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Knowledge Integration - The Practice of Knowledge Management in Small and Medium Enterprises
Preface
5
Table of Contents
7
1 Knowledge Management: More than a Buzzword
12
1.1 Introduction
12
1.2 The Relevance of Knowledge Management for High- tech Small and Medium Sized Firms
13
1.3 Knowledge Management – What Is It About?
14
1.3.1 Knowledge Management versus Competence Management
14
1.3.2 Approaches to Knowledge Management
14
1.3.3 Levels of Knowledge Management
16
1.4 What Aspects Are Related to Knowledge?
17
1.4.1 Content in Knowledge Identification and Acquisition Processes
18
1.4.2 Utilization of Knowledge in Contexts
20
1.4.3 Knowledge Flows
20
1.4.4 Knowledge Media
21
1.5 The Knowledge Integration Context
23
1.6 Outline of this Book
24
References
26
2 Knowledge Integration by SMEs – Framework
28
2.1 Introduction
28
2.2 High-tech SMEs: Characteristics and Differences
29
2.3 Types and Sources of Knowledge
30
2.4 KI Processes and Activities
33
2.5 KI Problems and Solutions
36
2.6 Summary and Conclusions
38
References
38
3 Knowledge Integration by SMEs - Practice
40
3.1 Introduction
40
3.2 Analysing KI in SMEs: Research Framework
40
3.3 Research Method
42
3.4 Results
43
3.4.1 NPD Process
44
3.4.2 Sources
44
3.4.3 KI Process
46
3.4.4 Problems
47
3.4.5 Solutions
48
3.4.6 Match
49
3.5 Differences between SMEs
50
3.6 Conclusions and Implications
52
References
54
Appendix: Questionnaire
54
4 Organizing the Toolbox - Typology and Alignment of KI Solutions
57
4.1 Introduction
57
4.2 Definitions and Principles of the Typology
58
4.3 Typology of KI Tools and Techniques
60
4.3.1 Activities for Latent Knowledge
61
4.3.2 Activities for Explicit Knowledge
62
4.3.3 Activities for Tacit Knowledge
68
4.3.4 Motivating Activities
68
4.4 Knowledge Integration Strategies
69
4.5 SME Suitability
72
4.6 Conclusions
72
References
74
5 Elicitation – Extracting Knowledge from Experts
75
5.1 Motivation and Introduction
75
5.2 A Psychological Perspective on Knowledge Elicitation
75
5.2.1 Theoretical Background
75
5.2.2 Relevance for Knowledge Management
78
5.3 Elicitation in Practice
79
5.3.1 Identification of Experts
79
5.3.2 Activation and Capture of Knowledge
80
5.3.3 Knowledge Interpretation and Documentation
81
5.4 Implementation Experience
82
5.4.1 Identification of Experts at CEROBEAR
83
5.4.2 Activation and Capture: Free Association & Episodic Interviews
83
5.4.3 Interpretation and Documentation: Building an Ontology
84
5.5 Discussion and Conclusions
85
References
85
6 Codification – Knowledge Maps
87
6.1 Introduction
87
6.2 Knowledge Codification and Knowledge Maps
87
6.3 Types of Knowledge Maps
89
6.3.1 Hierarchical or Radial Knowledge Structure Maps: Concept Maps and Mind Maps
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6.3.2 Networked Knowledge Structure Maps: Causal Maps
91
6.3.3 Knowledge Source Maps
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6.3.4 Knowledge Flow Maps
93
6.4 Case Study: Knowledge Maps to Improve NPD
95
6.4.1 Process Assessment
95
6.4.2 Improved Processes: AIXTRON’s Knowledge Application Map
97
6.5 Discussion and Conclusion
98
References
99
7 Detection – Electronic Knowledge Retrieval
102
7.1 Introduction
102
7.2 IR Systems for Knowledge Detection
102
7.2.1 Traditional IR Search Methods
103
7.2.2 Information Retrieval and the WWW
104
7.2.3 New Impulses in IR Systems
105
7.3 Implementation at a High-tech SME
107
7.3.1 The High-tech SME: CEROBEAR
107
7.3.2 Focus: Development of a Customer- Specific Ontology
108
7.3.3 Results and Evaluation
109
7.4 Discussion and Conclusion
110
References
111
8 Assessment – Making Sense of It All
112
8.1 Introduction
112
8.2 What Is Knowledge Assessment?
113
8.3 Critical Analysis of Assessment Practices
114
8.3.1 Theoretical Background and Practical Framework
114
8.3.2 Alignment of Available Practices
115
8.4 The Decision-Validity-Tracking (DVT) Method
116
8.5 Lessons Learned from the Implementation at Optibase
121
8.6 Conclusions
123
References
124
9 Transfer - Knowledge Transfer in Networks
126
9.1 Introduction
126
9.2 Theory on Knowledge Transfer in NPD Processes
126
9.2.1 The Character of Knowledge and Networks in Transfer Processes
127
9.2.3 Some Consequences of Cognitive Distance for Networking of Small Firms
128
9.3 The WAP Project, an Example of Knowledge Transfer in a Network
130
9.3.1 Context of the Project
130
9.3.3 Knowledge Transfer Mechanisms
132
9.4 Conclusions
135
References
136
10 Motivating – Incentive Systems for Knowledge Provision
138
10.1 Introduction
138
10.2 Design Areas of Incentive Systems for Knowledge Provision
139
10.2.1 Definition of Knowledge Goals
139
10.2.2 Definition of the Application Area
140
10.2.3 Definition of Incentive Tools
140
10.2.4 Measurement and Evaluation of Employee Performance
141
10.3 Implementation of Incentive Systems
141
10.3.1 Analysis of the Status-quo
141
10.3.2 Concept Development and Elaboration
143
10.3.3 System Introduction
145
10.3.4 System Checking
145
10.4 Case Study at HEAD Acoustics
146
10.4.1 HEAD Acoustics and the Focus of the Project
146
10.4.2 Results
147
10.5 Summary and Conclusion
151
References
151
11 Supporting Knowledge Integration at SMEs – The KINX Portal
154
11.1 Introduction
154
11.2 Information Services and Scope of the KINX Portal
156
11.3 Knowledge Integration Portal Description
157
11.3.1 The KINX Portal Public Area
159
11.3.2 The Private Area
161
11.3.3 The Administration Area
166
11.4 Portal Development Process
167
11.5 Conclusions and Discussion
168
References
169
12 Supporting Knowledge Integration at SMEs – Policies
172
12.1 Introduction
172
12.2 Reasons for Supporting KI in SMEs
172
12.3 Profiles of KI Support Measures for SMEs
173
12.4 Usage of Selected KI Support Measures
178
12.5 The Effectiveness of KI Support Measures
179
12.6 Summary and Recommendations
183
References
184
13 Wrapping It All Up - Past, Present and Future of Knowledge Integration
186
13.1 Introduction
186
13.2 Evaluation of KI - What Does It Promise and Does It Keep What It Promises?
187
13.2.1 The Theoretical Perspective
188
13.2.2 The Empirical Perspective
190
13.2.3 The Tools Perspective
192
13.3 The Further Development of KI Requirements and Opportunities for Improvement
196
13.3.1 Conceptual Improvements
196
13.3.2 Instrumental Improvements
197
13.4 Outlook - The Future of KI
199
References
201
Biographical Information about the Authors
204
List of Authors’ Addresses
208
Index
212
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