The Impact of Complementarity on the Performance of Entrepreneurial Companies

Transcription

1 The Impact of Complementarity on the Performance of Entrepreneurial Companies Mukunthan Santhanakrishnan * Arizona State University Department of Finance P.O. Box Tempe AZ Phone: (480) Fax: (480) muku@asu.edu March 2002 Please do not quote or distribute Comments are most welcome * I am thankful to Jeff Coles, Dan Deli and Mike Hertzel for being generous with their time and offering valuable suggestions to improve this paper. I have also benefited from very useful comments from Brian Adams, Scott Bauguess, Naveen Daniel, Greg Durham Susan Ji, Swaminathan Kalpathy, Tod Perry, Mike Lemmon, Spencer Martin, Lalitha Naveen, Kumar Venkataraman and the seminar participants at Arizona State University. All errors are my own.

2 Abstract This paper examines the impact of product complementarity on the role of corporate venture capitalists (CVCs) and success of the entrepreneurial companies. First, like Gompers and Lerner (1998), I find that entrepreneurial companies that are complementary to CVCs are more likely to have successful exits. Second, consistent with Hellmann (2002), I find that CVCs are more likely to provide product market support to complementary companies. Third, I find that product market support provided by CVCs increases the likelihood of successful exits by entrepreneurial companies, and hence such support is valuable to entrepreneurs. Finally, I show that product market support is the mechanism through which CVCs influence complementary companies to have successful exits.

3 1. Introduction Corporations increased their participation in financing entrepreneurial companies significantly in the last decade. The amount invested by corporate venture capitalists (CVCs) increased from approximately $70 million in 1991 to about $11 billion in In addition to financial returns, the investments by corporate venture capitalists are likely to result in strategic impact on the corporation s core-business. In this paper, I study the influence of such strategic impact on the role of corporate venture capitalists in companies they invest. In particular, I examine whether product complementarity affects the support provided by the corporate investor and whether such support is valuable to the entrepreneur. Previous studies that delve into the role of corporate venture capitalists 1 include Gompers and Lerner (1998) and Hellmann (2002) 2. Gompers and Lerner (1998) document that companies backed by corporate venture capitalists are more likely to have successful exits than those backed by independent venture capitalists. They also find that companies that have strategic fit with their corporate investors are more likely to have successful exits. Hellmann (2002) contends that the positive relation between the likelihood of success of the entrepreneurial companies and complementarity 3 is due to corporate investors having higher incentive to provide support to complementary companies. My study provides empirical evidence, consistent with Hellmann 1 This is in addition to the growing literature that documents the active role of venture capitalists in private companies (e.g. Barry et al, 1990; Lerner, 1995). More recent studies provide evidence on both the involvement of VCs in activities such as building the management team, setting up internal policies etc. (Hellmann and Puri (2001)) and the monitoring role played by VCs (Baker and Gompers (1999, 2000)). 2 These studies have been motivated, in part, by the differences between VCs and CVCs in organization structure, the effect of complementarity on their core-business, the comparative advantage in providing different types of support etc. 3 Complementarity is measured as the change in value of the CVC firm due to the success of the private company beyond the financial returns obtained directly from the private company. For example, Intel Corp., a semiconductor chip manufacturer, frequently claims that the success of software companies would result in an increase in demand for its high performance Pentium processors. Thus, they claim, investments in these companies create value for Intel Corp., in addition to the financial returns from these companies.

