Matthias Eckermann. Venture Capitalists' Exit Strategies under Information Asymmetry

Transcription

1 Matthias Eckermann Venture Capitalists' Exit Strategies under Information Asymmetry

2 GABLER EDITION WISSENSCHAFT

3 Matthias Eckermann Venture Capitalists' Exit Strategies under Information Asymmetry Evidence from the US Venture Capital Maricet Deutscher Universitats-Verlag

4 Bibliografische Information Der Deutschen Bibliothek Die Deutsche Bibliothek verzeichnet diese Publikation in der Deutschen Nationalbibliografie; detaillierte bibliografische Daten sind im Internet uber < abrufbar. Dissertation Technische Universitat Dresden, 2005 l.auflage Januar2006 Alle Rechte vorbehalten Deutscher Universitats-Verlag/GWV Fachverlage GmbH, Wiesbaden 2006 Lektorat: Brigitte Slegel / Nicole Schweitzer Der Deutsche Universitats-Verlag ist ein Unternehmen von Springer Science+Business Media. Das Werk einschlieblich aller seiner Telle ist urheberrechtlich geschiitzt. Jede Verwertung auserhalb der engen Grenzen des Urheberrechtsgesetzes ist ohne Zustimmung des Verlags unzulassig und strafbar. Das gilt insbesondere fur Vervielfaltigungen, Ubersetzungen, Mikroverfilmungen und die Einspeicherung und Verarbeitung in elektronischen Systemen. Die Wiedergabe von Gebrauchsnamen, Handelsnamen, Warenbezeichnungen usw. in diesem Werk berechtigt auch ohne besondere Kennzeichnung nicht zu der Annahme, dass solche Namen im Sinne der Warenzeichen- und Markenschutz-Gesetzgebung als frei zu betrachten waren und daher von jedermann benutzt werden diirften. Umschlaggestaltung: Regine Zimmer, Dipl.-Designerin, Frankfurt/Main Druck und Buchbinder: Rosch-Buch, ScheBlitz Gedruckt auf saurefreiem und chlorfrei gebleichtem Papier Printed in Germany ISBN

5 Preface This book has been submitted as dissertation at the Faculty of Business Management and Economics at Dresden University of Technology, Germany on January 19, Throughout the completion of this thesis, I received much encouragement and advice from mentors, colleagues and friends. I would like to take this opportunity to thank all of them. First of all, I would like to express my gratitude to my supervisor Prof. Dr. Michael Schefczyk for providing a fruitful research atmosphere at the SAP Chair for Entrepreneurship and Innovation at Dresden University of Technology. His comments and support helped me develop and complete this thesis. Moreover, I thank Prof. Schefczyk for supporting my ambitions to conduct research in the United States. Second, I am especially grateful to Prof. Andrew L. Zacharakis, Ph.D. for hosting me as visiting scholar at Babson College and for supervising my project during this time. This thesis benefited tremendously from his knowledge and from his outstanding support. His encouragement and support also helped me survive less productive times. A great debt is to Prof. Dr. Herman Locarek-Junge who accepted the burden of being my second examiner at Dresden University of Technology. The final paper benefited tremendously from conversations with several experienced researchers and practitioners in the United States. I want to thank Elaine I. Allen, Lowell Busenitz, Bill Bygrave, Les Charm, David Hsu, Ernest Parizeau, Elizabeth Riley and Shaker Zahra for their support. Moreover, I enjoyed fmitful discussions with my office colleagues Robert Dietrich, Jochen Neubecker, Frank Pankotsch and Jorg Wylegalla at Dresden University of Technology as well as Santeri Korri and Christian Vintergaard at Babson College. Their curiosity raised many questions which greatly improved this thesis. I owe special gratitude to Julio Perez for his outstanding technical support. Financial support from the German Academic Exchange Service (DAAD) is gratefully acknowledged. Last but not least, I would like to thank my mother for her extensive support during my time as a doctoral student and before. It is a pleasure for me to dedicate this dissertation to her. Matthias Eckermann

