2012 International Conference on Innovation and Information Management (ICIIM 2012)
IPCSIT vol. 36 (2012) © (2012) IACSIT Press, Singapore
Knowledge Management Analysis: A System Dynamics Approach
Jamal Hosseini Azabadi 1, a+, Rassoul Noorossana 1, b, Mostafa Jafari 1, c, Mohammad Saleh Owlia 2, d
and Mohammad Dehghani Saryazdi2, e
1
Department of Industrial Engineering, Iran University of Science and Technology(IUST),Tehran, Iran
2
Department of Industrial Engineering, Yazd University, Yazd, Iran
Abstract. In today’s competitive world, knowledge is considered an essential source of competitive
advantage for organizations. Thus, those organizations will be more successful that sustainably manage their
knowledge assets through operational activities. This research, with the aim of identifying and simulating the
dynamics of generating processes of knowledge management and also providing policy recommendations
for organizational knowledge management, uses system dynamics to study the interaction between effective
factors and structures of organizational knowledge management cycle including knowledge acquisition,
knowledge creation, knowledge sharing, and knowledge utilization. In this paper, based upon literature
review and interview with experts of knowledge management, the research model, incorporating
organizational knowledge, individual knowledge, and bilateral relations between critical success factors of
knowledge management and knowledge management practices, is developed using casual loop diagram and
stock and flow map. At last, after simulating and testing the dynamic model, it has been assessed under five
scenarios.
Keywords: Knowledge, Knowledge Management, Knowledge Management‘s Critical Success Factors,
Knowledge Management Practices, System Dynamics
1. Introduction
Image segmentation is one of the important missions in the image process and computer vision field. In
this paper, we focus on the color image segmentation, it can be divided into two categories, one is based on
color space division, the other is to use clustering segmentation. In the color space segmentation method,
often used in color space are RGB,YCbCr,HSV and so on. Although the RGB color space is the most direct
expression of the form, it is not necessarily suitable for color analysis[1], the YCbCr and HSV have good
effect in some applications and has often used algorithms in recent years[2][3][4]. The clustering method in
recent years than the classic method is K-means, it is not only the data clustering classification, the color can
also be classified[5].In this paper,we used color space segmentation pallet images, there are some research
results to engage pallets automatically in the past[6][7], due to the pallets color being similar to skin color,
we refer to the Jain AK articles as “face detection in color images”[8], this is the use of statistical skin
color distribution method in different color space, to find the closest color of the threshold. In our method,
we measured the pallet images in different color space to find the color of threshold. The rest of this paper is
organized as follows. Section 2 describes the basic image process method in the past. Section 3 describes the
proposed method, including color statistic and experimental procedure. Section 4 describes experimental
results. Finally, section 5 presents our conclusions.
In the literature, some researches have studied the effect of Critical Success Factors of Knowledge
Management on knowledge management practices. Akhavan et al. [1] investigated the importance and
+
Corresponding author
E-mail address: ahosseini.j@gmail.com, b Rassoul @iust.ac.ir, c jafari@iust.ac.ir, dowliams@yazduni.ac.ir,
e
ie.dehghani@gmail.com
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ranking of critical success factors of Knowledge Management in the knowledge management cycle including
knowledge acquisition, knowledge creation, knowledge sharing, and knowledge utilization. Results showed
that top management support, organization free atmosphere, continues improvement and suitable incentives
& motivational factors for people have the most effect on knowledge management cycle respectively.
Research of Allameh et al. [2], which is conducted in Isfahan Refinery Company in Iran, tries to identify the
influences of knowledge management enablers including technology, culture and structure, on knowledge
management processes. The results indicated that technology and culture are the most effective enablers
respectively. Also, some studies exploited system dynamics in the knowledge management. Drew and A.
Smith [3] in which, with regard to the importance of knowledge resources (as a competitive advantage) in
increasing the market share of a business, it is stated that the nature of these intellectual capitals and the
interactions of their system dynamics are recognized weakly yet. Eklöf et al. [4], have aimed at surveying the
knowledge management in a Law Firm with focus on the supportive role of information technology. For this
aim, system dynamics simulation tool is applied to present diagrams of cause and effect loops, stock and
flows, in order to describe different variables and their effects on each other. These diagrams indicate
variables influencing the general level of organization’s knowledge and the need to knowledge management.
