposefully intervening in company processes and recommending most
suitable (or effective) KM methods or tools to be applied.
The weak point of the questionnaire is the missing link to problem identification, i.e. to WHY the company
should change and into what direction. Here, questions and responses only allow a first rough insight
from analysing input data by use of benchmarking and clustering methodologies (Neumann and Tomé
2010). On one hand, relating investments into knowledge to priorities of those knowledge-related
activities leads to conclusions on the need for further investments into KM or for reducing or refocusing
respective activities. On the other hand, results compare the company’s attitude towards knowledge with
that one companies of the same type show, e.g. by (anonymously) presenting investments into and
priorities of the individual knowledge-related activities of those similar companies in a diagram. If
company results significantly differ from those of similar companies then company attitude towards
knowledge, its investments and priorities should be subject to further (and much more detailed)
investigation as this eventually might indicate problems in KM.
To further specify those problems or help companies in identifying their problems (instead of repairing
symptoms only), functionality for seeing the problems behind the symptoms could be of help.
Methodically this functionality might work in the same way as an e-coach does (Neumann and Krzyzaniak
2006): the user goes through a list of symptoms or works with a decision tree to self-directed learn about
the problem. Then, the support function matches the input against a problem-symptom matrix and
suggests possible problems causing symptoms as described. Precondition for this is a detailed
representation of relevant symptoms and underlying problems (corresponding to the type or business
sector of the company). This is to be achieved through an ongoing learning process for improving
matching functionality.
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5.2 How to help companies in purposefully intervening in their processes
Once actual problems in company processes and/or performance have been identified, strategies for
solving them through purposeful (knowledge-related or knowledge-focused) interventions can be found.
For this, a clear target function in terms of a certain KM maturity level or a performance situation to be
achieved is required. Amongst others it can be derived from SWOT indicators as defined from
intercompany/interarea KM maturity benchmarking. Based upon this the overall change process can be
designed, but also options for how to purposefully intervene through knowledge can be specified.
Questions to be answered in this context are:

Which of the necessary changes can be achieved through knowledge?

How the company knowledge base has to be developed?

How to best make use of a company’s “soft skills” (i.e. knowledge and competence)?
Based upon this, KM methods and tools fitting to the specific situation and required change can be
recommended. These recommendations should be accompanied by a detailed description and an
implementation checklist. In case a variety of interventions seem to be appropriate a kind of filter can be
used to narrow down the options. Possible characteristics to sort and filter results of this specification
step can be, for example, preferences with regard to the KM aspect to be influenced, i.e. technology,
human resources or organization, or limitations of the change process such as level of investment
available.
Additionally, coherences between particular methods, activities or tools might be pointed out and
discussed if this is important for them to work effectively. This even might lead to the proposal of a
development pathway composed from different methods and activities to be applied or implemented one
after the other. Here, KM maturity levels form a pattern of developmental steps with a specification of
what needs to be done to move from one level to the next one. This KM maturity development pathway is
not a straight line nor is it the same for all situations and companies. Instead, there are milestones along
the way which can be reached through a particular sequence of KM interventions applied in a certain
context and therefore give company managers orientation in developing an appropriate strategy for
knowledge-based and/or knowledge-focused development.
As there is usually not just one potential option to intervene in company processes another challenge
consists in deciding about which of these options might be the best one in terms of success,
effectiveness and efficiency. Here, a test-bed for scenario-based evaluation of possible intervention
strategies is of great help requiring a sensitivity model that explicitly shows the interactions between KM
activities and a set of measures for evaluating their effectiveness (i.e. impact) and efficiency (i.e. costs).
Carrillo et al. (2003) investigated the relationship between KM and business performance in order to
develop a three-stage framework for Improving Management Performance through Knowledge
Transformation (IMPaKT). It comprises activities for developing (i) a business improvement strategy, (ii) a
KM strategy, (iii) a KM evaluation strategy and an implementation plan. Here, effectiveness of KM is
assessed in terms of the degree to which strategic objectives of the business organization are realized.
For this a cause-effect-map is proposed that relates KM initiatives to performance measures and
strategic objectives. The challenge in applying this rather general map to a certain company setting
mainly consists in defining cause-effect relationships in detail and clearly specifying the quantitative or
qualitative impact of a certain KM initiative on appropriate performance measures. For this, a company
performance model is required that can be tailored to the business sector and particular company setting.
Therefore, a cause-effect model has been developed by applying Vester’s sensitivity analysis method of
networked thinking (Vester 2000) that represents interactions between a company’s key performance
indicators in both ways qualitatively and quantitatively (see Figure 2). As it hypothetically can be seen as
mode of operation of a profit-making company it might form a generic model of business management
enabling to investigate the role of different business aspects in the complex system of business
performance.
A second sensitivity model, the knowledge-activity model, is based upon a similar approach as the
business management model. The underlying assumption is that all KM initiatives, activities, methods,
strategies, tools do not only influence the system they are applied to or set up in, but even further that
they also influence each other when coming in place at the same time. As any KM initiative quite often
does not consist of just one specific activity, like e.g. implementing a KM IT system, but contains a bunch
of activities addressing technological, organisational and human factors at the same time, the impact of
the initiative on the company performance cannot be evaluated without taking interferences between
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newly launched and already running KM activities into account. Due to the many and diverse KM tools (in
the widest sense) it does not seem to be possible nor useful to try to create the ultimate knowledgeactivity model covering all of those tools. Instead it is necessary, either to focus on those tools already in
place in a certain company setting in order to analyse which are effective and efficient ones and which
are not, or to build the model based upon a pre-selection of suitable tools in order to evaluate and
compare them according to their effectiveness and efficiency. The latter allows selecting the most
appropriate tools and also checking in advance if the intended effects might be achievable at all.
Figure 2: Cause-effect map of aggregated variables
Figure 3: Cause-effect sub-model: impact from networking activities
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For purposefully interlinking both models relevant links between them are to be specified, i.e. the control
levers in the company system operated by the output variables of knowledge-activity have to be identified
and effectiveness as well as efficiency of their intervention must be defined. To be able to more clearly
describe each of these effects in terms of both the time until they start impacting and the strength they
achieve, the individual options for intervening and their respective effects are represented in separate
sub-models (see Figure 3). These sub-models contain influences by a single effective control lever only,
but show all effects directly or indirectly resulting from its intervention. To identify the most promising
activities for achieving a particular change of the system all options to influence the system (control
levers) would have to be investigated via a before and after comparison. On the other hand, the strength
of the effects and the time until they appear could be derived by use of simulation. In the end, possible
options of investments in knowledge or KM can comparatively be analysed in terms of their companyspecific impacts and with respect to their contribution to achieving a defined level of improvement in
relation to the respective need for investments. However, a serious prerequisite for such findings is in any
case a valid cause-effect model of both the business management and the knowledge-related activities
as external control levers.
6. Conclusions and further research
In order to better manage knowledge for unlocking its developmental potential a comprehensive set of
methods is required that helps companies in purposefully intervening in their core processes. As those
interventions can either be caused by a certain problem or unsatisfying situation or initiated from a kind of
regular routine check-up, this methodological framework also describes the fundamental concept of a
“knowledge clinic”. That “knowledge clinic” would enable companies to adjust from their actual maturity
level to the desired maturity level and also to run sensitivity analysis on their knowledge investments in
the same way as any process of medical treatment with the human body is (or at least should be)
organised: diagnosis – healing – evaluating/cross-checking.
To identify options for knowledge-based and knowledge-focused company development it is necessary to
know about knowledge resources, methods and tools already available in a company setting as well as
their current level of implementation and application. Furthermore, an in-depth understanding of the
problems to be solved (rather than just the symptoms to be seen or measured) or the objectives to be
achieved through knowledge-related interventions is required. These investigations form the diagnosis
phase of knowledge-based development in a four step procedure:

1. Define the constituents of the market for regions or the situation regarding those constituents for
organizations;

2. Define benchmarks for companies and for countries;

3. Compare countries and organizations with those benchmarks.

4. Diagnose problems using the mentioned benchmarks.
The healing phase of knowledge-based development uses KM maturity pathways and scenario-based
impact models to identify the most appropriate means and strategies to intervene in company processes
for solving the problems as specified before and achieving the target development as intended.
Evaluation or cross-checking uses simulation methodology with sensitivity models in order to determine
the impact a certain intervention might have on the company and to compare this impact with intentions.
This last phase of knowledge-based development ensures the success of any intervention and supports
critical reflection on what could be achieved in which way in order to find the most effective way of
intervention. With this, it also contributes to a learning process for ongoing improvement of both the
intervention strategy for knowledge-based company development and the procedure for deriving and
implementing it.
At the present stage, the research findings are essentially questions and not answers. In order to proceed
by implementing the “knowledge clinic” the following steps have to be done:

1. Integration of existing KM methods, tools and benchmarks into the framework (including
specification of their applicability or limitations)

2. Creation of a web portal;

3. Collection of data on companies;

4. Definition of benchmarks and quantitative characteristics of KM maturity levels;
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
5. Implementation of a self-learning algorithm for developing company-specific intervention
strategies;

6. Operationalization and dissemination of results.
We would like our portal to be something like a KM hospital for organizations and companies, i.e. we
create an Internet facility in which each company would serve itself in KM terms. This means each
company would have to find some data about itself and provide them via the website to be able to make
a diagnosis of its own situation and to trace a road map about the ways it would need to improve its
business performance and KM maturity. The website would therefore be an interactive instrument for
companies on one hand contributing to permanent improvement of the portal’s rule base but also
obtaining some very important information about themselves on the other. We would therefore obtain a
win-win situation through a collaborative game. Of course, companies might profit from the situation
entering false data, but this is a circumstance that quite unfortunately may happen in every survey and
we expect that situation not happening frequently enough to destroy the validity of the conclusions
derived.
Few would argue about the importance of knowledge in a long run sustainable economy. However, we
absolutely lack the instruments at organizational and at national level to successfully guide those
investments. Accordingly this paper proposes a model which tries to understand knowledge as a dynamic
force of change in an economic environment and setting. We therefore believe the creation of a
“knowledge clinic” will be necessary to improve the management of knowledge at the levels of society
and economy, too.
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