Empirical Evidence on Governance Mechanisms, Syndication Activities, and Partner Selection Strategies in Venture Capital Financing

(1)

Empirical Evidence on Governance Mechanisms, Syndication Activities, and Partner Selection Strategies in Venture Capital Financing

Dissertation

zur Erlangung des Grades

Doktor der Wirtschaftswissenschaften (Dr. rer. pol.) am Fachbereich Wirtschaftswissenschaften

der Universität Konstanz

Vorgelegt von:

Christian Hopp Kappelersgutweg 2a 78457 Konstanz

Konstanz, den 8. Februar 2008

Tag der mündlichen Prüfung: 30. April 2008 Prüfungskommission:

Dr. Christian Lukas (Vorsitzender), Universität Konstanz Prof. Dr. Dr. h.c. Günter Franke, Universität Konstanz Prof. Dr. Jens Carsten Jackwerth, Universität Konstanz

Konstanzer Online-Publikations-System (KOPS) URL: http://www.ub.uni-konstanz.de/kops/volltexte/2008/5578/

(2)

ii

Vorwort

Die vorliegende Arbeit ist im Zeitraum von Januar 2004 bis Januar 2008 im Rahmen des Promotionsprogramms „Quantitative Economics and Finance“ an der Universität Konstanz erstellt worden. An dieser Stelle möchte ich die Gelegenheit nutzen, um den Personen zu danken, die durch ihre tatkräftige Mithilfe, ihre Anregungen und Kommentare, und ihre Aufmunterung und Unterstützung zum Gelingen dieser Arbeit beigetragen haben.

Für die Betreuung der vorliegenden Arbeit in den letzten 4 Jahren möchte ich mich sehr herzlich bei Prof. Dr. Dr. h.c. Günter Franke bedanken, der mir bei zahlreichen Gesprächen und Diskussionen über frühere Versionen der eingereichten Papiere durch seine Fragen, Kommentare und Anregungen immer wieder neue Denkanstöße gab und durch das Stellen neuer Herausforderungen half meine Arbeiten weiter zu entwickeln. Die gelungene Mischung aus kontinuierlichem Fördern und Fordern, die ständige Ansprechbarkeit und die Unterstützung bei der selbstständigen Forschungsarbeit haben mich nachhaltig beeindruckt.

Prof. Dr. Jens Carsten Jackwerth danke ich für die Bereitschaft die Zweitkorrektur dieser Arbeit zu übernehmen.

Bei Prof. René Stulz und Prof. Rüdiger Fahlenbrach möchte ich mich für die Möglichkeit der Durchführung eines Forschungsaufenthalts an der Ohio State University in Columbus, OH, bedanken.

Akram El-Rikabi danke ich für die Bereitstellung eines Test-Accounts für die Thomson Venture Economics Datenbank und die Möglichkeit die Daten im Rahmen meiner Promotion und für weitere akademische Zwecke nutzen zu können.

Meinen Kollegen im Doktorandenprogramm möchte ich meinen Dank für viele Diskussionen und Gespräche im Rahmen unserer Brown-Bag, Brown-Beer, und Doktoranden Seminare aussprechen.

Für die vielen fruchtbaren Gespräche, Diskussionen und Anregungen in bezug auf meine Forschung und unsere Fachbereichstipprunde danke ich insbesondere meinen Lehrstuhlkollegen Julia Hein und Thomas Weber.

Ganz besonders danke ich natürlich meinen Eltern, die mich unermüdlich während meines Studiums und meiner Promotion unterstützt haben. Sie haben mir Vieles ermöglicht, was ohne sie nicht möglich gewesen wäre und ohne sie wäre ich sicherlich niemals soweit gekommen.

Meiner Freundin Katharina danke ich für ihre Geduld, ihre Aufmunterung und ihre immerwährende Zuversicht während der langen Durststrecken bei der Erstellung dieser Arbeit.

(3)

iii

List of Tables:

Table 1-1: Round Financing by Industry and Stage of Development 1995 – 2005 ... 28

Table 1-2: Descriptive Statistics and Correlation Matrix: Duration Analysis ... 29

Table 1-3: Descriptive Statistics and Correlation Matrix: Average Amount Analysis ... 30

Table 1-4: Estimation Results for the duration of financing rounds using a Weibull Duration Model . 31 Table 1-5: Estimation Results for the average amount provided per round using OLS Regression ... 32

Table 2-1: Descriptive Statistics and Correlation Matrix ... 59

Table 2-2: Rare Events Logistic Regression with clustering on the lead investor level ... 60

Table 3-1: Descriptive Statistics and Correlation Matrix ... 90

Table 3-2: Output Logistic and Multi-Level Regressions ... 91

Tabelle 4-1: Deskriptive Statistiken und Korrelations Matrix ... 127

Tabelle 4-2: Logistische Regression mit „Rare Events“-Anpassung ... 128

Table 5-1: Round Financing by Industry and Stage of Development ... 145

Table 5-2: Summary Statistics for VC categories ... 146

Table 5-3: VC Characteristics and Average Number of Financing Rounds ... 147

Table 5-4: VC Characteristics and Syndication Activities ... 148

Table 5-5: VC Syndication, Staging Activities and Investment Success ... 149

List of Figures:

Figure 2-1: Resources and Organizational Capabilities in VC Financing ... 36

Figure 2-2: Yearly transaction breakdown by number of total and syndicated transactions ... 40

Figure 2-3: Industry breakdown of transactions by number of total and syndicated transactions ... 41

Figure 3-1: Number of Deals and Syndicated Deals, thereof reinforcing/expansion events ... 69

Figure 3-2: Industry Breakdown over the period 1995 - 2005 ... 71

Grafik 4-1: Übersicht der Anzahl VC-Transaktionen nach Jahren ... 105

Grafik 4-2: Übersicht Anzahl VC-Transaktionen nach Branchen ... 106

Grafik 4-3: Reguläre Äquivalenz auf Basis des REGE Algorithmus ... 112

(7)

1

Executive Summary

This dissertation comprises five different stand-alone research papers that were written as part of the doctoral program in “Quantitative Economics and Finance” at the University of Konstanz within the period of January 2004 and January 2008. All of the papers deal with an empirical analysis of Venture Capital (VC) financing in Germany and Switzerland, with a special focus on the emerging trend of VC syndication (the provision of capital to high-growth firms by more then a single venture capitalist), the corresponding partner selection in VC syndicates and the governance choices in VC financing. The entire dissertation consists of four research papers in English and one in German.

Chapter one analyzes the governance structure in entrepreneurial financing contingent on the underlying transaction and the corresponding investment experience of the funding VCs. We find that a higher level of uncertainty positively affects a VCs incentive to commit capital incrementally in order to overcome the asymmetric information problem faced when providing capital to cash constraint entrepreneurs. The findings endorse the results of previous studies (Folta (1998); Kogut and Zander (1992)) showing that the option to learn through incremental investment activity can present an opportunity to soothe uncertainty. The duration of financing rounds (all else equal) is affected negatively by the level of uncertainty the VCs face and positively by investment experience that can be used to attenuate the corresponding uncertainty, but not by mere syndication efforts alone. Our results show that the existing combination of resources (investment experience within the transaction- relevant industry) can be unique to help the VCs conceive financing arrangements that other VCs can only partially imitate. VCs which are more able to analyze complex environments can better anticipate future contractual hazards and can make use of less protective forms of governance to control and monitor entrepreneurial effort.