Although many researches have done in the field of knowledge management, implementation of
knowledge management projects in the organizations is hard and complex yet. Based on mentioned studies
and ideas of area experts, it sounds that clarification of the effects of critical success factors of knowledge
management and dynamics between these factors and knowledge management practices could help in
solving this problem. On this basis, this research, with the aim of identifying and simulating the dynamics of
generating processes of knowledge management uses system dynamics to study the interaction between
effective factors and structures of organizational knowledge management cycle. In the following, at first,
concepts of knowledge management are investigated. Then, based upon literature review and interview with
experts of knowledge management, the research model is developed using causal loop diagram and stock and
flow map. At last, after simulating and testing the dynamic model, it is assessed under five scenarios.
2. Theoretical Bases
2.1. Knowledge Management
Knowledge is a powerful tool that can make changes to the world. It is now considered as the main
intangible ingredient in the melting pot that makes innovation possible [5]. Knowledge and knowledge
management (KM) are rapidly evolving as the starting point for action in all businesses, and over the past ten
years, this understanding has surfaced as a major focus for its role in the enterprise value process. Today,
knowledge and the capability to create and utilize knowledge are considered to be the most important source
of a firm’s competitive advantage [6].
2.2. System Dynamics
System dynamics is an approach to understanding the behavior of complex systems over time. It deals
with internal feedback loops and time delays that affect the behavior of the entire system. What makes using
system dynamics different from other approaches to studying complex systems is the use of cause and effect
diagrams and stock and flow diagram. These elements help describe how even seemingly simple systems
display baffling nonlinearity [7].
3. Modeling Process
3.1. Description of the Cause-and-Effect Diagram
In the first phase, the cause-and-effect diagram of the knowledge management model is designed
regarding the identified variables (see Fig. 1). It can be seen in this diagram that the investment on
knowledge management affect the critical success factors of knowledge management and consequently
critical success factors of knowledge management influence the knowledge management practices, which in
its turn improves the individual knowledge, knowledge creation and acquisition. Therefore, unshared
knowledge becomes raised. Afterwards, because of “Interaction Between people”, “Training Courses Held
by People for Other Organization's People” and “Best Practices sharing”, unshared knowledge becomes
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changed to shared knowledge. The total of unshared knowledge and shared knowledge become
organizational knowledge. Furthermore, in the backward direction, the organizational knowledge influences
the individual knowledge. Thus, these forward and backward paths create positive feedback loops.
Naturally, if the investment on knowledge management becomes more, knowledge enablers would be
enhanced and when the knowledge practices are managed better, the individual and organizational
knowledge would be amended. Increasing the values of organizational knowledge, results in the raise of
outcome indexes. On the other hand, better knowledge management results decrease the need to knowledge
management improvement. So, the loops of this diagram are negative (balancing) feedback loops. It is
notable that changes occurred for critical success factors of knowledge management impact the knowledge
practices after a delay, like what happens between knowledge practices and individual and organizational
knowledge. Regarding the relationships between variables the following points could be seen in Fig. 1:
3.2. Stock and Flow Map
In this section, the quantitative relationships between model variables are defined. Here, the time period
is set to one year. The model is simulated for 10 years beginning from year 2011. In this paper, levels of
“Individual Knowledge”, “Unshared Knowledge”, “Shared Knowledge”, and “Organizational Knowledge”
are defined. These levels show the cumulated effects of the investment on knowledge management through
the time. Regarding the effective variables on levels of model, the following points could be seen in Fig. 2, 3
and 4:
● In each time period the “Individual Knowledge” level is increased by “People Involvement in
Organization's Affaires”, “Job Rotation”, “Internal & External Organizational Training Courses”, “People
Hiring Ratio”, and “Shared Knowledge”. Also, this level is decreased by “Individual Knowledge Decay
Rate” and “Individual Knowledge Decrease Rate”. “Individual Knowledge Decay” is affected by “Average
life of Individual knowledge” and “Individual Knowledge Decrease Rate” is affected by “People Leaving
Ratio” variables. “Individual Knowledge” level and its cause variables are illustrated in Fig. 2.
● In each time period the “Unshared Knowledge” level is increased by “Knowledge Acquisition Rate”
and “Knowledge Creation Rate” variables. “Knowledge Acquisition Rate” is the result of “Organization
Absorptive Capacity”, “Time to Adjust External Knowledge Gap”, “Information Technology
Infrastructures” and “External Knowledge Gap”. Also, “Knowledge Creation Rate” is affected by
“Individual Knowledge”, “Organizational Practices”, “Improved & Innovated Processes” and” Research &
Development”. Moreover, “Unshared Knowledge” level is decreased by “Knowledge Sharing Rate”.
