Financing High-Tech Startups (eBook)

Robin P. G. Tech is a researcher at the Humboldt Institute for Internet and Society in Berlin. He is the principal investigator of a research group that focuses on the entrepreneurial exploitation of the ‘internet of things’. Prior to this, Robin studied Economics and Corporate Management at Zeppelin University (BA),Technology, Sociology, & Management (MSc) in Stockholm, and completed his MBA in Hong Kong. In his non-academic life, Robin is the co-founder of AtomLeap, a high-tech focused startup. He also worked in venture capital (2007), held a consulting position at the curating office Buro17 in Moscow (2009), worked for AUDI on inductive charging systems (2010-2011) and at the European Commission’s EIT Labs (2012-2013) in the field of business modeling for renewable energies. 

Dedication 5
Foreword 6
Acknowledgment 7
Contents 8
List of Abbreviations 11
List of Figures 12
List of Tables 14
Chapter 1: Introduction: High-Tech Startup Financing 15
1.1 Analyzing High-Tech Startup Financing 15
1.2 Startups and Entrepreneurs 20
1.3 Investors 30
1.4 Chapter Summary: Contextualizing High-Tech Startup Financing 35
Literature 36
Chapter 2: Theory: The Liability of Complexity 43
2.1 Complexity Lies at the Heart of High-Tech Startups 43
2.2 New Institutional Economics as a Venture Funding Framework 47
2.2.1 Transaction Costs Are Complexities in Disguise 52
2.2.2 Signals Mark Distinction 55
2.2.3 Agency and Property Rights Theory 64
2.3 Behavioral Economics and Finance 70
2.4 An Institutional and Behavioral Research Strategy 77
2.5 Excursus: Similar Approaches in Digital and Media Economics 79
2.6 High-Tech Startups Face an Institutional and Behavioral Dilemma 80
2.7 Chapter Summary: Theorizing Complexity and Signaling 82
Literature 83
Chapter 3: Methodology: Mixed Methods Approach 92
3.1 Background 92
3.2 Methodology 95
3.3 Mixed Methods Application 96
3.4 Chapter Summary: Pragmatist and Explanatory Sequence 98
Literature 99
Chapter 4: Study I: Survey of German Startups 101
4.1 Hypotheses 101
4.2 Data Sources and Sample Selection 102
4.3 Data Analysis 103
4.4 Findings 104
4.5 Chapter Summary: High-Tech Startup Financing Patterns 108
Literature 109
Chapter 5: Study II: Interviews with Entrepreneurs and Investors 110
5.1 Research Questions 110
5.2 Data Collection 111
5.3 Data Analysis 114
5.4 Findings 117
5.4.1 Internal Complexity 118
5.4.2 Product-Related Complexity 123
5.4.3 External Complexity 127
5.4.4 Investor Classes 136
5.4.5 Validation Panel 142
5.5 Chapter Summary: Complexity-Induced Uncertainty and Signals 143
Literature 144
Chapter 6: Framework: Matching Signals with Complexities of High-Tech Startups 145
6.1 Complexity Factor Framework 146
6.2 Startups´ Locus of Control 148
6.2.1 Internal Locus of Control 148
6.2.2 Intermediate Locus of Control 151
6.2.3 External Locus of Control 163
6.3 Investor Specificities 166
6.3.1 Differences Between the US and Germany 166
6.3.2 Investor Risk Profiles 167
6.4 Chapter Summary: The Complexity Signal Framework 172
Literature 175
Chapter 7: Discussion: Why Signals Can Help to Overcome the Liability of Complexity 179
7.1 Theoretical Implications 179
7.1.1 Behavioral Economics 179
7.1.2 Agency and Property Rights Theory 181
7.1.3 Signaling 185
7.1.4 Transaction Cost Theory 189
7.1.5 High-Tech Complexity 191
7.2 Practical Implications 192
7.2.1 Investors 192
7.2.2 Startups and Entrepreneurs 194
7.3 Limitations and Future Research 198
7.3.1 Limitations 198
7.3.2 Future Research 199
7.4 Chapter Summary: Taking Stock and Looking Ahead 203
Literature 204
Chapter 8: Conclusion: Taming Complexity 209
Chapter 9: Appendix 211
9.1 Investor Interviews Guide 211
9.2 Startup Interviews Guide 212
9.3 Themes from Interviews 214