Journal of Management Policy and Practice

Transcription

Journal of
Management Policy and Practice
North American Business Press
Atlanta – Seattle – South Florida - Toronto
Editor
Dr. Daniel Goldsmith
Founding Editor
Dr. William Johnson
Editor-In-Chief
Dr. David Smith
NABP EDITORIAL ADVISORY BOARD
Dr. Nusrate Aziz - MULTIMEDIA UNIVERSITY, MALAYSIA
Dr. Andy Bertsch - MINOT STATE UNIVERSITY
Dr. Jacob Bikker - UTRECHT UNIVERSITY, NETHERLANDS
Dr. Bill Bommer - CALIFORNIA STATE UNIVERSITY, FRESNO
Dr. Michael Bond - UNIVERSITY OF ARIZONA
Dr. Charles Butler - COLORADO STATE UNIVERSITY
Dr. Jon Carrick - STETSON UNIVERSITY
Dr. Min Carter – TROY UNIVERSITY
Dr. Mondher Cherif - REIMS, FRANCE
Dr. Daniel Condon - DOMINICAN UNIVERSITY, CHICAGO
Dr. Bahram Dadgostar - LAKEHEAD UNIVERSITY, CANADA
Dr. Deborah Erdos-Knapp - KENT STATE UNIVERSITY
Dr. Bruce Forster - UNIVERSITY OF NEBRASKA, KEARNEY
Dr. Nancy Furlow - MARYMOUNT UNIVERSITY
Dr. Mark Gershon - TEMPLE UNIVERSITY
Dr. Philippe Gregoire - UNIVERSITY OF LAVAL, CANADA
Dr. Donald Grunewald - IONA COLLEGE
Dr. Samanthala Hettihewa - UNIVERSITY OF BALLARAT, AUSTRALIA
Dr. Russell Kashian - UNIVERSITY OF WISCONSIN, WHITEWATER
Dr. Jeffrey Kennedy - PALM BEACH ATLANTIC UNIVERSITY
Dr. Dean Koutramanis - UNIVERSITY OF TAMPA
Dr. Malek Lashgari - UNIVERSITY OF HARTFORD
Dr. Priscilla Liang - CALIFORNIA STATE UNIVERSITY, CHANNEL ISLANDS
Dr. Tony Matias - MATIAS AND ASSOCIATES
Dr. Patti Meglich - UNIVERSITY OF NEBRASKA, OMAHA
Dr. Robert Metts - UNIVERSITY OF NEVADA, RENO
Dr. Adil Mouhammed - UNIVERSITY OF ILLINOIS, SPRINGFIELD
Dr. Shiva Nadavulakere – SAGINAW VALLEY STATE UNIVERSITY
Dr. Roy Pearson - COLLEGE OF WILLIAM AND MARY
Dr. Veena Prabhu - CALIFORNIA STATE UNIVERSITY, LOS ANGELES
Dr. Sergiy Rakhmayil - RYERSON UNIVERSITY, CANADA
Dr. Fabrizio Rossi - UNIVERSITY OF CASSINO, ITALY
Dr. Robert Scherer – UNIVERSITY OF DALLAS
Dr. Ira Sohn - MONTCLAIR STATE UNIVERSITY
Dr. Reginal Sheppard - UNIVERSITY OF NEW BRUNSWICK, CANADA
Dr. Carlos Spaht - LOUISIANA STATE UNIVERSITY, SHREVEPORT
Dr. Ken Thorpe - EMORY UNIVERSITY
Dr. Robert Tian – SHANTOU UNIVERSITY, CHINA
Dr. Calin Valsan - BISHOP'S UNIVERSITY, CANADA
Dr. Anne Walsh - LA SALLE UNIVERSITY
Dr. Thomas Verney - SHIPPENSBURG STATE UNIVERSITY
Dr. Christopher Wright - UNIVERSITY OF ADELAIDE, AUSTRALIA
Volume 15(3)
ISSN 1913-8067
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©Journal of Management Policy and Practice 2014
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This Issue
Twelve Best Practices to Mitigate Risk Through Continuity
Planning and a Scorecard to Track Success ........................................................................................... 11
Elizabeth McGrady, Sandra J. Blanke
This prescriptive research describes a continuity planning readiness scorecard based on twelve best
practices that can be used by organizations to focus planning, compare readiness with peers and track
internal progress. The study of a sample of community organizations revealed that 58% of respondents
had a continuity plan but most did not comply with all of the best practices. These findings assist in
defining continuity readiness and suggest additional guidance to strengthen the readiness of
organizations and communities in response to incidents, hazards and disasters. Training needs are also
identified.
Issues Surrounding Internationalization of China’s Currency ............................................................ 20
Xiaohong He
Recent global financial crisis has aggravated problems in the current world monetary system and has
called US dollar’s exorbitant privilege into serious question. There is a growing demand for a
multicurrency world monetary system based on an increasingly multipolar world economy. In this
context, the paper focuses on the issues of China’s currency internationalization and analyzes it impacts,
pros and cons, in the world monetary system in general and China in specific.
The Engine of Health Information Exchange......................................................................................... 30
Neera Bhansali, Sushil Gupta
We discuss barriers to implementation of Health Information Exchange (HIE). The focus is on
operational aspects of HIE to improve the process of sharing electronic health-related information
among various organizations. Various topics include: strategy development, project management,
architecture and infrastructure management.
University/Community Partnerships: Engaging Business
Students in Leadership and Solution-Based Approaches...................................................................... 36
Susan Kinsella, Nancy Wood
This paper will address the importance of engaging business students in new approaches to problem
solving that will enhance their ability to create vibrant economies and collaborate with other professionals in an effort to sustain development in a global economy. These approaches include servicelearning opportunities, teaching about micro-enterprises, and applying business principles to social
entrepreneurship. A review of the literature regarding how service learning can benefit business students
is included.
Bayesian Design of Inventory Systems to Minimize Expected Operating Costs ................................. 42
Tapan P. Bagchi
Inventory management requires optimal determination of (a) “when to order”, and (b) “how much to
order”. One also needs here two answers—what should be stocked initially, and should one adjust (a)
and (b) as time progresses? This paper uses the Bayesian approach to answer these. It uses the classical
(s, Q) model and a heuristic search in the unstructured decision space. It finds that one can make a
decent start by this approach—and stay the course nearly optimally—while upholding a target service
level and minimizing cost/unit time. Study finds high value in continually updating (a) and (b).
An American Expatriate in China: Evidence of Organizational Culture Crossvergence .................. 58
Eric Sanders
This article presents a detailed interview with an American expatriate in China, and shows evidence of
cultural crossvergence: a blending of both economic ideology and national culture in a new
organizational mindset. It explores each of Hofstede’s five dimensions of national culture as displayed by
employees. Through the expatriate’s perspective, we see how the firm has built a global culture and is
working to develop global leaders who share this new mindset.
The Impact of the Millennium Development Goals in Argentina, Brazil, and Chile.......................... 67
Michael Christian, Jose D. Alicea, Daniel J. West, Jr.
The Millennium Development Goals have been a great initiative throughout many countries around the
world since its creation in 2000. Among the countries of Argentina, Brazil, and Chile, this initiative has
been one of the major factors that have contributed to their economic growth, social improvement, and
health services and quality development during the first decade of the 21st Century. Regardless, there are
other major factors that may be of either positive or negative influence to the development of the
Millennium Development Goals in each country.
Adaptation to Water Stress in Nigeria Derived Savanna Area: The Indigenous
Knowledge and Socio-Cultural Nexus of Management and
Humanitarian Services ............................................................................................................................. 78
Amidu Ayeni, Alabi Soneye, Fatai Badru
Climate change exerts enormous impacts on natural resources both at the local and global scales. Its
effects on water resources over the Sub-Saharan Africa includes sea-level rises, floods, droughts and
water quality degradation. Communities in the rural areas are most disadvantaged through strains on
means of livelihood and access to water, food and health facilities. The paper underscores the challenges
of adapting to water stress from climate change and the implication on sustainability within the sociocultural context of the tropical rural environment. The findings suggest that indigenous culture and local
perceptions are vital for sustainable crisis intervention.
A Longitudinal and Multilevel Investigation on Factors
Influencing Knowledge Sharing Behavior .............................................................................................. 88
Quan Lin, Di Ye, Bocai Bi
In this paper, we explore the individual-level and group-level factors influencing knowledge sharing
behavior and its multi-phase influencing mechanism based on the data from 481 members and 67 groups.
The result demonstrate that: (1) individual-level knowledge sharing behavior affects knowledge sharing
behavior of next phase; (2) learning effect of previous phase has partial mediation effect on the
relationship between the previous knowledge sharing behavior and current knowledge sharing behavior;
(3) group-level knowledge sharing behavior has positive direct effect on individual-level learning effect;
(4) group cohesion has positive direct effect on individual-level knowledge sharing behavior. The
theoretical and practical implications of these findings are discussed finally.
GUIDELINES FOR SUBMISSION
(JMPP)
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The Journal of Management Policy and Practice is dedicated to the advancement and
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Objectives
Generate an exchange of ideas between scholars, practitioners and industry specialists.
Enhance the development of the management discipline.
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Twelve Best Practices to Mitigate Risk Through Continuity
Planning and a Scorecard to Track Success
Elizabeth McGrady
Appalachian State University
Sandra J. Blanke
University of Dallas
This prescriptive research describes a continuity planning readiness scorecard based on twelve best
practices that can be used by organizations to focus planning, compare readiness with peers and track
internal progress. The study of a sample of community organizations revealed that 58% of respondents
had a continuity plan but most did not comply with all of the best practices. These findings assist in
defining continuity readiness and suggest additional guidance to strengthen the readiness of
organizations and communities in response to incidents, hazards and disasters. Training needs are also
identified.
INTRODUCTION
The collaboration of community organizations including human service, health care, and public
service is critical to effective community response to disasters. The heroic outpouring of assistance of
community organizations in response to disasters has been well documented. While expectations of help
are often exceeded (Homeland Security Institute, 2006) the question remains – how prepared are
community organizations to ensure their continuity during a disaster or incident so that they are available
to serve clients and support each other during and after a disaster? The purpose of this study was to:
1. Identify continuity and disaster response best practices.
2. Assess the continuity and disaster response readiness and vulnerabilities of community nonprofit
organizations compared to the best practices.
3. Identify training needs.
4. Assess the ability of organizations to get help from or give help to other organizations.
5. Construct a scorecard that enables organizations to track progress of the organization and key
collaborators in continuity planning.
Community organizations hold unique and important roles in disaster response by serving the needs
of victims as first responders, repositories and distributors of monetary and in-kind donations, and
sheltering, feeding, and clothing victims (Robinson, 2003, Brudney & Gazley, 2009). Fundamental to the
success of disaster response is the ability of individual organizations to deliver on promised services
(Provan, Veazie, Staten, & Teufel-Shone, 2005). Disaster response requires a community-wide
Journal of Management Policy and Practice vol. 15(3) 2014
11
collaborative effort and a chain can only be as strong as the weakest link. A first step is individual
organization continuity planning.
Readiness Status
Completion of continuity plans improves organizational resiliency (Sommer, 2009). However,
government reports such as the Department of Homeland Security Office of Inspector General (2006) and
A Performance Review of FEMA’s Disaster Management Activities in Response to Hurricane Katrina
(2006) have indicated community organizations are not adequately prepared to respond to disasters.
In a study of the Katrina response by the Chicago Public Health Department the participating
community organizations reported lack of planning as their number one deficiency (Broz, Levin, Mucha,
Pelzel, Wong, Persky, & Hershow, 2009). While many organizations have at least a rudimentary
continuity plan in place (see Table 1) only half had tested the plans (Strategic Direction, 2008). This
compares with the study of Mayer, Moss, & Dale (2008) where only 39.3% of businesses reported
completing “many” preparedness activities and 46.1% “some”.
TABLE 1
ORGANIZATIONS COMPLETING AT LEAST SOME PLANNING
Study
Organizations with
at least some continuity planning
Clas, 2008
69%
Strategic Direction, 2008
50%
Mayer, Moss, & Dale, 2008
85%
Best Practices
Community organizations often have limited resources and typically devote those resources to
patient, resident and client needs. Continuity planning must be simple and focused for this sector. This
study identifies twelve best practices in continuity planning using a compilation of source material
including the FEMA Emergency Management Guide (FEMA, 2001), National Institute of Standards and
Technology (NIST) (Swanson, Wohl, Pope, Grance, Hash, & Thomas, 2002), the U.S. Department of
Homeland Security National Preparedness Guidance (2005) in addition to numerous articles and studies
(Wong, Monaco, & Sellaro 1994, Semer 1998, Harrald & Lee, 1999, Bandyopadhyay, 2001, Rike, 2003,
Robinson, 2003, Meyer-Emerick & Momem, 2003, Harris, 2008, Blanke & McGrady, 2008). Based on
our review the following were identified as best practices:
1. Identification of threats to the organization - A threat is described as an impending danger or
harm that can result in an undesired event. Threats are grouped into four categories including
human, forces of nature, infrastructure and technology.
2. Assigning probability of the threat occurring - This step focuses planning toward the most likely
specific threat occurrences. Natural disasters represent approximately only one percent of all
serious interruptions. Though their impact may be the greatest, their likelihood is lowest.
3. Identification of organizational vulnerabilities – Vulnerabilities include loss of resources, assets,
financing, funding, cash flow, ability to communicate, availability of human resources, facilities,
supplies, files, data and information.
4. Evaluation of potential impact of vulnerabilities – This practice describes the impact on the
organization and operations if assets are compromised or lost.
5. Having a plan and annual review of the plan – Not only should an organization have a plan but it
should be reviewed at least annually.
12
6. Updating the plan annually - Plan maintenance is as important as creating the plan, a grossly
outdated plan is like having no plan. This includes key contact information.
7. Testing the plan annually - Although the plan may be well constructed and documented on paper,
it is important to test the plan with either a simulated or real-life situation. As a general rule, all
continuity plans should be tested annually and more frequently if there are changes in the
services, systems, employees, processes and procedures. Testing of the plan can be accomplished
using a variety of methods including hypothetical exercises.
8. Listing key contacts in the plan – The plan should include current and accurate information on
assets, employee contacts, vendor contacts, up-to-date insurance plan information and coverage,
patient or client information, continuity collaborators, volunteers, members of the governance
board, and media contacts. It may include donors if the organization is dependent on
contributions for funding.
9. Electronic copy storage – Continuity plans may be destroyed by disasters such as fire or flooding.
The plan information needs to be available at any time and at off-site locations.
10. Alternate location to operate – The plan should describe how and where services can be delivered
in the event of a loss of the facility.
11. Service repair contracts – A list of the vendors under contract to restore key assets or services.
Once again this should be available electronically.
12. Communicating the plan with other organizations – Do the organization’s partners and
collaborators know of the organization’s plans, is there an agreement in writing, how they will be
contacted and in what circumstance, what is the relationship with Emergency Management (EM)?
METHODOLOGY
To address the research questions we developed a survey based on the best practices identified. We
then used the items to evaluate the readiness and level of continuity planning of Dallas, Texas area
community and public sector organizations. Open-ended questions were developed to identify specific
vulnerabilities and training needs. A panel of ten representatives from the community and public service
sectors tested the assessment and reviewed the instrument instructions and questions for clarity,
understandability and ease of use. The assessment was conducted using senior managers of the members
of the Community Council of Greater Dallas (2007). CCGD is a cross-sector coalition of human service,
legal aid, health care, educational and public service organizations.
We created the Readiness Index by converting the information found in the study to a scale that could
serve as a scorecard. The twelve best practices items were used to construct a Readiness Index by
tabulating affirmative responses of level of completing the practice. Each item accomplished was scored
one point and the total possible Readiness Index score was fourteen.
Indexes can be used in a variety of ways. They can be constructed to quantify multiple pieces of
information into a single number to provide a meaningful but simple indicator. Examples of indexes
include the Social Vulnerability Index which uses wealth, age of structure, density of the built
environment, occupant data and infrastructure dependence of inhabitants to predict social vulnerability as
a result of disaster-related outcomes (Myers, Slack, & Singlemann, 2008). Adrianto and Matsuda (2004)
constructed a Composite Vulnerability Index by weighting then adding economic exposure, economic
remoteness, and the economic impact of disasters. Vulnerability increased with the weighted higher
incidence of each. The Construction Industry Institute used best practices to construct a security-rating
index (SRI) to measure levels of incorporation of security practices (Marshall, Chapman, & Leng, 2004).
A simple index scale developed by Roberto, Bohmer, Richard, and Edmondson (2006) uses additive
responses to a Likert scale to six questions as a diagnostic tool to quickly determine an organization’s
preparedness for ambiguous threats. This scale was used as a basis for our Readiness Index.
13
ANALYSIS
Readiness
Fifty-eight per cent of respondents reported they had a disaster recovery plan in place, while 42% did
not. Though respondents stated they had constructed a plan not all best practice items were completed.
Only 16.7% had reviewed, updated, and tested the plan in the last year. A Readiness Index was compiled
by averaging the number of best practices completed. Table 2 lists the items included in the Readiness
Index and the percentage of organizations that reported completing each factor in the past year. The mean
score for the Readiness Index was 4.79 (sd= 2.83) out of the possible score of 12.
TABLE 2
PERCENTAGE OF ORGANIZATIONS COMPLETING READINESS INDEX ITEMS
Index Items
% Yes
Key contact list
71.2
Repair and service contract
69.7
Reviewed plan in past year
51.5
Identified vulnerabilities
47.0
Alternate location to operate
36.4
Updated plan in past year
36.4
Communication plan with reciprocal agencies 36.4
Electronic copy of plan stored
31.8
Identified threats
28.8
Identified vulnerabilities plus impact
28.8
Identified threats with probabilities
24.2
Tested plan in past year
16.7
Vulnerabilities and Impact
Respondents were asked if they had experienced a disaster using an open-ended question, and if so,
what was their top-of-mind greatest vulnerability or area of concern. Fifty-two per cent had experienced a
disaster of some type. The most frequently reported vulnerability items were funding, finances or cash
flow (30.8%) and the inability to communicate (30.8%). Human resources availability (including
volunteers) and facility and utilities were both reported by 11.5% of respondents. Security and safety
issues were the greatest concern of 7.7% of respondents and availability of supplies and data or files were
the top concerns of 3.8%.
Respondents were asked to select from a list which specific resources would cause significant
immediate impact to the organization’s ability to operate if unavailable or impaired. The resources with
the greatest immediate impact if lost were staff (46%), electricity (46%), cell phones (40%), water (40%),
telephones (38%), and information systems (34%). Respondents were asked the magnitude of loss impact
of specific resources (ranging from very low to very high). Resources that at least two thirds of the
respondents reported as having very high impact on the inability of the organization to function if
unavailable or impaired were donors, clients, computers and computer networks, data, and electricity.
Training and Preparation Needs
Ninety-six per cent of respondents agreed they needed disaster preparation training. The greatest need
reported was overall planning and training assistance. Specific items identified were training or planning
for preparation to ensure continuity of communications during a disaster, development of plans, ability to
14
coordinate and link with other organizations, finding resources, prioritizing actions internally, and
evacuation and relocation. (See Table 3).
TABLE 3
LIST OF TRAINING AND PLANNING NEEDS
Overall planning training
Communication during disaster
Development of plans
Ability to coordinate and link with other organizations
%
50.0
14.6
10.4
10.4
Reciprocity and Availability of Help
In the event of a disaster 42% of respondents reported that there was another agency that could
temporarily support their services. A slightly larger number (52%) reported they could temporarily help
another organization within their current staffing levels. In addition, 42% reported that they could
increase their staffing levels if needed in response to a disaster. Organizations with a higher overall
Readiness Index reported they were more likely to be able to support others in times of disaster implying
better compliance with the best practices could improve community collaboration and reciprocity. Two
best practices predicted a greater likely hood of being able to help others in time of disaster - having
repair and service contracts and having a key contact list. Almost half replied their organizations could
not identify a resource to help with continuity and disaster recovery training and planning.
The Compliance Scorecard
A scorecard utilizing the readiness index items was developed to serve as an internal and external
benchmark organizations can use to compare their continuity readiness with peer organizations and to
track progress in planning improvement. The compliance scorecard (See Table 4) indicates not only the
TABLE 4
CONTINUITY PLANNING COMPLIANCE SCORECARDS
0
Not identified
Identified
Vulnerabilities
Not identified
Identified
Written plan
Do not have
Have
Plan testing
Do not test
Test annually
Key contacts
Do not have list
Have identified and
listed
Alternate location to
operate
No alternate location
Identified alternate
location
Interoperability
Have not
communicated with
other organizations
Have communicated
plan with other
organizations
Threats
Item
+1
+2
Identified and
assigned probability
Identified and forecast
impact
Have and review
annually
Test and revise
annually
Have list stored
remotely or
electronically
Have alternate
location with written
agreement
Have written
organization
interoperability
Total Score
Score
15
completion of each of the seven practices but also a degree of compliance which includes all 12 best
practices. Level of compliance can be indicated using dashboard indicators of red (non-compliant),
yellow (partially compliant) and green (fully compliant) for easy visual tracking of progress.
IMPLICATIONS
Though the primary mission of community organizations will always be serving client needs,
organizations must devote time and resources to ensuring their continuity. No survival – no mission
fulfillment. This study found that almost half of community organizations do not have continuity plans
though these are the very organizations communities rely upon in times of disaster. Even organizations
that stated they had plans in place are not ready to the level of rigor recommended by experts. The study
identified a clear list of best practices in continuity preparedness and a means for organizations to assess
needs, gaps and progress. With ninety-six percent of the organizations participating in this study reporting
they need some form of training and plan development assistance it remains a senior management and
community priority, even in a time of diminished resources.
Continuity planning begins as a strategic imperative. Allocation of resources to planning, training,
risk mitigation and ongoing maintenance of the continuity plan requires ongoing commitment.
Organizations that must meet the requirements of external bodies or regulations such as state licensure,
accreditation, certification, HIPPA, or the Graham Leach Bliley Act must maintain this strategic
commitment to continuous quality improvement. A simple scorecard of best practices can be used by
individual organizations to ensure their ability to serve the community during disaster by increasing their
own readiness. Continued requirements by regulatory and accrediting bodies will assist community
organizations in prioritizing both planning and training. The Federal Emergency Management
Administration and other organizations have developed free web-based material to assist with planning
and preparation but an important first step is the recognition that your organization does not comply with
best practices. This simple scorecard can assist those responsible for governance of organizations in
evaluating continuity vulnerabilities and preparedness.
LIMITATIONS
We applied this scorecard to public service and community organizations who were members of
CCGD. Although this sample contained a variety of organizational types, caution should be used before
generalizing these results to other community and business entities.
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Provan, K, Veazie, M, Staten, L, & Teufel-Shone, N. (2005). The use of network analysis to strengthen
community partnerships. Public Administration Review, 65(5), 603-613.
Rike, B. (2003). BIA best practices – prepared or not… that is the vital question. Information
Management Journal, Lenexa, 37(3), 25-27.
Roberto, M., Bohmer, R, & Edmondson, A. (2006). Facing ambiguous threats. Harvard Business Review,
84(11), 106-113.
Robinson, M. Disaster recovery planning for nonprofits. Lanham Maryland: Hamilton Books. 2003.
Semer, L. (1998). Disaster recovery planning. The Internal Auditor. Altamonte Springs, 55(6), 40-46.
Sommers, S. (2009). Measuring resilience potential: an adaptive strategy for organizational crisis
planning. Journal of Contingencies and Crisis Management, 17(1), 12-23.
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17
TABLE 1
ORGANIZATIONS COMPLETING AT LEAST SOME CONTINUITY PLANNING
Study
Organizations with at
least some continuity
planning
Clas, 2008
69%
Strategic Direction, 2008
50%
Mayer, Moss, & Dale, 2008 (business)
85%
TABLE 2
PERCENTAGE OF ORGANIZATIONS COMPLETING READINESS
INDEX ITEMS IN PAST YEAR
Index Items
Key contact list
Repair and service contract
Reviewed plan in past year
Identified vulnerabilities
Alternate location to operate
Updated plan in past year
Communication plan with reciprocal agencies
Electronic copy of plan stored
Identified threats
Identified vulnerabilities plus impact
Identified threats with probabilities
Tested plan in past year
% Yes
71.2
69.7
51.5
47.0
36.4
36.4
36.4
31.8
28.8
28.8
24.2
16.7
N=66
TABLE 3
LIST OF TRAINING AND PLANNING NEEDS
Overall planning training
Communication during disaster
Development of plans
Ability to coordinate and link with other organizations
18
Per Cent
50.0
14.6
10.4
10.4
TABLE 4
CONTINUITY PLANNING COMPLIANCE SCORECARD
Item
0
+1
Threats
Not identified
Identified
Vulnerabilities
Not identified
Identified
Written plan
Do not have
Have
Plan testing
Do not test
Test annually
Key contacts
Do not have list
Have identified and
listed
Alternate location to
operate
No alternate
location
Identified alternate
location
Interoperability
Have not
communicated with
other organizations
Have
communicated plan
with other
organizations
+2
Identified and
assigned probability
Identified and
forecast impact
Have and review
annually
Test and revise
annually
Have list stored
remotely or
electronically
Have alternate
location with
written agreement
Score
Have written
organization
interoperability
Total Score
19
Issues Surrounding Internationalization of China’s Currency
Xiaohong He
Quinnipiac University
Recent global financial crisis has aggravated problems in the current world monetary system and has
called US dollar’s exorbitant privilege into serious question. There is a growing demand for a
multicurrency world monetary system based on an increasingly multipolar world economy. In this
context, the paper focuses on the issues of China’s currency internationalization and analyzes it impacts,
pros and cons, in the world monetary system in general and China in specific.
INTRODUCTION
China has become omnipresent in the world economy over the past three decades. Currently China
exports and imports have reached $3.87 trillion level slightly ahead of American’s $3.82 trillion. As the
world's second largest economy, China is facing the inevitable process of internationalization of its
currency (RMB). China’s increasingly large economic activity and active role in world trades and
investment have demanded RMB’s international currency role. What does this mean for China and the
world monetary system? To this end, this paper will address four questions in specific.
•
•
•
•
Why internationalization of RMB matters?
Is China up for the RMB internationalization challenge?
What will be the ultimate benefits and costs of RMB internationalization for China and its firms?
What are implications of RMB internationalization for world international monetary system in
general and the US dollar monopoly in specific?
WHY INTERNATIONALIZATION OF RMB MATTERS?
2008 world financial crisis deepens problems in the current global monetary system especially US$ as
the world dominant reserve currency in the system. The “made in the US” financial crisis has raised
serious doubt about the credibility of US$ and its exorbitant privilege. With unconventional monetary
policy and quantitative ease (QE) phase 1, 2, & 3 in process, some seriously doubt that US’ ability can
ever fulfill its debt obligation. Further it is real attention to inflate its debt obligation around the world as
US total public debt, which is more than $16.7 trillion, has exceeded its GDP. In other words America
was perceived no longer be able to bear the world responsibility for its currency due to its own financial
and economic performance, and its unsustainable debt level. This weakens the credibility of the dollar and
its ability ever to pay back to its creditors. Countries around world questioned US$ has unfair advantage
in lowering cost of its debt, in terms of financing cost, transaction cost, and ability to externalize its debt.
20
Russia Prime Minister then, Vladimir Putin, put it memorably when he accused United States of “living
like parasites off the global economy and their monopoly of the dollar.” (Eichengreen, 2012).
History told us the incumbency position of a world reserve currency cannot last forever and so does
US dollar. Currently due to US$ incumbent position and lack of alternative currency, the dollar’s world
currency role remains solid and actually appreciated during the worse phase of the recent world financial
crisis at the end of 2008. As the world economy recovers, some hope the noise around US$ may soon
over. If history can be any guidance, the most recent world currency, British pounds was not long lived.
Once Britain was the first world industrial power and the leading world trade nation, it once enjoyed more
than 60 percent of the world trade. Sterling as the world currency then was used as the invoice currency,
settled currency and reserve currency from later 19 century till early 20th century. Soon it was replaced
with larger and stronger American economic power. By 1931 at its peak before the WWII, US$ accounted
for more than 60 percent of official reserves of major central banks and governments (Eichengreen and
Flandreau, 2009). The history shows that a country’s share of global trade and investment determines the
demand of its currency. At the same time, the development of its currency market determines the liquidity
and convertibility of its currency as settlement currency and invoice currency.
With changing shares, as percentage of the world economy, among countries, there is a huge global
imbalance among three types of economies. It leads to asymmetry of currency and trade flows. On one
side of the world, we have financial and consumption driven US economy and welfare/entitlement
burdened Western European states. On another side we have manufacture and production oriented
economy, such as Germany, China, South Korea, Japan, and ASEAN countries. To support this, there is a
resource oriented economy (land agricultural business and minerals/petro business), like Russia,
Australia, Peru and so on. This has led to a huge trade imbalance in the world and shifted indebted status
to Western countries. At the same time, it is accompanied by the rising economic power of emerging
markets. As the world moves towards a multipolar economy, the imbalance and economic changes
demand more alternative world currencies besides the US dollar.
