Managing the Reality of Virtual Organizations (eBook)

Dr. Shekhar works in the area of Knowledge and Innovation Strategies. Her recent work focuses on helping organizations manage the challenges of global dispersion whilst leveraging market and innovation opportunities by extending organizational boundaries. She has worked at the confluence of industry and academic fraternities helping to build innovation ecosystems, in her former role as the first CEO of India’s first University Research Park. She also has extensive industry experience, having worked as Director, Asia Pacific Consulting, Gartner; CTO, BconnectB.com; Head, Knowledge Management Research, Aptech Ltd.; and Group Consultant, NIIT Ltd. She did her management studies at the Indian Institute of Management, Bangalore. She earned her PhD from IIT Madras, with her dissertation winning the award for outstanding doctoral research from the European Foundation for Management Development and Emerald. She currently serves as an independent director on the Boards of Bimetal Bearings Ltd. and IP Rings Ltd.                       

Foreword 8
Acknowledgments 12
Contents 14
About the Author 20
Abbreviations 22
Prologue 24
1: Introduction 26
1.1 The Overarching Motivation for This Book and What It Seeks to Address 26
1.2 What This Book Is Not About 28
1.3 How This Book Has Been Organized 28
1.4 Who Should Read This Book 30
Reference 30
2: Virtuality and the Reality of It All 31
2.1 Geosourcing 34
2.2 Off-shoring and Organic Growth in Multiple Geographies 36
2.3 Inorganic Growth 40
2.4 Extended Value Chain Linkages 41
2.5 E& M-Commerce
2.6 Virtual Banking 44
2.7 E-Government 46
2.8 e-Learning 49
2.9 Telecommuting 51
References 52
3: Virtuality and Virtual Organizations – The Conceptual Edifice 54
3.1 The Approach 55
3.2 Toward an Inclusive Definition of the VO 56
3.2.1 Rationale for the Proposed Approach 58
3.2.2 An Interpretation of the VO Based on the Resource-Based Theory 59
3.3 Existing Representations of Degree and Dimensions of Virtuality 61
3.4 Directionality and Granularity of Virtuality 62
3.5 Facets of Virtuality 63
3.6 The Integrated Model 65
3.7 Measuring DoV 67
3.8 Understanding Virtual Organizational Maturity (VOM) 70
3.9 Implications of the Model and Making It Work for You 71
3.10 Conclusions 73
References 74
4: A View from the Top – Conversations with Business Leaders 76
4.1 The Lulu Group 78
4.2 Marriott International 83
4.2.1 Company Overview and Growth 83
4.2.2 Insights from Marriott’s Growth Strategies 84
4.2.3 Measuring Knowledge Transfer Effectiveness 89
4.2.4 Virtualization 90
4.2.5 Inorganic Growth 91
4.3 Grundfos 93
4.4 The Patterns That Emerge 100
References 103
5: Bridging Distances in the Virtual Organization 104
5.1 Understanding Distances 105
5.1.1 Capability Distance 106
5.1.2 Cultural Distance 107
5.1.3 Organizational Distance 108
5.1.4 Temporal Distance 110
5.1.5 Social Distance 110
5.1.6 Environmental Distance 111
5.2 A Framework for Assessing Distances 113
5.3 Managerial Implications of Assessing Distances 114
5.4 The Structural Underpinnings of a VO 115
5.4.1 The VIPs 115
5.4.2 The SoI 117
5.5 A Framework for Linking SOI to Distance Factors 118
5.6 Industry Implications and Use 120
5.7 Measuring Distances 120
5.8 Knowledge Distance as an Input for Evaluating Partner Viability 121
5.8.1 A Methodology for Assessing Knowledge Distance 122
5.8.1.1 Methodology 124
5.8.1.2 Knowledge Score Interpretations 126
5.8.2 The Model 127
5.8.3 Managerial Implications 127
5.8.4 Other Potential Uses 129
5.9 Dissecting Distances to Bridge the Gaps 132
References 132
6: The Strategic Importance of Knowledge Transfer in VOs 134
6.1 Knowledge 138