4 (2002), which shows that the support provided by corporations to complementary companies drives the positive relation between complementarity and likelihood of successful exit. The analysis is based on a sample of 355 investments made by corporate venture capitalists during the sample period 1995 to 1997, collected from SDC s VentureXpert database. I supplement those data with hand-collected information on complementarity and product market alliances between the corporate venture capitalist and the private company. Like Gompers and Lerner (1998), I find that strategic fit/complementarity with one or more corporate venture capitalists increases the likelihood of a successful exit 4 by the entrepreneurial company backed by the corporate investors. Further, I find that the higher likelihood of successful exits by complementary companies is due, in part, to the support provided by corporate investors. Specifically, I find that, among sample companies receiving investments from corporate venture capitalists, complementary companies are more likely to obtain product market support. I also find that product market alliances with the corporations investing in the private company increase the likelihood of successful exit by the entrepreneurial companies. In addition, the product market support provided by corporate venture investors, and not the mere existence of complementarity, drives the higher probability of successful exits by complementary companies. Thus, this paper contributes to the literature by showing that the positive relation between complementarity and likelihood of successful exit documented by Gompers and Lerner (1998) is due, at least in part, to CVCs providing more product market support to complementary companies. The remainder of the paper is organized as follows. Section 2 discusses the role of corporate venture capitalists in private companies and develops several testable hypotheses. 4 I use going public, being acquired, and filing for registration with the SEC for going public as measures of successful exit. 2

5 Section 3 discusses the data collection and describes the sample. Section 4 presents the relation between complementarity and the private company s likelihood of success. Section 5 reports the influence of complementarity on the likelihood of product market alliances between private companies and CVCs. Section 6 shows the effect of product market alliances, controlling for complementarity, on the likelihood of successful exit. Finally, Section 7 concludes. 2. The role of corporate venture capitalists and hypothesis development In this section, I review the literature related to the role of corporate venture capitalists in entrepreneurial companies that receive venture investments. I also develop some testable hypotheses. 2.1 The role of corporate venture capitalists in private companies Much of what we know about corporate venture capitalists is described in Gompers and Lerner (1998), who survey the history of corporate venture programs and highlight the differences between VCs and CVCs. They show that: a) CVCs are structurally different from the VCs, being organized as subsidiaries or divisions of their parent company; b) Compared to VCs, CVCs make less use of incentive based compensation; c) Relative to VCs, CVCs invest in later stage companies; d) CVC backed companies are more likely to achieve a successful exit than companies backed solely by VCs. Gompers and Lerner (1998) also provide evidence of higher likelihood of a successful exit if there is a strategic fit between private companies and CVCs. This result is consistent with the existence of gains from complementarity between the CVC and the private company. Notwithstanding the higher success rate of CVC investments, the entrepreneur s decision to solicit capital from a CVC has both costs and benefits. The private company could benefit 3

6 from the involvement of the CVC in terms of technological expertise, sales and distribution network and certification of the product/technology. Christopher (2000) describes how the marketing and distribution strength of the corporate investors can accelerate the venture process. An example of a CVC providing support is Abbott Labs investing in SpectRx Inc. Abbott Labs provided a broad spectrum of support, including assistance in product development, manufacturing, regulatory clearance, and distribution of products. Portfolio companies can also gain from the technological strength of the CVC; for example, Bayer AG acquired an equity position in Symyx Technologies and initiated research collaboration to develop new products. The participation of a CVC as a large investor, however, could also impose costs on the private company. A corporate investor could influence the nature and direction of the private company to maximize the investor s benefits, resulting in sub-optimal outcomes for the private company. There are numerous examples of such detrimental involvement of CVCs in private companies. Kaplan (1995) describes an example of a conflict between GO, a pen computing start-up company, and IBM. For example, after initially promising distribution and marketing support, IBM attempted to sabotage GO by deciding to start a competing pen-computing project in-house. At the extreme, a CVC can kill an innovative idea that is likely to reduce the value of the CVC s parent company. The entrepreneur would therefore consider these costs and benefits of involving the CVC while making the choice of investor. Hellmann (2002) models the entrepreneur s choice between a venture capitalist, that attempts to maximize the direct financial returns from the private company, and a strategic investor that cares about the impact of the success of the private company on the value of their core business, in addition to the direct financial return from the private company. A basic assumption of the model is that the utility of the VC is a function of 4