6 VII Table of Contents Preface Table of Contents Table of Figures Table of Tables Abbreviations V VII XI XIII XVII 1. Introduction Venture Capital Investments and Divestments Information Asymmetry as Overall Problem The Neoclassic Economics' Research Stream Theory of Economics of Institutions and Information Asymmetry Imperfect Markets as Origin for Venture Capital Transactions Information Asymmetry upon Exit Literature Overview and this Study's Focus Purposeof this Dissertation Structure of this Study 18 2 Venture Capital Investing Development Stages and Financing Requirements of Start-ups Product-Life-Cycles and Start-ups' Development Early Stage Expansion Stage Late Stage Start-Up Finance Financial Instruments Sources of Finance Structuring the Start-up's Finance Throughout Its Development The Venture Capitalist's Business Model Motives to Engage in VC Finance The VC-Financing Process The Venture Capitalist's Return Requirements Typesof Venture Capital Firms Conclusive Remarks 61 3 Exiting Ventures The Venture Capitalists' Exit Means 63

7 VIII Exit Vehicles Contractual Exit Means The Exit Process Differences and Common Characteristics of Exit Processes Supporting the Initial Investment Decision Monitoring Intemal and External Conditions During the VC Period Deciding on the Exit Executing the Transaction Recent Exit Trends Declined Stock Markets and the Overhang of Portfolio Companies Increased Competition in the VC-lndustry Current Challenges for Venture Capitalists' Exits Conclusive Remarks 86 4 Building an Analytical Framework Exit Strategies in the Literature Methodological Approach Overall Theoretical Framework Venture Capitalists' Exit Considerations The Venture's Business as Source for Information Asymmetries Degree of Innovation Development Level Competitive Environment Ex-Ante Uncertainty after Departures of Entrepreneurial Team Members VC Intemriediation as Source of Infomiation Asymmetries Pre-Tests of the Research Model Qualitative Pilot-Study Approach Sample Selection Insights From the Pilot-Studies Conclusive Remarks Research Methodology Empirical Design Dependent Variables Independent Variables Control Variables Data Collection Secondary Data Collection 146

8 IX Primary Data Collection Representativeness of the Survey Data Employed Statistical Methods Conclusive Statistics and Hypothesis Testing Regression Analysis and Discriminant Analysis Hierarchical Cluster Analysis Conclusive Remarks Empirical Analysis Confirmatory Analysis The Holding Duration Exit Vehicle Promotion Third-Party Certification Explorative Analysis Agglomeration Schedule Characteristics of the Final Two Clusters Characteristics of the Final Three Clusters Contributions of the Cluster Analysis Conclusion and Implications General Conclusions Practical Implications Limitations Further Research Closing Words 247 References 249 Appendices A.I Semi-Structured Questionnaire for Pilot Studies A.2 Online Survey A.2.1 Interface A.2.2 A.2.3 A.2.4 A.2.5 A.2.6 Instmctions Selection-Menu Questionnaire Check-Out Final Page A.3 Contact Letter and Mails A.3.1 Initial Letter

9 A.3.2 First Reminder Mail 286 A.3.3 Second Reminder Mail 287

10 XI Table of Figures Figure 1: VC investments as percentage of national GDP 3 Figure 2: Types of information asymmetries 7 Figure 3: Interrelations and possible information asymmetries in VC finance 13 Figure 4: Perspectives in VC research 14 Figure 5: This study's focus contrasted to the existing literature 16 Figure 6: This study's structure 20 Figure 7: Development levels of start-ups 23 Figure 8: Internal and external financing options 30 Figure 9: Mutation of the financial stmcture and the impact of VC 35 Figure 10: Exchange transactions in VC finance 36 Figure 11: The VC financing cycle 44 Figure 12: Success indicators in VC finance 53 Figure 13: Selection scheme for suitable exit vehicles 77 Figure 14: Decision-based framework of the exit process 80 Figure 15: IPO-trends in the U.S. VC-market 83 Figure 16: Growth trends in the U.S. VC-market 84 Figure 17: BIbliometrIc analysis 90 Figure 18: Scheme of hypotheses 103 Figure 19: Exit-timing considerations 104 Figure 20: Exit channel considerations 105 Figure 21: Distribution of responses 151 Figure 22: Company major industry affiliations in both data samples 152 Figure 23: VCFs' entry-stages in both data samples 153