Triffin paradox offers insight to the role of the US dollar. Triffin paradox is the conflict between the
benefits and costs for a reserve currency country. The reserve-currency country enjoys the consumption
benefit of running a large current account deficit, while the rest of the world benefits from the additional
liquidity and helps facilitate trade. The cost ultimately comes from the declining credibility of reserve
currency which runs a persistent trade deficit. Over time the dollar is strained more and more as ever than
before. The US dollar monopoly and incumbency position may back fire. It could hold US hostage to its
own currency if US cannot deliver solid economic performance in the future. Again if history can be any
guidance, it is not because UK came out of WWI as a debt nation rather it has been its bad economic
performance afterwards.
There has been a demand to create a world currency independent of any sovereignty or a world
currency link to a basket of national currencies and key communities (Rogoff, 2001; Chen & Rogoff,
2003). In reality this seems not only remote and also not very practical in a perceivable future given the
world current political infrastructure and the logistics of the world currency market, if one looks at the
historical performance of SDR and the raising issues associated with SDR supporting Bretton Woods’
institutions. In 2013, the establishment of BRICS Development Bank in South Africa has further
highlighted these concerns. Does RMB have potential to be a good candidate to challenge the
monopolistic position of the dollar? In this context, China currency along with others is demanded as an
alternative for countries to diversify away from US$. Currently on the demand side for China RMB, more
and more central banks approached People’s Bank of China (PBoC) for currency swap (Fan, 2012). On
the supply side, there is a restriction for trading Chinese currency because China’s capital account is not
open.
Currently China not only bears the rising cost to store its wealth in US dollars for its $3.3 trillion
official reserve but also has had no bargaining power when it has to invoice its major imports and exports
in the US dollars. Although China is the world largest importer of energy and minerals, one of reasons
that China has no pricing power, subject to foreign exchange risks, and has to pay higher prices
consistently are due to majority of the world resources and commodities are traded, invoiced and settled
21
in the US dollar. Therefore it matters for China and the world that RMB has to be internationalized from
both demand and supply sides.
IS CHINA UP FOR RMB INTERNATIONALIZATION CHALLENGE?
Current Status
China has not opened its capital account till now. As Japan in the past (Kwan, 2012; Itoh, 2009),
China has been reluctant to open its capital account for good reasons. China has avoided world class
financial catastrophe twice in 1997 and 2008 partially because it has not liberalized its capital account,
has not internationalized RMB, and has kept the global hot money (short term capital flow) at bay. Now
China is continuously to benefit from this. As US Fed wires down QE3, it has money to leave emerging
markets and cause devaluation of local currencies and capital crunch. This created an opportunity for
RMB to fill in the vacuum without suffering the instability of large scale of hot money in and out of
China. Although China’s capital account is not liberalized, the RMB has found its way outside China
especially in the region. Market imperfection can induce “entrepreneurial” activities to circumvent rules.
It has become increasingly difficult for the Chinese authorities to maintain capital account controls, as the
economy is increasingly open and the offshore RMB market is rapidly developing. Companies have
become increasingly creative in exploiting loopholes and gray areas in regulations to get funds and to
arbitrage for higher-yield investments outside China. An increasingly transfer pricing activities made iPod
priced like gold bars as evidenced by the recent exaggerated monetary value of electronic exports from
Shenzhen to Hong Kong when the numbers of container shipment across Hong Kong and Mainland
border remain almost constant (Economist, 2013a). “If this phenomenon continues to spread, it will not
only distort macro data, but also make cross-border capital flows even more difficult to monitor, and
potentially more harmful to macro stability” (Brace, 2013). Given this reality, very recently China
adopted a series polices gradually internationalizing RMB.
According to 2013 the Bank for International Settlements (BIS), the RMB is the fastest growing
currency in global foreign-exchange turnover. In contrast to 2001, RMB did not even register on the BIS
ranking, accounting for less than 0.1% of all such transactions, but in the latest survey, published in
September 2013, RMB had accounted for 2.2% of all foreign-exchange transactions (out of 200%, owing
to the fact that each transaction involves two currencies). This ranked it as the ninth most commonly used
currency. However RMB still lies behind currencies like Mexican peso and Canadian dollar. It has a long
way to go before it matches even British pound, with 11.8% of transactions, let alone the US dollar's
87%.
Internationalization of RMB includes globalization and regionalization. At its infancy, recent trend
indicates RMB is starting to regionalize (Fan, 2012). Regionalization of RMB is on the way although
RMB globalization is yet to happen. Research (Subramanian and Kessler, 2012) shows that RMB’s
influence, measured by co-movement coefficient, has passed Japanese yen in the region since 2005.
Regional RMB bloc seems start to take shape as China is the largest trading partners of its neighbors. 52
percent of China’s trade occurred in neighboring Asia. Asia accounts for 78.6 percent of China offshore
RMB settlement in 2012 (Jin, 2012). Globally China share of World nominal GDP increased from less
than 2% (1978) to 11.5% in 2012 comparing with US 22% in 2012 according to World Bank data. In
2012 the total US exports and imports is $3.82 trillion, while for China is $3.87 trillion (Saigal, 2013a)
mentioned earlier. Current account surplus and large official reserve of $3.2 trillion are also strong
supports for RMB early stage of regionalization.
An international currency plays some or all three roles (Cohen, 2012): settlement currency (medium
of exchange for international trade and investment transactions), invoice currency (as unit of account or
anchor currency), and reserve currency (to store values/wealth). Three roles of RMB are analyzed in this
context. Pease note by and large RMB has not yet to be an invoice currency in the region.
22
RMB Used as a Settlement Currency
The total cross board trade using RMB settlement has grown from ¥3.6 billion (2009) to ¥2.08 trillion
(2011) increased 578 times in two years; and companies who are qualified to settle their cross board trade
in RMB also has grown from 365 pilot companies (2009) to 67,724 firms (2010) increased 186 times
(Fan, 2012). Firms in 206 countries are accepting payment in RMB for their international transactions
(Sina Finance, 2013). 47 countries settled more than 10% of their payments with Hong Kong or China in
RMB, with particularly widespread use of the currency in such transactions in South Korea, Taiwan,
Singapore, the Philippines, France, the UAE and the UK (Economist, 2013b).
One of the factors driving rise tide in RMB-denominated trade is to lower the cost. “In the past,
Chinese suppliers have typically needed to add a premium of 1% to 3% on to their US dollar quotes to
hedge against unfavorable exchange rate movement before a trade settles,” says Peter McIntyre, head of
UK trade, HSBC (Brace, 2013). By transacting in RMB, companies might find their Chinese
counterparties are willing to negotiate at the lower prices. A survey of Chinese companies trading
internationally carried out by HSBC found 41% were willing to consider offering discounts up to 3% on
RMB-denominated settlement. And 9% were willing to give even larger discounts (Brace, 2013). In
addition, companies that are willing to transact with their Chinese trading partners in RMB might find
they have access to a larger pool of potential China business counterparties, including smaller suppliers
who might be unwilling to trade in the US dollar. As such, there is a strong incentive for companies
outside of China to transact in RMB, although not all companies are prepared to make the move at this
point. Besides many non-US firms, like UK and European firms, also have incentives to use RMB since
using US dollar will expose them to additional foreign exchange risk.
RMB Used as Investment Currency
14 countries already diversed their investment in RMB denominated bonds issued by China. HK
offshore RMB center has issued a large scale RBM denominated securities to lay the foundation for
internationalization of RMB and to build its credit worth. ¥100 billion were issued in HK between
6/2007-11/2011.World Bank also issued RMB bond for the first time in HK since January 2011.
Announced in December 2011, RMB Qualified Foreign Institutional Investors (R-QFII) allow their HK
subsidiaries of Chinese fund companies and securities firms to re-invest RMB funds raised in HK back
into China. As of the first quarter of 2012, China FDI (inward and outward) settled in RMB is ¥47 billion
counted as 25.3% of total FDI, although outward direct investment is ¥2.87 billion or 2.76% of total FDI
in the quarter (Jin, 2012).
RMB Used as Reserve Currency
Thailand, Malaysia, Cambodia, and Nigeria have announced to use RMB as their reserve currency. In
April, 2013, the Reserve Bank of Australia announced it intends to invest 5% of its foreign currency
reserves of AUD38.2 billion ($39.2 billion) in Chinese government bonds. The Reserve Bank of New
Zealand is in negotiation with China to make its currency directly convertible with RMB. France has
announced its interest in implementing a swap line with Beijing as well at time of this paper.
By 2013, China has signed currency swap agreement with central banks of 20 countries/regions. Per
Sina Finance (2013) report, to promote international financial cooperation, gain financial security, and to
reduce foreign exchange rate risks, China has signed bilateral currency swap agreements with 20
countries and regions in the amount of ¥2.2 trillion. In Asia-Pacific region, it includes South Korea, Hong
Kong of China, Malaysia, Indonesia, Mongolia, Singapore, New Zealand, Uzbekistan, Kazakhstan,
Thailand, Pakistan, United Arab Emirates, Australia; In Europe, it includes Belarus, Turkey, Iceland,
Ukraine, United Kingdom; In Americas region, it includes Argentina and Brazil. For instance, China
signed three year currency swap agreement with UK in the amount of ¥200 billion vs. £20 billion in June
2013 and with Brazil in the amount of ¥190 billion vs. reals 60 billion in March 2013.
23
Offshore RMB Markets Also Start to Emerge
HSBC has projected that RMB will be the third most-widely traded currency in the world as early as
2015, on par with the euro and the dollar. In 2013, RMB accounts for 12% of global trade but it has also
been projected by HSBC that the currency will account for a third of all global trade in 2015 (Saigal,
2013a). As said earlier firms in 206 countries have accepting RMB payment. RMB offshore deposits also
grow fast as a result, there are ¥700 billion in Hong Kong and ¥140 billion in Singapore by 2013, and in
London it is ¥109 billion by January 2012. The total RMB offshore pool is estimated around ¥1.2 trillion
where Hong Kong is the largest with ¥900 billion (Xinhua News Agency, 2013). At the beginning of
2013, Taiwan became the latest offshore clearing house for RMB. Singapore & London are also market
for RMB deposits and spot market trading. The negotiation to be offshore clearing house for RMB in
these two countries is also under the process at the time of this paper (Saigal, 2013a). Tokyo also trades
RMB none delivery forward contracts (NDF) and yuan-yen direct exchange trading. Chicago CME also
offers RMB NDF. In 2013, RMB deposits in France are the second-largest in Europe after the UK. Along
with the offshore market development, the pace of RBM appreciation is accelerating. It hits 19-year highs
against the dollar nearly every day. Since 2005, RMB has appreciated more than 30 percent against U.S.
dollar.
Free “Financial” Trade Zone
In 2013, China established Shanghai Free-Trade Zone. At heart of this experimentation for the Zone
is financial sector liberalization. This will be a testing window for internationalization RMB inside China
territory and learning opportunity of setting up across boarder financial regulatory mechanism. It will
allow trials and errors of market guided interest rate; allow firms to convert money more freely from yuan
to foreign currencies, and move money overseas freely. Foreign firms inside the Zone will allow their
foreign-exchange operations and may give them a bigger share of the domestic bond market. Domestic
firms inside the Zone will have free access to global financial market as well.
What Are Major Challenges for China?
In the context of the above positive development for RMB internationalization, there are many
challenges because of its underdeveloped financial market, current global macroeconomic environment,
and domestic economic development policy transition. These are analyzed in details below.
Unstable Global Macroeconomic Environment & Domestic Policy Transition
Globally uncertainty surrounding the unconventional US monetary policy of government security
buying back program (QE1, 2, 3..), plus Euro-zone debt crisis, and Japan Abe’s economic policy to boost
country’s debt to 240% its GDP in fighting decades of deflation. All these add uncertain liquidity to the
global currency market and put pressure on emerging market currencies in general and China currency in
specific. Although there has been a slowdown for US Fed T-bond buying program, the loose monetary
policy activities of US Fed, ECB and Bank of Japan are yet to be settled. All these translate into
additional uncertainties for the world monetary system.
On domestic front, China economic policy is in transition and leads to the slower growth in China
market. Unusual higher growth in its financial sector relative to its real economy has raised concerns,
according to China Bank Regulation Committee, China banking sector grows 39.3% while its industrial
sector grows 25.4%, and its ROE has been higher than the most profitable state-owned tobacco and petro
sectors (Zhang, 2012). After 2013 new leadership change, China is shifting from a high GDP growth
economic development path towards more sustainable growth. China aims to shift its economic growth
activities towards real economy other than paper returns from its financial and real estate sectors. It also
plans to shift from export led growth to domestic consumption driven growth, and restructures the
economic activities from high carbon manufacturing to low carbon productions. It will promote and
support activities in sectors like service, IT, recycling or regenerating environmental friendly value added
economic sectors. Facing challenges of economic/environmental unsustainability, increasing social
inequality, and political corruption, policy makers always have stability in mind as precondition to go
24
through these transitions. To this end, RMB internationalization has to be coordinated with the domestic
economic, social, political, and environment policy priorities, especially for transition and upgrading for
China large size of labor intensive export oriented sector.
The Underdeveloped Financial Market Inside and Outside China Hinters RMB Denominated
Securitization
RMB is not a free exchange currency internationally, although recently policy measures and
regulations are gradually introduced to internationalize RMB. Premature of China’s domestic securities
markets has yet to support RMB internationalization. China’s debt and equity market are very small in
comparing with that of the US. For its debt market in 2011, $3.3 trillion outstanding stock of debt
securities issued domestically is very small in size, in contrast with $26.3 trillion of the U.S debt market.
In addition, bond liquidity remains very low in China since most debt securities are held until maturity
and never traded. For the equity market the capitalization of the Shanghai and Shenzhen stock exchanges
is about 80 percent lower than the combined market capitalization of the New York Stock Exchange and
NASDAQ Market. For the forward market, the RMB related foreign exchange derivative contracts is only
3% of the world total (Jin, 2012).
Institutional & Policy Impediments
China bank loans are still dictated or heavily influenced by administrative policy orders other than by
economic efficiency, although in July, 2013 Chinese government has taken the initial step to liberalize its
interest rate. State-owned enterprises usually have easier access to credit and more favorable loan terms
than private enterprises in receiving loans from state-owned banks. The “big four” state-owned banks
dominate the Chinese banking industry, and their too-big-to-fail status and explicit government support
undermine market discipline. As of 2012, only 12% loans go to private SMEs (Zhang, 2012). During the
world financial crisis, Chinese government stimulated its economy with a 4-trillion-yuan package, or
about $585 billion, an intervention far more aggressive than that chosen by any other major economy,
especially relative to China’s GDP. Because of this usual liquidity in the economy and higher returns
from financial activities, a majority of China leading manufacturing firms across industrial sectors are all
involved in real estate investment and/or land deals. The extra liquidity has been diverted from real
economy and gone to financial and housing sectors instead. Although inflationary pressures have eased
following the PBOC’s tightening monetary policy in the last two years, asset bubbles in the real estate
market and mounting local government debt remain serious threats to China’s financial outlook.
Large domestic shadow banking system is yet to be addressed as well. 4-trillion-yuan fiscal stimulus
has led an explosion in off-balance-sheet lending by banks and private loans by nonbank entities. This
shadow-banking lending activity accounted for an estimated 20 percent of China’s total loans in 2011.
With the cooling of the real estate market and with slower economic growth likely in the near term, a
large share of these loans could turn bad. Because these loans took place outside the view of regulators,
the effect of a sudden disruption in repayment is still difficult to predict.
Weak Financial Market Regulatory Infrastructure
Weak financial market regulatory infrastructure is way behind that of US and UK. It is under
equipped to handle across board financial flows at the moment. In retrospect, China needs to take gradual
steps to improve domestically financial market reform for efficiency, risk management, and
internationalization. Note a recent change in policy shift may introduce more challenges. July of 2013
policy on liberalization of interest rate on bank loans is yet to be realized and carefully managed. It is
better to be slow than fast and it is better to do it right than yield to global market pressures.
Geographic Location and Territory Conflict Can Make RMB as an Unsafe Haven, and Economic Power
along May Not Be Enough for RMB Internationalization
Unlike British sterling in 19th century and US dollar in 21st century, they are supported by stable
political system and strong military power while China only by its rising economic strength. Can this be
25
possible and sustainable? For instance American can apply its military power if OPEC members do not
conduct its oil trade in US dollars. Further China and Japan, China and South Asian territory conflicts
could add unusual demand for US dollars and could make RMB as a safe haven impossible.
Time seems pushing RMB internationalization process at the faster speed although China is not
ready. All above mentioned challenges will need time to work out before RMB can gain international
currency status. In recent years, the net balance of capital and financial accounts has outpaced that of
current account transactions, and has become the main source of China’s reserves accumulation. This has
not only put strong upward pressure on the RMB, but has also run a danger to create potential asset
bubbles, particularly in the housing sector.
WHAT ARE THE ULTIMATE COST AND BENEFIT OF RMB INTERNATIONALIZATION
FOR CHINA AND ITS FIRMS?
What are ultimate pros and cons for RMB internationalization in light of above challenges?
Liquidity Premium
RMB internationalization creates liquidity premium. Liquidity premium reduces China overall cost of
borrowing. Due to an international increase in RMB demand, China can sell bonds at higher price (low
yield) and buy bonds at lower price (higher yield). As more countries using RMB, it leads to a network
effects in favor of China term of trade as trading partners pay and sell in RMB increase. It also enhances
productivity and competitiveness for China companies years down the road. China manufacture firms can
use its own currency abroad to reduce foreign exchange risk and lower cost of international trade. It
enables Chinese firms to acquire overseas assets and advanced technologies. It facilitates firms industrial
upgrading by allowing low value- added & labor intensive industries to relocate production to lower-cost
countries (Saigal, 2013b). For Chinese financial intermediaries, RMB internationalization increases its
volume and allows financial intermediaries increase profits from trading commissions, payment and
investment services. Increase international demand for RMB leads its appreciation and increases purchase
power for Chinese people travel abroad, increases China import, and reduces domestic inflation.
Effects on China Economic Development
For trade account, the increase demand for RMB leads to appreciation of RMB and reduces
competitiveness of Chinese firms. Since 50-60 percent of Chinese economy still relies on export and
many of exporters are small firms, the impacts on China’s low cost and labor intensive manufacture
sectors are negative. Although China is changing its development model from “made in China” to “Create
in China” and moving up to value chain, China still needs labor intensive sectors for a long time to absorb
labors in the west region and rural area, and for a stable urbanization process to take place.
For the capital account, due to unfold Euro sovereignty debt problem, decrease US dollar credibility,
and unsustainable growing US debt level as more than 100 percent of its GDP, it will not only puts
upward pressure on RBM but also increase market volatility. Hot money would come to China for
diversification and profit rather than real economic development. This can cause bubble and burst.
Impatient capital flow is harmful for China development. Undeveloped China financial capital market can
amplify the problem. for the impact on official reserve, as dependence on RMB increases as an
international currency, it not only helps to increase China political power and importantly to reduce its
dependence on the US dollar especially for its official reserve. It lowers cost for China to store its wealth
($3 trillion reserve) in US dollars and to diverse its risk away from US dollars.
Triffin Dilemma
RMB role as a major world currency may require China to run a trade deficit if its capital account
cannot meets RMB demand from foreign markets via capital account adjustment that is short selling and
long investing.
26
China Domestic Policy Independence
RMB internationalization will reduce China domestic policy autonomy and increase the challenge
and reduce the control on monetary policy as increasingly RMB will be banked outside the country. It
would be difficult to interfere and stabilize monetary aggregates and interest rates.
It Helps to Increase China Political Power
When global dependence on RMB increases, it enhances China political power in the global affairs.
Yet China geopolitics and regional conflicts can water down China status as a “safe haven” which adds
volatility to RMB. An elite currency needs to be backed by political stability and strong military force to
ensure peace and stability for a big country like China.
WHAT ARE THE IMPLICATIONS OF RMB INTERNATIONALIZATION FOR WORLD
MONETARY SYSTEM IN GENERAL AND THE US DOLLAR MONOPOLY IN SPECIFIC?
RMB internationalization helps to diverse foreign exchange risks in the global monetary system, to
increase liquidity in the market, and to reduce transaction cost of only using one currency. It also allows
countries to diverse away from US$ as settlement currency, invoice currency, and reserve currency.
Adding RMB into the system will reduce the cost of capital and increase capital accumulation. Politically
it democratizes the world monetary system and disciplines the western central banks and forces them to
reduce deficits. It helps to improve international financial system stability and sustainability.
It reduces the US dollar role as the lender of the last resort and its ability by exchange real goods with
costless notes. It would be especially true when a sovereignty independence world currency is too remote
to accomplish and IMF/SDR is too weak to do anything at the moment. RMB acts as an additional hedge
(diversification possibility) for global investors and to share power and responsibility. The current global
monetary system gives US dollar unfair exorbitant advantages. It is not good for the world and not good
for the US as well. The increasing role of RMB along with other emerging market currencies as
alternatives in the global monetary system and declining role of US dollar may be inevitable in the long
run. Yet how to get there and how long it takes to get there are still open questions. This will affect global
monetary system and international business for years to come.
CONCLUSION
For the determinants of international currencies, IMF researchers (Maziad, Farahmand, Wang, Segal
and Ahmed, 2011) believe key determinants of currency internationalization are economic size,
macroeconomic stability, deeper financial markets and macroeconomic and structural policies support.
Based on historical perspective of US dollar (1913-1945), Deutsche mark (1973-1990), and Japanese yen
(1948-1991), Harvard University scholar (Frankel, 2012) argued there are three determinants of
international currency status, namely economic size, confidence in the currency, and depth of financial
market. Based on econometrics analysis of recent central banks’ official reserve (1967-2004),
international trade settlement (1999-2005), and international debt securities (1993-2006), Chinese
scholars from Tsinghua University (Li and Yi, 2010) identified there are five preconditions for an
international currency: large share of a country’s GDP to the world GDP, large scale of domestic financial
market, large official reserve, continue appreciation of the currency for certain period of time, and
convertibility of the currency. Specific for a reserve currency role, based on the history of British sterling
and US dollar (Richards, 2011), two additional conditions seems required in addition to Li and Yi (2010)
study – a stable political system of the country and military power in capable to intervene in the time of
the regional and world crisis. Based on these seven conditions, so far RMB can only meet three out of
seven, namely scale of the country economy, large official reserve, and continue RMB appreciation in the
past eight years or so. Hence RMB has long way to go to be an international currency. The same case can
be said for Euro. Till then, US dollar will be a world dominant currency in the world monetary system.
27
In a near future for the monopoly position of the US dollar, it will keep its world reserve currency
position. As potential rivals for the US dollar, RMB currently is still under too many state restrictions.
Further it may not be good for China and the world to internationalize RMB too fast; while euro on the
other hand is a currency without a state backing as its weakness in the opposite side of RMB. What really
challenges the US dollar, the same as in the past facing British pound, is the US itself. It is its own
unsustainable debt and weak economy. With emerging of several strong players in the world market, the
multiple currency system seems emerging. It may evolve into two tiers of international currencies system,
namely the first tier of US$, Euro, and RMB and second tier of pound, Japanese yen, Swiss Franc, and so
on. In a multipolar economy, we will be safer in a multicurrency world in the future though we may take a
bumping road to get there.
REFERENCE
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http://www.euromoney.com/Article/3206589/Renminbi-takes-off-as-tradingcurrency.html?single=true&copyrightInfo=true
Kwan, C.H. (2012). Japan’s Experience with Promoting the Yen as an International Currency: Lessons for
China, Presentation, Nomura Institute of Capital Markets Research
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133-160.
Cohen, B.J. (2012). The Benefits and Costs of an International Currency: Getting the Calculus Right."
Open Economies Review 23.1: 13-31.
Economist. (2013a). GlaxoSmithKline in China: Bitter Pill”. July 20-26th, 56-57.
Economist. (2013b). Towards a redback world”, September 24th 2013.
Eichengreen, B. (2012). Exorbitant Privilege: The Rise and Fall of the Dollar and the Future of the
International Monetary System. New York: Oxford University Press
Eichengreen, B. and M. Flandreau. (2009). The rise and the fall the dollar (or when did the dollar replace
Sterling as the leading international currency?)”. European Review of Economic History, 13, 377411.
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Presentation at June, 2012 Advance Financial Forum in Jinan University, Guangzhou, China.
Frankel, J. (2012). Internationalization of the RMB and Historical Precedents, Journal of Economic
Integration, Vol. 27, No. 3, pp. 329-365
Itoh, M. (2009). The Integration Process in East Asia: Japan’s Experience and Policy Agenda. Fostering
Monetary & Financial Cooperation in East Asia, Singapore: World ScientificPublishing.
Jin, Z.X. (2012). The Use of RMB in International Transactions: Background, Development and Prospect.
Sept. 27, Presentation at Sasana Kijiang, Kuala Lumpur, Bank Negara Malaysia.
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Finance Research. No.2. 2010, Issue 356, 31-43.
Maziad S, P. Farahmand, S. Wang, S. Segal, and F. Ahmed. (2011). Internationalization of Emerging
Market Currencies: A Balance between Risks and Rewards, IMF Staff Discussion Note,
SDN/11/17, Oct. 19, 2011
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Rickards, J. (2011). Currency Wars: The Making of The Next Global Crisis. Portiflio/Penguin, New York:
New York
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frontier.html?copyrightInfo=true
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http://finance.sina.com.cn/money/forex/20130802/080316323461.shtml
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Go? Working paper series. Oct. Washington D.C. Person Institute for International Economics.
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Zhang, Y.C. (2012). Three Imbalances between China Virtual Economy and Real Economy. Presentation
at June, 2012 Advance Financial Forum in Jinan University, Guangzhou, China.
29
The Engine of Health Information Exchange
Neera Bhansali
Florida International University
Sushil Gupta
Florida International University
We discuss barriers to implementation of Health Information Exchange (HIE). The focus is on
operational aspects of HIE to improve the process of sharing electronic health-related information
among various organizations. Various topics include: strategy development, project management,
architecture and infrastructure management.
INTRODUCTION
The healthcare system in United States is complex. Healthcare is delivered to patients in multiple
locations via multiple providers who do not share the same electronic medical records. It is fragmented
due to non-interoperable and non-integrated clinical data systems. Electronic health records and HIE are
perceived as solutions to address the issues caused by fragmented systems, inconsistent communication
and incomplete records.
As part of the affordable health care reform, Health information exchanges (HIEs) have been
explored as a platform that could facilitate timely sharing of electronic health-related information. This
information could be exchanged among organizations to provide timely and effective clinical information
at the point of care. The availability of complete clinical data is perceived as a critical component in
improving the quality of care and reducing costs (Vest, 2008). Health information exchanges aim to
facilitate patients’ health information to follow them to diverse provider settings in order to improve the
clinical decision processes. It has been suggested that the HIEs would enhance coordination of care,
reduce costs, reduce medical errors, improve patient safety and avoid duplication of services (AdlerMilstein et al., 2011).
Patient safety is affected when a complete clinical picture of the patient is not available at the point of
care. HIEs could, for example, greatly reduce the number of adverse drug events by finding prior allergies
of the patient and improving the accuracy of the allergy list (Kaelber and Bates, 2007). They also have the
potential to enhance patient safety through drug-disease information processing by making all patient
diagnoses available at the time of drug prescription. HIEs can also provide the ability to detect drug
seeking and doctor shopping behaviors (Hincapie et al, 2010). The ability to monitor and potentially
control the preceding behaviors can significantly reduce medication abuse and healthcare costs (Walker et
al, 2005). HIEs could also address interoperability problems associated with the ability to support
longitudinal analyses of care and public-health needs (Kuperman, 2011). It is also seen as a way to
quickly identify affected individuals in the case of a drug recall from the market or healthcare intervention
30
in the likelihood of a pandemic (Vest and Gamm, 2010). The provision of connectivity among providers
through HIE would facilitate the coordination of care and reduce duplicate therapy and medical errors
(Walker et al., 2005).
HIE benefits have already been perceived by emergency departments’ physicians as they see a larger
number of patients each day compared to non-emergency department physicians and have to often make
their decisions based on incomplete clinical information on the patients. The availability of patient data
through health information exchange, at the time of care at the emergency department is perceived as
having an important impact on the quality of care and patient safety (Hincapie et al., 2010; Kaelber and
Bates, 2007)). It has the potential of providing economic benefits by reducing redundant tests at the
emergency department, reducing patient inconvenience, improving patient care and reducing admissions
(Frisse and Holmes, 2007).
Regional data sharing initiatives were developed as a response to the ONC (Office of the National
Coordinator for Health Information Technology) initiatives and HITECH Act. The HITECH Act did not
specify how HIE should be achieved. Organizations and regions aimed to accomplish data sharing
through the formation of Regional Health Information Organizations with a goal of enabling exchange of
information within a geographical area. The RHIOs collect data using a pull model where clinical data
from across providers is pulled and integrated to provide comprehensive information on the patient. As
there was no common platform specified, multiple vendor based solutions, that could be used to
exchange data, arose. On the other hand, the Direct project initiated by NHIN (National Health
Information Network) utilizes a push model which allows providers to send health information securely to
another provider. For example, it could be used when a physician sends a referral to a specialist or when
the specialist returns the findings to the primary care physician. In the Direct Project, data is transmitted
by linking the data from an inbound message to the patient file. The linking can be done electronically
using patient identifiers or manually (Kuperman, 2011). However a lack of a sustainable business model
has emerged as a main obstacle for the continued growth of RHIOs(Vest and Gamm, 2010). Grant
funding was not found to be a viable source of finance and need was felt to develop self-sustaining
models.