7 only the value of the private company whereas the utility of the CVC is a function of the value of the private company and the strategic impact. The strategic impact is measured by the complementarity, given as the change in value of the CVCs assets due to the success of the private company. Complementarity ranges from highly positive (highly complementary companies) to highly negative (direct substitutes). If the CVC and the private company are unrelated, the complementarity is not different from zero. Investors provide costly noncontractible support, which influences the probability of success of the private company. The investor s utility is a function of the probability of success of the company, share of the company, the complementarity and its cost of support. The entrepreneur attempts to maximize his utility, which depends only on the value of the firm, through the choice of the investor and the share of the company allotted to the investor. This choice by the entrepreneur will be constrained by the minimum utility that will induce the investor to participate (participation constraint) and attempt to induce the investor to provide the optimal amount of support (optimality constraint). Based on this model, there are several predictions about the entrepreneur s choice of investor type and the resulting likelihood of success of the private company. Hellmann (2002) contends that, since the amount of support provided by the investor depends on the gains from the project, the CVC would have higher incentives to provide support to complementary companies due to the gains from the strategic interaction of the project. On the other hand, if the complementarity is negative and large the CVC may have incentive to participate in such projects and reduce the share of the company allotted to the VC. The reduction in the share of the company allotted to the VC dilutes the incentive of the VC to provide support to such companies. Hence, the model predicts that if the complementarity 5

8 between the CVC and the private company is either very high or very low, the CVC is likely to invest in the company. The model also predicts that the likelihood of success of the private company is a function of degree of complementarity. The complementarity between the private company and the CVC provides the CVC incentive to provide support to the private companies. Therefore, the likelihood of success of the private company increases with complementarity between the private companies and CVCs. Similarly, if the complementarity is low, the CVCs can obtain a share of the private company and dilute the incentives of the VCs to provide support to the private company. Hence, as the complementarity decreases the likelihood of successful exit also decreases. If the complementarity between the private company and the CVC is negative and small, the success of the private company is independent of the complementarity. 2.2 Hypotheses Based on the above discussion on the choice of investor and complementarity, I propose the following hypotheses to be tested using my data. Hypothesis I: Companies that are complementary to their corporate venture investors are more likely to have successful exits. A direct prediction of Hellmann (2002) is that the success of a company increases with the complementarity with its corporate investors. If we define successful companies as those that have successful exits, then I expect complementary companies to be more likely to have successful exits relative to companies that are unrelated or substitutes to the corporate venture investor. 6

9 Hypothesis II: Among companies that are complementary to their corporate venture investors, probability of a successful exit increases in the degree of complementarity. Hellmann (2002) predicts that as complementarity increases, the likelihood of success of the private company also increases. Hence, I expect strongly complementary companies to be more likely to have successful exits relative to weakly complementary companies. Hypothesis III: Companies that are complementary to their corporate venture investors are more likely to have product market alliances with the corporate venture investors. Hellmann (2002) contends that CVCs gain from the strategic impact of complementary companies and therefore have higher incentive to provide support for these companies. If product market alliances are one means by which private companies receive support from CVCs, then I expect complementary companies to be more likely to have product market alliances relative to companies that are unrelated or substitutes to the CVCs. Hypothesis IV: Among companies that are complementary to their corporate venture investors, probability of a product market alliance increases in the degree of complementarity. Based on the predictions of Hellmann s model, the gains from complementarity provide CVCs incentives to provide support to private companies. Since the gains to CVCs from strongly complementary companies are higher than from weakly complementary companies, CVCs are likely to have higher incentive to provide support to strongly complementary companies than to weakly complementary companies. Hence, I expect CVCs to be more likely to have product market alliances with strongly complementary private companies than with weakly complementary private companies. 7