“Knowledge Sharing Rate” increases “Shared knowledge”. “Knowledge Sharing Rate” is affected by “Best
Practices sharing”, “Training Courses Held by People for Other Organization's People” and “Interaction
Between people”.
● In each time period the “Organizational Knowledge” level is increased by “Shared knowledge” and
“Unshared Knowledge”. Also, this level is decreased by “Organizational Knowledge Decay Rate”.
“Organizational knowledge Decay Rate” is affected by “Average Life of Organizational knowledge”.
The stock and flow map is separated into different sectors as shown in Fig. 2, 3 and 4. Each of the stock
and flow maps is part of the conceptual system dynamics model, which is represented in Fig. 5.
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+
F ormal & Informal
Discussions Between +
People
T endency to
+
+
+
Organization Free
Knowledge Sharing
Atmosphere
+
Training Courses Held By Some People
T rust in Knowledge
+
for Other People of the O rganization
+
Knowledge
<Interanal & External
Sharing Culture
Sharing
<Organizational
knowledge Gap>
+
O rganizational Training
Courses>
+
.Proportion of Knowledge
Management Budget Invested in
Information Technology
<People
Data & Knowledge+
Satisfaction>
Security
+
Job Security
- +
Information
T echnology
Proportion of Knowledge
Infrastructures
Management Budget Invested in
People Empowerment
<Proportion of Knowledge Management Budget
+
+
Best Practices
sharing
Suppliers,Shareholders,Consultants, Experts,
+
+&
Communities of Practice
Industry and Customers ‘knowledge>
Best Practices Communities
Invested in Transferring of Competitors, Partners,
+
+
suitable Incentives&
Time to Adjust External
Knowledge Gap
<Interanal & External
+
O rganization
individual knowledge
+
+
Proportion of Knowledge
Absortive Capacity
<Training Courses Held By
Some People for O ther People of
+
New Developed
the Organization>
Technologies
+
Research&
People Hiring
Development(R&D)
++
- -Unshared +
Knowledge
Ratio
-
+
+
Shared
knowledge
+
Job rotation
Ratio
Interanal & External
Organizational Training
Courses
+
Knowledge Gap>
People Leaving
+
-
knowledge>
<External
Courses>
+ +
+
Individual
Knowledge
+
++
Satisfaction
People
<O rganizational
Between people
Organizational Training
Average life of
People
Motivational F actors for
+
Interaction
+
-
+
+
+
Improved &Innovated
+
Creation
Organizational
+
+
Competitors +
Knowledge Absorption
Practices
+
Partners, Suppliers and
+
Proportion of Knowledge Management Budget
Shareholders Knowledge
Knowledge
+
+ +
<Individual
Knowledge>
Absorption
+
Invested in T ransferring of Competitors, Partners,
+
Suppliers,Shareholders,Consultants, E xperts,
Industry and Customers ‘knowledge
+
Desired Organizational
External Knowledge Gap
+
knowledge
+
Organizational
Organizational -
knowledge
+
Customers Knowledge
Absorption
++
Partners, Suppliers and
Shareholders knowledge
Consultants, Experts and
+
+
Customers
Industry knowledge
<Unshared
Average life of
Absorption
+
+
Knowledge>
Organizational
knowledge
Competitors
knowledge
-
External
knowledge Gap
<Individual
Knowledge>
Improvement
+
+
sharing>
Between people>
<Organizational
knowledge Gap>
+
Processes
+
Knowledge +
+
<Interaction
+
New Product Development
-
<People Involvment in
O rganization's Affaires>
O rganization's Affaires
Management Budget Invested in
-
Processes Continues -
-
<Best Practices
+
Innovation
People Involvment in
knowledge
Customer
Relationship Ratio
+
<Shared
<People
Satisfaction>
knowledge>
Consultants, Experts and
Industry knowledge
Fig.1. Cause-and-Effect Diagram
Fig.2. The Individual Knowledge level
Fig. 3: The “Unshared Knowledge” and “Shared
knowledge “level
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Fig. 4. The Organizational Knowledge leve
F ormal & Informal
Discussions Be twe en
People
T e nde ncy to
Organization F re e
Knowledge Sharing
Atmosphe re
Knowle dge
T raining Courses Held By Some People
Sharing Culture
for O the r People of the O rganization
T rust in Knowledge
<Inte ranal & Exte rnal