11 XII Figure 24: Distribution of investment multiples in the data sample 154 Figure 25: Comparison of exit dates in both data samples 155 Figure 26: Regional origin of the venture companies 156 Figure 27: Overview on the outcomes for every hypothesis 166 Figure 28: Agglomeration schedule and relative changes in distances 223 Figure 29: Interdependencies of exit decisions 235 Figure 30: Recommeded exit strategies 241 Figure 31: Interface 278 Figure 32: Instructions 279 Figure 33: Selection-Menu 280 Figure 34: Questionnaire - First Page 281 Figure 35: Questionnlare - Second Page 282 Figure 36: Questionnaire - Third Page 282 Figure 37: Check-Out 283 Figure 38: Final Page 284

12 XIII Table of Tables Table 1: Underpricing as reported in previous studies 54 Table 2: Expected IRRs of VC investments across different stages 59 Table 3: Overview on the exit-related literature 100 Table 4: Impact of the investment banker's quality on the underpricing and fee structure 108 Table 5: Differences in the first-day-returns in VC-backed IPOs across Industries 110 Table 6: Market shares of the top 15 investment banks in the period of 1998 to Table 7: Selection criteria for survey instruments 148 Table 8: Exit vehicles in both data samples 154 Table 9: VCFs' ages across samples 157 Table 10: VCPs total known amount invested [in 1,000 US$] in all companies 158 Table 11: Significance levels and their implications 159 Table 12: Statistical tests contingent on the variables' scales 160 Table 13: Industry affiliation vs. timing considerations 167 Table 14: Industry affiliation vs. holding duration 167 Table 15: Industry affiliation vs. exit stages 169 Table 16: Development pace vs. timing 170 Table 17: Competition vs. holding duration 171 Table 18: Timing vs. departures 172 Table 19: VCF's age vs. holding duration 173 Table 20: Nominal control variables vs. holding duration 174 Table 21: Scaled control variables vs. holding duration 175

13 XIV Table 22: Regression analysis of the holding duration 176 Table 23: Innovation vs. exit vehicles 180 Table 24: Industry affiliation vs. exit vehicles 180 Table 25: Number of financing rounds in IPOs and M&A exits 182 Table 26: Exit stage vs. exit vehicle 183 Table 27: IPO frequency across exit stages 184 Table 28: Competition vs. exit vehicle 185 Table 29: Departures vs. exit vehicle 186 Table 30: VCF's age vs. exit vehicle 187 Table 31: Nominal control variables vs. exit vehicle 188 Table 32: Scaled control variables vs. exit vehicle 189 Table 33: Exit vehicle discriminant analysis 191 Table 34: Innovation vs. promotion 193 Table 35: Industry affiliation vs. promotion 194 Table 36: Underpricing across exit stages 197 Table 37: Nominal control variables vs. promotion 202 Table 38: Scaled control variables vs. promotion 203 Table 39: Regression analysis of the VCF's promotion 205 Table 40: Innovation vs. third-party certification 209 Table 41: Third-party certification across exit vehicles and industries 209 Table 42: Industry affiliation vs. third-party certification 210 Table 43: Third-party certification in IPOs across industries 211 Table 44: Third-party certification in M&A exits across industries 211 Table 45: Exit stages vs. third-party certification 213

14 XV Table 46: Nominal control variables vs. third-party certification 217 Table 47: Scaled control variables vs. third-party certification 218 Table 48: Regression analysis of third-party certification 219 Table 49: Differences in the final two clusters 224 Table 50: Ventures' differences across the last two clusters 226 Table 51: Differences in the final three clusters' exit strategies 228 Table 52: Ventures' differences across the last three clusters 229 Table 53: Differences in the final three clusters' characteristics 230 Table 54: Cluster analysis' impact on the regression models 232

15 XVII Abbreviations CAPM CEO CFO CR CVC DCF EVCA GDP GEM IPO IRR LBO M&A MBO MBI NASDAQ NVCA P/E PE PMC PMR PMVA R&D SD SDC SEC SEM VC VCF VIF Capital Asset Pricing Model Chief Executive Officer Chief Financial Officer Concentration Ration Corporate Venture Capital Discounted Cash Flow European Venture Capital Association Gross Domestic Product Global Entrepreneurship Monitor Initial Public Offering Internal Rate of Return Leveraged Buy-Out Mergers and Acquisitions Management Buy-Out Management Buy-In National Association of Securities Dealers Automated Quotation National Venture Capital Association Price/Earnings Private Equity Projected Marginal Costs Projected Marginal Return Projected Marginal Value Added Research and Development Standard Deviation Securities Data Company Securities and Exchange Commission Structural Equation Models Venture Capital Venture Capital Firm Variance Inflation Factor