6.2 Knowledge Transfer 139
6.3 A Conceptual Model for KT in VOs 140
6.4 Knowledge Transfer Effectiveness 143
6.5 The Need for Designing a Measurement Tool for KTE 144
6.6 Proposed Model for KTE 147
6.6.1 The Process Perspective – A Generic Model for KTE 147
6.6.2 The Importance of Adaptation and Innovation 148
6.6.3 The Locational Perspective – Incorporating the “Distance” Factor of VOs 149
6.6.4 Summarizing the Model 150
6.7 The Potential Customizability of the Model 151
6.8 Uses of the KTE Tool 151
6.9 Conclusions 152
References 153
7: Determinants of Successful Knowledge Transfers 155
7.1 The Preliminary Survey 156
7.2 KTE and Performance of Knowledge Workers 158
7.3 Factors Influencing KTE 159
7.3.1 Geographic Distance 159
7.3.2 Organizational Distance 160
7.3.3 Degree of Concordance 161
7.3.4 Trust 162
7.3.5 Knowledge Sharing Propensity 163
7.3.6 Customer Relationship 164
7.3.7 Attrition 165
7.3.8 Ease of Information Flow 166
7.3.9 Process Maturity 167
7.3.10 Technology Support 167
7.3.11 Virtuality 168
7.3.12 Interdependence 169
7.3.13 Tacitness 170
7.3.14 Knowledge Distance 171
7.3.15 Time Constraint 172
7.3.16 Demographic Variables 173
7.4 Research Model 174
References 176
8: The Research Rigor 177
8.1 Research Design 178
8.2 Instrument Development 180
8.2.1 Formulating the Questions 180
8.2.1.1 Content-Related Issues 182
8.2.1.2 Presentation and Layout 182
8.2.1.3 Question Formulation and Wording 182
8.2.2 Choice of Scale 183
8.3 Operationalization of the Scales 183
8.4 Pre-test 184
8.5 Pilot Study 184
8.6 Research Sites 185
8.7 Research Sample 185
8.8 Data Collection Procedure 186
8.9 Data Cleansing 187
8.10 Sample Profile 187
8.10.1 Organization Level 188
8.10.2 Project Level 188
8.10.3 Knowledge Worker Level 188
8.11 Reliability and Validity Testing 193
8.11.1 Reducing Measurement Error 193
8.11.2 Uni-dimensionality 194
8.11.3 Instrument Reliability 195
8.11.4 Validity Testing 196
8.11.4.1 Face or Content Validity 196
8.11.4.2 Construct Validity 197
8.11.5 Validity Testing for the KTE Scale 197
8.12 Overview of Analysis 199
References 201
9: Organizations Speak Through Their Data 203
9.1 Understanding the Data – Univariate Analysis 203
9.2 Examining the Impact of Demographic Variables 207
9.3 Hypothesis Testing of Independent Variables 211
References 224
10: Mining Deeper into the Data 225
10.1 Multiple Regression Analysis 225
10.2 Satisfying Multiple Regression Prerequisites 226
10.2.1 Adequacy of Sample Size 226
10.2.2 Assessing Multi-collinearity 227
10.2.3 Outliers 230
10.2.4 Linearity, Homoscedasticity and Normality 232
10.2.4.1 Linearity 232
10.2.4.2 Homoscedasticity 232
10.2.4.3 Normality 233
10.3 Understanding the Significant Predictor Constructs – Multiple Regression Analysis Results 234
10.4 Testing the Research Model Through Hierarchical Regression 241
References 246
11: Putting the Pieces Together 247
11.1 Understanding VOs Better Through a Strong Conceptual Underpinning 248
11.2 Bridging Distances in VOs 252
11.3 Conceptual Model for Knowledge Transfer in VOs and Development of a Knowledge Transfer Effectiveness Index 252
11.4 The Importance of KT in VOs and Debunking Some Myths on Knowledge Management 256
11.5 Impact of Virtuality 258
11.6 The Critical Success Factors 260
11.7 Some Important Patterns That Emerge 265
11.7.1 Some Counter-Intuitive Results 266
11.7.2 Toward a More Equitable World 268
Reference 269
Epilogue 270
Appendices 273
Appendix 1: Scales for Constructs Used in the Research 273
Appendix 2: Questionnaire Structure 274
Appendix 3: Partial Regression Plots (Dependent Variable is KTE in All the Plots) 275
Appendix 4: Hierarchical Regression Coefficients 282