10 Hypothesis V: Private companies that have product market agreements with CVCs are more likely to succeed. Hellmann (2002) contends that venture investors provide valuable support to private companies. Anecdotal evidence indicates that one of the ways in which CVCs add value to private companies is in the form of product market alliances. Hence, I expect companies that have a product market alliance with a CVC to have a higher probability of successful exit. 3. Data and sample description The primary source of data on venture investments used in this study is SDC s VentureXpert database. The sample consists of venture investments received by US private companies from US corporate investors between 1995 and The database identifies venture investments made by divisions, subsidiaries and venture capital funds directly affiliated to corporations from the database. I eliminate investments made by corporate venture firms (such as Softbank, Internet Capital Group, etc.) whose core asset is investments in other companies. The sample consists of 242 companies receiving venture investments from CVCs. Some companies in the sample receive financing from more than one CVC, resulting in 292 unique CVC-private company pairs. Due to non-availability of product market data for some companies, the complementarity measure (to be defined in the next section) is available for 278 unique CVC-private company pairs. However, Due to the participation of CVCs in more than one round of financing in the some companies, the final sample consists of 355 venture investments. 8

11 The database provides information on private companies receiving the investments, firms making the investments and details related to the investments. I track the companies receiving venture investments and obtain their status as of March Similar to Gompers and Lerner (1998), I use measures of successful exits based on the status of the companies as of March 2001 as proxies for the performance of the company receiving venture financing. I use two measures of successful exit: a) companies that have gone public through an IPO or have been acquired 5 ; b) companies that have gone public through an IPO or have been acquired or have filed a registration statement with the U.S. Securities Exchange Commission (a preliminary step before going public). 3.1 Complementarity The literature in strategic alliances and knowledge transfer between companies [see Mowery, Oxley and Silverman (1996) and Kale, Singh and Perlmutter (2000)] uses proxies for complementarity based on SIC codes. Specifically, these papers define two companies to be substitutes if they are in the same 4-digit SIC code. In contrast, two companies are said to be complements if they are in the same 2-digit SIC code but not in the same 4-digit SIC code. This definition of complementarity using SIC codes, however, may not be appropriate for my sample due to the concentration of companies within a few 4-digit SIC codes. Hence, I use the finer industry classification for technology companies provided by the Corporate Technology (CorpTech) Directory. The directory classifies companies into broad categories such as Software, Computer Hardware, Telecommunications and Internet etc. These broad industries are classified into subcategories such as software for healthcare, software for education etc., providing a second level 5 The valuations of sample companies that get acquired are higher than valuation of companies that merge with other companies. Moreover, valuations of acquired companies in the sample were significantly higher than the investments in the company and are hence considered a successful exit. 9

12 of differentiation between companies. These industries are further classified into finer categories such as software for patient care management, software for medical laboratory management etc. Appendix A1 provides a sample record for a holding company with subsidiaries and Appendix A2 provides a sample record for the subsidiary 6. I create a profile of private companies based on the company description provided by the SDC database and newspaper articles collected by searching the Dow Jones News Retrieval Service. Based on this profile, I assign industry codes for the sample companies using the industry classification provided by the Corporate Technology (CorpTech) directory (1997). I also collect industry codes for all products of the CVC s parent companies and its subsidiaries from the Corporate Technology directory. These industry codes of the products and services of the corporate investor enable me to assess the degree of complementarity between the private company and corporate venture investor. I define a private company and the corporate investor to be substitutes if the private company s product code and any of the product codes of the CVC match at all three levels of industry code. I define a private company and the corporate investor to be strong complements if their product codes match only at the first two levels. I define the private company and the CVC to be weak complements if their product codes match only at the first level. In order to define the complementarity between private companies and CVCs with products in different industries such as software and computer hardware companies, I obtain more information on them from news articles by searching the Dow Jones News Retrieval Service. If the products are sold together or if the technology of one company is integrated into the product of another company then I define them to be strong complements. If the two 6 For more detailed overview and validity of the CorpTech directory and their industry classification, see Lerner (2001). 10

