Reveals how consumer choice can be better understood and influenced using social networks analysis (SNA)

Intuitively, we all appreciate that we can be influenced by our friends and peers in what we do, how we behave, and what products we consume. Until recently, it has been difficult to measure this interdependence, mainly because data on social networks was difficult to collect and not readily available. More and more companies such as mobile phone carriers or social networking sites such as Facebook are collecting such data electronically. Daniel Birke illustrates in compelling real-world case studies how companies use social networks for marketing purposes and which statistical analysis and unique datasets can be used.

Social Networks and their Economics:

• Explores network effects and the analysis of social networks, whilst providing an overview of the state-of-the art research.
• Looks at consumption interdependences between friends and peers: Who is influencing who through which channels and to what degree?
• Presents statistical methods and research techniques that can be used in the analysis of social networks.
• Examines SNA and its practical application for marketing purposes.
• Features a supporting website www.wiley.com/go/social_networksfeaturing SNA visualizations and business case studies.
  

List of figures ix

List of tables xi

Preface xv

Acknowledgements xvii

1 Consumer choice in social networks 1

1.1 Motivation 1

1.2 Using mobile telecommunications to illustrate the economics of social networks 3

1.3 Structure of the book 4

1.4 Why you should read this book 6

References 9

2 Research into social networks in economics, sociology and physics 11

2.1 Introduction 12

2.2 The economics of networks: Key findings from economics and marketing 13

2.3 Social network analysis: Key findings from sociology 24

2.4 Key findings from physics research into complex networks 30

2.5 Empirical research on social networks and network effects 32

2.6 Summary 40

References 40

3 Marketing in social networks: The iPhone 47

3.1 Executive summary 47

3.2 Case study 1: Social network and viral marketing 48

3.3 Case study 2: Social advertising on Facebook 52

3.4 Introduction to the empirical study 54

3.5 Product diffusion in social networks 55

3.6 Modelling diffusion in social networks 57

3.7 Model estimation 59

3.8 Model results 62

3.9 Discussion 67

References 68

4 Switching and churn in social networks 71

4.1 Executive summary 71

4.2 Case study: Customer retention in social networks 72

4.3 Introduction to the empirical study 75

4.4 Key findings from the switching cost literature 76

4.5 Modelling concept 78

4.6 Description of the data used: Another large-scale mobile network 79

4.7 Model results 81

4.8 Discussion 86

References 88

5 How social networks influence consumer choice of mobile phone carriers in the UK, Europe and Asia 91

5.1 Executive summary 92

5.2 Case study: Using homophily for social network marketing 92

5.3 Introduction to the empirical study 96

5.4 Methodology 98

5.5 Understanding the properties of the social networks 102

5.6 The impact of friendship on operator choice 108

5.7 Robustness of results 112

5.8 Are stronger relationships more influential? 117

5.9 Friendship networks and choice of handset brand 120

5.10 Multi-country case study of operator choice in social networks 122

5.11 Discussion 133

References 134

6 Coordination of mobile operator choice within households 137

6.1 Executive summary 138

6.2 Case study: Social network marketing to communities 138

6.3 Introduction to the empirical study 142

6.4 Data 143

6.5 Descriptive statistics 144

6.6 The model 146

6.7 Multinomial logit model 148

6.8 Multinomial probit model 153

6.9 Discussion 158

References 158

7 How pricing strategy influences consumer behaviour in social networks 161

7.1 Executive summary 161

7.2 Case study: Pricing digital products with network effects 162

7.3 Introduction to the empirical study 165

7.4 The mobile telecommunications industry in the UK 167

7.5 The model: Price discrimination between on- and off-net calls 169

7.6 Estimation results: Adapting consumption choice to price signals 173

7.7 Discussion 175

References 176

8 Conclusions 177

8.1 Main results 177

8.2 Implications of interdependent consumer choice 178

8.3 Looking ahead: How social network analysis is changing research and marketing practice 180

References 181

Appendix A Success factors for viral marketing campaigns 183

A.1 Proposition excellence 185

A.2 Observability of the product or its use 186

A.3 Design the campaign around a good understanding of the specific role of word-of-mouth in propagating your product 187

A.4 Word-of-mouth for economic benefit 187

A.5 Exploit storytelling and tap into the zeitgeist 188

A.6 Exploit influential expert users 189

A.7 Appeal to communities of interest 189

A.8 Conclusion 190

References 191

Appendix B Student questionnaire 193

Index 197

Daniel Birke, Visiting Researcher, Aston Business School, Birmingham, and works in a leading international management consultancy in Germany.