Chapter two discusses and presents the factors impacting partnering decisions in Venture Capital syndicates using a unique dataset of 2,373 VC transactions in Germany. By including time varying information about industry experience and cooperation patterns we explicitly take into account not only the changing social context for partner selection but also the dynamic nature of financial and managerial resources of VCs. The data suggests strong evidence that lead investors try to access additional industry experience that allows the provision of higher quality managerial advice to the funded entrepreneur. Moreover, we find strong evidence that information sharing and trust can create a foundation for future cooperation. The data indicates that the chances to participate in a newly formed syndicate rise significantly for a potential partner VC when previous direct ties are present with the current lead investor.

(8)

2

Chapter three analyzes the origins of social networks in VC financing and documents how they evolve over time given that potential gaps between existing VC resources and aspired value creation exist.

We focus specifically on the industry and investment experience of VCs as a resource to allow for better screening of business proposals and to provide a higher quality of managerial advice to the financed entrepreneur. The data reveals that a lack of industry experience for a given transaction forces VCs to adapt to new circumstances and eventually alter strategic foci in partner selection. Our findings show, that upon entrance into new industries, and in the case of unsuccessful collaborations, lead investors in VC syndicates tend to work with new partners and ultimately expand their social networks. Hence, we document that resource-based theories comprise a logic of change when tested in dynamic market environments, where competitive advantages might erode over time and venture capitalists are coerced to adapt and re-configure competences.

Chapter four (a research paper in German) emphasizes the role of complimentary skills and competencies for the achievement of sustainable competitive advantages. Lead-Investors prefer to team up with partners that differ in their strategic position and allow for the creation of superior returns through the combination of comparative advantages for mutual gain. A likely reduction of uncertainty in partner selection through the selection of similar partners is outweighed by the better quality of advice generated through the pooling of complimentary skills and competencies. Overall this article emphasizes the role of resources and capabilities for the selection of appropriate partners in VC syndicates and underpins the role of complementarities and idiosyncratic competencies in the creation of sustainable competitive advantages.

Chapter five deals with the determinants of staging and syndication in VC financing in Switzerland and analyzes the corresponding performance consequences. The results suggest that among the different affiliations of VC investors in Switzerland especially independent investors make more extensive use of staged capital infusions. Moreover, the results suggest that staging is employed as a tool for mitigating risks in VC financing. In addition, syndication can serve as an entrance strategy for foreign VCs. Furthermore, the data provides evidence that VCs, which realize the benefit of staging, do also perceive the value added stemming from the involvement of partners. Consequently, VCs that make use of staging are also more open to syndication. With respect to the value-added of co- Investment behavior, syndication positively impacts the success rate of a VC, whereas VCs that are more locally embedded do exhibit lower success rates for their investment portfolio.

(9)

3

Zusammenfassung

Die vorliegende Dissertation beinhaltet fünf unabhängige Forschungspapiere, die im Rahmen des Promotionsprogramms „Quantitative Economics and Finance“ an der Universität Konstanz im Zeitraum von Januar 2004 bis Januar 2008 erstellt wurden. Der Fokus bei allen Papiere liegt auf einer empirischen Analyse von Venture Capital (VC) Finanzierung in Deutschland und der Schweiz, mit einem besonderen Augenmerk auf den aufkommenden Trend der Syndizierung von Venture Capital, also der Bereitstellung von Wachstumskapital für junge Unternehmen durch mehr als einen VC- Geber, der Partnerselektion in VC Syndikaten und der Governance-Struktur bei der Kapitalbereitstellung. Die Dissertation umfasst vier englisch-sprachige und einen deutsch-sprachigen Beitrag

Kapital eins analysiert die Governance-Struktur bei der Finanzierung von jungen Wachstumsunternehmen unter Berücksichtigung der zugrunde liegenden Transaktionscharakteristika und den Eigenschaften der beteiligten VC-Geber. Die Ergebnisse zeigen, dass ein höheres Maß an Unsicherheit über die finanzierte Transaktion die Anreize für den beteiligten VC-Geber zur Implementierung einer gestaffelten Kapitalzuführung und damit zur Überwindung des Problems der asymmetrischen Informationsverteilung signifikant positiv beeinflusst. Die Ergebnisse bekräftigen die Resultate früherer Studien (Folta (1998); Kogut and Zander (1992)), die zeigen, dass die Lern-Option der VC-Geber (durch die inkrementelle Zuführung von Kapital) eine Möglichkeit darstellt, die bestehende Unsicherheit abzuschwächen. Die Zeit zwischen den einzelnen Finanzierungsrunden wird (ceteris paribus) negativ durch die Unsicherheit (mit der die VC-Geber konfrontiert werden) und positiv durch die Investitions-Erfahrung der VC-Geber (um bestehende Unsicherheit abzumildern) beeinflusst. Syndizierungsaktivität der VC-Geber ist alleinig nicht in der Lage Unsicherheiten abzuschwächen und beeinflusst die Dauer der Finanzierungsrunden daher nicht signifikant. Die Ergebnisse zeigen, dass die bestehende Kombination von Ressourcen (Investitions-Erfahrung in der zugrunde liegenden Branche) einzigartig sein kann, und es VC-Gebern somit ermöglicht Finanzierungsstrukturen zu wählen, die anderen VC-Gebern in dieser Art und Weise nicht offen stehen. VC-Geber, die in der Lage sind komplexe Situationen besser zu analysieren, können zukünftige vertragliche Unwägbarkeiten genauer abschätzen und daher weniger restriktive Governance-Strukturen der VC-Finanzierung implementieren, um den finanzierten Entrepreneur zu überwachen.

Kapitel zwei beschäftigt sich mit der Partner-Selektion in VC-Syndikaten. Anhand eines Datensatzes von 2.373 VC Transaktionen in Deutschland werden mithilfe zeitvarianter Informationen über die Branchen-Erfahrung und Kooperationsmuster der VC-Geber die bestimmenden Faktoren der Partnerwahl in VC-Syndikaten untersucht. Die empirische Analyse berücksichtigt sowohl den sich

(10)

4

zeitlich verändernden sozialen Kontext der Syndikatsbildung, als auch die dynamische Entwicklung der finanziellen und betrieblichen Ressourcen der VC-Geber.