13 companies have any customer/supplier relation or if their products are input/outputs to each other or if their performances are linked (for example, graphic software and microprocessors) then I define them to be weak complements. If a company has a technology or product that is an alternative for products of another company (such as research to produce new drugs), then I classify the two companies as substitutes. 3.2 Product market alliances I also obtain product market alliances between the private company and the CVC by searching all publications that are available in the Dow Jones News Retrieval Service. Since I study small private companies, I am concerned about the coverage of the sample companies in the Dow Jones News Retrieval Service. Hence, I obtain the strategic alliances and product market agreements using the Dow Jones News Retrieval Service for 100 randomly chosen venture backed private companies that go public through an IPO. I obtain strategic alliances for the same set of companies from the prospectus issued at the time of IPO and find no significant difference in the set of strategic alliances obtained using the two methods. I classify the product market alliances into five categories: distribution and marketing, product development and integration, research and technology development, customer support and others. Anecdotal evidence suggests that product market alliances are one of the primary means in which corporations provide support to companies they invest in. In addition, these are one of the most observable forms of interactions between the corporations and the private companies. Hence, I use the existence of product market alliances as a proxy for support provided by the CVC to private companies. 11

14 3.3 Sample Description Table 1 provides summary statistics for the sample. Panel A reports the status of the sample companies, investments and unique CVC-private company pairs. Of the total 242 companies, 91 (37.6%) go public through an IPO and 49 (20.3%) are acquired. Overall, 63.6% of the companies and 66.4% of the CVC investments have a successful exit. The proportion of investments resulting in successful exits in the sample is similar to that documented in Gompers and Lerner (1998), who report 64.3% of the investments result in successful exits during the sample period Panel B of Table 1 reports the distribution of unique CVC-private company pairs across levels of complementarity. The majority of the pairs are weakly complementary or strongly complementary with very few pairs being substitutes. Overall, 21% of the pairs are strongly complementary, 46% are weakly complementary and 27% are non-complementary companies. The cross-sectional differences in pairs in the sample across complementarity enable me to study the impact of complementarity on the likelihood of successful exit and on the support provided by a CVC to the private company. Panel C reports the distribution of product market alliances in the sample companies. Overall, 139 of the total of 292 (47%) pairs between CVC and private companies result in product market alliances. Table 2a reports the distribution of sample companies and investments across industries. The sample companies are concentrated in Medical (14.5%), Computer Software (29.3%) and Telecommunications and Internet (33.9%) industries. We also observe that 90.00% of the companies in the biotechnology industry have successful exits and 71.94% of the companies in the Telecom & Internet industry have successful exits. The proportion of companies having successful exit is lower among sample companies in the Computer Hardware and Computer 12

15 Software industries at 63.63% and 56.33% respectively. This is due to the higher proportion of companies that are alive in these industries; a possible explanation for this higher proportion could be that CVCs invest in earlier stages in these industries. I also examine (not reported here) the distribution of investments across industries and their status as of March 2001, and find similar results. Table 2b reports the distribution of complementarity between CVCs and private companies across industries. I find that CVC investments in a few industries are more likely to be complementary than investments in other industries. Telecommunications & Internet (68.42%), Computer Software (78.31%), and Computer Hardware (85.71%) have an above average proportion of complementary investments. Since industry effects could drive such complementarity, we need to control for these effects in the multivariate analysis. Table 2c reports the distribution of product market alliances across industries. Biotechnology (54.55%), Computer Software (53.01%), and Telecommunications & Internet (54.38%) companies have an above average proportion of product market alliances with CVCs. 4. Are complementary companies backed by CVCs more likely to succeed? In this section, I examine factors that influence the likelihood of successful exits by private companies. Specifically, I test the prediction of Hellmann (2002) on the positive relation between the degree of complementarity between the CVC and the private company and the success of the private company. As discussed earlier, I use measures of successful exit, based on the status of the company as of March 2001, as a proxy for the success of the firm. Panel A of Table 3 provides the distribution of status of companies across the levels of complementarity. These results indicate that complementary companies are more likely to have 13