CHALLENGES
In the last two decades that HIE efforts have been underway, it has been found that the number of
unsuccessful HIE efforts far outnumber the successes (Vest and Gamm, 2010). Health information
exchanges face challenges on multiple fronts, including a lack of funding, concerns about privacy and
security, legal and regulatory issues, technical issues, and organizational concerns.
The rising threat of identity theft through data loss has increased privacy and security concerns in
HIEs. HIPAA regulations have been found to be inadequate as a privacy assurance for health information
exchange as it does not apply to entities outside healthcare that collect, store and manage information e.g.,
Google or Microsoft. Also, deidentified data is not covered by HIPAA and raises concerns of third parties
being able to reidentify data. Fear of identity theft would promote information withholding behaviors
among both patients and providers (McGraw et al., 2009) which would further impede successful health
information exchange.
HIEs are faced with technical challenges of combining data from different technology vendors and
organizations as well as dealing with complicated administrative issues (Fontaine et al., 2010).
Inappropriate organizational workflows and lack of training adds further barriers. Lack of informatics
training among business and medical personnel has hampered their ability to develop successful HIE
strategies. Lack of financial resources to purchase the software, hardware and network systems to build
the infrastructure for HIE, coupled with the lack of technical proficiency to implement and maintain the
HIEs between providers present major barriers to HIE implementation (Vest and Gamm, 2010,
Blumenthal, 2010).
Patients are important stakeholders in HIE as their consent is required for their medical information to
be shared electronically by their physicians and other healthcare providers. Personal Health Records
31
(PHR) and patient portals could enhance patients access to their medical information and lead to
enhanced patient-provider communication. PHRs could allow the sharing of patients medical information
electronically with their doctors and other healthcare providers through HIE. It could help patients with
chronic diseases like diabetes to manage self care and engage actively with their healthcare providers,
improving both health quality and safety. However widespread adoption of HIE by patients has been
impacted by privacy and security concerns (Donnell et al., 2011). Moreover, physicians question the
accuracy and completeness of data collected and maintained solely by the patients (Vest and Gamm,
2010).
In spite of the positive benefits that would accrue from engaging in HIE, few physicians are found
willing to participate in exchanging information. The existing business models require the physicians to
pay a considerable fraction of the cost of the infrastructure of the HIE. A survey of physician’s attitude
towards HIE showed limited willingness to pay for it (Wright et al., 2009). Apart from concerns regarding
privacy, there are issues of liability based on decisions made on bad quality data derived from the HIE
that deter physician engagement.
Competitive implications of HIE also act as barriers to successful HIE implementation (Vest and
Gamm, 2010). Patient data confers a competitive advantage to the participating hospital by tying the
patient to the provider. HIE on the other hand requires competing organizations to share their most
valuable asset – patients and patient data. It requires exchange of data and cooperation between
competing entities which is difficult to achieve. The competitive nature of the health care system provides
a disincentive to sharing of information through HIE as it would lose competitive advantage by
participating in HIE. Using nationally representative data, Adler-Milstein et al. ( 2011) found that forprofit hospitals and hospitals with a small market share are less likely to engage in HIE because of their
concern about loss of market share. On the other hand they found that hospitals with a dominant market
share may perceive participation in HIE as an opportunity. Yet again, responding to market and
competitive pressures, organizations may share only a subset of data with a subset of healthcare providers
to prevent patient erosion.
GOVERNANCE
Successful outcomes in IT implementations suggest that project outcomes are dependent on the
quality of implementation strategy. Inadequate buy-in by stakeholders, lack of trust in the quality of data
and in the secure exchange of data, resistance to change by users, financing of costly network technology,
need for process redesign and unclear leadership are some of the common barriers observed between IT
implementations and HIE implementation. Applying an over-arching governance framework could
address many of these barriers by providing a common framework and policies and procedures for
exchanging information and by providing oversight and accountability measures.
No study has thus far addressed the operational issues of HIE from a governance perspective.
Implementing HIEs is a multi-dimensional process that is more than a technical issue. The magnitude of
the task is usually significantly greater than expected. It requires the managing of several factors
simultaneously (Sicotte and Pare, 2010). The socio, human (Buntin et al., 2011) organizational and legal
dimensions of HIE implementation are as important as the technical ones. A governance model is
required to develop policies and procedures to provide a clear vision, oversight and coordination over the
multiple dimensions of HIE process.
Governance entails the distribution of decision making responsibilities and the definition of the roles
that various organizational members would have in HIE. Governance within participating organizations
would involve the development of processes for making decisions regarding HIE strategy development,
HIE initiative prioritization and budgeting, HIE project management and HIE architecture and
infrastructure management. It would involve defining policies and procedures that would govern the
organizational use of HIE. HIE organizational responsibilities would involve developing and managing
the architectural plan; developing HIE standards, defining procedures to assess sourcing options,
32
managing the portfolio of applications, infrastructure and services and establishing communication
mechanisms.
User and stakeholder responsibilities within participating organizations would involve understanding
the HIE activities that support their function, ensuring that the goals of HIE initiatives reflect the
function’s needs, developing specifications for HIE projects, providing feedback to HIE on
implementation issues, application enhancements and HIE support, and participating in developing the
HIE agenda and priorities within the organization. Management responsibilities within the organization
would entail ensuring that the organization has an HIE strategy, balancing the perspectives of users and
HIE needs, establishing processes for budgeting, acquiring and implementing applications and
infrastructure, ensuring that HIE processes conform to policies and procedures, ensuring that HIE
applications and activities conform to relevant regulations and internal controls and encouraging HIE
experimentation.
A specific governance board or committee would have to be instituted that would bear responsibility
for HIE implementation, initiative specific committees and roles, manage HIE liaison relationships and
act as HIE champion. This governing body would be responsible to review and critique HIE technical and
organizational strategies, review and critique overall HIE tactical plans and budgets and discuss and
provide advice on major HIE issues and challenges.
The questions that remain to be answered are:
• Who should be included in the governing body?
• What powers should be given to the governing body to hold participants accountable?
• Who should establish the rules of data sharing? What should they encompass? How should
they be established and enforced?
• What role should the governing body play in financing the HIE?
• Should the governing body be established within a separate entity, such as a not-for-profit?
• Who will hold the governing body accountable for establishing functional health information
exchange?
The governance process would help address the predominant barriers to HIE - need for standards,
data security, political factors, and disparities in HIE acceptance and use. It would ensure accountability
and enforcement of policies and procedures. Effective governance could facilitate a more coherent vision
and inter-organizational business process redesign in HIEs. Support by leadership within and outside the
organization could help address conflicting interests regarding data ownership and facilitate HIEs
implementation.
Policymakers and stakeholders in HIE should seek to implement comprehensive data security policies
that would allow secure transmission of data between organizations thereby increasing confidence in data
privacy and security. A governance model addressing privacy issues through privacy policies and
regulations would enhance trust in the data exchange through HIEs.
Developing and implementing standard vocabularies for various healthcare data types would facilitate
efficient data communication and exchanges between organizations and providers. Developing standards
on both the type of data exchanged as well as the breath of information to be exchanged would facilitate
better information exchange. Allowing data to be stored and exchanged with metadata would reduce
many of the errors associating data to the same patient, between organizations. Instituting processes for
clearly defining relationships between different owners of data would facilitate better data exchange
processes. Instituting processes for formal patient consent for data exchange, data access and data use
policies (Frisse et al., 2011) would further help alleviate data security and privacy related issues.
Users and physician attitude towards adopting electronic health record and HIEs is important to its
success. Soliciting the views and participation by all stakeholders early in the process of implementing
HIEs would lead to greater buy-in and easier adoption down the road. Design of the HIE system based on
stakeholders feedback and providing adequate user support during implementation are important
considerations. Participation by all stakeholders early in the process help in reducing political barriers and
33
provide deeper understanding of information constraints and information need and use among the
different stakeholders of healthcare. Managing stakeholder expectations also helps in minimizing
conflicts and facilitate better risk management. Providing incentives to stakeholders would further assure
their participation. Although an HIE could financially benefit the payers substantially, yet they are absent
from most HIE initiatives (Fontaine, 2010; Adler-Milstein et al., 2011).
Coordination of health IT standards is required for uniform implementation and integration of
administrative, financial and clinical data transactions. Health data exchanged over HIE would include
patient electronic record data, medication data, laboratory data and patient consents. Several base
standards for data types already exist such as HL7, a healthcare informatics interoperability standards,
PACS (Picture Archive and Communication System)standard within the field of radiology, LOINC
(Logical Observation Identifiers Names and Codes) standard for identifying laboratory observation,
SNOMED CT (Systematized Nomenclature Of Medicine Clinical Terms),that could be referenced.
Standardization and integration of clinical and administrative data would facilitate communication and
lead to greater efficiencies. Through standardized operating rules, it would allow for more seamless
exchange of information leading to a reduction in costs and efforts for patients, providers, and payers
(Buntin et al., 2010)
Legislative mandates would be a powerful motivator to institute governance for successful health
information exchange. State and federal policymakers would have to address the barriers to HIE either by
instituting penalties or stronger incentives would be needed to overcome concerns of competition and loss
of market share, to successfully engage organizations in health information exchange.
CONCLUSION
Health information exchange (HIE) is the process of sharing electronic health-related information
among organizations according to nationally recognized standards. The HITECH Act and meaningful use
aim to promote the building of a health Information infrastructure in which patient data is exchanged
across a national health information exchange. State and regional HIE leaders face an uphill journey to
health data interoperability between disparate healthcare information systems. This paper explores the
role of governance in navigating the barriers to Health Information Exchange (HIE). It discusses the
governance processes and structure, organizational and stakeholder responsibilities, governance issues
that need to be addressed and applicable lessons learnt from effective application of IT.
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Organizations in the United States: Implications for Meaningful Use. Annals of Internal Medicine
154:666-671.
Adler-Milstein, J., DesRoches, C.M. & Jha, A.K. (2011). Health Information Exchange Among US
Hospitals. The American Journal Of Managed Care 17(11):761-768.
Blumenthal, D. (2010). Launching HITECH. The New England Journal of Medicine 362, 5.
Buntin, M.B., Burke, M.F., Hoaglin M.C. & Blumenthal, D. (2011). The Benefits Of Health Information
Technology: A Review Of The Recent Literature Shows Predominantly Positive Results, Health
Affairs 30 (3): 464-471.
Buntin, M.B. Jain, S.H. & Blumenthal, D. (2010). Health Information Technology: Laying The
Infrastructure For National Health Reform. Health Affairs 29 (6):1214-1219.
O’Donnell, H.C., Patel, V., Kern, L.M., Barrón, Y., Teixeira, P., Dhopeshwarkar, R. & Kaushal, R.
(2011). Healthcare Consumers’ Attitudes Towards Physician and Personal Use of Health
Information Exchange, Journal of General Internal Medicine 26(9):1019–26.
Frisse, M. E. & Holmes, R. L. (2007). Estimated financial savings associated with health information
exchange and ambulatory care referral, Journal of Biomedical Informatics 40: S27–S32.
34
Frisse, M.E., Johnson, K.B., Nian, H., Davison, C.L., Gadd, C.S., Unertl, K.M., Turri, P.A. & Chen, Q.
(2012) The financial impact of health information exchange on emergency department care,
Journal of American Medical Informatics Association 19: 328-333.
Fontaine, P., Ross, S. E., Zink, T. & Schilling, L. M. (2010). Systematic Review of Health Information
Exchange in Primary Care Practices, Journal of the American Board of Family Medicine
September–October. 23(5).
Hincapie, A.L., Warholak, T.L., Murcko, A.C., Slack, M. & Malone, D.C. (2011). Physicians’ opinions
of a health information exchange, Journal of the American Medical Informatics Association
18:60-65.
Kaelber, D.C. & Bates, D.W. (2007). Health information exchange and patient safety, Journal of
Biomedical Informatics 40: S40–S45.
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toward health information exchange: results of a statewide survey, Journal of American Medical
Informatics Association 17:66–70.
35
University/Community Partnerships: Engaging Business Students in
Leadership and Solution-Based Approaches
Susan Kinsella
Saint Leo University
Nancy Wood
Saint Leo University
This paper will address the importance of engaging business students in new approaches to problem
solving that will enhance their ability to create vibrant economies and collaborate with other professionals in an effort to sustain development in a global economy. These approaches include servicelearning opportunities, teaching about micro-enterprises, and applying business principles to social
entrepreneurship. A review of the literature regarding how service learning can benefit business students
is included.
INTRODUCTION
In the last few years, companies have implemented this phrase, Integrated Talent Management, to
describe an integrated system approach to recruiting, employee development, performance management,
compensation, and overall training and development of their workforce (Bricout, 2004). Besides creating
a more efficient talent management system, organizations require the ability to rapidly address and
effectively respond to business needs. Just as companies are in desperate need of a critical thinking
workforce and abled leaders, business schools have come under more scrutiny for teaching practical and
critical thinking skills to their students. Courses where students can apply theory to practice are becoming
popular as universities respond to issues of sustainable community development and social responsibility.
Service-learning opportunities within the classroom are now encouraged so that students can practice the
skills they are learning and apply them to real situations in their local community.
LEADERSHIP TRAINING
Leadership is a key topic in global business as well. (Pless, Maak, & Stahl, 2011) However, while the
literature review provides much inquiry on leadership, little is known about responsible leadership. The
new challenge in global management is to develop a new model of leadership training that provides the
‘out of the box’ experience, encouraging students to think critically about new solutions to existing
problems. (Pless, Maak, & Stahl, 2011a). This has become a challenge for educators as well. While some
schools are using virtual and online courses to teach students about practical business problems and
solutions, others are offering their students real opportunities to test their newly acquired skills in areas of
the world where leadership and business solutions are lacking. In study abroad programs students are
36
getting the chance to work with teams of other international professionals to create businesses, work in
agriculture, develop plans for housing, and sustainable food and water for impoverished communities.
Many universities now have campuses on other continents and encourage their students to spend time in
another country before graduating. This experience allows the student to usually learn another language,
participation in the culture, work with other international students and professionals in their discipline,
and expand their perspective regarding issues effecting that country and how their combined knowledge
may assist the growth of new solutions.
The scholarship of engaging students in the learning process has become more important in
institutions of higher learning. Due to changes in awareness, teaching of ethical issues and values, and a
sense of social responsibility, universities have an increasing interest and often a social mandate to
develop courses on student leadership, sustainable community development and social enterprise. It is not
unusual to see a multidisciplinary approach to teaching this plethora of skills. Harvard University now
offers a summer institute every few years to bring Human Services and Business professionals together to
collaborate on social problems and combine their expertise. Teaching Human Services professionals
about marketing, budgeting, working with a nonprofit agency, or conducting a program evaluation, the
Harvard Institute brings new business skills to the social service profession. At the same time they
develop the business professionals’ skills in interpersonal helping, group dynamics, an understanding of
social policy, and current social problems. Combined groups of Human Services and Business
professionals tackle real life problems using a combination of skills that each discipline possesses. Role
plays are sometimes used but a common thread in the development of these leadership skills for both
human services and business students is the service-learning opportunity. This enables the student or
professional to visit an agency and put into practice the knowledge, values, and skills they have learned to
assist the program in some way.
LITERATURE REVIEW
Engaging Students in Service Learning
The literature review reveals that service learning programs foster student engagement within the
community and promote leadership, social, and civic responsibility. Several studies have presented their
findings regarding the engagement of students in these activities. Experiential education and service
learning activities is an area which can easily complement the traditional business classes, by enhancing
business students’ learning outcomes (Manring, 2004). Specifically, these engagement activities would
include service learning projects embedded within courses while providing community service
opportunities and leadership training for the class. These activities would enhance the learning and allow
students to apply what they have learned in the classroom to a real life situation. An evaluation of the
activity would occur in the classroom at another time, giving students the opportunity to learn a concept,
practice it, and then evaluate the outcome. This type of learning is seen as beneficial at all levels of higher
education.
The development of university and community partnerships has been studied indicating that service
learning and internships allow students the opportunity to link theory to practice at both the micro and
macro level. Students receive invaluable community practice opportunities and when universities and
communities work together, they have the necessary resources to enable residents to strengthen the
capacity for control over their lives. In two separate university projects in the state of Georgia, students
from various disciplines were actively engaged in sharing the knowledge they learned in the classroom
with residents of their community. (Brown and Kinsella, 2006)
Brown and Kinsella talk about two separate Service Learning Projects which were developed in
Georgia with a focus on university and community partnerships. In one project, a neighborhood family
support center was established in a disadvantaged neighborhood near the University of Georgia in Athens.
Approximately 163 residents who were African American, Latino, or Anglo shared a resource center that
provided English classes, day care, parenting classes, legal assistance, case management, needs
assessments, counseling, as well as social activities for the children and adults in an attempt to develop a
37
cohesive neighborhood. The goal was for people to benefit from locating resources, and to meet and
sustain good relationships with their neighbors in an effort to become empowered to maintain a healthy
and vibrant neighborhood by working together with other residents. Students from a variety of disciples
were recruited to use their expertise in working with the residents, assist with the creation of the center,
complete the landscaping, develop a playground for the children who attended the after school program,
teach the children in the day care center, translate both the English and Spanish languages for the
immigrant families who lived nearby, help with issues like family budgeting, tax preparation, or banking,
and finally to assist with the legal aspect of citizenship for many of the families. The Center was an
ongoing project coordinated by the School of Social Work with other university faculty, students, and
community resources collaborating for a number of years to benefit both the residents of the community
as well as the students who completed volunteer and service learning activities at the center. A number of
project grants enabled the continued development of the program for 8 years, after which the Center was
incorporated as a local Boys and Girls Club. Successful outcomes for the residents included a more
engaged and safer community with parental involvement in school and educational activities for their
children. English as a second language was useful for immigrants who needed the skills to obtain jobs and
acquire citizenship. Local gangs were deterred from entering the neighborhood since parent, community
and university cohesion was strong. The occurrence of crime decreased and the availability of local
resources was beneficial to the residents who were not aware of all the community services. Outcomes for
the university students included learning about a variety of community development models, learning
about and using advocacy models, assisting in the development of cultural diversity curricula and then
teaching residents the program, facilitating groups, and using business accounting techniques with the
residents like tax preparation, budgeting, and maintaining a check book. Student assessment methods
included observation of students by a faculty member, writing assignments that focus on theories used in
practice, evaluating peers in their teams, conducting research projects, reviewing service learning
journals, and obtaining resident feedback about student contact.
A second project at another public institution, Georgia Southern University, also involved a
partnership with the university and several rural counties surrounding the school. As a result of an
increasing Latino population in southeast Georgia due to agricultural needs, services were seen as vital for
this population. A Latino Outreach Center was developed with the goal of the partnership to increase
practice on the individual, family, and community level with the Latino population. Academic and social
supports for the children were seen as essential since many of the children did not speak English and
could not participate in school assignments. English as a second language was seen as imperative for the
families and seminars on work permits and immigration law was also necessary. Community support was
needed as well since businesses and local residents were not knowledgeable about Hispanic culture,
language or customs. The Center for Latino Outreach and Research Services was developed and included
faculty from such disciplines as political science, sociology, social services, business, education, nursing,
and dental hygiene. Many grants were received to continue providing basic services like English classes,
tutoring for the children, an after-school program and summer camp, immigration and legal services,
referrals to local resources for food, clothing, or housing, banking information, and other socialization
programs for the families. The community was provided with interpretation services and information on
the Hispanic culture. Businesses were informed as to immigration law and worker permits so they were in
compliance with federal and state policies. Student learning outcomes included increased knowledge of
cultural diversity, community problem solving, better skills in observing, interviewing, and researching,
and increased empathy and knowledge regarding social issues. Assessment techniques included reflective
journaling, writing assignments, and observations by faculty members.
In other service-learning projects, students used their skills to think and work globally. A program
called Project Ulysses was launched by PricewaterhouseCoopers to explicitly link leadership
development to global community development and channel the resulting learning back to the
organization to assist in strategic management. Using an integrated service-learning program, small teams
were sent to developing countries to apply their business expertise to complex social and economic
challenges. The cross-cultural PricewaterhouseCoopers teams worked on a pro-bono basis in field
38
assignments for eight weeks with Non Government Organizations, community-based organizations and
intergovernmental agencies where communities were facing the effects of poverty, political conflict and
environmental devastation. Some of the learning outcomes indicated that cultural differences should be an
enabler, not an inhibitor; team collaboration will bring success; and leadership is about building sustained
relationships.(Pless, Maak, & Stahl, 2011a) After interviewing 70 of the participants about their
experiences of living and working abroad, a learning narrative was produced which highlighted five key
areas. This evaluation of the service-learning project revealed that learning occurred in ethical literacy,
cultural intelligence, global mind-set, self-development, and community building. A post-program survey
was sent to the participants and later confirmed that the project had the long term effect of developing and
enhancing these five competencies which are seen as necessary for global leadership. International
service-learning is recommended in this study as a valuable tool in developing global leaders.
There have been many successful collaborations between business students and service-learning
projects which involved non-profit, human services agencies. In one project, business communication
students used their skills to incorporate Facebook and Twitter into the non-profit’s communication
profile. They improved the public image and visibility of the agency, allowing people to donate to the
non-profit’s fundraising campaigns as well as promote their annual activities. The students marketed a
new Facebook slogan for the organization and encouraged people to donate to several of their events
bringing a visibility to the nonprofit that had not existed beforehand. Outcomes for the students included
learning how to think critically, write more concisely, and to use social media in a constructive and
socially responsible way. They also learned about the agency’s mission statement, history, and purpose
of their service. (Crews and Stitt-Gohdes, Wanda, L. 2012)
In some projects human services professionals have worked with business students as they interned
with non-profit agencies and learned about Board of Trustee governance, developed leadership skills, and
an understanding of the value of community service. (Purdy and Lawless, 2012) This study discusses how
a course in Board Governance combines an internship with a non-profit organization to create a servicelearning activity. Students learn about community needs, social responsibility, and how working with
other disciplines can produce unique results. The community also benefits because students now
recognize the value of service and leadership.
SOCIAL ENTREPRENEURSHIPS AND MICRO-ENTERPRISES
Micro-enterprises have also become increasingly important in social development and have helped to
alleviate some poverty in developing countries. This concept can be utilized in business classes to teach
both financial and non-financial issues to students as they embark on a humanitarian service-learning
activity. The value of stimulating entrepreneurs and the impact this has on student learning has been
discussed in several papers. (Mungaray et. al., 2007) Students can participate as a class in making a loan
to a small enterprise in a developing country. For as little as $25 a class can make an investment in a
micro-enterprise and learn about models of finance. As the class continues, the students can get updates
on how their company is doing. Within time, they may even see their money repaid and the fruits of their
labor realized in the continuation of an enterprise in a developing country. Many micro-enterprises in
developing countries can be accessed online for further research.
Along these same lines, service-learning can be used to teach sustainable development. (Brower,
2011) Students may spend time actually studying abroad or in a local indigenous community where they
experience poverty, malnutrition, education that lacks resources, and other social problems. In her study,
Holly Brower, took 2 faculty members and 8 students to such a community in an undeveloped country
and spent one month studying the issues and then worked with her class to develop a plan of sustainable
change. She then developed a framework for a business elective that includes service learning as a
component of change. As an alternative, they may study about the experience of living abroad virtually,
but then learn to apply the same techniques to bring sustainable change to a local indigenous community
without ever leaving their own country.
39
Building upon recent developments in entrepreneurship education, business students can be taught
how to use the same skills they have learned in private entrepreneurship to develop social
entrepreneurship. This will involve learning about three competing and distinct logics. These include
learning about social welfare, the public sector, as well as commercial strategies. In an article by Pache
and Chowdhury (2012) they discuss how students need to create new and innovative hybrid strategies in
the development of social entrepreneurship. Since business students need to address the services that are
necessary for all people, the social entrepreneurship is another avenue for building a business within a
community that may be lacking in such services as affordable housing, job skills training, or health care.
In the article they address the strategy of adapting pedagogical tools to the goal of teaching students how
to combine the three logics successfully.
CONCLUSION
Creating vibrant global economies is a challenge that affects everyone. Using a multidisciplinary
approach and then applying techniques like service learning, and teaching about social entrepreneurship
and micro-enterprises, we will enhance the traditional method of teaching to engage business students in
leadership and solution based approaches that will be necessary if we are to sustain development as we
move forward in the twenty-first century. It is recommended that universities and communities work
together to become partners for the mutual benefit of student learning as well as local and global
community development.
REFERENCES
Bricout, V. (April, 2010). Developing an integrated talent management program. Retrieved from
http://www.exec.gov.nl.ca/exec/hrs/publications/developinganintegratedtalentmanagementprogra
m.pdf
Brower, H. (March, 2011). Sustainable development through service learning: A pedagogical framework
and case example in a third world context. Academy of Management Learning & E ducation, 10
(1), 58-76.
Brown, E. & Kinsella, S. (Fall, 2006). University/community partnerships: Engaging human services and
social work students in service learning. Human Service E ducation, A Journal of the National
Organization for Human Services, 26 (1), 59-73.
Crews, T. & Stitt-Gohdes, W. (March, 2012). Incorporating facebook and twitter in a service-learning
project in a business communication Course, Business Communication Quarterly, 75 (1), 76-79.
Hagan, L. (Sept/Oct, 2012). Fostering experimental learning and service through client projects in
graduate business courses offered online. American Journal of Business E ducation, 5 (5), 623632.
Harvard University (2010). The next generation of human services: Realizing the vision. Retrieved from
http://nstore.accenture.com/public_service/integratedservicedelivery/Accenture_HS_The_Next_G
eneration_of_Human_Services_Realizing_the_Vision.pdf
Manring, S. (April, 2004). Using academic service-learning in a business school curriculum to foster
development of emotional intelligences. Retrieved from
http://www.aacu.org/meetings/pdfs/POE04Manring.pdf
Mungaray, A., Ramirez-Urquidy, M., Texis, M., Ledezma, D., & Ramirez, N. (2007). Promoting learning
in small entrepreneurs and higher education students through service learning programs.
International Journal of Business Research, 7 (3), 10-28.
n.d. (January, 2010). Microsoft and the Corporation for National and Community Service Launch New
Initiative to Promote Student Leadership in the Classroom. Retrieved from
http://www.microsoft.com/en-us/news/press/2010/jan10/01-25STARTPR.aspx
40
Pache, A. & Chowdhury, I. (Sept, 2012). Social entrepreneurs as institutionally embedded entrepreneurs:
Toward a new model of social entrepreneurship education. Academy of Management Learning
and E ducation, 11 (3), 494-510.
Pless, N.M., Maak, T., & Stahl G.K. (2011). Promoting CSR and sustainable development through
service learning programs. Academy of Management Best Paper Proceedings, Montréal.
Pless, N.M., Maak, T., Stahl G.K. (2011a). Developing responsible global leaders through international
service learning programs? The Ulysses experience at PricewaterhouseCoopers. Academy of
Management Learning & E ducation, 10 (2), 237-260.
Purdy, J. & Lawless, J. (Feb, 2012). Learning about governance through nonprofit board service. Journal
of Management E ducation, 36 (1), 33-65.
41
Bayesian Design of Inventory Systems to Minimize Expected Operating Costs
Tapan P Bagchi
KIIT University
Inventory management requires optimal determination of (a) “when to order”, and (b) “how much to
order”. One also needs here two answers—what should be stocked initially, and should one adjust (a)
and (b) as time progresses? This paper uses the Bayesian approach to answer these. It uses the classical
(s, Q) model and a heuristic search in the unstructured decision space. It finds that one can make a
decent start by this approach—and stay the course nearly optimally—while upholding a target service
level and minimizing cost/unit time. Study finds high value in continually updating (a) and (b).
INVENTORY CONTROL THEORY
Inventories are a common insurance against uncertainties impacting most production or service
operations ranging from blood banks (plasma, bags and syringes), auto plants (equipment, parts and
finished vehicles), hospitals (beds, operating theaters, specialists and drugs), book stores (books and
stationeries), supermarkets and stores (household and consumer goods), restaurants (supplies and semifinished recipes), banks (currency, tradable assets, forms, etc.), project sites (labor, equipment and
materials), etc. However, inventories behave characteristically like money placed in a drawer—not
producing any “return”, and even forcing a borrowing cost (Jensen and Bard 2003). On the positive side,
inventories help out in breakdowns or crisis, and generally improve customer service in parts and goods
transactions. A balance here may be struck by optimally determining (a) “when to order”, and (b) “how
much to order”. Uncertainties are particularly high for a new business entering an established market. One
needs here two answers—how much should the organization stock initially, and should it adjust decisions
(a) and (b) as time progresses?
This paper re-visits the Bayesian approach to test its efficacy in answering these two questions.
Much has been researched and reported in the past decades on the optimal way of planning and
managing inventories, recent ideas coming in the form of JIT, Lean Production, and the Theory of
Constraint’s throughput accounting way. Mathematical modeling engaging various types of costs and
management objectives has been the broad approach to help evolve policies and decision guidelines.
Authoritative references here include Prabhu (1965), Silver et al. (1998), Jensen and Bard (2003),
Winston (2003) and several others. Broadly, based on the environment in which inventories are created
and managed, two large classes now exist, namely, the constant or deterministic demand rate condition,
and the stochastic demand condition when demand fluctuates randomly, following some statistical
distribution. As special conditions emerge due to challenges in supply chain management, much scope yet
remains to help maximize the utility of strategic inventories while the external world continues to be
unpredictable.
