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Financing High-Tech Startups

Using Productive Signaling to Efficiently Overcome the Liability of Complexity

  • Book
  • © 2018

Overview

Authors:
  1. Robin P. G. Tech

    1. Alexander von Humboldt Institute for Internet and Society, Berlin, Germany

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  • Tackles emerging trends of technology venture development and investment
  • Combines new institutional economics and behavioral economics with startup financing to identify concrete signaling strategies
  • Provides an accessible framework and insights for startup founders and high-tech investors

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Table of contents (9 chapters)

  1. Front Matter

    Pages i-xix
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  2. Introduction: High-Tech Startup Financing

    • Robin P. G. Tech
    Pages 1-28

  3. Theory: The Liability of Complexity

    • Robin P. G. Tech
    Pages 29-77

  4. Methodology: Mixed Methods Approach

    • Robin P. G. Tech
    Pages 79-87

  5. Study I: Survey of German Startups

    • Robin P. G. Tech
    Pages 89-97

  6. Study II: Interviews with Entrepreneurs and Investors

    • Robin P. G. Tech
    Pages 99-133

  7. Framework: Matching Signals with Complexities of High-Tech Startups

    • Robin P. G. Tech
    Pages 135-168

  8. Discussion: Why Signals Can Help to Overcome the Liability of Complexity

    • Robin P. G. Tech
    Pages 169-198

  9. Conclusion: Taming Complexity

    • Robin P. G. Tech
    Pages 199-200

  10. Appendix

    • Robin P. G. Tech
    Pages 201-206
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Keywords

About this book

This book examines the adverse effects of complexity, information asymmetries, transaction costs, and uncertainty on investors’ decision making. It suggests mitigating those effects using appropriate and matching signals, and analyzes a sample of 903 German startups to quantitatively highlight the distinct financing patterns and characteristics of high-tech startups. It then investigates the reasons for these patterns on the basis of a qualitative study that includes 34 interviews with investors and entrepreneurs in the US and Germany and an international expert panel. Lastly, it presents a framework that matches complexity factors with appropriate productive signals. 



Authors and Affiliations

  • Alexander von Humboldt Institute for Internet and Society, Berlin, Germany

    Robin P. G. Tech

About the author

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. 



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