Die Resultate zeigen eine starke Evidenz, dass Lead-Investoren (die federführenden Parteien in einem VC-Syndikat) versuchen, durch die Auswahl ihrer Partner Zugang zu zusätzlicher Investitions- und Branchen-Expertise zu erhalten, die eine bessere Beratungs- und Betreuungsleistung der finanzierten Unternehmen ermöglichen kann. Des Weiteren zeigen die Ergebnisse, dass Vertrauen in der beidseitigen Beziehung der VC-Geber eine Basis für zukünftige Kooperationen sein kann. Die Wahrscheinlichkeit einer Syndikatsteilnahme für einen potentiellen Partner steigt signifikant an, wenn eine direkte Beziehung zu dem einladenden Lead-Investor vorhanden ist.

Kapitel drei untersucht die Herkunft und Entstehung sozialer Netzwerke zwischen den beteiligten VC- Gebern im Rahmen der VC-Finanzierung und zeigt, dass die Entwicklung dieser Netzwerke durch potentielle Lücken zwischen bestehenden Ressourcen-Portfolios und der angestrebten Wertschöpfung getrieben wird. Die Investitions- und Branchenerfahrung der VC-Geber (die eine bessere Auswahl der Transaktionen und eine qualitativ höhere Beratungsleistung ermöglichen soll) findet in der empirischen Auswertung besondere Berücksichtigung. Die Ergebnisse zeigen, dass ein Mangel an Branchenerfahrung für eine zugrunde liegende Transaktion dazu führt, dass sich Lead-Investoren den neuen Gegebenheiten anpassen müssen und dementsprechend gezwungen sind ihre Partner- Selektions-Strategien zu adaptieren. Bei der ersten Transaktion in eine neue Branche (und im Falle vorheriger erfolgloser Zusammenarbeiten) tendieren Lead-Investoren dazu, neue Partnerschaften einzugehen und ihr soziales Netzwerk zu erweitern. Die Resultate dokumentieren, dass Ressourcen- basierte Theorien eine Logik des Wandels beinhalten, wenn Wettbewerbsvorteile in dynamischen Märkten über den Zeitverlauf verschwinden und VC-Geber gezwungen sind, sich neuen Umgebungen anzupassen und Kompetenzen auffrischen müssen.

Im vierten Kapitel (ein Arbeitspapier in deutscher Sprache) werden die treibenden Faktoren bei der Partner Selektion in Venture Capital-Syndikaten untersucht. Um eine bessere Beratungs- und Management-Unterstützung zu gewährleisten, bilden Ressourcen und Fähigkeiten der potentiellen Partner das Kernstück der Analyse zur Partnerwahl durch den einladenden, sog. Lead-Investor. Die Resultate zeigen, dass sich die Investitions-Erfahrung eines potentiellen Partners positiv auf die Wahrscheinlichkeit einer Einladung auswirkt. Darüber hinaus betonen die Ergebnisse die Rolle komplementärer Eigenschaften. Einladende Investoren bevorzugen die Zusammenarbeit mit Partnern, die sich in ihrer strategischen Ausrichtung von der eigenen unterscheiden und in dieser Hinsicht die Verbindung von komparativen Stärken zum gemeinsamen Vorteil ermöglichen. Die mögliche Reduzierung von Informationsasymmetrien durch die Einbindung ähnlich ausgerichteter Partner wird somit durch den Mehrwert der qualitativ hochwertigeren Beratungs- und Management-Unterstützung in der Kooperation mit komplementären Partnern aufgewogen. Insgesamt zeigen die Ergebnisse die Bedeutung von Ressourcen/Fähigkeiten bei der Auswahl geeigneter Partner im Rahmen der Bildung

(11)

5

von VC-Syndikaten auf und betonen die Wichtigkeit der Verbindung von komplementären, idiosynkratischen Kompetenzen zur Erzielung langfristiger Wettbewerbsvorteile.

Kapitel fünf analysiert die Determinanten des Syndizierungsverhalten und der Einsatzes von gestaffelten Kapitalzuführungen (Staging) bei der Venture Capital (VC) Finanzierung in der Schweiz.

Die Resultate zeigen, dass unter den unterschiedlichen Arten von Beteiligungsfirmen in der Schweiz insbesondere unabhängige Investoren deutlich stärker auf gestaffelte Kapitalzuführungen zurückgreifen. Darüber hinaus zeigt die empirische Analyse, dass staging zumeist als Mittel zur Abmilderung von VC-Finanzierungsrisiken verwandt wird. Ferner gibt es Evidenz, dass VC Gesellschaften, die den Vorteil von staging erkennen Infolgedessen sind VC Gesellschaften die vermehrt staging einsetzen auch offener für Kooperationen mit anderen VC Gesellschaften., in der Regel auch verstärkt auf den Mehrwert durch die Einbindung von Partnern zurückgreifen.

Darüberhinaus kann die Syndizierung von VC Transaktionen eine Möglichkeit zum Markteintritt für ausländische VC Gesellschaften bieten. Bezüglich der Existenz eines Mehrwerts durch die Einbindung von Partnern zeigen die Ergebnisse, das Syndizierung einen positiven Effekt auf die Erfolgsrate der VC Gesellschaften hat, wobei lokal ansässige VC Gesellschaften in der Regel geringere Erfolgsraten für ihre Portfolios aufweisen.

(12)

6

1 The Impact of Transaction Characteristics and Investment Experience on the Governance Structure of Entrepreneurial Financing

1.1 Introduction

Venture Capital (VC) financing takes place in emerging and knowledge intensive industries where the value of the funded projects is highly uncertain and future pay offs are distant. The difficulty to disentangle the contribution of individual activities and the outcome of bad luck gives substantial leeway to the entrepreneur. Moreover, asset specificity increases the conditions for bilateral dependency and coordinated responses and calls for more direct control in the exchange relationships (Monteverde (1995); Monteverde and Teece (1982); (Folta (1998)). Given the low (or sometimes even non-existent) value of collateral and the high involvement of asset specific tacit knowledge, the level of uncertainty faced is more pronounced for the venture capitalists (VCs) and defection by the entrepreneur might go undetected (Gompers (1995); Gompers and Lerner (2002)). Accordingly, the implementation of suitable governance mechanisms is important to cope with the inherent uncertainties and the highly explorative character in VC financing. By implementing staged financing structures to manage the relationship with the entrepreneur as their mode of governance, VCs can capitalize on incremental investments by creating a portfolio of growth options. Through staging the investment amount into smaller increments VCs can create options to defer investments that can limit downside exposure when the financed venture turns out to be less profitable then expected or limit opportunistic behavior of the funded entrepreneurs (Leiblein and Miller (2003); Gompers (1995);

Mayer and Salomon (2006), Holmstrom (1979)).

Using a unique sample of 2,373 Venture Capital transactions in Germany during the period of 1995 – 2005 we analyze governance choices implemented in entrepreneurial financing contingent on the underlying transaction and the corresponding investment experience of the VCs. We find that higher uncertainty positively affects a VCs incentive to commit capital incrementally. The data reveals that if an investment is made in an earlier stage VCs tend to portion their payments into successive stages rather than providing a lump sum payment upfront. We offer insights into the understanding of how VC resources (investment experience within the transaction-relevant industry to proxy for technological, financial and managerial expertise) and capabilities (the ability to better screen business proposals and offer a higher quality of advice to the funded entrepreneur) along with transaction specific characteristics jointly determine the optimal governance form and identify how pertinent industry experience affects a VCs ability to monitor entrepreneurial progress more effectively and allow the implementation of weaker forms of governance to control and monitor the entrepreneur.