42
This paper is organized as follows. This section recalls the salient approaches to handle inventories
optimally. Section 2 summarizes the features of the (s, Q) model, an effective approach to minimize costs
as well as sustain customer service when demand is random, but controlled by a stationary distribution.
Section 3 reports inferences drawn from certain computational experiments conducted with this model.
Section 4 introduces the Bayesian approach of continually inferring the true characteristics of demand,
and the gradual reduction of uncertainty about the true demand. Section 5 incorporates Bayesian learning
into the challenge of keeping the operating values of the decision parameters s, the reorder point, and Q,
the order quantity near optimal. This would keep the total expected inventory management cost minimum
as time progresses. Section 6 lists the conclusions.
IDEALIZATION OF PRODUCT OR SERVICE DEMAND
Inventory modeling, now incorporated into the broad collection of mathematical methods to apply
scientific approaches to decision making in stock management, attempts to idealize several aspects of the
reality of stocking materials, parts and goods—to make the solution tractable. Simplifications are done,
for instance, when one assumes that demand is constant and deterministic. The other extreme is when not
only it is random, but even nonstationary (Graves 1999). To produce tractable solutions a large collection
of approaches have been proposed (Silver 1981, Winston 2003). This body of knowledge may be divided
into the nature of the demand (deterministic and stochastic), the decision period, the nature of the product
involved, as well as other aspects. For the purpose at hand, demand is assumed to be stochastic,
continuing indefinitely over multiple periods. But broadly, analysis has been split into two classes based
on the nature of demand fluctuation as follows.
Deterministic Demand Condition
One way to deal with the chaotic behavior of market demand is to take the first stab—assume that
products are demanded at a uniform (constant, = a) rate as time progresses. Indeed this was the basis for
developing perhaps the first quantitative representation of the inventory manager’s decision space,
leading to the celebrated EOQ model of inventories. The object here was to set up cost models
incorporating the two earlier stated questions (a) and (b)—when to order new stock, and how much to
order—to sustain the business. Ordering cost, Setup cost, product cost, holding cost, shortage (back order)
cost, etc. were identified as the relevant constituents, leading to the optimal (minimum cost) value for the
order quantity Q. This optimal order quantity is called the Economic Order Quantity (EOQ) as it helps
minimize the total cost comprising the setup cost, product cost and holding cost. The correct time between
the placement of orders here is Q/a, which avoids excess inventory piling up or stock outs due to late
receipts. By far, devised some 70 years back, the EOQ model remains the backbone of many “modern”
inventory management systems and ERP packages, even if it is known that demand itself is rarely
constant—it fluctuates with time, seen frequently to follow the Poisson or other similar distribution
(Tersine 1994).
Stochastic Demand Condition
When uncertainty dominates demand conditions, it becomes difficult to determine how much to order
and when to order, so as to keep customer service level sufficiently high while also minimizing the total
expected operating cost per unit time. When the quantity ordered is too small, one may lose sales. On the
other hand, if the order size is too high, sold quantities many not consume the stock completely and the
excess may remain for considerable time tying up working capital, space, etc. and entailing housekeeping,
insurance, etc. Researchers have addressed this situation using probabilities. Thus several well-formulated
models and their solutions have been developed to address what we call the stochastic demand case.
Prominent are the single period stochastic model, the (s, S) model, and the (s, Q) model, descriptions
being given in Silver et al. (1998), Jensen and Bard (2003) and Winston (2003).
It is argued by Murray and Silver (1966) that initially one would have a great uncertainty concerning
the sales potential of an item but would have the opportunity to develop a better feel for this uncertainty
43
as actual sales become known. Learning, in the decision theoretic sense, is the process of basing one’s
initial decisions on an informed or inspired guess to start one’s business, and subsequently updating that
initial guess by some rational logic—to assure optimality of future decisions. Various approaches have
been proposed to assist one in structured learning, good examples being the construction of econometric
models, Bayesian models in management science, and Neural Nets. Econometric models generally use
historical data to produce statistical estimates of such quantities as product or service demand, while
neural networks use a training-validation-testing approach to help learning to occur about the future
possible course of a datum of interest (here demand).
The Bayesian approach of learning or adaptation to help develop a better sales forecast appears to
have been used first by Murray and Silver (1966). They used Bayes’ Rule to adaptively change the
distribution of sales and Dynamic Programming to show how decisions may be thus improved. Other
studies that have used adaptation-aimed learning in inventory design/operation problems include Sharma
et al. (2001), Huh et al. (2009), Huh et al. (2010), and others. Few however have directly addressed the
assessment of the potential benefits of Bayesian adaptation/learning of the stochastic demand condition.
The exception appears to be the work of Azoury and Miller (1994), who provide a comparison of the
optimal ordering levels of Bayesian and Non-Bayesian n-period nondepletive inventory models. They
show that the quantity ordered under the non-Bayesian policy would be greater than or equal to that under
a Bayesian policy. Aside from such applications of learning in managing inventories better, Bayesian
methods have been used also to design queuing systems with initially unknown demand (see Bagchi and
Cunningham (1972) and Morales et al. (2005) who utilized posterior probabilities of arrivals with the
assumption of stationarity of the distribution imposed). For the present study we propose the question,
Can the Bayesian learning logic (prior  prior + data  posterior) of observing and updating
stochastic information help reduce the total expected cost for operating an inventory management
system?
As detected by Azoury and Miller (1994) for the n-period nondepletive inventory model, we
anticipate that for the popular (s, Q) policy, the Bayesian approach would let one see how the successive
incorporation of new data would improve decisions (reduce the total expect cost (EC) and/or improve
service level) as Q* and s* are continually updated with accumulating demand data. Besides, one would
also like ask: up to what point such updating would be meaningful? We expect that that answer may
depend on the estimated unknown but stationary demand rate for that might require meeting certain
minimum sample size. How long should one sample demand (X) might depend on the cost of the effect of
using non-optimal rather than a near-optimal EC (see Levi et al. 2007). We shall not probe this here.
To study these we use a well-developed stochastic demand inventory model from the literature—the
(s, Q) model. This model incorporates safety stock into the reorder stock level (s) and uses an optimum
constant quantity Q to size release of an order every time the current stock level touches or falls below s.
The optimum combination of s and Q minimizes the total expected inventory operating cost per unit time
(Silver 2007).
THE (s, Q) INVENTORY MODEL
This section is based on the material in Chapter 25 of Jensen and Bard (2003) as it aims to recall the
essential and relevant relationships among inventory quantity z, the decision variables s and Q, and costs,
to help proceed to the analysis that follows in the rest of this paper. In the present case we assume that
only a single item is being stocked and sold whose inventory is to be managed to keep the expected total
cost minimum, the total cost comprising holding, replenishment and stock out costs. Winston (2003) also
discusses this case.
Ordering too much or too little or at the wrong time can disrupt the optimal control of inventory, an
event easily caused by uncertainty or randomness in demand. In such cases the deterministic approach
clearly does not minimize the expected total cost.
44
At some instant of time if inventory level is z, then the probability of shortage (Ps), the probability of
excess (Pe), the expected shortage (Es ) and expected excess (Ee ) are, respectively,
Ps = P[ x > z ] = 1 − F ( z )
Pe = P[ x ≤ z ] = F ( z )
∞
E s = ∫ ( z − x) f ( x)dx ( for continuous demand x)
z
∞
E s = ∑ ( x − z ) P( x) ( for discrete demand x), and
z
Ee = z − µ + E s
The (s, Q) inventory management policy is adopted in the present paper to serve as the test bed to
probe our research question. In this case demand is stochastic. This policy first determines the optimum
values (s* and Q*) for the reorder point (s) and the order quantity (Q) and then monitors the level of
inventory continuously through the repeated execution of order cycles. An order of size Q* is placed the
moment the current inventory level z touches s*. The order (quantity = Q* ) is received after lead time L
and it immediately replenishes the stock.
The optimum parameters s* and Q* are found as follows. When L is small compared to the expected
time required to exhaust Q, only 1 order would be outstanding. (In practice a plant may place multiple
orders on a vendor when expediting becomes ineffective, but we do not consider this case here.) An order
cycle here is the time between two successive order receipts. If a and L respectively represent the average
demand rate and lead time, then the mean demand during lead time is μ = aL. The reorder point being s,
Ps is 1 – F(s), and the system’s service level (fraction of demand during lead time that is met) is 1 – Ps =
F(s). The safety stock (excess stock beyond μ) will thus be SS = s – μ. The general solution for the (s, Q)
policy for this situation has been given by Jensen and Bard (2003) as follows.
If the per SKU unit holding cost is h per unit time, then

Q
+ s − µ

a
Expected holding cost/unit time = h
The time between orders is a random variable with mean of Q/a. If the cost of replenishment per
order (or the order cost) is K then the expected replenishment cost/unit time is
Expected replenishment cost/unit time = (Ka/Q)
If the expected shortage cost per order cycle is Cs, then the expected shortage cost/unit time will be
Cs/(Q/a) = Csa/Q. The general model for the expected total cost/unit time for the (s, Q) policy will be
 Ka a
Q
EC ( s, Q) = h + s − µ  +
+ Cs
 Q Q
a
(1)
Equation (1) gives the general expression for the expected total cost/unit time for an inventory system
being operated by the (s, Q) policy. In order to optimize it we may utilize the two decision variables—s,
the reorder point, and Q, the quantity ordered in each order cycle. Analytically, (1) may be partially
differentiated with respect to s and Q and the derivatives equated to zero. Doing this yields two conditions
that simultaneously characterize the two optimal values Q* and s*. These conditions are
45
2a ( K + C s
h
Q* =
(2)
and
∂C s
hQ
=−
∂s
a
(3)
Peterson and Silver (1979) have enlisted several special cases for obtaining the optimal values Q* and
s . The first case assumes that a constant cost π1 is expended whenever a stock out event occurs. This
assumption gives us a quick way to evaluate Cs—the expected shortage cost/order cycle. This is
*
∞
C s = π 1 P[ x > s ] = π 1 ∫ f ( x)dx = π 1 [1 − F ( s )]
(4)
s
Equation (3) may be now utilized since we have Cs expressed in (4) as a function of s. Thus
∂C s
hQ
= −π 1 f ( s * ) = −
∂s
a
(5)
which gives
f (s * ) =
with
hQ
π 1a
C s = π 1 (1 − F ( s * )
(6)
(7)
Equation (6) helps link s* with Q* via (2).
Note here that seeking a solution to the (s, Q) policy problem by simultaneously solving (2), (6) and
(7) for arbitrary demand distribution F(s) is not trivial.
A variant of the constant cost π1 per stock out event is a cost π2 incurred for every unit short in a stock
out. Then the expected shortage cost/order cycle will be dependent on how many units are expected to be
shorted in each order cycle (Es). Here,
∞
E s = ∫ ( x − s ) f ( x)dx
s
and therefore C s = π 2 E s . This gives
∞
∂C s
= −π 2 ∫ f ( x)dx = −π 2 (1 − F ( s ))
∂s
s
Combining (3) and (8) one obtains
∂C s
hQ
= −π 2 (1 − F ( s )) = −
∂s
a
46
(8)
which for a specified order quantity Q gives the condition for the optimal reorder point s* as follows.
F (s * ) = 1 −
hQ
π 2a
(9)
The optimum decision (s*, Q*) is the combination of s and Q that minimizes EC given by (1).
VALIDATION OF THE HEURISTIC METHOD OF MINIMIZING EC(s, Q) BY
MANIPULATING s AND Q
The Expected Total Cost/unit time (EC) of operating the inventory system given by (1) is a non-linear
function of the two decision variables s and Q. To optimize (minimize) EC Jensen and Bard (2003) use an
iterative procedure (Example 13, Jensen and Bard, 2003). We use this example, which uses a cost π2
incurred for every unit short in a stock out to compare a heuristic method that Solver® in Excel 2007 uses
with the Jensen-Bard iterative procedure. (We made a typographic correction in the Jensen-Bard text. In
Example 13 Density φ(.) was changed to CDF Φ(.), to be consistent with Equation 43 in Jensen-Bard.)
This example uses the following cost and demand data: Lead time L = 1 week = 0.25 month, Monthly
demand a = 100 units/month, normally distributed with variance = 400, giving lead time demand ~ N(25,
102); Holding cost h = $10/unit-month; Cost expected for every unit short in a stock out event π2 = $200
per unit backordered; and Order cost K = $800. Note that in this example, mean demand during lead time
μ = a/4 = 25 and the standard deviation of demand during lead time σ = 10.
To find optimal Q* and s* together, Jensen and Bard used an iterative procedure that initially assumed
Cs = 0 and then successively found Q, s and the next Cs, and then repeated this till Q and s appeared
converged. The answers after three iterations were Q* = 130.9 and s* = 40.1. The present work used the
Solver analysis option built in Excel® (Solver 2012). A computational Add-in to Excel®, Solver uses a
hybrid of classical, metaheuristic and evolutionary algorithms to produce near-optimal solutions. The
answers reached by Solver were Q* = 127.48 and s* = 40.34. With this being a satisfactory validation of
the Solver-based approach to optimize (s, Q), we used Solver rather than iteration in this work. In
computations we used Equation (2) for Q*, Φ(ks) = 1 – hQ/(a π2), and Cs = π2 σ [φ(ks) - ks{1 – Φ(ks)}].
The factor ks determines the service level, and the optimal reorder point by the relationship s* = μ + ks σ.
PRELIMINARY INFERENCES FROM COMPUTATIONAL EXPERIMENTS WITH (s, Q)
In order to prepare now for investigating whether the Bayesian approach would let one see how the
successive incorporation of new data would improve decisions (reduce the total expect cost (EC) or
improve service level) as Q* and s* are continually updated, we set up the following machinery:
Owing to the non-linear and complex nature of the expressions (1) through (9) we used an orthogonal
array experimental computational framework to first determine the sensitivity of the two performances
(responses)--% service level and total expected cost. For this we selected two working levels for each of
the factors—monthly demand (a), holding cost (h), shortage cost (π1) and order cost (K) as shown in
Table 1, and a L8 array (Montgomery 2008). Table 1 and Figures 1 and 2 show the results. The following
inferences may be drawn:
• Optimal Order Quantity Q* is responsive to a, h and K, but only mildly to shortage cost π1.
• Service level seems to be robust relative to most factors considered in the region of the cost
parameters studied. It is closely related to the setting of the reorder point s*.
• Total Expected Cost/unit time is relatively robust with respect to shortage cost per stock out event
π1, but sensitive to a, h and K.
These deductions—typically unavailable to the inventory manager—suggest that it would be wise to
spend effort in optimally setting the reorder point s* and order quantity Q* before one sets out to declare
47
the operational policies of an inventory system to cope with stochastic demand. In one sense, this
information is similar to the relative robustness of the total operating cost/unit time to EOQ for a
deterministic inventory system. Limited generalization of such deductions may be attempted in a given
cost-demand scenario to assess how accurately the parameters a, h, K and π1 need to be estimated, to
assure minimum cost operation of the inventory system. In this study we focus on the factor with perhaps
the highest uncertainty—the stochastic nature of X, the demand per unit time.
TABLE 1
AN L8 COMPUTATIONAL EXPERIMENT TO UNCOVER THE SENSITIVITY OF SERVICE
LEVEL AND TOTAL EXPECTED COST OF AN (s, Q) INVENTORY SYSTEM
Orthogonal
Experiment #
1
2
3
4
5
6
7
8
a Units
/month
π1
h
50
50
50
50
100
100
100
100
5
5
10
10
5
5
10
10
K
500
1000
500
1000
500
1000
500
1000
400
800
400
800
800
400
800
400
s*
%Service
Level
Q*
19.25
19.88
18.56
19.25
33.61
36.22
32.51
35.41
91
127.9
64.9
91
181.2
128.4
129.1
91.5
97.2
98.2
95.7
97.2
95.74
98.76
93.35
98.13
Total Expected
Cost/unit time
488.76
676.6
709.93
977.51
949.29
698.3
1366.1
1019.2
FIGURE 1
SENSITIVITY OF OPTIMAL REORDER POINT (s*), ORDER QUANTITY (Q*) TO
MONTHLY DEMAND RATE AND COSTS
Quantity or $
150
Sensitivity of (s, Q) Policy Performance to
Demand Rate and Cost Factors
100
50
0
a = 50
100
h=5
10
π1 =
500
Reorder Point "s"
% Service Level
48
1000
K = 400
Order Quantity "Q"
800
FIGURE 2
SENSITIVITY OF EXPECTED TOTAL COST/UNIT TIME TO
MONTHLY DEMAND RATE AND COSTS
The Demand Distribution
The demand scenario being stochastic, the demand/unit time is a random variable (X), which may be
discrete, or continuous. For calculating safety stocks, the majority of stochastic demand models assume
the demand during lead time to be normally distributed. Whereas Jensen and Bard (2003) have also used
the normal distribution to illustrate the use of the models in determining s and Q in their writing, in the
present work we engage the well-justified Poisson distribution (Tersine 1994) for demand. When
individual demand events occur independently, the demanded quantity being discrete, one may
reasonably assume the underlying distribution to be Poisson. If the average demand rate is a (units of
SKD per unit time), then for any time interval t the expected demand is at, and
P( x) =
(at ) x e − ( at )
x!
P(x) can be approximated by a normal distribution with mean μ = at and standard deviation σ = √𝑎𝑡.
BAYESIAN LEARNING AND INFERENCING
Generally, the data given to the decision maker is obtained from past history; it is not in his control. It
is not possible to design experiments either to obtain this information. Indeed many inventory design
problems involving uncertainty are frequently tackled using historical or subjective data. Though
somewhat bothersome for practitioners, Bayesian inferencing of such uncertainty would be specially
suited when learning is expected to be taken advantage of to aid the system to improve its performance,
because in such learning the existing or prior knowledge can be updated as new data is accumulated,
yielding posterior inferences. Unless the situation is dynamic that must be adapted to to sustain
optimality, the assumption of stationarity is generally made to keep the analysis straightforward (Graves
1999). In the present case also we assume stationarity; specifically, the parameters that control the
distribution of demand are assumed to be unknown, but stationary.
49
Since the Bayesian learning logic (prior  prior + data  posterior) follows the path of presupposing information, observing the phenomena and then repeatedly updating stochastic information, it
is important here to select an appropriate subjective probability function for the “prior”. Indeed it is often
difficult to find a suitable family of prior distributions that would help one to capture the decision maker’s
subjective belief, and also be algebraically workable to produce the “posterior” as new data is received. In
theory this is done by deriving the posterior density from the likelihood function and the prior density,
and deriving the distribution of the reduced-form parameters from the initial information on the unknown
parameters controlling the stochastic process (here the random occurrence of demand).
For the present case, therefore, demand is being assumed to be random, Poisson distributed with an
unknown parameter (average rate) λ/unit time. This assumption has two advantages: First, the Poisson
distribution is often quite realistic when the quantities demanded are random and independent of earlier
and future demands. Secondly, from analytical point of view, the Bayesian prior-posterior conjugate
family (Raiffa and Schlaifer 1961) of the distribution of the possible values of λ is Gamma, a twoparameter distribution that is convenient to update. However, we note that this is not a major restriction—
Bayesian inference may be performed using stochastic simulation of the process also (Morales et al.
2005).
The Bayesian Learning Framework
Poisson being the assumed distribution controlling demand with an unknown stationary rate λ/unit
time, we will treat this uncertainty as a prior probability distribution, to be updated as a posterior
distribution on the basis of new demand data as observed. The conjugate prior distribution for the Poisson
rate parameter is the Gamma distribution with two parameters α and β, the density function being
β α α −1 − βx
Gamma( x) =
x e , x ≥ 0, α > 0, β > 0
Γ(α )
∞
∫
where Γ(α ) = t α −1e −t dt .
0
In Bayesian statistics, the Gamma distribution is used as a conjugate prior (Raiffa and Schlaifer 1961)
distribution for various types of rate parameters, such as the λ of an exponential distribution or a Poisson
distribution. The Gamma distribution has a mean of α/β, variance α/β2 and it is known to be flexible in
shape. The interpretation is as follows: There are α total occurrences in β time intervals. Updating the
Gamma prior is straightforward. For instance, if r quantities are demanded from the inventory in a time
period of length t, the posterior density of λ will be a Gamma distribution with α’ = α + r and β’ = β + t.
The maximum likelihood estimated of λ is obtained from the posterior mean
E (λ ) =
α +r
β +t
This posterior mean E(λ) approaches λ MLE in the limit as α  0 and β  0. In the present application
our intention will be to start with some reasonably assumed prior value of Poisson demand rate λ (= α/β)
and then continually update it using r (the demand observed in the time span t) as time t progresses.
The Bayesian approach to updating modeling parameters, such as the random demand that an
inventory should be capable of satisfying, gives us a way around a special decision problem. In many
such cases the object is to make the best decision on the basis of a given set of data (Lancaster 2004). This
data may be available from past history, or it may be produced by conducting some special statistical
experiments. What if there is no such history available, or there is no opportunity to conduct the desired
experiments? As said above, the Bayesian approach begins with an assumed prior about the decision
environment, and then by using a learning logic (prior  prior + data  posterior) follows the path of
pre-supposing information, observes the phenomena and then repeatedly updates the information at hand
(see Brown and Rogers 1972, Aronis et al. 2004, Morales et al. 2005).
50
FIGURE 3
TRACE OF CONTINUALLY UPDATED POSTERIOR MEAN ESTIMATES PRODUCED BY
SUCCESSION OF SAMPLES DRAWN FROM A SIMULATED POISSON DISTRIBUTION
WITH λ = 100
Simulated Posterior Poisson Mean
Demand, True λ = 100/month
Prior assumed to be Gamma(5,1)
120.00
100.00
80.00
60.00
40.00
20.00
1
6
11
16
21
26
31
36
41
46
51
56
61
66
71
76
81
86
91
96
0.00
Mean estimated
95% upper limit
95% lower limit
Figure 3 and Table 2 display the effect of updating the maximum likelihood estimate of the mean
demand of a Poisson distribution. In this case a Poisson demand process with true mean demand (λ) of
100 units/month was observed (simulated) in succession of months 1, 2, 3, … etc. and the estimates of the
posterior along with the ±95% limits of this estimate was calculated. The prior of λ was assumed to be a
Gamma(α = 5, β = 1) distribution with an average of 5 units/month. The simulated monthly demands are
shown in the second column (ki) of Table 2. Continual updating of the estimated value of λ produced a
95% confidence band for λ as (96.81, 100.77) after 100 updates. Clearly, another assumed value of the
prior would produce another trace of estimates. But it can be assured based on the standard deviation of
the estimated λ that they would all eventually converge toward the true demand as time t increases.
REGULAR BAYESIAN UPDATES OF DEMAND RATE HELP KEEP TOTAL EXPECTED
COST NEAR MINIMUM
It is clear from the foregoing section that when demand is unknown and stochastic, the original
assumption about demand shifts gradually toward the true demand when the estimate of the true demand
is suitably updated. One method for accomplishing this would be to incorporate Bayesian learning. This
section adds in Bayesian learning into the (s, Q) policy to help evaluate the utility of doing this. Such
learning would help in moving the operating values of the two decision parameters—s, the reorder point,
and Q, the order quantity—closer to their optimal values as time advances and new demand data become
known. For effectively using the (s, Q) policy the motivation for continually adjusting s and Q therefore
would be to keep the total expected inventory management cost near its minimum throughout the period
for which the inventory is maintained and managed.
51
TABLE 2
100 POISSON RANDOM VALUES SIMULATED WITH λ = 100. ASSUMING A PRIOR AS A
GAMMA(α = 5, β = 1) DISTRIBUTION, WE COMPUTE MEAN OF THE GAMMA POSTERIOR
DISTRIBUTIONS AS MONTHLY DEMAND IS SUCCESSIVELY OBSERVED
Month #
i
Month 1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
52
Observed
Monthly
Demand
ki
111
111
92
104
102
98
103
92
100
99
90
95
103
108
91
94
109
92
102
95
96
101
116
110
112
88
97
96
105
99
89
111
102
85
97
111
109
108
113
100
99
109
98
83
103
92
98
96
109
109
λ = Mean of Gamma
For Posterior
Gamma (α, β):
Sum ki
111
222
314
418
520
618
721
813
913
1012
1102
1197
1300
1408
1499
1593
1702
1794
1896
1991
2087
2188
2304
2414
2526
2614
2711
2807
2912
3011
3100
3211
3313
3398
3495
3606
3715
3823
3936
4036
4135
4244
4342
4425
4528
4620
4718
4814
4923
5032
α = α + sum ki
116
227
319
423
525
623
726
818
918
1017
1107
1202
1305
1413
1504
1598
1707
1799
1901
1996
2092
2193
2309
2419
2531
2619
2716
2812
2917
3016
3105
3216
3318
3403
3500
3611
3720
3828
3941
4041
4140
4249
4347
4430
4533
4625
4723
4819
4928
5037
Posterior
β=β+n
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
λ estimate = α/β
58.00
75.67
79.75
84.60
87.50
89.00
90.75
90.89
91.80
92.45
92.25
92.40
93.21
94.20
94.00
94.00
94.83
94.68
95.05
95.05
95.09
95.35
96.21
96.76
97.35
97.00
97.00
96.97
97.23
97.29
97.03
97.45
97.59
97.23
97.22
97.59
97.89
98.15
98.53
98.56
98.57
98.81
98.80
98.44
98.54
98.40
98.40
98.35
98.56
98.76
SD =
SQRT(α/β2)
SD (λ est)
5.39
5.02
4.47
4.11
3.82
3.57
3.37
3.18
3.03
2.90
2.77
2.67
2.58
2.51
2.42
2.35
2.30
2.23
2.18
2.13
2.08
2.04
2.00
1.97
1.93
1.90
1.86
1.83
1.80
1.77
1.74
1.72
1.69
1.67
1.64
1.62
1.61
1.59
1.57
1.55
1.53
1.52
1.50
1.48
1.46
1.45
1.43
1.42
1.40
1.39
Upper/Lower
estimates of λ
+95%
68.77
85.71
88.68
92.83
95.14
96.13
97.49
97.24
97.86
98.25
97.80
97.80
98.37
99.21
98.85
98.70
99.42
99.15
99.41
99.30
99.25
99.42
100.21
100.69
101.22
100.79
100.72
100.62
100.83
100.83
100.51
100.89
100.98
100.56
100.51
100.84
101.10
101.33
101.66
101.66
101.64
101.85
101.79
101.40
101.47
101.30
101.26
101.18
101.37
101.55
-95%
47.23
65.62
70.82
76.37
79.86
81.87
84.01
84.53
85.74
86.66
86.70
87.13
88.05
89.19
89.15
89.30
90.24
90.22
90.69
90.79
90.93
91.28
92.20
92.83
93.48
93.21
93.28
93.31
93.63
93.75
93.55
94.02
94.20
93.90
93.94
94.35
94.68
94.98
95.39
95.46
95.51
95.78
95.80
95.49
95.62
95.51
95.53
95.51
95.75
95.98
TABLE 2 (CONTD.)
100 POISSON RANDOM VALUES SIMULATED WITH λ = 100. ASSUMING A PRIOR AS A
GAMMA(α = 5, β = 1) DISTRIBUTION, WE COMPUTE MEAN OF THE GAMMA POSTERIOR
DISTRIBUTIONS AS MONTHLY DEMAND IS SUCCESSIVELY OBSERVED
Month
#
Observed
Monthly
Demand
i
ki
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
93
86
96
92
93
93
116
103
105
105
85
95
109
108
81
94
91
92
93
120
107
104
105
87
89
94
91
115
95
98
96
104
93
112
106
101
96
100
98
105
119
92
106
99
99
111
88
103
88
90
For Posterior
Gamma (α, β):
Sum ki
5125
5211
5307
5399
5492
5585
5701
5804
5909
6014
6099
6194
6303
6411
6492
6586
6677
6769
6862
6982
7089
7193
7298
7385
7474
7568
7659
7774
7869
7967
8063
8167
8260
8372
8478
8579
8675
8775
8873
8978
9097
9189
9295
9394
9493
9604
9692
9795
9883
9973
α = α + sum ki
5130
5216
5312
5404
5497
5590
5706
5809
5914
6019
6104
6199
6308
6416
6497
6591
6682
6774
6867
6987
7094
7198
7303
7390
7479
7573
7664
7779
7874
7972
8068
8172
8265
8377
8483
8584
8680
8780
8878
8983
9102
9194
9300
9399
9498
9609
9697
9800
9888
9978
β=β+n
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
λ = Mean of
Gamma Posterior
λ estimate = α/β
98.65
98.42
98.37
98.25
98.16
98.07
98.38
98.46
98.57
98.67
98.45
98.40
98.56
98.71
98.44
98.37
98.26
98.17
98.10
98.41
98.53
98.60
98.69
98.53
98.41
98.35
98.26
98.47
98.43
98.42
98.39
98.46
98.39
98.55
98.64
98.67
98.64
98.65
98.64
98.71
98.93
98.86
98.94
98.94
98.94
99.06
98.95
98.99
98.88
98.79
SD =
SQRT(α/β2)
SD (λ est)
1.38
1.36
1.35
1.34
1.32
1.31
1.30
1.29
1.28
1.27
1.26
1.25
1.24
1.23
1.22
1.21
1.20
1.19
1.18
1.18
1.17
1.16
1.15
1.15
1.14
1.13
1.12
1.12
1.11
1.10
1.10
1.09
1.08
1.08
1.07
1.06
1.06
1.05
1.05
1.04
1.04
1.03
1.03
1.02
1.02
1.01
1.00
1.00
0.99
0.99
Upper/Lower
estimates of λ
+95%
101.41
101.14
101.07
100.93
100.81
100.69
100.98
101.04
101.13
101.22
100.97
100.90
101.04
101.17
100.88
100.80
100.67
100.56
100.47
100.76
100.87
100.93
101.00
100.83
100.68
100.61
100.50
100.70
100.64
100.62
100.58
100.64
100.56
100.71
100.78
100.80
100.75
100.76
100.74
100.80
101.01
100.92
100.99
100.98
100.97
101.08
100.96
100.99
100.87
100.77
-95%
95.90
95.69
95.67
95.58
95.51
95.45
95.77
95.87
96.00
96.13
95.93
95.90
96.08
96.24
96.00
95.95
95.86
95.79
95.73
96.05
96.19
96.28
96.38
96.24
96.13
96.09
96.01
96.24
96.21
96.22
96.20
96.28
96.23
96.40
96.50
96.54
96.52
96.55
96.55
96.63
96.86
96.80
96.88
96.90
96.91
97.04
96.94
96.99
96.89
96.81
53
One way to operate the (s, Q) inventory policy when demand is stochastic is to be myopic (Levy et al.