Sharing
O rganizational T raining
Courses>
.Proportion of Knowledge
M anage me nt Budget Investe d in
Information T e chnology
<Pe ople
Data & Knowledge
Satisfaction>
<O rganizational
Se curity
Information
Job Security
knowledge Gap>
T echnology
Proportion of Knowledge
Infrastructures
M anagement Budget Inve sted in
Pe ople E mpowerment
<Proportion of Knowle dge Manageme nt Budge t
Investe d in T ransfe rring of Competitors, Partne rs,
Be st Practice s
Suppliers,Shareholde rs,Consultants, Expe rts,
Communities of Practice &
Industry and Customers ‘knowle dge>
Be st Practice s Communities
sharing
Suitable Incentives&
<Inte ranal & Exte rnal
M otivational F actors for
T ime to Adjust Exte rnal
O rganizational T raining
Interaction
Knowledge Gap
Courses>
Betwee n people
People
Satisfaction
Inte ranal & Exte rnal
Pe ople
<O rganizational
Organizational T raining
knowledge>
Course s
<External
Ave rage life of
individual knowledge
Knowledge Gap>
Ratio
Individual
Individual knowle dge Knowle dge
Decay Rate
People Involvment in
O rganization
People H iring
O rganization's Affaire s
Absortive Capacity
<T raining Courses H eld By
Proportion of Knowle dge
Some Pe ople for O the r People of
New Deve loped
the O rganization>
T echnologie s
<Individual
De velopment(R&D)
Knowledge >
Increase Rate
Unshared
Share d
Individual knowle dge
knowle dge
De crease Rate
Knowle dge
N e w Product De velopment
Rese arch&
Knowle dge
acquisition Rate
Individual knowle dge
M anage me nt Budget Investe d in
Innovation
<O rganizational
Improveme nt
knowledge Gap>
Knowle dge
O rganizational
Creation Rate
Practices
Competitors
Knowledge Absorption
Partners, Supplie rs and
O rganization's Affaires>
Ratio
Shareholders Knowle dge
Exte rnal
Job rotation
knowledge
Proce sses
<People Involvment in
People Leaving
Compe titors
Improve d &Innovated
Knowle dge
Sharing Rate
Proce sse s Continues
<Best Practice s
<Interaction
sharing>
Betwe en people>
Proportion of Knowledge M anage me nt Budget
Absorption
Knowle dge
<Individual
Invested in T ransferring of Compe titors, Partne rs,
Suppliers,Shareholders,Consultants, Experts,
Knowledge>
Industry and Custome rs ‘knowle dge
Desired O rganizational
Exte rnal Knowledge Gap
knowledge
Customers Knowle dge
Absorption
Partners, Suppliers and
Share holde rs knowledge
O rganizational
O rganizational
knowledge
O rganizational
knowle dge Gap
Knowle dge Decay Rate
Consultants, E xpe rts and
O rganizational
Industry knowledge
Knowle dge Increase
Absorption
Rate
Customers
knowle dge
Custome r
Re lationship Ratio
Ave rage life of
<Shared
O rganizational
<Unshare d
knowle dge>
Knowledge>
knowledge
<People
Satisfaction>
Consultants, E xpe rts and
Industry knowledge
Fig.5. Stock and Flow Map
4. Performance Tests of the Developed Model.
In this research, diverse types of tests such as unit’s consistency test, collaborative error test, scope
sufficiency test, parameter evaluation test, structure evaluation test, and boundary conditions test are used in
order to evaluate the model performance.
5. Scenario Making.
● First Scenario: This scenario highly focuses on information technologies required for knowledge
management. Technology plays important role in the growth of knowledge management. In this scenario the
significant variable is “Proportion of Knowledge Management Budget Invested in Information Technology”
variable and is increased 50%.
● Second Scenario: Employees are the most valuable resources of an organization that should raise the
knowledge. In this scenario the significant variable is “Proportion of Knowledge Management Budget
Invested in People Empowerment” variable and is increased 50%.
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● Third Scenario: This scenario highly focuses on innovation in Products. New Product Development
play important role in achieving knowledge management goals. This scenario emphasizes “Proportion of
Knowledge Management Budget Invested in New Product Development” variable and is increased 50%.