(13)

7

Existing and combined investment experience influences the contemporaneous governance choices implemented in VC financing and can be unique to help the VCs conceive financing arrangements and implement the corresponding governance structure that other VCs can only partially imitate. VCs which are more able to analyze complex environments can better anticipate future contractual hazards and can make use of less protective forms of governance. The findings endorse the results of previous studies (Folta (1998); Kogut and Zander (1992)) showing that the option to learn through incremental investment activity can present an opportunity to attenuate uncertainty thereby affecting the choice of governance in entrepreneurial financing. Whilst our results show that the transaction specific factors impact the governance structure in entrepreneurial financing, we go one step further by documenting how characteristics of the principal (the VCs) affect the chosen governance structure to monitor and control the effort provision of the agent (the financed entrepreneur). The resource based view of the firm (RBV) thus complements transaction cost economics and taken together, both enhance our understanding of governance choices implemented in VC financing. In line with a multitude of papers on organizational capabilities our findings suggest that VC-specific capabilities significantly impact governance decisions and that investment experience of VCs can translate into governance capabilities that could diminish the costs of monitoring and oversight (Barney (1991); Wernerfeldt (1984); Peteraf (1993); Penrose (1959)). Investment experience can enable a solid understanding of the technical background of the financed technology and allows the VC to verify the entrepreneur’s abilities and monitor the R&D progress, and (at least partly) prevent shirking. Moreover, the results support the view that VCs are value added investors that create returns beyond the pure provision of growth capital. Entrepreneurs are correspondingly trading off the value added from being backed by a more experienced VC over the price for such an affiliation. Consequently, the data shows that more experienced VCs can access financing relationships at better terms and the average amount provided is substantially lower for more experienced VCs.

We will proceed as follows. Chapter two will provide the theoretical background and develop the hypotheses. Chapter three will present the dataset and provide the descriptive statistics along with the independent and dependent variables used in the empirical part. Chapter four presents the estimation results and discusses implications of the findings. Chapter five summarizes the results and considers potential limitations and further extensions.

1.2 Theoretical Background and Hypotheses

1.2.1 Staging as a mechanism of Venture Governance

According to transaction costs economics, the chosen form of governance is a function of the underlying transaction characteristics. More uncertainty surrounding a transaction increases the

(14)

8

number of contingencies and hence, raises the costs of writing, enforcing and monitoring a contingent claim contract. Practically it is impossible to incorporate all future contingencies into a transaction- specific contract which creates room for subsequent re-negotiations and opportunistic behaviour. Due to the infeasibility to actually write fully contingent contracts in VC financing, substantial leeway is given to the entrepreneur to extract private benefits. In fact, in the absence of asymmetric information problems VC financing becomes simple. All money would be provided upfront and entrepreneurs would decide on continuation/abandonment based on their own private information. However, in practice entrepreneurs can accumulate private benefits and have incentives to continue investing in bad projects to maximize their own wealth at the detriment of their financiers. Entrepreneurs can either invest in strategies that have high personal but low monetary returns (Gompers (1995) coins the example of research for one´s own recognition rather then for commercialization) or engage in high- variance projects, as they benefit on the upside and do not lose on the downside (gambling with other people´s money). Hence, significant conflicts between the VC and the entrepreneur exist, that make monitoring of entrepreneurial effort valuable for the VC. According to Kirilenko (2001) control rights can help VCs overcome the problems of asymmetric information and turn entrepreneurial talent into commercial success. Accordingly the choice of governance modes in VC financing is a means that affects the costs of monitoring and administering a transaction (Leiblein (2003); Williamson (1975);

Williamson (1985)). Each time monitoring takes place and decisions over subsequent funding are made, contracts need to be re-written and negotiated, subsequent costs are incurred for the VC. Hence, continuous monitoring would become too costly to perform and VCs therefore finance entrepreneurs in discrete stages and check upon the funded venture´s progress periodically. Moreover, given the uncertainty in timing and amount of future cash flows, committing all resources upfront would forego valuable learning opportunities for the VC. Increases in resource commitment might be detrimental for the overall project value given the highly explorative nature of investments that are often done in new technical domains. By financing sequentially VCs can capitalize on the upside of the venture while being able to terminate the investment when prospects turn out to be unfavourable. The value through staging is derived from a VCs ability to defer future capital commitments and makes the investment analogous to a compound option. Hence, the VCs invest in a portfolio of nested growth options (where the current options are prerequisites for later ones) consisting of the funded firms ability to search and develop future competencies (Kogut and Zander (1992); Balakrishnan and Koza (1993)). Each stage of investment then yields valuable insights into the value of embedded options. When the investment is staged and the capital infusions take place in small increments, rather than involving a large upfront payment, the prospects of the firm are re-evaluated on an ongoing basis. McDonald and Siegel (1986) show that the option value increases with higher levels of uncertainty. Hence, this incremental mode of governance economizes on the costs of committing resources to a project of uncertain value and learning about growth opportunities (Folta (1998)).

(15)

9

Sahlman (1990) concludes that the staging of capital commitment is one of the strongest control mechanisms to help VCs overcome the asymmetric information problem faced. Staging the capital infusion enables the VC to keep the entrepreneur on a tight leash. The more likely conflicts with the entrepreneur are and the more pronounced the effect of uncertainty over the outcome is, the higher will the value added through oversight be (Gompers (1995); Sahlman (1990); Fluck et al. (2006)).¹ In more uncertain environments (with higher asset specificity and correspondingly a greater dependence on entrepreneurial effort) VCs are more likely to encounter unforeseen contingencies and would benefit more from staging capital infusions. For funded firms with substantial amounts of intangible assets and where products are far from commercialization theses problems become even more severe (Gompers and Lerner (2002)). Scrutiny in deal selection and subsequent monitoring and control is of importance to align managerial effort with the goals of the financing VCs. Gompers (1995) documents that VCs invest in early stage ventures and high technology industries where the value of monitoring and oversight is potentially more valuable. In general, increases in asset tangibility increase funding duration and reduce monitoring intensity. Consequently, when VCs face more uncertainty upon investing, a more protective form of governance (with more intense monitoring and shorter durations in-between financing rounds) should be implemented. We therefore formulate the following hypothesis:

Hypothesis 1: With an increase in investment uncertainty faced, VCs re-evaluate and monitor firm progress more frequently and provide funding for a shorter period of time.

1.2.2 Investment Experience and Governance Capabilities

Williamson (1975) posits that the optimal organizational form is driven by efficiency considerations.