2007) when one sets the operating values of s and Q at some initial (prior) guess for the demand rate λ, or
perhaps collects only a limited amount of demand data and then estimates λ. Such trust on an initial guess
for λ and not changing it later may even be favored, for this may save the added effort needed to
incorporate any emergent evidence about true demand as the business moves forward and one becomes
busy. Many practitioners indeed do not change the initial assumption about a or λ or even costs, though
Azoury and Miller (1994) have amply highlighted the effect of not utilizing emerging information—by
comparing Bayesian and non-Bayesian methodologies for it.
Plainly, the s and Q derived using the initial guess for λ would almost surely be suboptimal, except by
accident (Figure 2 indicates the strong dependence of EC on a (hence on λ)). To test any possible merit of
the myopic approach we set the course computationally. Table 3 displays the effect of setting the
unknown demand rate λ at some unsubstantiated value (assuming mistakenly this to be the true demand),
deriving the flawed s* and Q* from it, and incurring the consequent expected total cost EC when the (s, Q)
policy is used. It is straightforward to compare these higher values of EC with the near optimal EC
achievable by getting close to the true demand rate. We show this here by using the Bayesian approach.
The illustration in Table 3 used 100 units/month as the true demand rate whereas the (“wrongly”)
presumed values of λ were set respectively at 25, 50, 75, 150, 200, and 300 units/month. The costs used
were h = $10/unit-month, π1 = $500 per backorder event and K = $800/order placed.
Figures 4 and 5 respectively display the effect of using a flawed (differing from the true) demand
conjecture (“prior”) on the expected total cost (EC), and the service level experienced by customers.
TABLE 3
COSTS AND SERVICE LEVELS EXPERIENCED WHEN s* AND Q* ARE SET BASED ON A
PRIOR ESTIMATED DEMAND, BUT TRUE DEMAND (aT) IS DIFFERENT FROM THE
PRIOR ESTIMATE (a)
a = Estimated demand/month based on a flawed prior guess
25
50
75
100
150
200
300
aT = True demand/month
100
100
100
100
100
100
100
s* = Optimum Reorder Point based on prior
10
18
25
33
47
61
88
Q* = Optimum Order Quantity based on prior
65
91
111
129
158
183
224
Holding Cost based on a and (s*, Q*)
360
510
624
720
883
1019
1248
Holding Cost based on (s*, Q*) but facing True demand
173
385
569
721
989
1269
1748
Replenishment Cost by a and (s*, Q*)
310
438
537
620
759
876
1073
Replenishment Cost based on (s*, Q*) but facing True demand
1239
876
715
620
506
438
358
Shortage Cost by a and (s*, Q*)
13
18
22
26
32
36
45
Shortage Cost based on (s*, Q*) but facing True demand
52
36
21
26
36
18
15
Expected Total Cost by a and (s*, Q*)
683
966
1183
1366
1673
1932
2366
Expected Total Cost based on (s*, Q*) but facing True demand
1464
1297
1305
1366
1531
1725
2121
Service level experienced at True Demand but operating at
(s*, Q*)
98.8
%
97.2
%
95.4
%
93.4
%
88.5
%
82.5
%
59.6
%
54
FIGURE 4
THE EXPECTED TOTAL COST FOR A (s, Q) SYSTEM THAT USES A
FLAWED PRIOR ESTIMATE THAT IS FAR FROM THE TRUE DEMAND VALUE
FIGURE 5
SERVICE LEVEL PROVIDED BY A (s, Q) SYSTEM THAT USES A
FLAWED PRIOR ESTIMATE THAT IS FAR FROM THE TRUE DEMAND VALUE
% Service Level facing True Demand (= 100/month) but using
(s*, Q*) based on Prior λ
100.0%
95.0%
90.0%
Service Level
85.0%
80.0%
75.0%
70.0%
65.0%
60.0%
55.0%
50.0%
Prior
Demand
25/month
50
75
100
150
200
300
55
A review of Table 3 and Figures 4 and 5 would suggest that the results of using Bayesian learning to
keep continually updating the demand estimate provide a mixed message. But a closer look reveals that
the minimum total cost (s, Q) policy should indeed be based on a demand estimate as close to the true
demand as is possible. But Figure 4 appears to suggest that a lower guess for demand actually improves
customer service! Prima facie, therefore, guessing a low value of demand appears to be doing something
good. But such inference is shortsighted and most misleading. More seriously, this is not a defect in the
model or its analysis, rather perhaps in the analyst’s formulation of the problem at hand.
Recall that our objective of setting up the (s, Q) model to help find a rational way to manage
inventories when demand is stochastic included spelling out the objective first—that of minimizing (1),
the expected total cost/unit time. This total cost included three components—the holding cost, the
replenishment cost, and the shortage cost. At least for this model, therefore, maximizing customer service
per se was not the objective. Customer service (F(s)) enters into (1) via Cs (= π1(1 – F(s))), the cost of
short shipment. If one requires the final (s, Q) solution to assure a high level of customer service, one
would need to use a large value for π1. Thus, like any optimization attempted, one would need to be clear
about the objective of the decision maker—where does he want to put priority?
CONCLUSIONS
This study has investigated the value of incorporating Bayesian learning into the popular (s, Q) model
for managing inventories when demand is stochastic. The study finds that one can indeed make a decent
start by the Bayesian approach—and stay the course nearly optimally—while upholding a target service
level by suitably selecting costs and also keeping the expected operating cost/unit time minimum.
Specifically, this study uncovers the high value in continually updating the decisions (a) “when to order”,
and (b) “how much to order”, rather than sticking to the initial guess for the demand average, as is
frequently practiced.
Demand has been assumed to follow a stationary Poisson distribution in this work. The Bayesian
learning process uses the Gamma conjugate family of distributions to incorporate the latest observed
demand data. The learning logic follows the path prior  prior + data  posterior of observing and
updating stochastic information.
Owing to the non-linear and complex nature of the expressions in the (s, Q) model, this work utilized
an orthogonal array experimental framework to determine the sensitivity of the two performances
(responses)--% service level and total expected cost. For this two working levels for each of the factors—
monthly demand (a), holding cost (h), shortage cost (π1) and order cost (K) were selected and a L8 array
was adopted to guide the computations. The following inferences could be drawn:
• Optimal Order Quantity Q* is affected significantly by a, h and K, but only mildly by shortage
cost π1.
• Service level seems to be robust relative to most factors considered in the region of the cost
parameters studied. It is closely related to shortage cost π1 and the setting of the reorder point s*.
• Total Expected Cost/unit time is relatively robust with respect to shortage cost per stock out event
π1, but sensitive to a, h and K.
• A myopic estimate of the true demand rate λ would regularly turn out a suboptimal EC.
These deductions—typically unavailable to the inventory manager—suggest that it would be wise to
spend effort in optimally setting the reorder point s* and order quantity Q* before one sets out to declare
the operational policies to cope with stochastic demand. In a sense, this information is comparable to the
knowledge of relative robustness of the total operating cost/unit time to EOQ for a deterministic
inventory system (see Winston 2003, page 853).
In summary, this study, like the work of Azoury and Miller (1994) conducted for the n-period
nondepletive inventory model, establishes the worth of following the Bayesian approach to update
stochastic information used in the (s, Q) inventory system as new demand data become continually
available. The result is lowering of the total expected cost throughout the time this inventory system is
56
operated. As already shown in the literature in a large number of applications, the Bayesian learning path
prior  prior + data  posterior, it appears, would benefit the design and operation of other similar
stochastic systems as well.
REFERENCES
Aronis, K-P, R Dekker, I Magou and G Tagaras (2004). Inventory Control of Spare Parts using a
Bayesian Approache: A Case Study, European Journal of Operations Research, Vol 154(3), 730739.
Azoury Katy S and Bruce L Miller (1994). A Comparison of the Optimal Ordering Levels of Bayesian
and Non-Bayesian Inventory Models, Management Science.
Bagchi, Tapan P and A A Cunnigham (1972). Bayesian Approach to the Design of Queuing Systems,
INFOR Journal, Vol 10(1).
Brown Jr, G F and W F Rogers (1973). A Bayesian approach to demand estimation and inventory
provisioning, Naval Research Logistics Quarterly, Vol 20(4), 607–624, December.
Graves, Stephen C (1999). A Single-Item Inventory Model for a Nonstationary Demand Process,
Manufacturing & Service Operations Management, Vol 1(1), 50-61.
Huh, W T, R Levi, P Rusmevichientong and J Orlin (2010). Adaptive data-driven inventory control
policies based on Kaplan-Meier estimator for censored demand, Operations Research, Vol 59,
929-941.
Huh, W T and P Rusmevichientong (2009). A nonparametric asymptotic analysis of inventory planning
with censored demand, Mathematics of Operations Research, Vol 34, 821-839.
Jensen, P A and J F Bard (2003). Operations research: Models and Methods, John Wiley & Sons Inc.
Lancaster, Tory (2004). An Introduction to Modern Bayesian Econometrics, Blackwell.
Levi, T, R O Roundy and D B Shmoys (2007). Provably near-optimal sampling-based policies for
stochastic inventory control models, Operations Research, Vol 32, 821-839.
Montgomery, D C (2008). Design and Analysis of Experiments, 5th ed., John Wiley.
Morales, J, M E Castellanos, A M Mayoral and C Armero (2005). Bayesian Design in Queues: An
Application to Aeronautic Maintenance, Centro de Investigacion Operative, Elche.
Murray, George R and Edward A Silver (1966). A Bayesian Analysis of the Style Goods Inventory
Problem, Management Science, 1966, vol. 12 (11), pages 785-797.
Peterson R and E A Silver (1979). Decision Systems for Inventory Management and Production
Planning, John Wiley.
Prabhu, N U (1965). Queues and Inventories: A Study of Their Basic Stochastic Processes, John Wiley.
Raiffa, Howard and Robert Schlaifer (1961). Applied Statistical Decision Theory. Division of Research,
Graduate School of Business Administration, Harvard University.
Sharma, Sunil, C Erik Larson and Lars J O (2001). Optimal Inventory Policies when the Demand
Distribution is not Known, Journal of Economic Theory, Vol. 101, No. 1, pp. 281-300, November.
Silver, E A (1981). Operations Research in Inventory Management: A Review and Critique, Operations
Research, vol. 29 no. 4 628-645.
Silver, E A, D F Pyke, R Peterson (1998). Inventory Management and Production Planning and
Scheduling, Wiley
Silver, E A (2007). Inventory Management: A Tutorial 2007-03, University of Calgary.
Solver (2012). Optimization Methods, www.solver.com, Frontline Systems Inc.
Tersine, R J (1994). Principles of Inventory and Materials Management (4th ed.), Prentice-Hall.
Tim Huh, Woonghee, Retsef Levi, Paat Rusmevichientong and James B Orlin (2012). Adaptive DataDriven Inventory Control with Censored Demand Based on Kaplan-Meier Estimator, Operations
Research, July/August 2011 vol. 59 no. 4, 929-941
Tim Huh, Woonghee and Paat Rusmevichientong (2009). A Nonparametric Asymptotic Analysis of
Inventory Planning with Censored Demand.
Winston, W L (2003). Operations Research: Applications and Algorithms, Cengage Learning.
57
An American Expatriate in China: Evidence of Organizational
Culture Crossvergence
Eric Sanders
Benedictine University
This article presents a detailed interview with an American expatriate in China, and shows evidence of
cultural crossvergence: a blending of both economic ideology and national culture in a new
organizational mindset. It explores each of Hofstede’s five dimensions of national culture as displayed by
employees. Through the expatriate’s perspective, we see how the firm has built a global culture and is
working to develop global leaders who share this new mindset.
INTRODUCTION
There has been discussion among organization development professionals over the past several years
over whether national cultures are converging or diverging (Yaeger, 2004). Ralston (2008) argue in favor
of crossvergence with national culture dominance. What seems clear in our age of global expansion of
business in nearly all sectors is the importance of developing a global perspective that balances both
strategy and talent development between the headquarters country and local business units (Bellin and
Pham, 2007; Mendenhall et al., 2003).
Ralston, Holt, Terpstra and Yu (1997) present a strong study of managers from four nations: the U.S.,
Japan, Russia and China, to represent the four quadrants of a two by two grid with national culture
(individualism vs. collectivism) on one axis and economic ideology (individualistic vs. socialistic) on the
other. They go on to say that a Venn diagram showing the overlapping nature of these factors might be
more appropriate to show what they called crossvergence (Figure 1): “when an individual incorporates
both national culture influences and economic ideology influences synergistically to form a unique value
system that is different from the value set supported by either national culture or economic ideology.”
This model seems to fit well with the data of how global firms behave and has implications for how
national culture develops also. My research adds qualitative details to their quantitative findings.
METHODOLOGY
As part of a graduate course on global organization development, I conducted a detailed interview
with an American expatriate working in China. It shows that the organizational culture of his company—a
US-based multinational manufacturer—is much more alike than different, regardless of where you are
located in the world. There are certain allowances for differences in local culture, and blended economic
choices with national culture in a crossvergence that seemed much closer to the headquarters culture than
the interviewee or I expected.
58
FIGURE 1
CULTURAL CROSSVERGENCE, ADAPTED FROM RALSTON, ET AL. 1997
In this paper, I will use the definition of culture of Roger Keesing, as quoted by Alfred Jaeger (2001,
p. 82). Culture is…
…an individual’s theory of what his fellows know, believe, and mean; his theory of the
code being followed, the game being played. Thus culture is not an individual
characteristic, but rather a set of common theories of behavior or mental programs that
are shared by a group of individuals.
The interview is constructed around Hofstede’s model of national culture (Hofstede & Hofstede,
2005), in which there are five main dimensions: power distance, individualism (vs. collectivism),
masculinity (vs. femininity), uncertainty avoidance, and long-term orientation. He has measured the
culture of the US and of China on each of these dimensions as follows (figure 2, taken from Hofstede,
2007):
I will briefly describe my interviewee, and then go through each of the dimensions of culture, as the
subject sees them in his work in China. By his perception, the culture of his organization in China is more
like the US than China along Hofstede’s measures, especially in terms of Power Distance.
RESULTS
Background of the Interviewee
The person I interviewed was an American working as an expatriate in Western China for a large
multinational manufacturer, whom I will refer to as “Pat.” He was married with children, and the entire
family was living in China at the time of the interview. He holds an MBA, worked in Europe for two
years and speaks a foreign language fluently, and had been with his employer for about ten years, with
good progression in his roles. His role in China had Pat leading the operations of two plants with a total of
approximately 1,400 employees. He had about 40 direct reports, including three managers.
59
FIGURE 2
NATIONAL CULTURE PROFILES OF THE UNITED STATES AND CHINA
Dimensions of National Culture of a Multinational Firm in China
Power Distance
Power distance refers to “the extent to which the less powerful members of institutions and
organizations within a country expect and accept that power is distributed unequally. Institutions are
defined as the basic elements of society such as the family and the community, while organizations are
where people work (Hofstede & Hofstede, 2005, p. 46).
In terms of organizational structure, Pat said that the employer is a large multinational manufacturer
with strong quality control and a relatively standardized product. For those reasons, major decisions
regarding production levels and processes are made at corporate headquarters. He went on to say that line
layout and allocation of local resources are decided locally, within a certain range of flexibility. This
shows relatively high power distance.
However, Pat finds there are fewer layers of management in his operation in China than in the US, so
he has greater ability to make decisions there than he had in US operations. Part of this may be due to his
promotion to a higher level in the company, but part is due to the structure of the operations in China.
In making decisions regarding his work, Pat gets input from his employees, depending upon the
situation. For example, his is responsible to decide personnel levels for his operation, and he does that
with limited input from his staff. However, who to hire and who to fire he leaves to his employees, so
long as they follow company protocol. He stressed that at all times it is important to the employees and
the company that it be clear he is in charge.
Pat socializes with his employees at quarterly team-building company events, the same as is done in
the US. These might include dinners, outdoor activities or games. At these events, Pat interacts with
employees at all levels. Employees do want to see their bosses outside of the work setting, but he feels
that is similar to what he has seen everywhere else, and not unique to Western China.
The plant receives visitors from the US and elsewhere regularly, and frequently it is Pat’s job to greet
and entertain them. This has included US Ambassadors, officials from the Federal Reserve Bank, Chinese
business and political leaders, and senior officers of his own company, including the CEO and Chairman
of the Board.
60
One of the questions I asked was: “Are you seen more as a resourceful democrat or as a benevolent
autocrat (“good father”)?” Pat said: “Hopefully more of the latter, because that is what they are looking
for.” However, he then said that he tries hard to expose them to multiple leadership styles, but
acknowledges their preference. He is more outward in his approach in that respect, so the employees can
learn. For example, Pat notes that overseas it is more important to be sensitive to the culture of the entire
audience than in the US, where presentations focus only on the decision maker. He explains to them:
“This is how someone in the US might view this; this is how someone from Malaysia might view this.
How are you preparing your presentation, given who is going to be in the room, and what their decision
style is?” He said that his goal is to develop leaders who can work globally, not just locally. If he were
just to use his employees’ preferred style of leadership, he feels he would be doing them a great
disservice.
All of these factors combined tend to show a relatively medium power distance in the firm, much
closer to what one would see in the US than what is usually found in China.
Individualism (Collectivism)
This dimension is defined in terms of contrast. “Individualism pertains to societies in which the ties
between individuals are loose: everyone is expected to look after himself or herself and his or her
immediate family. Collectivism as its opposite pertains to societies in which people from birth onward are
integrated into strong, cohesive in-groups, which throughout people’s lifetimes continue to protect them
in exchange for unquestioned loyalty” (Hofstede & Hofstede, 2005, p. 76).
I mentioned the departmental social activities above. Pat noted that attendance at these events varies
by location. In the US and in coastal cities of China, attendance rates run about 50%. In his location,
attendance is nearly 100% every time. There are a few possible reasons for this difference: First, is the
local environment. They are in a relatively remote area, so there isn’t a lot for young people to do. This
makes the work events more popular than they might be otherwise. Second, most of his employees are
recent college graduates in their early twenties. They generally like their coworkers, and they take
advantage of any chance for a social activity with their friends.
A third reason he modestly alluded to, is that he and his staff conscientiously try to make these great
events. His predecessor created a strong team culture in the department, and it has been recognized as
such in the company. People from elsewhere have come to analyze his team, to see why they work
together so well, so they can emulate that teamwork in their own areas.
A final reason for the high attendance rate is the local culture. The collectivist nature of society can be
seen in the attendance itself. When the community (in this case the employer) holds an event, you attend,
period. In addition, most of the employees are single and live with their parents, which also says
something about the collectivist culture. Pat noted that most of the employees left the events at about
11:00 to 11:30 at night, so they would be home by midnight and their parents wouldn’t worry about them.
That is behavior one generally would not expect of Americans in their twenties, whether or not they lived
at home. It implies high collectivism, and also high power distance (in showing such respect to their
parents).
Pat also found that even when the employees do not live with their parents, they try to stay close by.
Given the long-standing one-child policy in China, and the historically strong extended families, this is
not surprising, but it is different from what Pat found in the US. He works to set up a career path for his
employees, which may include opportunities in his plant and elsewhere. He then helps them learn,
develop and advance in the company, but that often requires relocation. The key limiting factor he noted
was their mobility. Many of the employees prefer to forego advancement, in favor of staying close to their
families.
When asked which was more important to the employees, the individual or the group, Pat said that he
used to say the group immediately. Cooperation is always stressed over competition. For example,
company programs such as contests for his employees, tend to be team-based, and focused on achieving
business results (such as more accurate forecasting) rather than on “beating the other team.” Also
employees’ annual evaluations are based in part upon the quality of their team participation and
61
cooperation, as well as on team performance. All that considered, after being in China for a while, Pat
now sees that even though group accomplishment is most important, the individuals want to see that they
are noticed also. This is not necessarily a contradiction, but does show that although the level of
collectivism in China is quite high, there is a slightly higher degree of individualism than he initially
found.
Masculine (Feminine)
Again using Hofstede and Hofstede’s definition: “A society is called masculine when emotional
gender roles are clearly distinct: men are supposed to be assertive, tough, and focused on material
success, whereas women are supposed to be more modest, tender, and concerned with the quality of life.
A society is called feminine when emotional gender roles overlap: both men and women are supposed to
be modest, tender and concerned with the quality of life” (2005, p. 120).
One indicator of masculinity is the preference for money and accomplishment over leisure time. Pat
felt that in his area, the employees in general preferred leisure time to money. However, he qualified that
by saying that there were many exceptions to that rule. He also noted that for groups of employees with
similar age and experience in the US, he would likewise expect a preference for leisure time.
In discussing his own leadership style, as mentioned above, Pat is conscious that he clearly has to be
in charge at all times, but he works to include his employees when possible. He gives them the
opportunity to make decisions at whatever level they are able. Indeed, he feels his job is to work himself
out of a job, by training his employees, so they can replace him, or another at his level in another location.
Another indicator sometimes used for this dimension is the contrast between logic (a more masculine
trait) and intuition (a more feminine trait). For example, Pat said that his work in finance requires a
reasonable balance of both. He said, the first answer to any question is always, “it depends.” You have to
consider the circumstances of any choice. When reviewing a decision (whether made by himself or an
employee) he said, “It has to feel right and it has to look right. If it doesn’t look right, it won’t feel right.
And if it doesn’t feel right, I’m going to go back and look at the numbers.” And his employees try to
emulate that balance in their work as well.
Uncertainty Avoidance
Uncertainty Avoidance can “be defined as the extent to which the members of a culture feel
threatened by ambiguous or unknown situations” (Hofstede & Hofstede, 2005, p. 167).
One way to reduce uncertainty is to have clear, detailed instructions. At Pat’s level, he gives general
instructions. The next level down does get involved in the details (especially since they have a young
staff). If Pat is involved in the details, it is either because he is personally interested in the topic, or
something is not working and requires his attention. This seemed to him to be the same as he would
expect in the US.
Another indicator is how the employees are with open-ended learning situations and active
discussions. Pat felt most of his employees are relatively comfortable with ambiguity. Because his work
regularly involves finance, he tends to hire people who have this ability, because it is useful in that field.
People are expected to challenge the status quo and they are expected to challenge decision making, so he
needs people who are comfortable with open-ended situations and critical thinking.
Another indicator of one’s comfort with uncertainty is involvement in volunteer organizations. The
reasoning is apparently that higher volunteerism implies greater comfort with ambiguity. Pat was asked
how much he participated in volunteer efforts now, compared to when he was in the US. He said that it
was slightly higher now, with greater participation in his children’s school, in church and community
work sponsored by the company. His entertaining of guests from abroad might fall under this category
also, which shows even greater comfort with uncertainty.
Indeed, when asked directly how well he handled ambiguity and chaos, Pat said that he was very
comfortable with them. He also said that was a skill he was tested for in the US prior to being given the
assignment, as it was a key skill that the company felt he would need in this position.
62
Pat did qualify that it is easier for him than for his family, because his responsibilities at work
remained similar to what they were before. For his wife, simple tasks like shopping have become much
more difficult. Besides the language barrier, only about half of the products they were accustomed to
buying in the US are available in that part of China, so she had to learn to substitute other things.
Additionally, transportation is also difficult, even while having a driver. That is because the driver serves
both the husband and the wife, so for daily tasks like shopping, she has to verify the driver is available,
then wait for him to come, explain where they are to go and what they are to do in a way he can
understand, and finally go do the shopping or whatever task they want to accomplish.
Overall, it appears that Pat personally has very low uncertainty avoidance, and his staff members in
China are similar in that dimension, by design.
Long-Term Orientation
“…Long-term orientation stands for the fostering of virtues oriented toward future rewards—in
particular, perseverance and thrift. Its opposite pole, short-term orientation, stands for the fostering of
virtues related to the past and present—in particular, respect for tradition, preservation of “face,” and
fulfilling social obligations” (Hofstede & Hofstede, 2005, p. 210).
When asked directly about thrift and saving by his local employees, Pat commented that his
perception is skewed on this point because he has read many papers that show that in general, the Chinese
save more than Americans. However, it appears to him that his employees do not save as much as the
literature suggests. He believes that this is because his employees are mostly single and in their 20’s, and
that their savings rate will likely increase as they enter later phases of life.
Another indication of time orientation is the emphasis on equality in the society. Following the
research of Geert and Jan Hofstede (2005, pp. 220-221), I asked Pat to choose which of the statements
below he agreed with most.
A. Too much liberalism is producing increasingly wide differences in people’s economic and
social life. There should be more equality among individuals.
B. There is too much emphasis upon the principle of equality. People should be given the
opportunity to choose their own economic and social life, according to their own abilities.
He said that he personally agreed more with B. He felt that people should be given a level playing field,
but that then they should be rewarded according to their efforts and abilities.
Perhaps most interesting, was our discussion of the importance of mutually beneficial long-term
relationships (guanxi) in the host country compared to the US. Wei, Chiang and Wu (2012) discuss this in
terms of both individual relationships and also team relationships (guanxiwang), wherein networks
improve both job performance and personal career growth. Pat said that in China, relationships are
important, but he thinks that is the same everywhere. However, in China, they are more outward with it. It
is absolutely recognized that it is critical to have relationships in place, and is stated as such. In the US, it
is understood that you need those relationships, but it is not talked about. Since the need for guanxi is
explicit in China, it is inherently an indication of greater long-term orientation than in the US. As
Hofstede & Hofstede (2005, p. 221) observed, guanxi lasts a lifetime, so it would be foolish to waste it on
a short-term objective.
Estimated Crossvergent Culture
Based on the interview data, I would estimate that the combined or crossvergent corporate culture in
Pat’s organization would be somewhere in between the national cultures of the U.S. and China, as
illustrated in Figure 3. On the Power Distance scale, I would put the operation somewhat higher than in
the U.S., but not as high as China, given Pat’s strong relationships with his staff members, yet while
intentionally maintaining his status their supervisor. On the Individualism (vs. collectivism) scale, the
Chinese national culture prevails, yet it is moderated slightly by the corporate culture, drawing it slightly
more individualistic than China in general. On Masculinity (vs. femininity) the U.S. and China are very
63
similar, and the corporate culture did not change that factor. In Uncertainty Avoidance, the corporate
culture that Pat built was different from that of both the U.S. and China. Because of their work
responsibilities, Pat intentionally developed a mindset that was more tolerant of uncertainty than one
would usually find in either country. Finally, in Long Term Orientation, Pat found that his younger
employees showed somewhat less of a long-term orientation than he would have expected, but still with a
much longer view than ordinarily encountered in the U.S.
FIGURE 3
ESTIMATED CROSSVERGENT CULTURE OF A MULTINATIONAL MANUFACTURING
ORGANIZATION IN WESTERN CHINA (SHOWN BY THE RED STARS).
DISCUSSION
The composite, crossvergent culture displayed above shows important contributions by the national
cultures of both the U.S. and China, and also variance from both national cultures in ways that would
benefit the firm, especially regarding uncertainty avoidance. In that regard, crossvergence, rather than
convergence seems a more accurate description of how the local corporate culture developed.
Clearly the key limitation of this research is that it was with a sample of one. That said, it coincides
well with Ralston et al’s (1997) larger study showing crossvergence, where economic ideology blends
with national culture to form an entirely unique mindset for the organization. Future research including
qualitative interviews with additional expatriates and their local employees, and/or quantitative
assessments of the local corporate organizational culture would strengthen this assessment greatly.
As mentioned in the introduction, the most interesting part of this interview was Pat’s perception that
the culture of his organization in China was more similar than different from that of the organization in
the US. It seems reasonable, and indicates a conscious choice of the firm to develop that culture. This is
perhaps best encapsulated by a discussion Pat and I had about the philosophy of multinational
corporations regarding expatriates. Pat feels that his ultimate goal is for his employees to be able to
replace a person at his level, whether it is there or elsewhere in the company. His employees will be able
64
to work not only in China, but in Malaysia, Indonesia, the US, or any other location, wherever their
talents can be best used.
Developing leaders who can work anywhere is the difference between being a global company and a
national company with a global presence, according to Pat, and that is well documented in the literature as
well (e.g. Bellin and Pham, 2007; Mendenhall et al., 2003). Firms in the latter category have a strategy of
teaching the headquarters culture by expatriates and then replacing them with local talent as quickly as
possible. Expatriates are expensive, so it makes financial sense to run operations with local personnel.
