List of figures and tables
Figures
1.1 Business and IT relationship 7
2.1 Organisational learning process 14
2.2 Business knowledge 15
2.3 Data, information and knowledge 20
2.4 Three varieties of knowledge 23
2.5 The duality of knowledge 24
2.6 Five types of knowledge 25
2.7 Knowledge conversion lifecycle (simplistic view) 28
2.8 Ba and the SECI Model (adapted by Depres and
Chauvel, 2000 from Nonaka, 1991) 29
3.1 Lotus Solutions Framework – part 1 44
3.2 Lotus Solutions Framework – part 2 45
3.3 Lotus Solutions Framework – part 3 45
3.4 Lotus Solutions Framework – part 4 46
3.5 Knowledge management process model 50
3.6 Knowledge management process model – activities 51
3.7 Three levels of knowledge management 52
3.8 Evolution of knowledge management 53
3.9 KPMG’s five-step implementation stack 59
4.1 The intellectual capital model 68
4.2 Positioning the three domains of intellectual capital 70
5.1 Learning, working, and innovation interrelationships 77
Coping with Continuous Change in the Business Environment
5.2 An organisation’s three domains 78
5.3 Enterprise model 81
5.4 Successful enterprise learning 83
5.5 Learning spiral 87
5.6 Individuals learn in the context of the organisation 87
5.7 From organisational learning to a knowledge-enabled
organisation 90
6.1 Evolution of business cultures and knowledge management
technologies 95
6.2 Positioning of communities of practice 100
7.1 Knowledge transfer cycle 105
7.2 A model for best practice transfer 106
8.1 Knowledge management becomes ‘just business’ 113
9.1 The e-business implementation spiral 127
9.2 E-business model 129
10.1 Knowledge management process model 136
10.2 Knowledge management broad categories
10.3 Knowledge management technology conceptual 137
framework
10.4 Knowledge management technology framework – 138
processes and activities
10.5 Knowledge management technology framework – 139
enablers and applications
10.6 Knowledge management technology framework – 139
six categories model 141
11.1 Complexity of different knowledge base sources 149
11.2 The ‘smart’ data continuum 153
11.3 Semantic web services 157
11.4 Example of a taxonomy 159
11.5 Ontology levels 161
11.6 The ontology spectrum: from weak to strong semantics 162
11.7 Metadata and semantic annotations 163
11.8 Positioning the XML stack architecture 163
12.1 Concise knowledge conversion spiral model (left) 176
13.1 Systems positioning 183
13.2 The three ‘C’s link people to process to information 185
13.3 Areas of groupware 187
13.4 Time and distance barriers 188
13.5 Collaboration technologies for time and place 188
13.6 Concise knowledge conversion spiral model (right) 190
14.1 Growth in global volume of knowledge 202
14.2 Examples of the values in the information overload 202
16.1 Conceptual knowledge portal 220
16.2 Typical knowledge portal system configuration 222
17.1 Information filtering and knowledge discovery 224
17.2 Pattern recognition algorithms 226
17.3 Key text-mining technologies
Tables 232
2.1 Artificial expertise preferred to human expertise 19
2.2 Human expertise preferred to artificial expertise 19
2.3 Information versus knowledge 22
2.4 Tacit and explicit knowledge 27
2.5 Knowledge conversion 27
2.6 Knowledge conversion lifecycle
3.1 Summary of the knowledge management principles of 31
O’Dell and Grayson (1998) and Tobin (2003) 43
3.2 Information management versus knowledge management 60
3.3 Business intelligence versus knowledge management 61
4.1 Comparison of the three domains of intellectual capital 71
Coping with Continuous Change in the Business Environment
5.1 Transformation in organisations 79
9.1 Knowledge management responses to e-business demands 128
9.2 Differences between client/server and e-business
applications 131
13.1 Connecting people, process, and information 185
13.2 Knowledge conversion lifecycle 191
16.1 Comparison of knowledge retrieval and a knowledge
portal 220
17.1 Comparison of document-handling technologies 228