Problems of opportunism are resolved through the use of appropriate governance choices. In fact, TCE argues that the governance between VCs and entrepreneurs is costly and governance forms differ in their capacity to ease the exchange given the attributes of the underlying transaction. These arguments mainly build upon the existence of costs to enforce, monitor and control the VC – entrepreneur relationship. On the contrary, RBV theories argue that VC-level resources (investment experience within the transaction-relevant industry to proxy for technological, financial and managerial expertise) and capabilities (the ability to better screen business proposals and offer a higher quality of advice to

1 The two commonly employed mechanisms of staged financing are milestones and round financing. In round financing, each new capital infusion is negotiated separately, whereas in milestone financing the decision whether to inject new capital is made contingent on the portfolio company meeting predefined targets in terms of product development or financial figures. Talmor and Cuny (2005) analyze various factors impacting the choice between round financing and milestones. They find that if the role of the VC is more important than the entrepreneur, milestone financing is more efficient than round financing and vice versa. Bienz and Hirsch (2005) analyze the role of milestones versus round financing in the context of German VC agreements. The form of staging is determined by the predictability of the development process. They find that milestone financing is used more often with advanced firms, where adequate milestones can be implemented. For younger and inexperienced firms round financing with successive renegotiation is implemented. In this paper no distinction between round and milestone financing can be inferred from the dataset.

(16)

10

the funded entrepreneur) can counter and mitigate the detrimental effect of transaction-specific characteristics like technological uncertainty and lack of collateral. While it is costly (in terms of time and resources) for VCs to acquire and interpret information concerning the underlying venture and eventually future progress, little is known about the role of VC-specific capabilities in attenuating uncertainty and mitigating information asymmetries vis-à-vis the funded entrepreneur, although variations in skills and resources (and ultimately performance) do exist (Kaplan and Schoar (2005)).

Williamson (1998) notes, that the question is not what is the best governance structure given the transaction-characteristics, but rather which governance structure is most suitable for a firm (with certain characteristics) organizing a transaction (with its own characteristics).

With respect to the decision how to implement staging in entrepreneurial financing, VCs have to identify and assemble resources to cope with the underlying investment (to ensure future value added) and secondly, decide on how to capture value through the implementation of governance mechanisms.

Leiblein (2003) points out that RBV and real option logic can help to identify a set of resources and investment opportunities that can directly influence governance decisions in combination with common transaction specific concerns. The investment capabilities of VCs are comparable to the technological capabilities in Mayer and Salomon (2006) who argue that that the possession of stronger technological capabilities improves a firm’s ability to govern transactions. RBV theories predict that the existence of superior firm-level resources and capabilities affects the ultimate drivers of transaction costs, namely contractual hazards, negatively. More developed investment capabilities enable VCs to select better deals, effectively monitor the venture’s progress and share knowledge with the entrepreneur to create value. The decision of governance therefore depends on transaction and VC- specific characteristics alike. By focusing exclusively on the characteristics of the underlying transaction, differences in capabilities and experience of participating VCs do not enter the picture.

Recent theoretical and empirical work stresses, however, the role of differing resources and capabilities across firms. The existence of strengths, and correspondingly weaknesses, in financing and advising start-ups has substantial performance impacts (Gompers and Lerner (2002); Kaplan and Schoar (2005)). Given the substantial differences in VC-level resources and capabilities, one would therefore expect to see variations in governance structures implemented. The prevailing governance choices implemented in VC financing could be heavily influenced by the existing repository of investment experience of VCs that leverage upon their idiosyncratic resources. Hence, we would expect that variations in investment experience explain differences in governance modes implemented by VCs to control and monitor effort provision of the financed entrepreneur. Experience in the underlying industry of investment can help to better define roles and responsibilities, identify future milestones and appropriate financial incentives. Investment capabilities therefore attenuate the problem of asymmetric information and correspondingly should affect the observed governance structure. Hence, these investment capabilities could translate into governance capabilities. The combination of resources can be unique to help the VCs conceive and implement financing

(17)

11

arrangements and the corresponding governance structure that other VCs can only partially imitate.

We therefore argue that VCs can use their existing investment experience to create governance capabilities that allow them to alter the choice of governance modes. VCs which are more able to analyze complex environments can better anticipate future contractual hazards and can make use of less protective forms of governance (Barney and Hansen (1994); Leiblein (2003)). We formulate the following hypothesis:

Hypothesis 2: More investment experience in the transaction-relevant industry allows VCs to create governance capabilities that enable more effective monitoring of firm progress, so that the time period in-between financing rounds can be lengthened.

1.2.3 Syndication and Governance

RBV theories argue that factor markets exist that allow firms to acquire or develop resources to engage in product market competition. Resources therefore affect a firm’s ability to implement successful strategies and capture economic value. While internal firm resources are key to acquiring and sustaining competitive advantages, the lack thereof leads to alternative routes of generating and accessing knowledge to prosper (Pfeffer and Salancik (1978); Barney (1991)). Accordingly, inter- organizational relationships can create value by allowing firms to combine resources and share knowledge. Alliances and partnerships are an attractive mean for a firm to enhance its resources if the current repository is not sufficient to achieve the desired outcome (Harrison et al. (2001)). Experiences made can be combined with the tacit knowledge of the partners for mutual gain. Developing and taking advantage of new opportunities can be achieved through the integration of different sets of resources and capabilities that are private and unique in nature (Barney (1991); Hoskisson and Busenitz (2001)).

Collaboration between multiple VCs can present an enhanced opportunity for learning and sharing of resources that can help VCs to reduce the level of uncertainty faced when financing risky ventures. If more than one VC is involved in the screening process before the selection of an investment opportunity the evaluation of the venture proposal becomes more efficient and reduces the potential danger of adverse selection (Lerner (1994); Brander et al. (2002; Lockett and Wright (2003)).

Cumming (2006) documents that the syndication of VC can attenuate the problems of adverse selection and argues that syndication can reduce informational asymmetries, as VCs investing jointly are able to combine resources in order to share information and improve screening abilities. Among others, Sutter (2005) finds experimental evidence for the effectiveness of decision making in groups and Rockenbach et al. (2007) find that teams exhibit better risk/return profiles. Barney and Hansen

(18)

12

(1994) suggest that firms with management teams might be better able to analyze complex environments and consequently, are able to better anticipate contractual hazards. Hence, VCs with the appropriate investment experience (within a given industry) can combine their resources for mutual gain.

In fact, combining knowledge of multiple VCs can help to manage the inherent uncertainties faced and could therefore impact the need to implement protective modes of governance negatively. A VCs governance decision could thus be influenced by the desire to exploit advantages in developing or accessing capabilities (Barney (1999); Teece (1980)). We therefore argue that VCs can opt for intensive collaborative arrangements with partner VCs in order to get access to new resources and capabilities to mitigate contractual hazards. As a matter of fact, the implementation of governance modes can also be influenced by the combination of VC experiences within a given industry to overcome a potential shortage of resources to offer a better quality of advice and improve continuation/abandonment decisions. These considerations lead to the following hypothesis.