Truly global firms want to find the best and the brightest from around the world, keeping economic cost
as one of many factors, but always using the best talent possible, wherever they might come from.
The global strategy Pat presented shows this consideration of culture to be a conscious strategy of the
firm. And as Hofstede and Hofstede observed, it is impossible to separate national management culture
from national culture (2005, p. 20). If the corporate leaders of a nation develop a global culture, the nation
will eventually develop a similar culture. Future researchers will see what this new culture in China and
indeed in the world, will look like.
REFERENCES
Bellin, Joshua B. and Pham, Chi T. (2007). "Global expansion: balancing a uniform performance culture
with local conditions", Strategy & Leadership, Vol. 35 Iss: 6 pp. 44 – 50.
Hofstede, Geert. (2007) Cultural Dimensions. Downloaded from http://www.geerthofstede.com/index.shtml, January 2007.
Hofstede, Geert & Hofstede, Gert Jan. (2005). Culture and Organizations: Software of the Mind,
McGraw-Hill, New York.
Jaeger, Alfred M. (2004) “Organization Development and National Culture: Where’s the fit?” in
Sorensen, Peter F. Jr., Head, Thomas C., Yaeger, Therese and Cooperrider, David. (2004). Global
and International Organization Development, Fourth Edition, Champaign, Illinois: Stipes
Publishing LLC, pp. 81-100.
Mendenhall, Mark E.; Jensen, Robert J.; Black, J. Stewart; and Gregersen, Hal B. (2003). Seeing the
Elephant: Human Resource Management Challenges in the Age of Globalization. Organizational
Dynamics, Vol. 32, No. 3, pp. 261–274. Retrieved from Business Source Elite.
Ralston, D.A. (2008). The crossvergence perspective: reflections and projections. Journal of International
Business Studies (2008) 39, 27–40.
Ralston, D. A., Holt, D. A., Terpstra, R. H., & Yu, K. C. (1997). The impact of national culture and
economic ideology on managerial work values: A study of the United States, Russia, Japan, and
China. Journal of International Business Studies, 28(1): 177–208. Retrieved from Business
Source Elite.
Wei, Li-Qun; Chiang, Flora F. T. and Wu, Long-Zeng (2012). Developing and Utilizing Network
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Yaeger, Therese. (2004). “Globalizing Organizational Development: Convergence or Divergence,” in
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and International Organization Development, Fourth Edition, Champaign, Illinois: Stipes
Publishing LLC, pp. 249-256.
65
APPENDIX
Readers may find the actual interview protocol of interest. Note that on each of the dimensions of
national culture, I had two questions regarding “desirable” behavior (what is expected in the culture) and
two questions regarding “desired” behavior (what the interviewee actually does himself or herself)
(Hofstede & Hofstede, 2005, p. 21-22).
Interview Questions
General
1) Would you please tell me a few of your best experiences in the new host country?
2) How have you had to alter your management style (or following style, or both) in the new country?
3) What preparation did you (and your family) have before going in-country? How helpful was it?
Power Distance
Q. How centralized are your company’s operations in this region?
Q. How often are you expected to socialize with employees? At what levels?
Q. How much input do you get from employees when making important decisions?
Q. Are you seen more as a resourceful democrat or as a benevolent autocrat (“good father”)?
Individualism (Collectivism)
Q. Which is more important to the employees, the individual or the group? Why?
Q. Do relationships prevail over tasks, or do tasks prevail over relationships?
Q. How much mobility in the workforce do you give your employees?
Q. How have you cultivated long-term relationships (guanxi) in the host country compared to at
home?
Masculinity (Femininity)
Q. Which do the local employees prefer, more leisure time or more money?
Q. To what degree are you expected to run your organization with an active, forcible approach?
Q. Do you depend more on logic or on intuition in making decisions? Is it the same for your local
managers?
Q. How do you encourage cooperation and/or competition between your employees?
Uncertainty Avoidance
Q. How important is it to have instructions for work spelled out in detail?
Q. How comfortable are your employees with open-ended learning situations and active discussions?
Q. How involved are you in voluntary associations and movements?
Q. How well do you tolerate ambiguity and chaos?
Long-Term Orientation
Q. How important is thrift and saving to the local employees?
Q. Does your company focus more on the bottom line or on market position?
Alt. Q. How far out do you plan operations for the company?
Q. Which of these statements do you prefer, and why.
A. Too much liberalism is producing increasingly wide differences in people’s economic and
social life. There should be more equality among individuals.
B. There is too much emphasis upon the principle of equality. People should be given the
opportunity to choose their own economic and social life, according to their own abilities.
Q. How has your time orientation changed since you went to the host country?
66
The Impact of the Millennium Development Goals in Argentina,
Brazil, and Chile
Michael Christian
University of Scranton
Jose D. Alicea
Daniel J. West, Jr.
The Millennium Development Goals have been a great initiative throughout many countries around the
world since its creation in 2000. Among the countries of Argentina, Brazil, and Chile, this initiative has
been one of the major factors that have contributed to their economic growth, social improvement, and
health services and quality development during the first decade of the 21st Century. Regardless, there are
other major factors that may be of either positive or negative influence to the development of the
Millennium Development Goals in each country.
INTRODUCTION
During the month of September 2000, leaders from the United Nations were gathered in order to
create an initiative with the purpose of promoting health and eradicating poverty throughout the world by
2015. This initiative was strategically planned and divided into goals, also known as The Millennium
Development Goals (MDGs). The MDGs are composed of a total of eight goals that target the
development and promotion of human rights and social determinants of health with the focus on
coordinated efforts ranging from poverty, hunger, gender inequality and diseases reduction, along with
the advancement in education, sustainable use of natural resources and the regulation of the cooperation
between developed countries by 2015 (United Nations, 2012).
This initiative has obliged governments to elaborate strategic alliances between international health
institutions and Non-Governmental Organizations (NGOs) in order to create the opportunity to fight
poverty, hunger and diseases, stop environmental degradation, promote primary education and gender
equality worldwide. Each developmental goal is designed differently by each UN country to meet its
individual needs. The main objective of the MDGs is providing growth and improvement throughout the
world as a common initiative between all countries.
Millennium Development Goals
Millennium Goal I seeks the eradication of extreme poverty and hunger. This goal has three aims or
targets in order to end/lower poverty and hunger. The first target is to reduce by half the number of the
67
people whose income is less than $1 dollar a day between 1990 and 2015. This target is measured by the
poverty gap ratio, share of poorest quintile in the national consumption and percentage of population
below $1 (PPP) per day. The second target is to achieve full and productive employment and decent work
for all, including women and young people. This target is measured by the growth rate of the Gross
Domestic Profit (GDP) per person employed, employment-to-population ratio, and the percentage of
employed people living below $1 (PPP) per day. Finally, the third target is to reduce by half the number
of people who suffer from hunger between 1990 and 2015. This target is measured by the prevalence of
underweight children under-five years of age, and the percentage of population below minimum level of
dietary energy consumption.
Millennium Goal II seeks the achievement of universal primary education. This goal has only one aim
or target in order to accomplish universal primary education. The main target is to ensure that every child
around the world, boys and girls alike, complete a full course of primary schooling by 2015. This goal is
measured by the net enrollment ratio in primary education, total percentage of pupils starting grade one
who reach the last grade of primary education, and literacy rate of 15-24 year-olds, both woman and men.
Millennium Goal III seeks gender equality and women empowerment. This goal has only one aim or
target in order to promote gender equality and empower women. The main target is designed to eliminate
gender disparity in primary and secondary education preferably by 2005, and at all levels by 2015. This
target is measured by ratios of girls to boys in primary, secondary and tertiary education. It is also
measured by the share of women in wage employment in the non-agricultural sector and the proportion of
seats held by woman in national parliament.
Millennium Goal IV seeks the decrease of child mortality. This goal has only one aim or target in
order to reduce the child mortality rate. The main target concentrates on reducing by two thirds the
mortality rate among children under five between 1990 and 2015. This target is measured by both the
under-five mortality and infant mortality rates along with the proportion of one year-old children
immunized against measles.
Millennium Goal V seeks the improvement of maternal health. This goal has two primary aims or
targets in order to improve maternal health. The first target is to reduce by three quarters the maternal
mortality ratio between 1990 and 2015. This target is measured by maternal mortality ratio and the
proportion of births attended by skilled health personnel. The second target is to achieve universal access
to reproductive healthcare by 2015. This second target is measured by contraceptive prevalence rates,
adolescent birth rates, antenatal care coverage, and unmet need for family planning.
Millennium Goal VI seeks to combat HIV/AIDS, malaria and other diseases. In order to achieve this,
the goal was divided into three targets. The first target is to halt and begin to reverse the spread of
HIV/AIDS by 2015. This target is measured by the HIV prevalence among population aged 15-24 years,
condom use for high-risk sex, proportion of population aged 15-24 years with comprehensive correct
knowledge of HIV/AIDS, and the ratio of school attendance of orphans to school attendance of nonorphans aged 10-14 years. The second target is to achieve universal access to treat HIV/AIDS for all those
who need it by 2010. This target is measured by the proportion of population with advanced HIV
infection with access to antiretroviral drugs. The third target concentrates on halting and beginning to
reverse the incidence of malaria and other major diseases. This target is measured by the incidence and
death rates associated with malaria, the proportion of children fewer than five (5) sleeping under
insecticide-treated bed-nets, the proportion of children fewer than five (5) with fever who are treated with
appropriate anti-malarial drugs. As for tuberculosis, it is also measured by the incidence, prevalence and
death rates associated with tuberculosis along with the proportion of tuberculosis cases detected and cured
under directly observed treatment short course.
Millennium Goal VII seeks to ensure environmental sustainability. This goal is of severe complexity
due to the fact that it has been divided into four targets. The first target aims at integrating the principles
of sustainable development into country policies and programs, reversing the loss of environmental
resources. The second target aims at reducing biodiversity loss by 2010. These first two targets are
measured by the percentage of land area covered by forest, CO2 emissions per capita and per $1 GDP
(PPP), the percentage of fish stocks within safe biological borders, the percentage of total water resources
68
used, the percentage of terrestrial and marine areas protected, and the percentage of species threatened
with extinction. The third target addresses the number of people who are living without sustainable
access to safe drinking water and basic sanitation with the objective of reducing the actual percentage of
people without safe drinking water by half. This third target is measured by both the amount of
population using an improved drinking water source and the amount of population using an improved
sanitation facility. The last target of the seventh MDG is to achieve significant improvement in lives of at
least 100 million slum dwellers by 2020. This last target is measured by the percentage of urban
population living in slums.
Millennium Goal VIII promotes global partnerships for development. This last goal is divided into six
targets. The first target aims to develop further an open, rule-based, predictable, non-discriminatory
trading and financial system. This target also promotes the commitment to good governance, growth and
poverty decrease; both nationally and internationally (United Nations, 2012). The second target addresses
the special needs of the least developed countries. This target encourages the least developed countries’
exports to be tax free along with an improved program of debt relief and cancellation of official bilateral
debt (United Nations, 2012). The third target promotes the special needs of landlocked developing
countries and small islands developing States through the Program of Action for the Sustainable
Development of Small Island Developing States. The fourth target promotes dealing extensively with the
debt problems of emergent countries throughout national and international initiatives with the purpose of
making debt sustainable from a long-term perspective. The fifth target promotes the cooperation with
pharmaceutical companies and the access to affordable essential drugs in developing countries. This
target is measured by the percentage of the population with access to affordable essential drugs on a
sustainable basis. Finally, the last target within the eighth goal aims at the cooperation with the private
sector the availability of new technologies’ benefits, such as information and communications. This target
is measured by the number of fixed telephone lines per 100 people, the number of mobile cellular
subscriptions per 100 people and the number of internet users per 100 people.
MILLENNIUM DEVELOPMENT GOALS’ ACTUAL STATUS
The Continent of South America has three interesting sub-developed economies that are on their way
to economic expansion and country growth as shown in Table 1. During the first decade of 21st Century,
the Millennium Development Goals played a major role in the development of Argentina, Brazil and
Chile’s health profiles, as well as general economic progress since the planning and implementation of the
MDGs within these countries in 2000.
Argentina
In the early 21st Century, Argentina, a vast country of natural resources, began the new millennium
with a devastating economic and political crisis which led to a series of unfortunate events, including the
rise of the poverty level within the Argentinean population.
Argentina’s poverty level has been unstable throughout the last thirteen years. Due to the financial
crisis in 2002, the poverty level increased from 6.1% in 1990 to 21.5% in 2002. Furthermore, from June
2007 to June 2009, the poverty level decreased 40.6% from 23.4% to 13.8% respectively, but not until
2010 in which it increased again to 30% and it has remain constant ever since (Central Intelligence
Agency [CIA], 2013).
Since 1994 primary and secondary education has been obligatory. Argentina’s universal education
goal of obtaining 100% of literacy level among citizens is about to achieved. This percentage has
increased from 91% in 2001 to 95% 2007. However, according to the Program for Development of the
United Nations the lack of Argentina’s ability to achieve their education goal is due to people living in
rural areas (Programa de Naciones Unidas para el Desarrollo, 2009).
Conversely, the primary level literacy is one of the goals that Argentina has already accomplished.
According to the same report, the Program for Development of the United Nations, Argentineans
achieved 100% primary level of literacy by 2008, meaning that all Argentineans are primary level
69
educated. This initiative promoted gender equality greatly since this achievement includes both sexes
(Programa de Naciones Unidas para el Desarrollo, 2009).
The unemployment rate has also dropped over the years from 17.3 in 2003 to 7.2 in 2012. It is
believed that the recent government interest and improvement of Argentina’s social infrastructure after
the 2002-2003 crises was cause of this positive outcome.
Argentina also aimed at decreasing their mortality rate by 2/3 by 2015. This goal helped decrease the
mortality rate drastically during the first decade of the 21st century when Argentina’s mortality rate
decreased almost by half from 25.6 in 1990 to 13.3 in 2007 (per 10,000 population). This goal was
achieved by 2010 when they reached a National Mortality Rate of 7.8 (Pan American Health Organization
[PAHO], 2012). Although the goal was achieved, there was a slight change on Argentina’s maternity rate
since it decreased relatively slow during the period of 1990-2007 from 5.2% to 4.4% (Programa de
Naciones Unidas para el Desarrollo, 2009). By 2012, this rate increased back to 7.7%. In addition, the
goal to reduce maternal mortality by 50% in Argentina has not been achieved. Regardless, during 2010
the maternal mortality rate was 4.6% (per 10,000 populations) representing a decrease of 30% (United
Nations, 2012).
Furthermore, some of the primary causes are Coronary Heart and Cerebrovascular Diseases,
Influenza/Pneumonia and Lung Cancer as shown in Table 2.1. These diseases are also the primary causes
of death in Brazil and Chile with the exception of Lung, Colon-Rectum and Breast Cancers which each of
the rates are relatively high, 2.2, 1.7 and 2.5, respectively (per 10,000 populations). Both Colon-Rectum
Cancers and Breast Cancer’s rates are worrisome since their world comparison is ranked 22nd and 15th
respectively by the WHO. Appropriately it is noted that although Argentina’s Coronary Heart Diseases
has the highest percentage (16.8%) of total causes of deaths between three countries, it is Brazil who has a
higher rate with 8.1 vis a vis Argentina’s 7.1 per 10,000 population. Also, Diabetes Mellitus and
Hypertension are two of the primary causes of death in Argentina, their rates, 1.8 and 1.2 respectively, are
lowest between the three compared countries.
The actual HIV prevalence rate, 0.5, was constant and barely decreased in the early 2000s. The goal,
to decrease HIV prevalence rate by ¾ (0.37 per 10,000 populations), is the third goal that Argentina has
already achieved since the rate reached 0.37 (per 10,000 populations) in 2007 (Programa de Naciones
Unidas para el Desarrollo, 2009). Moreover, as the second decade of the 21st starts, the HIV prevalence
rate continues to slightly decrease reaching a 0.3 in 2010 (PAHO, 2012). Although there are 110,000
Argentineans living with HIV/AIDS, this disease is not one of the primary causes of death
Brazil
Brazil’s rise to power and its potential of becoming the new emerging economy in South America
was halted during the last four years when the Gross Domestic Product growth decreased from 7.5% in
2010 to 1.3% in 2012. Still, Brazil is one of the few countries that might achieve all of their goals in
time by the year 2015.
The percentage of the population living on less than a US $1 per day has decreased from 9.9% to
5.7% over a period of 13 years (1990-2003). According to the Pan American Health Organization
(PAHO), if this percentage of living on less than a $1 was considered, Brazil would accomplish the first
MDG by 2015 (Pan American Health Organization [PAHO], 2008). Furthermore, the population below
the poverty line has also decreased in the last two years from 26% in 2010 to 21.4% in 2012. Regardless,
due to the vast population of 201,009,662 it is estimated that there are at least 43 Million people living
below the poverty line.
Access to education and gender equality has also been increasing within the population of Brazil.
From 1992-2003, the rate of primary school attendance increased from 81.4% to 93% respectively and
gender equality within middle schools also increased from 15.1 Males & 21.3 Females to 38.1 Males &
48.2 Females. Also, child mortality decreased from 1996 to 2004 with rates of 332 to 226 respectively
(per 10,000 live births).
Brazil may look like the most ideal country to follow but they are lacking implementation of some
major MDGs objectives. One of these objectives is the maternal mortality rate, the one that has remained
70
inconstant for the last thirteen years since it increased from 5.16 to 7.61 per 10,000 live births from 1996
to 2004 and reached its peak during 2010 at 11 per 10,000 of population and by 2012, suddenly decreased
to 5.6. There is little or no evidence on why these statistics are vastly varied.
Another ongoing issue in Brazil that distinguishes Brazil from Argentina and Chile is the Violence
Rate as one of the Primary Causes of Death as shown in Table 2.2. The violence rate in Brazil has been a
continuous issue that represents almost 6% of the total deaths in the country, making it the 5th Primary
Cause of Death in the Country. This percentage ranks number 19th worldwide and since the targets and
objectives from Brazil’s Millennium Development Goals do not address this issue, there is little or no
information/data to report. It is important to note that Brazil also has the highest death rate of Coronary
Heart Diseases (8.1), Cerebrovascular Diseases (7.4), Diabetes Mellitus (3.8), and Hypertension (3.2) per
10,000 populations, among others, between these three countries.
The number of people living with HIV/AIDS in Brazil has increased from 600,000 (1998) to 730,000
(2007), the HIV/AIDS adult prevalence rate has been constant from 1996 to 2010 at 0.6%. This
percentage of HIV/AIDS occurrence within Brazil has been the result of a synergetic work effort between
international organizations and both the private and public industry in Brazil. None the less, by 2012 this
rate increased to 1.8 but, regardless of Brazil’s prevalence, HIV/AIDS is not one of the primary causes of
death as noted previously.
Chile
In the last decade, Chile has served the world as an economic role model. Inspired by change and
political crisis, Chile’s economy has been aimed at a superior level for foreign trade throughout the last
twenty years. By 2010, exports were already responsible for at least 25% of their total GDP. In addition,
Chile has a total of 57 joint regional trade agreements throughout the world (including US, China, India,
Mexico, among others), making them one of the countries with the highest level of regional trade
agreements. Moreover, while Argentina’s and Brazil’s GDP Real Grow Rate halted by the end of the last
decade (2.6% and 1.3% respectively), Chile’s has barely decreased since 2010 from 6.1 to 5.0% in 2012.
Not to mention that Chile’s GDP Per Capita is also the highest with $18,400 compared with Argentina
and Brazil which are $18,200, $12,000 respectively (CIA, 2013).
Within a period of 10 years, Chile has greatly decreased poverty from 12.9% (1990) to 4.7% (2003).
By 2005 it was the only country in America that had already cut the poverty level in half. In addition,
their goal of having a 1.7% proportion of the population with an income of less than one dollar a day has
already been achieved by 2006 when they reached 1.1% (Chili Ministry of Planning, 2008). And although
the population below the poverty line has increased from 11.5% to 15.1% in the last three years (20102012), Chile still has the lowest Poverty Rate between the compared countries.
Unlike other countries, Chile has a very small proportion of malnourished children less than 6 years
old. They have also achieved their 0.5% goal of decreasing malnourished children when the rate
decreased from 0.7% in 1994 to 0.5% in 2000. By 2006, this rate was already 0.3%. Obesity within the
same age category, on the contrary, is vaguely an issue in Chile. During 1996, 6.2% of children younger
than 6 suffered from obesity and by 2000 this percentage increased to 7.2%. Their actual goal is to reach
6% obesity percentage by 2015 (Chile Ministry of Planning, 2008).
During a period of ten years (1990-2000), Chile was able to slowly increase access to primary school
for children from 88% to 91% (respectively) until 2006 when the rate decreased to 88%. Primary level
literacy rate has also increased slowly within the same period of time from 98.4% to 98.7% and, although
it has not been enough to achieve their goal of 99.8% by 2015, it has promoted gender equality within
Chile since same genders have the same percentage of alphabetization. The country’s literacy rate by
2002 was 95.7% and it is estimated that this number will increase to 99.1% by 2015 (Chile Ministry of
Planning, 2008).
Child mortality has decreased by more than half. During 2005 the rate was 79 (per 10,000
populations) live births compared to the year 1990 in which the rate was 160 (per 10,000 populations).
The goal to reduce it to 53 by 2015 and has still not been achieved. Also, the maternal rate goal of 10 (per
10,000 populations) has not been achieved. Regardless, it has decreased drastically since its peak of 40
71
(per 10,000 populations) in 1990 to 19.8 in 2005 (Chili Ministry of Planning, 2008). By 2012 the
mortality rate increased once again to 26.
Additionally, Road Traffic Accidents is not a Primary Cause of death in Chile compared to Argentina
and Brazil. Chile also has the lowest rates of Coronary Heart Disease (5.1) and Influenza/Pneumonia (2.1)
as a cause of death per 10,000 populations, but what truly distinguishes Chile is Dementia being one of
the primary causes of death as shown in Table 3.3. By 2010, there were 4,059 deaths related to dementia
(including the Alzheimer’s disease) which represented a rate of 2.0 per 10,000 populations, ranking
number 8th in the World. Stomach Cancer also distinguishes Chile from Brazil and Argentina since 4.3%
of the total deaths in 2010 were cause by it, ranking 17th worldwide.
Chile’s estimated HIV prevalence cannot be compared to Argentina or Brazil because their rates have
been constant. Chile’s rate has slightly increased over the past years from 0.25% in 2000 to 0.4% in 2009.
In addition, the number of people living with HIV has also increased from 20,000 in 1998 to 40,000 in
2009 (CIA, 2013). Surprisingly, in order to calculate this HIV/AIDS increase, Chile utilizes other
measures, HIV prevalence not being one of them. According to the Central Intelligence Agency, Chile
had an HIV prevalence rate of 0.4 and 40,000 people were living with HIV/AIDS by 2010 as shown in
Table 3. Regardless of Chile’s prevalence, HIV/AIDS is not one of the primary causes of death.
MITIGATING FACTORS
Political Factor
The political factor has been the major contributor to most of the Millennium Development Goal’s
success within the countries of Argentina, Brazil and Chile. These three governments strategically
prioritized social development as a primary target since the MDGs’ implementation planning.
Within these countries, Argentina may be seen as the greatest example since they had to overcome
political and economic crisis during 2002-2003 while other countries already started their MDGs’
implementation. This achievement was caused by the adoption of aggressive policies that obliged both
private and public entities either to perform vast layoffs or to decrease salaries in order to keep
Argentina’s workforce employed and with full compensation. This political initiative stopped the
development of the economic crisis in Argentina. Increasing access to health care was also another
aggressive initiative from the Argentinean government. This supplementary policy favored the access of
both health and essential medicines to the population, consequently reducing the infant mortality rate
(Programa de Naciones Unidas para el Desarrollo, 2009).
Similarly, Chile aimed at social policies as part of their political planning. By 2002, their government
created a new Health Reform in order to promote access to health and raise health quality within the
country. By 2008, Chile’s government created a Provisional Reform with the purpose of providing
pensions to previous citizens that did not have the right to own personal pensions. Moreover, their new
social priority from a political perspective is to promote equality within citizens, regardless of their social
or economic class, and most importantly, to eliminate risk opportunities that might threaten low income
families (Chile Ministry of Planning, 2008).
Economic Factor
The economic factor has also played a major role in the development of the Millennium Development
Goals of these three countries. Evidently, as shown in Table 1, these countries have an actual positive
Gross Domestic Product (GDP) and Growth Per Capita Rate. These indicators clearly represent the
capability of investing in both social and health development. Regardless of the fact, these countries have
their own political priorities.
The political priority in Argentina was social development and by 2003 the Argentinean government
invested 20% of their GDP in order to put a stop to the economic and political crisis of 2002-2003. This
political initiative succeeded due to the economic planning and investment within the year 2003. By 2008,
social development represented 23.7% of their GDP expenditure (Programa de Naciones Unidas para el
Desarrollo, 2009). This percentage assisted the country of Argentina in regaining stability.
72
Geographic Factor
The geographic factor also plays a major role in the development of the Millennium Development
Goals. Although most of the population of these three countries lives within urban areas, access to health
in rural areas is a major issue since there is little or no health workforce or facilities. Areas such as el
Chaco Sur Americano (South-American Chaco) which includes Argentina, Bolivia, Paraguay and
Southwestern Brazil, and some other regions in Western Brazil, lack health professionals and schools
since most of health professionals, shown in Table 4, work within urban areas. The majority of the
population living in these areas is indigenous and during the years these people have been marginalized
by governments. Since there is little or no government involvement within these places, there is a lack of
quantitative data in order to properly analyze these regions.
In order to address this issue, in 2006 the Pan American Health Organization lunched an initiative
called Faces, Voices and Places with the purpose of accelerating progress toward the achievement of the
Millennium Development Goals. The initiative focuses its efforts on the most vulnerable communities in
different regions in the Americas and the Caribbean including Argentina, Brazil and Chile, from a
perspective of health and development (Pan American Health Organization [PAHO], 2011)
Education Factor
Argentina’s geographical factor has also affected the education in the country since it has not been
able to obtain 100% level of literacy within the population. This is a result of having 5% of children or
people fewer than 17 years of age living in unfavorable rural sectors (Programa de Naciones Unidas para
el Desarrollo, 2009). Their actual national literacy rate, for people of age 15 and over who can read and
write, is 97.2% and they are expected to reach their goal regardless of the effect of the geographical factor
on their education system. Still, 97.2% is a decent number for an emerging economy and, actually,
Argentina has the highest literacy rate between the three compared countries and their government
expends 4.9% of their Gross Domestic Product (GDP) on Education (CIA, 2013).
Chile, on the contrary, has a lower Literacy rate of 95.7%, compared to Argentina. There is little or no
information regarding the reason as to why Chile does not have 100% national literacy rate. It could be
assumed that the main reason is due to the geographical factors and regions of indigenous population,
same as Argentina and Brazil. Furthermore, by 2010 the Chile’s government expended only 4.0% of their
GDP on education, making it the country with the lowest contribution on education between the
compared countries (CIA, 2013).
Unfortunately, Brazil has an even lower literacy rate than Argentina and Chile. By 2010 their literacy
rate was only 88.6%, which makes it the lowest literacy rate between the three compared emerging
economies, and as same as Chile and Argentina, the reason may be due to the vast rural area that Brazil
has to the West which makes it impossible for children to travel to schools, or even to build schools.
Although it has the lowest literacy rate between the three, Brazil has the highest government expenditure
on education with 5.08% of their GDP, raking number 55th worldwide (CIA, 2013).
Wealth Inequity Factor
According to the World Factbook from the Central Intelligence Agency, Brazil and Chile are within
the top 20 wealth inequity countries. Calculated with the Gini Index, a tool that measures the degree of
inequality in the distribution of family income in a country, Brazil has the highest rate of wealth inequity
between the three compared countries with 53.9 (CIA, 2013). This coefficient has increased from 49.6
(2004) to their actual 53.9 (2009) and ranks number 13th worldwide. This creates a worrying issue in
Brazil since 26% of their citizens are already below the poverty line and may increase the percentage of
the population living on less than a US $1 in the years to come if this coefficient does not stop increasing.
One of the major reasons for this inequity in Brazil is the different salaries between professionals from
urban and rural areas. These salaries create a direct threat to Brazil’s Health System since most health
professionals are only willing to work in urban areas leaving the rural areas without competent staff or
adequate health professionals, and making it impossible to compete with other private health institutions
located in urban areas (Pan American Health Organization [PAHO], 2008).
73
By 2009 Chile also had a high Gini Index Coefficient with 52.1, making it the 16th highest wealth
inequity region of the World (CIA, 2013). Unlike Brazil, this coefficient, for Chile was 52.0 in 2003, has
barely increased but it may still affect the total population who are below the poverty line (11.5%) and
increase the population living on less than a US $1.
Argentina has the lowest Gini Index Coefficient in the whole South-American Region with 45.8.
Compared to Brazil and Chile, Argentina is the only country whose coefficient decreased from 48.8 in
2007 to their actual 45.8 in 2009, making it the 36th country with the highest wealth inequity and it is also
estimated that by 2010 their Gini Coefficient decreased to 41.1 according to the World Factbook (CIA,
2013). Although there is not a concrete report explaining these events in Argentina, it is speculated that
the previous political corruptions, the last economic crisis, and their actual 30% of population living
below the poverty line are some of main factors that are decreasing this coefficient.