● Fourth Scenario: External knowledge absorption can raise internal knowledge. This scenario
emphasizes “Proportion of Knowledge Management Budget Invested in Transferring of Competitors,
Partners, Suppliers, Shareholders, Consultants, Experts, Industry and Customers knowledge” variable and is
increased 50% in this scenario.
Fifth Scenario: This scenario highly focuses on all the four aspects of information technology, people,
new product development and external Knowledge simultaneously. Accordingly in this scenario the
significant variables are stated variables in above. In this case regarding the limited resources and the need to
hold a trade-off between all the four aspects, the organization should have a slower and equal progress in all
of them. So, all the above variables are increased 20%.The results are illustrated in Fig. 6.
Organizational Knowledge
1
5
5
5
5
5
0.75
5
5
0.5
3 4
1 2
0.25
5 1
2
1
2
1
3 4
3
2
3
2
1
3
4
2
1
3
4
2
3
4
1
2
2
3
4
1
1
3
4
2
3
4
4
0
0
1
Organizational Knowledge : scenario 1
Organizational Knowledge : scenario 2
Organizational Knowledge : scenario 3
Organizational Knowledge : scenario 4
Organizational Knowledge : scenario 5
4
5
6
Time (Year)
1
1
2
3
5
5
5
2
3
3
4
4
5
10
1
2
3
4
9
1
2
3
4
8
1
2
3
4
7
4
5
5
Fig.6. Trends of Organizational Knowledge for different scenarios
As it is obvious from figure 6, organizational knowledge has an S-shaped growth in the five scenarios. In
the first years of the simulation results, organizational knowledge in all of the scenarios increases faster than
of the next years; it grows less in the next years and this behavior continues forever. By comparison between
five scenarios, it’s indicated the fifth scenario follows a better trend than the other scenarios. The better
performance of the fifth scenario is that conventionally the investment in one dimension alone has not
significant impact on the organizational knowledge. Therefore, investment in all the dimensions of the
critical success factors of knowledge management simultaneously has more significant impact on the
organizational knowledge. Hence it had better that firms should strike and focus balance on all the critical
success factors. Even if it’s necessary to take smaller improvements.
6. Summary
Organizational knowledge is very complex and has multiple dimensions. Organizations need to
understand the dynamics of their knowledge capital and knowledge acquisition policies. The model
suggested in this research demonstrates the relationships between the investment on the critical success
factors of knowledge management and organizational knowledge growth through system dynamics modeling
approach, and finally analyzes the organizational knowledge trends for different values of variables. The
chief benefits of this model are:
●In the generated model the time distance between the effect of cause and appearance of its effects is
mentioned by including delays.
●Applying the “What happens if”. This action reduces the risk of program failures before implementing
them. In the proposed model five scenarios are designed and examined in order to find the best one.
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7. References
[1]
P. Akhavan: Development of Processes of Knowledge Management Cycle Based on Critical Success Factors of
Knowledge Management, Journal of Science and Technology Policy, Vol. 3, No. 2, (2011).
[2] S. M. Allameh, S. M. Zare and S.M. Davoodi: Examining the Impact of KM Enablers on Knowledge Management
Processes, Procedia Computer Science, Vol. 3(2011), pp.1211–1223
[3] S.A. Drew, P. A. Smith: Competitive Advantage Through Knowledge Management: A System Dynamics Approach,
Fourtheen International Conference of the Systems Dynamics Society, Cambridge, Ma. (1996).
[4]
E. Frida, H. Fiskum, L. Haalien,E. Haugland, B. Melling, E. Spieler, A.L. Sværen and O. Tukh: System Dynamics
Simulation for Knowledge Management in a Law Firm, BI Sandvika Master of Science in Business GRA 6643
Knowledge Management Systems.(2004).
[5]
S.O.S.B. Syed-Ikhsan, F. Rowland: Benchmarking Knowledge Management in a Public Organization in Malaysia,
Benchmarking knowledge: An International Journal, Vol. 11, No. 3 (2004), pp. 238-66.
[6] M. Jafari, M. Fathian, A. Jahani and P. Akhavan: Exploring the Contextual Dimensions of Organization from
Knowledge Management Perspective, Journal of Information and Knowledge Management Systems, Vol.38, No. 1
(2008), pp.53-71
[7] J. D. Sterman: Business Dynamics: Systems Thinking and Modeling for a Complex World, Irwin McGraw-Hill,
London, (2000).
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