Hypothesis 3: Syndication allows for the combination of investment experience in the transaction-relevant industry to create governance capabilities, so that the time period in- between financing rounds can be lengthened.

1.2.4 Investment Experience, Syndication and Capital Provided

For the entrepreneurs it might matter more, whose money they are actually receiving instead of worrying how much money they will actually get. The general notion is that VCs are value added investors and that the support by VCs goes far beyond the mere provision of growth capital. Given the mobility of capital and the easy access to the market there could hardly be any sustainable competitive advantage for VCs if they only act as financial intermediaries that offer risk capital to cash constraint entrepreneurs. At least some of the resources and capabilities that VCs develop have to be limited in supply or rather costly to imitate in order to generate superior rents (Barney (1991); Shapiro (1983)).

Developing investment capabilities therefore presents a valuable strategy to achieve higher long-term returns. Kaplan and Schoar (2005) document substantial differences in VC performance and support the view of heterogeneously distributed investment resource and capabilities. Creating rare and costly to imitate investment capabilities can help to differentiate VCs and could also deter entry from competitors (Shapiro (1983); Barney (1991), Hochberg et al. (2006)).

Initial endowments of entrepreneurs in terms of managerial skills and capital available might differ substantially and thus there is also heterogeneity in demand for VCs skills based on the differential expectations of marginal benefits of advice (Hsu (2004)). Given that capital infusions are the outcome

(19)

13

of negotiations between the VC and the entrepreneur rather then driven by pure calculation (as valuations are somewhat problematic given the surrounding technical and demand uncertainty that renders standard valuation techniques infeasible), these expectations are reflected in prices offered (by VCs) and offers accepted (by entrepreneurs) when trading off the capital infusions and the corresponding equity sold (alongside the resulting control implications). Empirical evidence shows that entrepreneurs are therefore more willing to forego higher valuation offers if they can work with VCs that are more reputable and experienced, although they might receive less cash and rather benefit from better advice and network resources (Hsu (2004)). According to Megginson and Weiss (1991) entrepreneurs might have to compromise on the valuation to attract more experienced and reputable VCs. Hsu (2004) finds that entrepreneurs are more inclined to work with more experienced VCs and tend to accept offers with a two-digit discount. While entrepreneurs might give up a larger equity stake, or receive less money for a given equity stake, they anticipate to recoup money in the long run due to the higher quality of advice offered by more reputable VCs. Hence, when VCs bring more to the table then the pure provision of capital, there has to be an incentive for the creation of the corresponding investment capabilities. Industry experience of the VCs should therefore not only be reflected in the actual governance structure of the financing relationship but should likewise affect the conditions of the financing arrangement. We therefore formulate the following hypothesis:

Hypothesis 4: VCs with more investment experience in the transaction-relevant industry (that eventually allows for the provision of better managerial advice) can access financing relationships at better terms and are more likely to provide lower amounts of capital for a corresponding venture.

1.3 Data Description and Methodology

1.3.1 The Investment Sample

The sample consists of 2,373 Venture Capital transactions in Germany within the period 1995 - 2005.

The number of total financing events (2,373) comprises capital injections of 447 VCs that are subsequently made over different stages (Start Up, Early Stage and Late Stage) into 964 firms. On average a funded firms thus goes through 2.2 rounds of financing. The transactions have been compiled by using public sources and the Thomson Venture Economics (TVE) Database. We identified the involved parties in each transaction and the corresponding information on the VC along with the funded firms. The result is a deal survey exhibiting who funded a new company and was joined by which partner. Moreover, we collected information about each financing round. As such, we identify which VC made an investment into a target firm at which point in time. In addition, we

(20)

supplemented the database with information regarding the VCs and the funded firms, along with information specific on the actual deal. Therefore it is possible to make more distinct inferences about the driving characteristics of staging patterns at the point of investment. The analysis carried out is made on the basis of investments rounds as indicated through Thomson Venture Economics. A distinction between milestone and round financing cannot be observed. ²

1.3.2 Methodology

Gompers (1995) reasons that the duration of financing rounds (the time in-between subsequent injections of fresh capital) proxies for the intensity of monitoring. The shorter the duration of the financing rounds is, the more frequent are the monitoring activities of the VC to gather information on the venture´s progress. Kaplan and Stromberg (2004) point out that by providing less funding in a given round and shortening the time until the next financing round the VC increases the ability to liquidate the venture if performance is unsatisfactory. Correspondingly, we use the duration between successive financing rounds as the dependent variable in hypothesis 1 to 3 and estimate a Weibull Duration model using robust standard errors. The sample under consideration uses only firms that have been subject to at least two rounds of VC financing to get an accurate estimate of durations in- between capital injections.³

As in Gompers (1995) funded firms have a certain probability of receiving financing in a subsequent round. Hence, the instantaneous probability of receiving financing is modeled by the hazard rate that measures the probability of receiving funding between t and t + Δt over the probability of receiving funding after t. The distribution of the hazard rate is assumed to follow a Weibull distribution as in Gompers (1995), other distributions did not qualitatively affect the coefficients and signs estimated.

As opposed to Gompers, we model the likelihood of receiving financing using the days in between financing events as opposed to months. The coefficients are estimated using maximum likelihood technique. Positive coefficients shown in the tables indicate longer financing durations on average.

Table 4 displays coefficients rather than exponentiated coefficients (hazard ratios). The hazard for all models estimated is monotonically increasing indicating that with more time elapsed, the probability of receiving additional funding increases. The estimated model is equal to:

ht

14

2 Gompers and Lerner (2002) study the completeness of the TVE database and argue that most VC investments are contained and that those missing are among the less significant ones. The studied sample therefore is unlikely to suffer from a sample selection bias by focusing on TVE data.

3 By taking the amount of capital provided as exogenous we follow the typical procedure in theoretical and empirical work (see among others Keuschnigg (2003) or Manigart et al. (2005). We did control for the impact of the amount provided, but given the substantially reduced sample size (less than 200) no meaningful inferences can be drawn from this analysis.

(21)

k kx

e x

t h t

h( )= ₀( ) ^β⁰⁺^β¹¹⁺^...⁺^β with the baseline hazard function being equal to h₀(t)=t¹^/(^σ⁻¹⁾

With the explanatory variables to and the corresponding coefficients to , respectively. For hypothesis 4 we estimate an OLS regression (with robust standard errors) using the average amount provided per involved VC for each capital injection. In contrast, this sample includes all transactions where the funded firm receives capital and information about the actual amount provided is available through TVE. TVE provides information about the total amount of financing provided within a specific round. In order to retrieve the separate contributions of each VC we simply divide the total amount by the corresponding number of involved VCs, as TVE does not provide any information about the varying percentage stakes acquired by the involved VCs. Funded firms do appear in the dataset as often as they received capital over the investment horizon. Therefore, we cluster the standard errors on the funded firm level in order to control for firms with multiple rounds of financing observed over time.