CONCLUSION
It is evident that the Millennium Development Goals have been a fundamental factor for the
development of the countries of Argentina, Brazil and Chile from a macro perspective. Most of the goals
set up by the governments are on their way to being achieved by 2015 while others have been already
achieved. Regardless, it is because of these goals that these three countries are emerging as potential
power economies.
Although, the recent economic and political crisis in Argentina proved that these are vulnerable
countries, the MDGs’ indicators have been of great assistance and guidance by creating awareness and
promoting social and health development within the countries’ governments. Nevertheless, some factors
such as the geographical factor are impeding the development and the successful achievement of some of
these goals. It will be interesting to see if these three countries do reach and achieve all of their eight
goals by 2015 and are able to identify the reasons that enabled these achievements.
REFERENCES
Central Intelligence Agency. (2013). World Factbook. Retrieved from
https://www.cia.gov/library/publications/the-world-factbook/index.html
Chile Ministry of Planning. (2008). Millennium Development Goals Executive Summary.
Pan American Health Organization. (2008). Health Systems And Services Profiles: Brazil.
Pan American Health Organization. (2011). Faces, Voices and Places. Retrieved from
http://www.paho.org/english/mdg/MDGs32p2.pdf
Pan American Health Organization. (2012). Basic Indicators: Health Situation in the Americas.
Programa de Naciones Unidas para el Desarrollo. (2009). Objetivos de Desarrollo del Milenio. Consejo
Nacional de Coordinación de Políticas Sociales.
United Nations. (2012). The Millennium Development Goals Report 2012. New York: United Nations.
World Health Organization. (2011). Countries. Retrieved from
http://www.who.int/countries/en/
World Health Organization. (2012). Argentina: Health Profile. Retrieved from
http://www.who.int/gho/countries/arg.pdf
World Health Organization. (2012). Brazil: Health Profiles. Retrieved from
http://www.who.int/gho/countries/bra.pdf
World Health Organization. (2012). Chile: Health Profile. Retrieved from
http://www.who.int/gho/countries/chl.pdf
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APPENDIX A
TABLE 1
COUNTRY INDICATORS
Total
Population
(20013 est.)
Argentina
Brazil
Chile
%
Living
Urban
Area in
20102012
𝟒𝟐, 𝟔𝟏𝟎, 𝟗𝟖𝟏 92%92%
𝟐𝟎𝟏, 𝟎𝟎𝟗, 𝟔𝟔𝟐 87%87%
𝟏𝟕, 𝟐𝟏𝟔, 𝟗𝟒𝟓 𝟖𝟗%89%
GDP Per GDP Real
Capita
Growth
2010-2012
Rate
20102012
$16,700$18,200
$11,700$12,000
$16,800$18,400
Source: Central Intelligence Agency, 2013
9.2%𝟐. 𝟔%
7.5% 1.3%
6.1%- 𝟓%
GDP %
Expended
in
Healthcare
2009-2010
Unemploy
ment Rate
2009-2012
Populatio
n Below
Poverty
Line in
2010-2012
10.1% 8.1%
7.5% -9.0%
8.7%7.2%
8.1%6.2%
9.6%6.4%
30%𝟑𝟎%
26%21.4%
11.5%15.1%
8.2% -8%
TABLE 2.1
PRIMARY CAUSES OF DEATH IN ARGENTINA
Causes of Death
Coronary Heart Disease
Cerebrovascular Disease
Influenza & Pneumonia
Lung Cancer
Diabetes Mellitus
Colon-Rectum Cancers
Kidney Disease
Breast Cancer
Hypertension
. Road Traffic Accidents
Other (Rest)
Deaths in
2010
36,415
22,859
20,366
10,033
8,911
8,575
7,807
6,702
6,487
4,880
-
Rate Per 10,000
population 2010
7.1
4.4
3.6
2.2
1.8
1.7
1.2
2.5
1.2
1.2
-
Total Distribution
(100%)
16.8%
10.5%
9.4%
4.6%
4.1%
4.0%
3.6%
3.1%
3.0%
2.3%
38.6%
World
Rank
(2010)
154
151
90
51
133
22
102
15
151
116
-
Source: World Health Organization, 2011. Note: This table includes both sexes.
75
TABLE 2.2
PRIMARY CAUSES OF DEATH IN BRAZIL
Causes of Death
Deaths in 2010
Diabetes Mellitus
Violence
Hypertension
Lung Disease
Road Traffic Accidents
Lung Cancer
. Breast Cancer
Other (Rest)
133,992
123,034
61,987
60,951
56,841
53,466
43,373
42,071
22,747
12,573
-
Rate Per 10,000
population
8.1
7.4
3.8
3.6
2.8
3.2
2.7
2.2
1.4
1.4
-
Total Distribution
(100%)
13.8%
12.6%
6.4%
6.3%
5.8%
5.5%
4.5%
4.3%
2.3%
1.3%
37.2%
World
Rank
134
117
84
91
19
68
83
57
104
102
-
TABLE 2.3
PRIMARY CAUSES OF DEATH IN CHILE
Causes of Death
Dementia
Diabetes Mellitus
Hypertension
Lung Disease
Stomach Cancer
Liver Disease
. Lung Cancers
Other (Rest)
Deaths in
2010
9,799
8,757
4,364
4,059
3,784
3,681
3,378
3,351
3,058
2,587
-
Rate Per 10,000
population
5.1
4.5
2.1
2.0
2.0
1.8
1.7
1.8
1.7
1.4
-
76
Total Distribution
(100%)
12.6%
11.3%
5.6%
5.2%
4.9%
4.8%
4.4%
4.3%
3.9%
3.3%
39.7%
World
Rank
177
149
132
8
123
131
116
17
44
87
-
TABLE 3
HEALTH INDICATORS BY COUNTRY
Argentina
Brazil
Chile
Life
Expectanc
y by male
and female
2010-2012
72/7974/81
69/7669/76
74/8175/81
Infant
Mortality
(per 10,000
live births)
2010-2012
111.1-105.2
Maternal
Mortality
(per 10,000
live births)
2010-2012
4.6-7.7
Total
Fertility
Rate
2010-2013
(est.)
2.33-2.27
HIV/AIDS
Adult
Prevalence
Rate 20102012
0.5 – 0.3
People living
with
HIV/AIDS
2012 (est.)
211.7-205
11-5.6
2.18-1.81
0.6 – 1.8
730,000
73.4-74
16-25
1.88-1.85
0.4 – 0.4
40,000
120,000
Source: Central Intelligence Agency, 2013
TABLE 4
HEALTH PROFILE
Contraceptive
Prevalence
2010-2012
Argentina
Brazil
Chile
65%-75%
88%-80%
64%-64%
Births
attended by
skilled
health
personnel
2010-2012
99%-98%
98%-99%
100%-100%
Source: World Health Organization, 2012
Measles
Immunization
in 1-year-olds
2010-2012
Number of
Physicians
(per 10,000
population)
2010-2012
99.6%-99%
99%-99%
96%-93%
31.6-20
17.2-17.6
10.9-10.3
Number of
Nurses &
Midwives
(per
10,000)
2010-2012
4.8-7.25
65-64.2
6.3-1.4
Obesity
by Male
& Female
(2008)
27.4/29.7
16.5/22.1
24.5/33.6
77
Adaptation to Water Stress in Nigeria Derived Savanna Area: The Indigenous
Knowledge and Socio-Cultural Nexus of Management and
Humanitarian Services
Amidu Ayeni
University of Lagos, Lagos, Nigeria
Alabi Soneye
Fatai Badru
Climate change exerts enormous impacts on natural resources both at the local and global scales. Its
effects on water resources over the Sub-Saharan Africa includes sea-level rises, floods, droughts and
water quality degradation. Communities in the rural areas are most disadvantaged through strains on
means of livelihood and access to water, food and health facilities. The paper underscores the challenges
of adapting to water stress from climate change and the implication on sustainability within the sociocultural context of the tropical rural environment. The findings suggest that indigenous culture and local
perceptions are vital for sustainable crisis intervention.
INTRODUCTION
The demand for water is much greater than the available supply in many parts of the world. This is
also affecting the developed world, where burgeoning demand simply cannot continue to be met and not
only developing countries, where water infrastructure is poor and where many people do not have access
to safe drinking water (The Royal Academy of Engineering, 2010). The degree of vulnerability among
different communities and households within the same country varies significantly from one to another.
This should be seen from the viewpoint that vulnerability is closely linked with social characteristics such
as ethnicity, religion, culture and norms amongst others (Pelser, 2001). For example, in rural areas of the
Natal Midlands, the Venda region and the Eastern Cape, traditionally, common people are forbidden to go
near sacred water sources, and only traditional healers associated with the water are allowed to approach
such areas (Bernard, 2000). Also, many communities restrict the distance to which cultivation can take
place and where buildings can be erected near their surface water sources (Ayeni, 2012). This is to honour
the gods of their forefather through the spirit of the water in question. Nonetheless, the growing impacts
of modernization and population pressure in many places are now reducing these traditional fears and
restraints (Bernard, 2000). To many traditionalists, this has been the causes of environmental change and
continually increases in wide anticipated water stress in most rural areas. For instance, most rural
78
communities in Southwestern Nigeria have been experiencing climatic uncertainties and changes in
responses to water stress and scarcity in the last three decades. These can be seen in their short-term
responses to water-climate risks and changes, in some cases, leading to mal-adaptation or the adoption of
measures that result to and/or create further health risk from hazards (Barnett and O’Neill, 2010; Fazey et
al., 2011).
Moreover, due to influence of cultural and traditional belief, adaptation in rural areas has been
oriented more towards short-term responses (rationing of surface water during the dry season) and less
towards long-term planning (involving local stakeholder participation and high level community water
management). Religious and traditional beliefs among rural communities play diverse roles and are
important in water management and defining adaptation strategies. There are different societal roles and
capacities to adapt to the impacts of climate change and climate change-induced water stress implications
that are bound to have varying and significant effects on the livelihoods of rural communities. Adaptation
is the means of reducing vulnerability to climate-induced changes and could occur either proactively via
anticipated concrete planned activities of projected needs and changes, or reactively, using available
resources in coping with the change (Hisali, et al., 2011). It could as well occur on both individual and
community levels (Jaglin, 2002). Understanding these diverse societal cultures and beliefs as well as
religious influence is essential for developing effective and proactive adaptation mechanisms.
There have been notable studies/researches at both global and regional scales on how governments,
societies as well as individuals will practically adapt to climate change. These include the works of
Burton (1996); Smit and Pilifosova (2001); Adger et al. (2005); Schipper and Burton (2009). Adger et al.
(2003) examined climate change adaptation in the developing world. Ayeni et al. (2011) evaluate the
basin optimization as effective adaptation strategy. The works of Barnett and O’Neill (2010); Fazey et al.
(2011) assess the various climate change mal-adaptation while assessment of the effectiveness actions for
ranking and developing normative criteria for successive adaptation was the focus of Adger et al. (2005).
Agrawala and Fankhauusal (2008) explored the adaptation scope and actions in various developed
countries, Agrawal and Perrin (2009) generated inventories of best practice and action in a change
scenario. Their works were clearly silent on the influence of cultural and traditional belief on poor
adaptation to climate change as well as a water stress adaptation mechanism. This creates the lacuna that
the study intends to fill.
As climate change progresses it is likely to have dramatic effects on the supply of water. In some
areas it may increase, for example at higher latitudes, but water-stressed areas in the mid-latitudes are
expected to face a reduction in available water. On a sub-continental scale, there are regional variations of
temperature trends. For instance, warming is observed in southern and western Africa, and the tropical
forests, while cooling is observed near lakes or coastal areas (Boko et al., 2007).
The study discusses adaptation challenging and rural water technologies for bridging loophole within
the framework of SW Nigeria rural communities. It will therefore examine how demeaning socio-cultural
and tradition nexus have influenced poor adaptation responses to water stress and what it might imply for
policy formulation.
METHODOLOGY
The set of required data for this research work includes historical and documented records over time
as well as relevant literature on the subject matter. Data were gleaned from existing literature and
critical/guided personal observation during the first author’s research field work for this study. The study
targets rural dwellers and therefore, answers from interactive questions during the field activities were
used to support authors existing literature and personal observation.
79
RESULTS
Factors Influencing the Usage of Surface Water
The significant factors that shape state of water availability in rural communities of Nigeria include
population, anthropogenic activities/land uses and changes and effects of climate change on the
hydrologic cycle especially the aspect of surface waters availability e.g. ponds, streams, springs, lakes and
rivers.
Population
Surface waters are the main sources of water in most derived savanna rural communities. As a result,
availability of these sources only last for about two months after raining season in October and by
February water scarcity is already at its peaks. It is noted that the increase in population resulting from
augmented immigration and birth rate could trigger a rise in basic demands i.e. food, water and housing.
Therefore, the consequence could eventually put an immense pressure on available limited water for
domestic use. Subsequently, high demand of food could result in a situation where land use change
converts natural recharge area for groundwater to agriculture and settlement areas. Intense water demand
as a coherent consequence of increased population may intensify the problem, as water might be overharnessed beyond its physical availability that is directly linked with recharge performance of the land.
Population increase gives additional burden to natural resources particularly water in the waterstressed regions. As the population growth rate rises, demand for water consumption becomes higher due
to direct relationship that exists between population and water withdrawals (Carter and Parker, 2009). The
influx of migrant is also a contributing factor to an increase in population growth in the area and this
situation is clearly noted in the rural communities where springs/ponds are the only source. This has
become a big obstacle for future sustainable water management and the problems have become even more
severe, especially during the peak dry season.
Anthropogenic Activities
Anthropogenic activities are yet other factors that have direct correlation with water
balance/hydrologic parameters, i.e. rainfall, infiltration, runoff and evapo-transpiration. A potential of
hydrologic impact of global warming may contribute to the change in water balance as changes in water
balance parameters increase or reduce, water recharge and change storage capacity. As a result, the
capacity of surface water to potential supply water for the rural communities is degraded as rainfall
reduces and ultimately, as water supply from surface water declines in the area water scarcity intensifies
and ends in water insecurity in the communities.
Slight changes in soil-atmospheric behavior may lead to environmental problems particularly removal
of vegetal cover and subsequently prone to water loss due to run-off (Gillieson, 1996). Soil capacity to
infiltrate water decreases as vegetated areas anthropogenically transforms to impermeable features such as
settlement, roads and buildings, land capacity to let water infiltrate decreases. This complicates water
shortage in water-stressed region.
Climate Change
The change in climate condition, to some extent, may have a significant impact on surface water
availability. The increased temperature leads to an increase of evapotranspiration, thus reducing the
recharge rate on a watershed scale and trigger more severe water depletion during dry season (IPCC
2007a; IPCC 2007b).
Demeaning Local Knowledge and Cultural Practices
Incorporation of indigenous knowledge on managing natural resources such as surface water is
crucial for building a strong foundation that will serve as a basis for long-term water conservation.
Finding shows that there is a serious danger when policy makers fail to recognize and embrace the
significant value of local water rights and knowledge access to water by all users (Cremers et al., 2005) as
80
preservation of biodiversity requires a cultural control that shares its manifestation in the form of
indigenous knowledge (Bridgewater and Arico, 2002). The indigenous socio-cultural dimension of
resources management in the rural communities has been changed due to modern social factors.
Traditional knowledge of managing water is important among rural communities because those who live
with natural resources are the ones that are most capable of preserving them (Agrawal, 2001). The failure
to recognize the local wisdom by policy makers have created a gap between the society and achieving
sustainable water use based on local knowledge, instead government demeaned the system that has been
embraced for generations and therefore, has resulted to decline in conservation measures by indigenes
around surface water sources.
Humanitarian Services in Water Management and Adaptation Mechanisms
Water insecurity in many places of the world has become a problem that without any urgent attention
may result to problems such as health, sanitation, poverty and food insecurity problems. As about 25% of
world population lives in regions with low or no access to fresh water (Gardner-Outlaw and Engleman,
1997), rapid economic growth and the increased population rate will intensify the situation in the future if
appropriate conservation mechanisms of the available fresh water are not well channeled.
The ability to manage water as a crucial natural resource entails a comprehensive set of concerns to
administer water in a way that accommodates ecological, economical, technical and societal acceptance
of a broader society (Bernhardi et al., 2000). Sustainable water management approaches vary spatially
with respect to how it is being addressed by communities with different social backgrounds and diverse
physical characteristics. According to Smet and Wijk (2002) it is an answer to the large scale breakdown
of water supply systems and government failure either to provide clean water or to devise a reliable and
consistently system where other agencies would supply water. Since governments were not good at
supplying the infrastructure for their populations, communities should utilize their skills and motivations
to meet their own domestic water needs through various humanitarian services. Water management option
in some rural communities of Southwestern Nigeria is not only considered as local knowledge but also
encourage physical characteristics into best conservation strategies through self-help services. Therefore,
efficient water preservation strategy needs to be designed in order to combat societal problems (water
issues and related conflicts) and the plausibility of the impact of global climate change.
Ponds and springs that are major water supply sources for most rural communities in Southwestern,
Nigeria are at stake, and as a result, potentially contribute to the decline in water supply. Water insecurity
remains the utmost problem as rural communities in the region depend on surface water (ponds, springs,
streams, rivers) for domestic water supply. Therefore, it is important that conservation mechanisms are
embarking on in order to overcome further future potential consequences. In acknowledging this,
communities’ effort-based sustainable water management methods that are friendly to rural communities
are drawn as humanitarian services framework for adaptation mechanisms in this study. They are
examined as follows.
Surface Water Catchment Protection
Recharge process is mainly governed by physical characteristics of the surface and drainage system
underneath. It is assumed that, with regard to the hydrologic cycle, the groundwater recharge process
initially starts upstream where precipitation occurs. Water infiltrates and feeds the aquifer which retains
and transports water to the adjacent outlets. This is crucial in determining the quantity and quality of
groundwater that emerges downstream as spring. Any negative modification such as removal of
vegetation, increase in built up size and waste disposal in this area could result in a decline of safe water
supply. Therefore, the extent of vegetation in the diffuse recharge area is very important to mainly act as a
buffer zone for water before it interacts with the earth's surface and appropriately penetrates the soil.
Reforestation can take place in the defined diffuse recharge area. The fundamental rationale that
underlays reforestation measures are not limited to the physical concept of the hydrologic cycle, but also
the economic purposes. The selection of local vegetation needs to take into account that the improvement
of inhabitants’ livelihood is the most important long-term objective in efforts to enhance natural resources
81
management in developing countries (Merrey et al., 2005). As a result, conservation of catchment surface
waters (ponds, rivers, streams, springs, lakes) areas should be totally embraced by rural communities by
cultivating plants/crops in the diffuse recharge area (Afrasiabian, 2007). This will accentuate infiltration
by increasing the quantity of water percolating down to the water table (Allen and Chapman, 2001). Type
of mini vegetation around sacred surface water catchment varies among different trees as observed in
most parts of Southwestern Nigeria e.g. around Osun Oshogbo river catchment, Arigiya spring at Ikare
Akoko, and in most communities. These trees require to be protected due to their dense canopy and high
adaptation with tropical environment (Russell-Smith et al., 2007). In addition, they could as well
strengthen local’s economy based on their economic value.
Public Awareness Campaign for Adaptation Mechanisms
Human and natural resources are exclusively interrelated. Man cannot survive to his utmost best
without making use of the resources, therefore, the resources at the same time must be well conserved.
Perceptions and attitude towards immediate environment and available natural resources (e.g. Water
source) determine life sustainability and the fate of the coming generation. Therefore, the recognition and
understanding of resource conservation in the context of sustainable water management is crucial in rural
domains. This could be achieved in rural areas through environmental education (promote water values,
habits and skills through training, indigenous knowledge coach) using local dialect as a means of
communication (Mogome-Ntsatsi and Adeola, 1995). Awareness campaign is, therefore, recommended
and to be facilitated by both federal, state and local governments.
Strengthening Communities’ Socio-Cultural Roles
In sub-Saharan Africa, the problem of resource scarcity prescribes that governments can no longer
rely on conventional means to successfully address the basic needs of their populations. Most rural
communities have historically developed adaptation mechanisms to deal with water-related stress and
scarcity problems (Tompkins et al., 2010). Community participation has been advanced in some places,
and strategically and potentially viable in complementing efforts to meet the needs (Njoh, 2002;
Fonchingong and Fonjong, 2003). The community head, elders and Community Development
Associations’ (CDAs) function is to regulate and manage water sources in their immediate environment
with various respected norms and customs. Ideally, this plays a crucial role in ensuring equal water usage
among inhabitants and conservation measures at spring site. In addition, in rural settings, community
members meet at community square at certain day depending on the elders’ arrangements to discuss
socio-economic, cultural values, technical issues and problems related to water sources management and
conservation measures. According to Ayeni (2012), the outcome of such meeting would be a significant
input for the regional authority to assess current policy concerning water and other socio-economic
policies. Empowering such system is an option that promotes sustainable adaptation mechanisms.
Government at all tiers should encourage and assist community heads and elders in coordinating and
promoting such system by incorporating it in their water policy.
Participatory Approach allows the community stakeholders to collectively share their viewpoints and
interest in a free and equal communication. It is expedient that there is no periodic discharge and water
quality data but the trend of the situation has been passed from one generation to another through
historical discussion (past and recent of water situations physically, socially and culturally) with respect
to functions and territories by communities, stakeholders - the heads, elders, and CDAs. This issue is
suggested to be driven by existing local knowledge.
The Case of Akoko Northeast, Nigeria
Akoko Northeast is a Local Government Area (LGA) in Ondo State, Nigeria with its headquarters in
the town of Ikare. The LGA lies between longitude 5o38’ & 6o04’East, and latitude 7o26’ & 7o42’N. It has
an area of about 372 km² and a population of 175,409 at the 2006 census. Other towns in the LGA include
Akunnu, Iboropa, Ikakumo, Ise and Ugbe.
82
Access to potable water in this LGA has been in continuous decrease. Where public water exists,
services are unreliable and unsustainable. This is because of the difficulties in maintenance, pricing and
operation/operational costs. In order to manage water crisis, various communities particularly the rural
indigenes adopted friendly humanitarian services to cope with water stress and other environmental
change nexus. The services include but not limited to searching, rationing, and storage amongst others.
The services are mainly small-scale water supply management of finding solution to the problem of
water stress. Searching strategy implies sourcing for water wherever is available, even outside one’s
community. It also requires long trek and/or walk to access available water sources, which at times
require one to cover as long as 10kilometers returned trip.
Rationing means that each community or household is allowed to access and collect/fetch water by
agreement and at an agreed time of the day or day of the week. This method is peculiar to wells and some
community boreholes. Vendor/packaging water means a situation where a household buys water from
truck vendors or buys sachet water for drinking and other domestic purposes. Some households store rain
water in a big container, which sustained them for a few weeks after the rains. Some abide by the queuing
system where fetching containers are lined up based on a first-come first-serve.
Access and time restriction in their custom simply means that they stay away completely from the
water supply sources in question for a period of time (some hours) to allow the source yield appreciable
quantity.
Springs Protection Techniques
Traditionally, the values placed on the springs make its protection and management unique.
Historically, springs protection represented an ingeniously simple idea and first developed in the late
1940s when public water supply was under the control and supervision of native authority. In spite of the
inauguration of pipe borne water in parts of the LGA in the late 1950s, the communities still maintain
their indigenous protection and service culture as if they foresee the future water stress and scarcity.
The spring’s environment is cleared and made clean, then, mixture of stones between 15 to 30kg and
cement will be used to mount a solid concrete wall around the spring so that dirt, debris and other solid
will not contaminate the embarked water. Staircase or steps are made on one side for people to fetch
water at their convenience (Figure 1). Stones and fine sand particles are spread along the entrance and
surroundings of others to prevent debris and dirt from entry the springs (Figures 2 & 3). Spring is also
housed (concrete material and roofed) with dispensing outlet through which community members can
fetch water (Figure 4) and amongst other methods.
83
FIGURE 1
SURFACE WATER PROTECTION
FIGURE 2
84
FIGURE 3
FIGURE 4
85
CONCLUSION
To complement government efforts in reducing the impacts of climate change and water stress in the
rural area, protection of surface water is important for the rural communities as it continuously provides
water for domestic uses. If exclusively managed in line with knowledge that suits local tradition, it will
meet the primary functions (basic life support and economic roles in the community) and secondary
functions (administrative, social and ecological). This is because the local knowledge by which the
communities manage their surface water and its ecosystem has a well-designed organizational
arrangement. Stakeholders’ roles and community water rules should therefore be encouraged by
community members, and emphasizing the importance of humanitarian services and indigenous water
management to younger generations for the system sustainability. It is, therefore, concluded that the
inhabitants will keep on supporting and promoting their village system if exclusively supported by policy
and their indigenous knowledge taken into cognizance in planning.
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A Longitudinal and Multilevel Investigation on Factors
Influencing Knowledge Sharing Behavior
Quan Lin
Shantou University
Di Ye
Shantou University
Bocai Bi
Shantou University
In this paper, we explore the individual-level and group-level factors influencing knowledge sharing
behavior and its multi-phase influencing mechanism based on the data from 481 members and 67 groups.
The result demonstrate that: (1) individual-level knowledge sharing behavior affects knowledge sharing
behavior of next phase; (2) learning effect of previous phase has partial mediation effect on the
relationship between the previous knowledge sharing behavior and current knowledge sharing behavior;
(3) group-level knowledge sharing behavior has positive direct effect on individual-level learning effect;
(4) group cohesion has positive direct effect on individual-level knowledge sharing behavior. The
theoretical and practical implications of these findings are discussed finally.
INTRODUCTION
In the new economy, the organizing innovative capacity is considered to be one of the key abilities for
organizational development. The process of innovation is aimed at searching for and transmitting the new
technical and organizational knowledge through the circulation of knowledge creation, reserve, transfer
and application (Alavi & Leidner, 2001; Nonaka, Byosiere, Borucki, & Konno, 1994). To some extent,
the knowledge transfer in the organization relies on the employees’ knowledge sharing behavior.
Therefore, the degree of knowledge sharing behavior affects the organizing innovative ability and
development ability directly. Knowledge is present in the human mind, but as the subject of knowledge
sharing behavior, employees do not tend to take the initiative to sharing knowledge because of the
conflicts of interest, social dilemmas and etc. Thus, how to stimulate individual knowledge sharing
behavior has become the key of organizational knowledge management(H.-L. Yang & Wu, 2008).
The factors which is affected the knowledge sharing behavior have been studied from different levels
and perspectives, including the cultural characteristics, environmental factors, motivational factors,
interpersonal and team characteristics, individual characteristics, etc (Wang & Noe, 2010). However, most
of these researches focused on a single level (He & Wei, 2009), and verified hypotheses based on the
cross-sectional data, thus the results are not very much reliable and persuasive. Furthermore, such
researches are very difficult to analyze the influences which the organization, team and individual factors
88
bring to knowledge sharing behavior in multi-levels. In fact, the knowledge sharing behavior is inevitably
influenced by bound to be influenced by different factors in multi-levels because it is embedded in groups
and teams. Therefore, the researches on the knowledge sharing behavior are multilevel in essence. Many
scholars have pointed out the lack of multilevel research on the knowledge sharing behavior (Hsu, Ju,
Yen, & Chang, 2007; Wang & Noe, 2010), and now the researchers call for more longitudinal study to
complement (G. W. Bock, R. W. Zmud, Y. G. Kim, & J. N. Lee, 2005; Jiacheng, Lu, & Francesco, 2009;
S.-C. Yang & Farn, 2009).
In conclusion, this study decides to adopt multi-stage and longitudinal data and hierarchical analysis
method. The influence factors and process of knowledge sharing will be studied from both individual and
group level. At the individual level, we focus on the effect between inter-period knowledge sharing
behaviors, namely, the effect of individual knowledge sharing experience on the emerging of knowledge
sharing behavior and mediating effect of individual learning on inter-period knowledge sharing behavior.
At the group level, we focus on team knowledge sharing behavior, and cross-level effect of team cohesion
and group task conflict on individual knowledge sharing behavior. In addition, we will examine the crosslevel and interactive effect of individual level and group level.
This research makes the contributions to the research of knowledge sharing in the following aspects.
First, based on individual learning effect, this study researches the influence process and degree of
previous individual knowledge sharing behavior to current individual knowledge sharing behavior, and
reveals the importance of knowledge sharing experience in the influence factors of individual knowledge
sharing behavior. Second, we take knowledge sharing behavior of group level into consideration and
examine the effect of previous team knowledge sharing behavior on current individual knowledge sharing
behavior. Finally, based on Interactional psychology (Schneider, 1983; Tett & Burnett, 2003; Tett &
Guterman, 2000) and theory of situational strength (Mischel, 1968, 1977), we integrates the variable of
individual and group level through the interaction of hierarchical variables to investigate group
differences of the effect of previous individual learning effect on current knowledge sharing behavior. As
far as we know, it is very rare to apply the hierarchical longitudinal research methods in the study of
knowledge sharing behavior. We tested the model with using Hierarchical Linear Modeling(Bryk &
Raudenbush, 1992) and longitudinal data. This study also answered the researches’ call (e.g. G. W. Bock
et al., 2005; Jiacheng et al., 2009; S.-C. Yang & Farn, 2009) for using longitudinal data to research
knowledge sharing behavior.
THE THEORETICAL BACKGROUND AND RESEARCH HYPOTHESES
Individual Knowledge Sharing Behavior: The Concept and the Understanding in Cross-Level
Knowledge sharing refers to the provision of task information and know-how to help others to solve
problems, develop new ideas, and implement policies or procedures (Cummings, 2004; Hansen, 1999;
Wang & Noe, 2010). It is an interactive process between team members in the workplace (Srivastava,
Bartol, & Locke, 2006). Other studies have shown that the social exchange theory and the theory of social
dilemma may help us to understand under what circumstances knowledge sharing is most likely to occur
(Wang & Noe, 2010).
Suppose that team knowledge sharing is considered as a generalized social exchange process. Social
exchange process depends on the foundation of trust. As a result, trust will play an important role in the
process. That is, high trust is beneficial to the occurrence of knowledge sharing, and vice versa. Existing
researches also supported this view. For example, source trustworthiness helps enhance knowledge
transfer across units (Szulanski, Cappetta, & Jensen, 2004), perception of trust also affects knowledge
sharing (Jones & George, 1998). At the same time, individual knowledge sharing behavior is a decisionmaking process to decide whether to share the knowledge or not by considering its costs and benefits.
Only when predicted earnings are more than predicted cost can knowledge sharing happen (Constant,
Kiesler, & Sproull, 1994). Individual knowledge sharing makes more organizational members to master
knowledge. To gain organizational innovation and development it is necessary for organization to transfer
knowledge. In this case, it is very likely to appear "free-rider" phenomenon. That is, the individual shares
89
benefits from others’ thoughts and knowledge with no payment. The phenomenon makes the members
who shared knowledge can’t get relevant repayment. Accordingly, rational individuals will chose not to
share knowledge. Consequently, individual-rationality will expand to collective-irrationality, this could
ultimately lead the process of knowledge sharing to trap to social dilemma (Wang & Noe, 2010) which
affects the members’ will to sharing knowledge. Above knowable, the risk perception exists in the
decision-making process of knowledge sharing would clearly affect the occurrence of knowledge sharing
behavior.
FIGURE 1
A MULTILEVEL MODEL OF TEAM KNOWLEDGE SHARING BEHAVIOR
Group
Team characteristics (T2)

Team cohesion

Team task conflict
Team knowledge sharing
behavior (T1)
H4a & H4b
H3
Bottom-up
Individual
Individual knowledge
sharing behavior (T1)
H5
Individual learning
effect (T1)
Individual knowledge
H1 & H2
Therefore, the increasing trust and perceived risk reduction can promote knowledge sharing behavior
in group interaction. At the individual level, individual positive experience on knowledge sharing may
improve the mutual trust between team members and reduce the perceived risk, and that ultimately
promote individual knowledge sharing. In addition, according to situational strength theory (Mischel,
1968, 1973), there is consistency of individual behaviors in different situation. At the same time, the
situation can lead to the similarity in behaviors of different individuals. Under the condition of high
situational strength, individual differences are small, while in the case of low situational strength,
individual differences are great. And from the perspective of team characteristics, team cohesion and task
conflict have influence on team trust and risk perception. Above all, we propose the research model
shown in Fig. 1.
The Individual Level of Knowledge Sharing
The core of social exchange theory is "reciprocity". Its reward and cost can be material wealth,
psychological wealth and social wealth. The theory insists that social exchange produced social rewards,
such as respect, admiration and status. The sharer can gain recognition and respect through showing the
expertise. The underlying reason is that people were eager to be regarded as experts and partners. This
will let them want to share the knowledge (O'Dell & Grayson, 1998). As the typical form of social
exchange, reciprocity makes the individual produce the feeling of responsibility, gratitude and trust. The
purpose of the individual to choose sharing knowledge is to gain future reciprocity and the recognition of
others. Expected reciprocity has a significant effect on the individual attitude toward knowledge sharing.
90
People generally believe that knowledge sharing is an effective way to form, maintain and strengthen the
relationships, and hope to gain the benefits from the relationships (G.-W. Bock, R. W. Zmud, Y.-G. Kim,
& J.-N. Lee, 2005).
The positive experiences of individual knowledge sharing in the past make the members produce
more trust to knowledge sharing and build trust between the team members, which lead the members to
produce more expectation to future reciprocity. It is the expectation to material, psychological and social
rewards in the future that makes the members’ attitude toward the next knowledge sharing more positive.
In addition, the positive experiences can also help the sharer and other members increase the familiarity
of the process of knowledge sharing, and reduce the risk perception because of the lack of experience and
insufficient information. The reduction of risk perception will be beneficial to promote more knowledge
sharing behavior. In conclusion, we suggest that:
Hypothesis 1: the current individual knowledge sharing behavior is positively related to
the next individual knowledge sharing behavior.
Building on hypothesis 1 as well as the above arguments and research evidence, the reason why
people share knowledge is social exchange, and the core of social exchange is “reciprocity” (G.-W. Bock
et al., 2005). If knowledge sharing between the team members is regarded as a social exchange in a broad
sense, then the benefits that the member gain from the knowledge sharing mainly show by others’
knowledge and information. Those knowledge and information are benefit to improving learning effect.
So, individual learning effect plays an important role between the previous knowledge sharing behavior
and current knowledge sharing behavior. Specifically, individual knowledge sharing behavior brings the
improvement of learning effects. This improvement makes the individual perception to benefits more
obviously. Meanwhile, it can also help to reduce the risk perception on the knowledge sharing of next
phase, then make the significant and positive impact on the attitude toward the next knowledge sharing.
So, we suggest that:
Hypothesis 2: individual learning effect is a mediator between the previous knowledge
sharing behavior and current knowledge sharing behavior.
The Group Level of Knowledge Sharing Behavior
Situational strength theory (Mischel, 1968, 1973, 1977) argues that individual behavior is interactive
action of the individual and situation. Situational cues are clearer under the condition of high situational
strength, which make the expectations of the situation convey to the individual more powerful, and thus
limit the expression of individual characteristics. Individual behaviors are more affected by the situation,
and individual differences are smaller. On the contrary, situational cues are vague in the case of low
situational strength so that the limitation of the expression of individual characteristics is weaker. Thus
Individual differences are bigger.
In view of the above, team knowledge sharing, team cohesion and team task conflict are all important
team situational variables to individual knowledge sharing. With low situational strength, there is no close
relationship between team situational variables and individual knowledge sharing behavior. While in the
case of the high situational strength, the relationship is closer.
Team Knowledge Sharing Behavior
In the team that knowledge sharing activities are frequently, team members can have more
opportunities to gain other members’ exclusive knowledge and information. These knowledge and
information can improve the individual learning effect. In addition, if the atmosphere of knowledge
sharing in the team is stronger, the member affected by the atmosphere may be more active and willing to
accept the knowledge and information which other members shared. Therefore, we argue that in the team
that knowledge sharing activities are more frequently, the member’s learning effect is higher, and vice
versa. So, we suggest that:
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Hypothesis 3: after controlling the influences on individual knowledge sharing of
individual level, knowledge sharing of group level is positively related to individual
learning effect.
Team Cohesion
Team cohesion is the attraction between the team members and the strength of the willingness to stay
in a organization (Keyton & Springston, 1990). In the team of high cohesion, members have more intense
to cooperate and interact. George and Bettenhause (1990) have revealed that team cohesion would have a
positively prediction effect on the prosocial behavior. A meta-analysis also shows that the high correlation
between cohesion and behavior performance (Beal, Cohen, Burke, & McLendon, 2003). Based on the
above analysis, we assume that high team cohesion is positively related to individual knowledge sharing
behavior. So, we suggest that:
Hypothesis 4a: after controlling the inter-period influences on individual learning effect
of individual level, team cohesion of group level is positively related to individual
Team Task Conflict
Team task conflict is referred as the disagreement among the member on the task process, because of
the difference of the members’ cognitive on the process and the way to achieve the task’s purpose. (K.A.
Jehn, Northcraft, & Neale, 1999). On the one hand, when the conflict exists, the member lacks the will to
share knowledge with others and tends to think that other members want to influence him by sharing
knowledge. This will lead to distrust on the shared knowledge. On the other hand, the existence of the
conflict will lead the member to doubt about other members’ motivations to put forward different ideas,
even think normal interaction as a personal attack (Karen A Jehn, 1997). (R. A. Baron, 1984) also pointed
out that the exchange of the divided opinions would often become the transmission of the negative
emotion in the early stage of the conflict, thus causing members to waste too much time and energy on it
and eventually leading to the reduced level of knowledge sharing related to the task. So, we suggest that:
Hypothesis 4b: after controlling the inter-period influences on individual learning effect
of individual level, team task conflict of group level is negatively related to individual
The Multi-Level Interactions of the Situation
The past experience on knowledge sharing behavior has different influences in different
situation(Wang & Noe, 2010). As situational strength theory (Mischel, 1968, 1977) said, under the
condition of high situational strength, individual behavior will be more affected by the situation. And
members’ behaviors have higher consistency. On the contrary situation, individual behaviors will have
more individual differences because of the lack of corresponding norms or rules. In the team with obvious
team character (such as high team cohesion), team knowledge sharing behavior is less affected by
individual experience, inter-individual differences on knowledge sharing behavior will be smaller. In the
other team with weak team characters (such as low team cohesion), team knowledge sharing behavior is
less affected by the situation, but more affected by individual experience. That is, situational factors
moderates the relationship between individual learning effect and inter-period individual knowledge
sharing behavior. So, we suggest that:
Hypothesis 5: team character of group level moderates the relationship between
individual learning effect and inter-period individual knowledge sharing behavior such
that the relationship is weaker when the team characters are more obvious, and vice
versa.
92
METHODS
Sample and Procedure
Participants were chosen from a comprehensive university with high popularity. They were all
undergraduates who participated in human resource management and operation management courses. 535
students had participated in our survey for one semester (16weeks). Of these students, 246 were male,
accounting for 46% of the sample.
The research is conducted as follows: over a 3-week period at the beginning of new semester, we
administered questionnaires of personal qualities to the students who volunteered to participate. Then they
were randomly divided into groups. Finally, we have 67 groups and the group scale ranged from 5 to 9. In
the middle of the semester, the students were given group assignment to complete in groups. The
assignment was related to the courses they studied. After the assignment was completed, the students also
completed a survey with questions about the relevant variables.
The survey during the research process was implemented by online-questionnaires. So we also
objective recorded of the time that the students used in the process of questionnaire completion to help us
judge the validity of the questionnaire. If the time was less than 2 minutes or the completion was less than
90 percent of the questionnaire, that questionnaire was judged as invalid. Finally, we obtained 481 valid
questionnaires. The valid rate was 90%.
Measures
Knowledge sharing behavior: using the 5-item measure from Chen et al (2009). A 5-point Likert-type
scale, ranging from 1 (“strongly disagree”) to 5 (“strongly agree”), was applied to the measure. The items
are “I often spend a lot of time sharing knowledge with team members” “I often actively share my
knowledge with team members”, “I often take part in discussing several aspects of the task, rather than a
particular aspect”, “I often respond to comments that others make to my advices”, “I often participate in
knowledge sharing activities in group”. The Cronbach’s alpha for the scale was .84.
Learning effect: because of no ready-made measure, we independently developed a 4-item measure
according to the definition of learning effect and the situation. A 5-point Likert-type scale, ranging from 1
(“strongly disagree”) to 5 (“strongly agree”), was applied to the measure. The items are “learn a lot of
new knowledge”, “get lots of new inspiration”, “learn the new method to solve the problem”, “learn the
new way to thinking”. The Cronbach’s alpha for the scale was .84.
Group-level antecedents: the group-level antecedents are formed by individual-level antecedents. We
examined the validity of the group-level constructs using Rwg (James, Demaree, & Wolf, 1984, 1993),
intraclass correlation (ICC[1]) and reliability of the mean (ICC[2]). The indexes of all variables met the
requirement well. Specific indexes are presented in table 1.
Team cohesion: using the 6-item measure by adapting the measures from Faraj & Yan (2009) and
Tekleab et al (2009) into group-level. A 5-point Likert-type scale, ranging from 1 (“strongly disagree”) to
5 (“strongly agree”), was applied to the measure. The items are “our team members try the best to achieve
its performance targets together”, “all our team members are responsible for any loss or low
performance”, “our team members can communicate freely and complete our respective responsibilities
to this project”, “Our team members can help each other when we do the group projects”, “our team
members get along well”, “our team members work closely together”. The Cronbach’s alpha for the scale
was .91.
Task conflict: using the 3-item measure from Jehn et al (1999). A 5-point Likert-type scale, ranging
from 1 (“never”) to 5 (“very infrequently”), was applied to the measure. The items are “number of times
that the member don’t agree to what every member should do”, “number of times that the member don’t
agree to the way to complete group tasks”, “number of times that the appearance of the conflict on the
task assignment in group”. The Cronbach’s alpha for the scale was .87.
93
Data Analysis
First, we tested the reliability and validity of the scale of variables. The variables of group level were
combined by variables of individual level, so we tested the validity the construct of group-level variables
by testing variables’ intraclass consistency Rwg (James et al., 1984, 1993), intraclass correlation (ICC[1])
and reliability of the mean (ICC[2]).
The model of knowledge sharing behavior in this study was cross-level. The dependent variable,
knowledge sharing behavior and the mediator, learning effect are the variable of individual level and the
independent variables includes variables of individual level and group-level. So, we use Hierarchical
Linear Model (HLM) (Bryk & Raudenbush, 1992) to test the model in the following steps. First, we
estimated the following models according to the steps related to testing mediator(R. M. Baron & Kenny,
1986): (1) the dependent variable, individual learning effect (T1) was predicted by individual knowledge
sharing behavior (T1) in the model; (2) the dependent variable, individual knowledge sharing behavior
(T2) was predicted by individual knowledge sharing behavior (T1) in the model; (3) the dependent
variable, individual knowledge sharing behavior (T2) was predicted by individual learning effect (T1) in
the model; (4) the dependent variable, individual knowledge sharing behavior (T2) was predicted by
individual knowledge sharing behavior (T1) and individual learning effect (T1) in the model. In addition,
we estimated the model, which included the dependent variable, individual learning effect (T1) and the
independent variables, individual knowledge sharing behavior (T1) of individual level and team
knowledge sharing behavior (T1) of group level. In order to test cross-level and direct effect of team
characters, we analyzed in the following three steps: (1) we estimated a null model to analyze the makeup
of intraclass and interclass variance of individual knowledge sharing behavior. The null included the
independent variable, individual knowledge sharing behavior (T2) but no other independent variables of
individual and group level. (2) individual-level analysis: adding individual learning effect to test the effect
on knowledge sharing behavior. (3) group-level analysis: adding team cohesion and team task conflict to
test cross-level and direct effect on knowledge sharing behavior. Finally, we analyzed the interaction by
estimating the slope of group-level variables to individual-level variables. All model estimations have
controlled the influence of individual gender and GPA.
RESULTS
The Validity of Measures
The Validity of Knowledge Sharing Behavior
Due to knowledge sharing behavior is the main dependent variable and we applied self-report to
measure, we analysis in the following steps to verify the validity of the construct of knowledge sharing
behavior. First, we tested the dimension of knowledge sharing behavior by factor analysis. The results
showed that the items all belong to a factor, and have high factor loadings (the load average is 0.78), the
factors’ cumulative explained 61% of variance. Then, we tested the criterion-related validity of
knowledge sharing behavior by testing the relationship between knowledge sharing behavior and other
variables which are related to knowledge sharing in theory. In the table 1 we can see the correlation
results are consistent with the theoretical model proposed. At the individual level, knowledge sharing
behavior (T1) and knowledge sharing behavior (T2) are significant related to learning effect (T1)
; r .38, p < .01 ). At the group level, team knowledge sharing behavior (T1) is significant
( r .37, p < .01
=
=
related to team cohesion (T2)
( r .71, p < .01 ) and team task conflict ( r =
=
−.38, p < .01 ). These results
indicate that knowledge sharing behavior has a good criterion-related validity.
In addition, we tested the discriminate validity of knowledge sharing behavior by testing the
relationship between knowledge sharing behavior and other uncorrelated variables to knowledge sharing
in theory. There is no theoretical and empirical evidence can test the significant correlation of knowledge
sharing behavior to individual gender and GPA. The data results show that there is no significant
relationship between knowledge sharing behavior (T1) and gender
( r .09, p > .1 ) or GPA
( r .05, p > .1
=
=
), and also between knowledge sharing behavior (T2) and gender ( r =
( r .03, p > .1 ).
=
−.01, p > .1 ) or GPA
94
So, this measure has acceptable discrimination validity.
In a word, the above results show that the knowledge sharing behavior is the structure of a single
factor. And it is significantly related to the relevant variables in theory, while there is no significant
relationship with the unrelated variables which comes from the same source. So, the measurement of the
scale is effective.
TABLE 1
CORRELATIONS, CREDIBILITY, MEANS, STANDARD DEVIATIONSa
Variables
Mean
Level 1
1. Individual knowledge sharing
3.73
behavior (T1)
2. Individual knowledge sharing
3.73
behavior (T2)
3.84
3. Learning effect (T1)
b
0.54
4. Gender
3.21
5. GPA
Level 2
1. team knowledge sharing behavior
3.72
(T1)
2. team cohesion (T2)
3.96
3. team task conflict (T2)
2.33
SD
1
3
2
4
0.58
(0.84)
0.58
0.62** (0.87)
0.71
0.50
0.59
0.37** 0.38** (0.90)
0.09
-0.01 -0.01
0.05
0.03
0.07 0.29**
0.31
(0.84)
0.32
0.71** (0.91)
(0.87)
0.38** 0.45**
0.36
a
n＝481 at the individual level, n=67 at the group level. Internal consistency reliabilities of variables
are provided in diagonal parentheses.
b
Intraclass R2 is calculated based on the proportion of variance in team which can be explained by
the variables of level 1.
†
P<0.10, * P<0.05, ** P<0.01
The Combination of Variables of Group Level
We tested the feasibility of group-level variables (team knowledge sharing behavior, team
identification, innovation atmosphere, relationship conflict and task conflict) on the merging of individual
data. So, we calculated variables’ Rwg, ICC [1] and the ICC [2] to test intraclass consistency and
hierarchical characteristics. Rwg is calculated by reference uniform distribution (James et al., 1984, 1993),
the calculation of ICC [1] applied the formula=
( ICC[1] τ 00 / ( τ 00 + σ 2 ) which was suggested by
Hofmann, ICC[2] was calculated with using the formula ( ICC[2] =
k * ICC(1)
)(Bliese, 2000).
1+(k - 1)* ICC(1)
The results are shown in table 2. And we can see the data is suitable for merge operations.
TABLE 2
VARIABLES’ Rwg AND ICC
Variables
Team knowledge sharing behavior (T1)
Team cohesion (T2)
Team task conflict (T2)
Rwg
0.94
0.94
0.87
ICC[1]
0.11
0.13
0.04
ICC[2]
0.90
0.91
0.74
95
The HLM Results: The Cross-Level Effect of Individual Knowledge Sharing and Mediating Effect
of Learning Effect
The Inter-Period Effect of Individual Knowledge Sharing Behavior
We purposed that individual knowledge sharing behavior had positive influence on inter-period
knowledge sharing behavior. The hypothesis 1 gets support, which means that regression coefficients of
individual knowledge sharing behavior (T1) to individual knowledge sharing behavior (T2) must be
significant. So, we estimated the model which included control variables and individual knowledge
sharing behavior (T1) model with HLM. The result shows that the regression coefficient is significant
( β.64, p.01
=
< ) in model 3 of table 3. So, hypothesis 1 gets the support.
TABLE 3
HLM RESULTS OF INTER-PERIOD PROCESS OF INDIVIDUAL
KNOWLEDGE SHARING BEHAVIOR a
Variables
Fixed effect
Level 1
1.96**
(0.07)
Individual
knowledge 0.45**
(0.00)
Individual learning effect
(T1)
Gender
-0.10
GPA
0.08
Level 2
Team knowledge sharing
behavior (T1)
Variance analysis
Intraclass variance
0.43
Deviance
776.15
Intercept
a
Individual learning
effect (T1)
Model
Model 2
1
Individual knowledge sharing
behavior (T2)
Model
Model 4 Model 5
3
0.20
(0.27*)
0.25**
(0.02)
1.28**
(0.37)
0.64**
(0.03)
-0.10
0.08
2.48**
(0.16)
-0.07
0.03
0.32**
(0.01)
-0.02
0.01
1.01**
(0.46*)
0.57**
(0.02*)
0.14**
(0.01**)
-0.06
0.03
0.19
385.25
0.27
489.06
0.18
376.21
1.34*
0.43
774.56
n＝481 at the individual level, n=67 at the group level (because the missing items are deleted in model
1and model 2, n=49), random variance is provided in parentheses.
b
Intraclass R2 is calculated based on the proportion of variance in team which can be explained by the
variables of level 1.
†
P<0.10, * P<0.05, ** P<0.01
The Mediating Effect of Learning Effect
We estimated the following three models according to the steps related to testing mediator (R. M.
Baron & Kenny, 1986): (1) the dependent variable, individual learning effect (T1) was predicted by
individual knowledge sharing behavior (T1) in the model; (2) the dependent variable, individual
knowledge sharing behavior (T2) was predicted by individual learning effect (T1) in the model; (3) the
dependent variable, individual knowledge sharing behavior (T2) was predicted by individual knowledge
sharing behavior (T1) and individual learning effect (T1) in the model. Results are shown as model 1,
model 4 and 5 of table 3. We can see the regression coefficient of individual knowledge sharing behavior
96
(T1) is significant to individual learning effect (T1)
( β.45, p.01
). The regression coefficient of
=
<
individual learning effect (T1) is significant to individual knowledge sharing behavior (T2)
). And in the model 3, the coefficients of individual knowledge sharing behavior (T1)
( β.32, p.01
=
<
and individual learning effect (T1) are still significant=
( β.57, p.01
, β.14, p.01
), but the
< =
<
coefficient of individual knowledge sharing behavior (T1) drops. So, individual learning effect has partial
mediating effect, hypothesis 2 gets partial support.
The HLM Results of the Cross-Level Effect of Team Knowledge Sharing and Team Characters
The Cross-Level Direct Effect of Team Knowledge Sharing Behavior
We applied HLM to analysis because of the involved individual and group level. At the individual
level, we controlled the influence of individual gender and GPA. At the group level we included team
knowledge sharing behavior. Results showed that there is significant positive correlation between team
knowledge sharing behavior and individual learning effect
( rˆ .25, p < .01 ). So, hypothesis 3 gets
=
support.
The Cross-Level and Direct Effect of Team Characters
The hypothesis 4a and 4b get the support, which means that the inter-team variance of knowledge
sharing must be significant. To test hypothesis 4a and 4b, we estimated the three HLM model. First, we
estimated the null model which only consists of the control variables of individual level with no variables
of individual and group levels. The results are shown in the null model of table 4. The variance of the
intercept of group level is significant =
( τˆ00 .02, p < .05 ). The ICC [1] of individual knowledge sharing
behavior (T1) is .11, indicating 11% of the variance of knowledge sharing behavior between groups, 89%
of the variance is within the group.
TABLE 4
THE RESULTS OF CROSS-LEVEL EFFECT ON KNOWLEDGE SHARING BEHAVIOR a
Variables
Fixed effect
Level 1
Intercept
Individual
learning
effect (T1)
Gender
GPA
Level 2
Team cohesion (T2)
Team task conflict (T2)
Variance analysis
Intraclass variance
Intraclass R2 b
Inter-class R2
Deviance
a
Individual knowledge sharing behavior (T2)
Null model
Model 1
Model 2
3.67**(0.02*)
-0.03
0.03
2.48** (0.16)
0.38(0.29*)
0.32** (0.01)
0.25** (0.02)
-0.02
0.01
-0.02
0.03
0.55**
0.06
0.32
636.09
0.27
0.16
489.06
0.25
0.07
465.41
n＝481 at the individual level, n=67 at the group level (because the missing items are deleted
in model 1and model 2, n=49), random variance is provided in parentheses.
b
Intraclass R2 is calculated based on the proportion of variance in team which can be
explained by the variables of level 1.
†
P<0.10, * P<0.05, ** P<0.01
97
Model 1 included individual learning effect (T1) of individual level. Model 2 added team cohesion
(T2) and team task conflict (T2) on the basis of model 1. Results showed that there was a significant and
positive correlation between team cohesion
( rˆ .55, p < .01 ) and knowledge sharing behavior after
=
controlling the influence of individual level. So, hypothesis 4a is supported, while hypothesis 4b is not
supported.
The Test of Cross-Level Moderating Effect of Team Characters
Hypothesis 5 proposed the cross-level moderating effect. The premise behind the test of the effect is
individual learning effect have significant random variance in the model whose result is the intercept. As
we can see from the random variance which is provided in parentheses of model 2 in table 4, individual
learning effect did not have significant random variance. Above all, hypothesis 5 did not get the support.
DISCUSSIONS
Existing researches on knowledge sharing behavior are divided and focused on the individual or
group level, but this study considered two perspectives of macro and micro, combined with the effect of
these two levels. We proposed and tested a hierarchical model of knowledge sharing behavior, and
verified the effect of variables of individual level (inter-period individual knowledge sharing behavior,
individual learning effect) and group level (team knowledge sharing behaviors and characteristics), and
multi-level moderating effect. Our study found that there are individual and group differences among
knowledge sharing behaviors, inter-period individual knowledge sharing behavior and team characters of
group level—team cohesion can explain most of the variance.
Individual knowledge sharing behavior which had been combined to group level can explain the
majority of the variance of individual learning effect through a bottom-up process. At the same time, there
is a positive relationship between the individual knowledge sharing behavior and learning effect. In
addition, we used HLM to analysis in cross-level. Thus we can test multi-level moderating effect of team
characters on knowledge sharing behavior while testing the effect of individual learning effect on
knowledge sharing behavior. This study answers the calls of researchers(Wang & Noe, 2010) as
mentioned above it is also benefit to do deeper into the research about the affecting factors of knowledge
sharing behavior.
This study triggered our further thinking on the knowledge sharing behavior. Future research may
need to make some necessary changes of the model or variable measurement. For example, there was no
significant correlation between task conflict and knowledge sharing behavior. Based on the situational
strength theory, the cross-level interaction of individual and group level should have a moderating effect
on knowledge sharing behavior. However, the hypothesis in the study did not get support. It means that no
matter how to change team characters, the effect of individual learning effect on knowledge sharing
behavior is not change. One possible explanation is that this cross-level moderating effect may also be
affected by knowledge complementary difference of members. Stronger the knowledge complimentary is,
more obvious the moderating effect is, and weaker the knowledge complimentary is, weaker the
moderating effect is. In other words, in this interactive moderating effect is a three-way interaction. We
can add knowledge complementary to further test the existence of the three-way interaction adjustment in
the future.
STUDY LIMITATIONS AND FUTURE RESEARCH DIRECTIONS
This study has at least several limitations that may be addressed by future research directions. First, as
the mainly dependent variable in the study, the knowledge sharing behavior was measured by means of
self-report, this may bring the problem of common method variance. We have verified that there was no
problem of common method variance in the data of this study. However, future research still need to try to
98
further strengthen the research of reliability and persuasive through a variety of data sources (e.g., add the
measuring way of others’ evaluation).
Second, although we proposed the key factors that may have influence on knowledge sharing
behavior of different levels, we did not take some other important and deserved variables into
consideration (e.g., individual experience and attitude of knowledge sharing, structural factors of team
characters: knowledge complementarity of team members, the heterogeneity of education levels and
values, etc).
Third, the limitation is a common problem in the findings of the studies. Participants for this study are
university students. Even though the knowledge sharing behavior of students in the university do not have
a fundamental difference with the knowledge sharing behavior of the members in other organizations,
future studies need to promote the finding to be generalizable.
MANAGERIAL IMPLICATIONS
To a large extent, the success of organizational knowledge management lies on the degree of team
knowledge sharing activity, so organizations must consider how to transfer expertise and knowledge from
experts who have it to novices who need to know (Hinds, Patterson, & Pfeffer, 2001). However, the
process of knowledge sharing does not happen naturally, there are a lot of factors that affect team
knowledge sharing. To help managers to better trigger team knowledge sharing we should understand
these factors and how these factors interactive affect.
The results of this study show that the degree of the members’ knowledge sharing with others is
affected by individual experience of knowledge sharing, and individual learning effect is the mediator in
the effect. So in the process of knowledge management, managers should pay the attention to members’
knowledge sharing behavior and willingness in the early stage of team knowledge sharing. And
strengthen the management of individual learning effect. Factors which affect individual learning effect
are various (e.g., others’ support and help, organizational training, individual knowledge structure and
learning ability). In addition, team cohesion can also promote team members for knowledge sharing, so
managers can improve team cohesion through a variety of ways to promote the interaction and
cooperation between team members. That is conducive to team knowledge sharing.
The study takes the variable of individual level and group level into account at the same time, puts
forward a hierarchical and theoretical framework of knowledge sharing behavior, and tests the cross-level
effect through the cross-level and longitudinal data. In conclusion, this study makes great contribution to
the research on knowledge sharing behavior and learning effect.
ENDNOTES
1.
Acknowledgements: This work is supported by Humanities and Social Sciences Foundation of the Ministry
of Education in China (No. 13YJA630049), the Natural Science Foundation of Guangdong (No.
10451503101006375), Foundation for Developing National Foundation of Shantou University (No.
NFC12006), Foundation for Creative Research Groups of Shantou University (No. ITC10004).
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