X1 x_k β₁ β_k

In order to rule out censoring effects that could stem from investments into portfolio firms at the end of the analysis horizon (deals in 2004/05 could be subject to censoring as the next financing round could not have been observed yet and firms are therefore not in the sample investigated) or due to bankruptcy (firms were not long enough solvent to obtain a new round of financing or VCs where reluctant to finance an additional round) we re-estimate the regressions shown using a year dummy for the year of the first investment and focusing on active firms in the sample, respectively. Bankruptcy data has been obtained through the German commercial register. It turns out that none of the time dummy variables is robustly significant. Moreover focusing on active firms only, does not affect the results shown (neither signs nor coefficients change noticeably). Therefore we will present in the following the results from the full regression specifications.

1.3.3 Explanatory Variables

Funded Firm Age: With respect to hypothesis 1 arguing that with a higher risk of investing VCs should rely to a larger extent on staging we gathered data about the funded firms founding date and combined that information with the investment date to arrive at the age of the funded firm at the date of each capital infusion. As pointed out in Bygrave (1987) younger firms are more likely to fail and consequently firm age at investment can serve as a proxy for the riskiness of a venture.

Stage of Development: In addition, we collected information about the different stages of company development when an investment was made. Gompers (1995) points out that early stage companies have short or no corporate histories and the evaluation of growth prospects becomes even

15

(22)

16

more difficult in these phases. TVE gives information about five different stage categories: Start Up/Seed, Early Stage, Expansion, Later Stage and Other. Similar to Gompers (1995) who labels the categories for bridge, second and third stage financing as "Late Stage" financing, we combined the TVE categories Expansion, Later Stage and Other to form a new category, that we also label "Late Stage". As there is no clear distinction between expansion financing that almost always occur in later phases and other financing activities, namely bridge financing or special purpose financing, from the

"Later Stage" category, this combination appears to be the most reasonable classification scheme.

Given that the quality of the outcome might be more difficult to observe in earlier stages individual contributions cannot accurately be measured and defection by the entrepreneur might go undetected.

In contrast, in later stages more information can be gathered and the potential of the venture can be more easily judged upon. The dummy variables take on the value of one if the stage of development belongs to one of the above mentioned categories and zero otherwise. ⁴

Industry Experience: Concerning hypothesis 2 and the impact of investment experience on the intensity of monitoring we calculate the investment experience (in the given industry the funded firm is active in) of the involved VCs until the end of the year prior to the year when the capital infusion takes place (t-1 Analysis). When the investment is undertaken by a syndicate of VCs we calculated the total number of transactions within the given industry (in which the funded firms operates in) that the lead investors as well as the partners invested in (until the end of the year prior to the given year) and sum over all involved VCs. The use of aggregated experience differs for example from the approach taken in Hsu (2004) who only uses the experience of the lead investor when entrepreneurs are financed through a syndicate. We use the sum of industry experiences when the investment is made through a syndicate to better cope with a potential value added of combining investment experience. Industry experience of the VC(s) proxies for the ability to better screen and manage transactions.

First Round Syndication Dummy: We include a dummy variable equaling one when the investment in the first round was financed through a syndicate and zero otherwise, to test for Lerner´s (1994) selection hypothesis. Sourcing high quality deals might impact the need to subsequently implement protective governance mechanisms negatively.

4 This category does not include any Buy-Out transactions or recapitalizations that are named differently in TVE and are not included in this paper.

(23)

17

Current Round Syndication Dummy: Furthermore, we included a dummy variable indicating whether a syndicate of VCs provides financing in the current round. If the current round is financed through a syndicate the variable takes on the value one and zero otherwise. VCs investing in syndicates might benefit from processing information more efficient when making abandonment/continuation decisions.

Cumulated Previous Syndicated Rounds: Lastly, we also cumulate the number of previously syndicated financing events. The variable sums over all previous syndicated financing round. We thus proxy for more effective work and decision routines (as opposed to single investors) in all previous rounds that could help to reduce information asymmetries in the given round of financing. VCs investing in the given round could therefore capitalize on previous syndication efforts.

Industry Dummies: Additionally, we used information from TVE to identify the industry of a particular venture. The industry dummy variables take on the value one when the firm belongs to one of the industries and zero otherwise. We make use of the Venture Economics Industry Classification (VEIC) - a Venture Economics proprietary industry classification scheme. Moreover, we reviewed relevant information about the Company Business Description from the TVE database and from the Balance Sheet databases (Markus and Amadeus). We used the information from TVE to identify the industry of a particular venture and include industry dummies in each regression. In order to draw more distinct conclusions we further split the industries in the sample, which results in finer industry clusters. We divided the Medical/Health classification in two separate categories. Moreover, we split the Industrial Sector into Industrial Products (such as Chemicals and Industrial Equipment) and Industrial Services (such as Transportation, Logistics and Manufacturing Services). We created categories for Software and Internet Firms to cope with the particularities of investments into "New Economy" Firms over the period. Greater degrees of R&D intensity could, for example, represent higher levels of asset specificity given the higher levels human and dedicated transaction specific capital, exposing the partners to an aggravation of the chances for opportunism. Metrick (2006) and DiMasi et al. (2003) provide insights into the product development process in classical R&D investments. Given the multitude of clinical phases and research trials, medical firms might by nature be subject to staging. The successive provision of capital could be a natural consequence given the dynamics of the underlying research process. However, how the duration between incremental stages is affected does do not become clear from their results. Including these dummy variables should therefore control for possible effects of certain industries on the intensity of staging due to inherent industry characteristics.

(24)

18

1.4 Results

Table 1 summarizes the distribution of investments across industries and stages of development. It reveals that the total number of round financing peaked in the years 2000 and 2001 and sharply declined thereafter. The focus on high-technology industries is evident, despite changes in the overall investment activity level. The importance of the software and internet industries, however, changed over the years. After the bursting of the dot.com bubble VCs had to overcome a tremendous decrease in fund inflow. Especially Internet and Software investment were cut down after the year 2001. In contrast, the relative weight of investments in Biotech and Pharmaceutical firms increased.

Furthermore, table 1 also provides information about the distribution of yearly rounds across stages of development for the funded firms. There has been an increasing focus on late-stage financing over the recent years.

[Insert table 1 about here]

Table 2 and 3 provide the correlation matrix and descriptive statistics for the two different samples used to test the hypotheses. Given that the size of the sample varies during the course of the analysis we decided to show the statistics in two separate tables in order to allow for a more meaningful understanding of possible constraints. Table 1 reveals that the average duration of financing rounds is equal to 499 days with a standard deviation of 400. At the maximum number of days a firm had to wait around 6.5 years before the second round of financing took place. The lowest number of days in the dataset is equal to 42 days.

With respect to the firm age one can observe that the average firm is about 5.5 years old, with a maximum of 105 years (an established manufacturing firm changing product focus) and a minimum of zero (indicating that the firm has been founded with the capital infusion). In the second sample the age is around 4.5 years with a standard deviation of 9.5 Moreover, there are 20% of the total transactions in the start-up stage, and 29% of the transactions in the early stage. These percentages only vary slightly between the first and the second sample with 16% and 24%, however the percentage of late stage investments increases from 50% to 59%. With respect to the industry experience one can infer that VCs accumulated experience in around 12 (with a standard deviation of around 20) transactions.

First round syndication seems to be quite pronounced; around 50% of the transactions have a first round where two or more VCs inject capital. However, due to firms with multiple rounds this number is biased towards firms with an initial syndicated round and subsequent financing rounds, as the first round syndication dummy is accounted for in all subsequent financing events for the same company.

Moreover, the cumulated number of syndicated rounds indicates that the analyzed rounds have on

(25)

19

average 0.85 to 0.91 rounds that have been subject to syndication previously. In fact, this does not imply that almost 90% of all funded firms have been subject to syndication; overall only 60% of all funded firms are financed by multiple VCs. Again, given that firms are accounted for as often as they receive financing this numbers might be misleading at first glance. The industry dummies show a larger presence of Biotech and Software firms in the two samples. With respect to potential problems of multicollinearity the tables reveal that only the syndication dummies and the level of industry experience are significantly correlated. Consequently, we include these variables one at a time in the estimations.

[Insert table 2 and 3 about here]

Table 4 shows the results of the regressions for hypothesis 1 to 3. First of all, one can see that with respect to hypothesis 1, the age at investment is not significantly related to the duration of financing rounds. The coefficient associated with the age variable is not significant at conventional levels in all regression specifications used. However, the start-up dummy turns out negative and significant in two out of four regression specifications estimated, while the early stage dummy is not significant at conventional levels (shows, however the expected sign). There is evidence, that in the earliest stage the uncertainty surrounding the investment is higher for the corresponding VCs and consequently financing duration is shortened to evaluate the prospects of the company more closely. Hence, the more incremental mode of governance economizes on the costs of committing resources to a project of uncertain value and learning about growth opportunities. We also estimated the likelihood of stage financing (results are not shown here, but available upon request from the authors) for the funded firms in the sample using a logit regression and found the same effect. The start-up and early stage dummy are positive and significant, indicating higher chances of staging in earlier rounds. Moreover, when estimating the total number of financing events using Poisson regressions (results are not shown here, but available upon request from the authors) the dummy variable Biotech turns out to be highly significant; indicating a more intensive use of staging when investing in this industry suggesting evidence for differences in staging intensity due to the underlying chain of events in clinical trials, for example.

With respect to hypothesis 2, arguing that VCs can use their investment experience to create governance capabilities that affect the time in-between financing rounds negatively, table 4 reveals that the coefficient associated with the number of transactions the corresponding VC (and his partners in the case of a syndicate) financed has a positive and significant (at the 1% level) effect on the duration of financing rounds. Hence, there is evidence that investment experience germane to the

(26)

20

industry of investing can enable VCs to better anticipate future contractual hazards and allows them to implement less protective forms of governance.

Turning towards hypothesis 3 we find that neither the dummy indicating whether the first round of financing was subject to syndication nor the dummy equaling one when the current round of financing was subject to syndication is significant at conventional levels. This indicates no significant impact of syndication decisions on the implementation of governance choices. Given the high degree of syndication shown in the descriptive statistics it seems that not all these syndicates can actually benefit from a combination of investment experience. The results show, however, that the cumulative number of syndicated rounds is positive and significant at the 5% level indicating that the duration of financing rounds increases as a response to previous syndication efforts. The more often VCs made a joint decision over continuation/abandonment of a certain venture, the longer will they let an entrepreneur work with the money provided. However, a larger number of previous rounds also indicates a higher maturity of the funded firm and the results found for cumulative syndication behavior could therefore simply be an artifact of progressing funded firm development rather then of positive impacts of syndication efforts.

With respect to hypothesis 4 we include the same explanatory variables as in the estimation for hypothesis 1 to 3 to gain insights into the impact of syndication and experience measures on the average amount provided by VCs in each financing round. Concerning hypothesis 4 we find that none of the syndication variables is significant at conventional levels. Partnering decisions do not affect the average level of money provided for a specific start up. We do, however, find that the industry experience has a negative and significant impact on the average amount of money that VCs provide for the funded firms. In line with hypothesis 4 we find that with an increase in the industry experience, VCs tend to provide less money. Hence, the data reveals evidence that more experienced VCs, that potentially provide a better quality of managerial advice and allow for better returns (as documented in Kaplan and Schoar (2005)) are entering financing relationships on better terms.

Additionally, we also control for the effect of certain stages on the average amount provided. In earlier stages the uncertainty surrounding the investment seems to be higher (as the results from the previous

(27)

21

analysis suggest) and consequently we find that both, the start up dummy (at the 1% level) and the early stage dummy (also at the 1% level) is negative and significant, indicating that less money is provided. In later stages, when firms already made progress, VCs seem to provide more capital on average and (as the results presented earlier indicate) for a longer period of time. An alternative interpretation would be that earlier stages are inherently less capital intensive and VCs henceforth provide less money compared to later rounds. With respect to the industry control variables table 5 reveals that none of the industry dummies is significantly different from the omitted industrial products dummy. Only the Media & Communication dummy turns out to be positive and marginally significant in a single regression. Hence, we find no significant evidence, that some industries are inherently more capital intensive and more money is provided by VCs.

1.5 Discussion and Conclusion

In this paper we analyzed the impact of characteristics of the underlying transaction and the financing VCs on the implemented governance structure in VC financing. Given the highly explorative character in VC financing administrative control mechanisms can be paramount to cope with the inherent uncertainties in the VC - entrepreneur relationship. Our work is complimentary to previous studies on transaction cost economics and real option theory explaining the choice of governance modes in VC financing to mitigate conflicts of interest in the VC – entrepreneur relationship. We move beyond the analysis of pure transaction specific characteristics and incorporate characteristics of the financing VCs into our empirical analysis. We document an interactive contingency of governance choices based on the underlying transaction and VC-level resources and capabilities. Moreover, we link the presence of VC experience to the choice of governance modes and show how industry experience can help to alter the governance structure of financing arrangements.

Our results suggest that VCs can capitalize on staging the investment amount thereby creating a portfolio of growth options. By staging the investment amount into smaller increments that are paid over time VCs can create options to defer investments that can limit downside exposure when the funded venture turns out to be less profitable then expected or limit opportunistic behavior of the funded entrepreneurs. The results show that due to the higher uncertainty in earlier stages less money is provided in general and usually for a shorter period of time. Moreover, there is evidence, that financing durations between successive capital injections increase with more industry experience of the financing VC(s). As RBV logic would suggest, we find that VCs derive experience from previous investments (within a given industry) that helps them to develop strong governance capabilities, that can mitigate contractual and technological hazards and correspondingly, less protective forms of governance can be implemented. When more industry expertise is involved in the continuation/abandonment decision in a specific round the duration of financing rounds increases.

Empirical Evidence on Governance Mechanisms, Syndication Activities, and Partner Selection Strategies in Venture Capital Financing