16 successful exits such as going public, getting acquired and registering with the SEC for an IPO. Results in panel B, which compares the frequency of successful exits between complementary and non-complementary CVC-private company pairs, support the claim than complementary companies are more likely to have successful exit. Panel C reports the results of the Pearson s Chi-squared test of independence between complementarity and likelihood of successful exits. The statistical test rejects the null hypothesis of independence of complementarity and the likelihood of successful exit at the 5% significance level, with complementary companies being more likely to have successful exits. I proceed to test these univariate results in a multivariate framework. Sample statistics indicate that percentage number of companies that have successful exit is greater in some industries relative to others. In addition, we expect the likelihood of successful exit to increase with age of the company. An experiment must control for these effects in order to isolate the effects of complementarity on the likelihood of a successful exit. Table 4 reports the results of the logistic regression controlling for the industry and age of the company. In model A, the dependent variable takes the value 1 if the company has gone public through an IPO or has been acquired, 0 otherwise. The variable of interest, complementarity, is represented by a dummy variable which takes the value 1 if the private company and the CVC are complementary, 0 otherwise. Controlling for the age and the industry of the firm, the coefficient of complementarity is positive and significant at the 5% level (p = 0.025). This implies that complementary companies are more likely to succeed relative to other companies funded by CVCs. The marginal change in the implied probability of successful exit due to change in complementarity from 0 to 1 (with other variables at their means) is 13.4%, which implies that 14

17 complementary companies are 13.4% more likely to have a successful exit. This result is consistent with the prediction of hypothesis I. In model B, the dependent variable takes the value 1 if the company has gone public through an IPO, has been acquired, or has registered with the SEC before going public, 0 otherwise. The results are similar to those obtained in model A, with complementarity being positively related to the likelihood of successful exit. These results are consistent with hypothesis I and the prediction of Hellmann (2002). In order to test hypothesis II, on the effect of increase in complementarity on the likelihood of successful exits, I separate complementarity variable into weak and strong complementarity. The results of the logistic regression of successful exit with different level of complementarity and the control variables are reported in models C and D. In model C, the dependent variable takes the value 1 if the company has gone public through an IPO or has been acquired, 0 otherwise. Controlling for the age and industry of the firm, the coefficients of weak and strong complementarity are positive and significant at the 10% level, implying positive relation between complementarity and likelihood of successful exit, similar to the results in model A and B. In addition, the coefficient of strong complementarity is greater than the coefficient of weak complementarity. This implies that the strongly complementary private company is more likely to have a successful exit than a weakly complementary private company. The change in implied probabilities of successful exits due to weak complementarity and strong complementarity (at the mean values of the explanatory variables) is 12.54% and 13.59%. This implies that both strongly complementary and weakly complementary companies are more likely to have successful exits than companies with no complementarity. Moreover, strongly complementary companies are also more likely to succeed than weakly complementary 15

18 companies. This result is consistent with hypothesis II, that an increase in complementarity implies an increase in likelihood of successful exits. The estimated coefficients, however, are not significantly different from each other at conventional level of statistical significance. In model D, the dependent variable takes the value 1 if the company has gone public through an IPO or has been acquired or has registered with the SEC for going public, 0 otherwise. The results of the logistic regression are similar to those obtained in model B, with strongly complementary companies more likely to have a successful exit than weakly complementary companies. This result is consistent with hypothesis II that increase in complementarity leads to increase in likelihood of successful exit. Again, the probability of successful exits for strongly complementary companies and weakly complementary companies is not different at conventional statistically significance level. These results show that complementary companies backed by CVCs are more likely to have a successful exit. The next section examines whether the positive relation between complementarity and likelihood of successful exit is due, at least in part, higher incentives for CVCs to provide support to complementary companies. 5. Does complementarity affect the likelihood of product market alliances with the CVC? As discussed earlier, relative to the VCs, CVCs often are better able to provide support related to the product/technology of the company. Moreover, these relations are also one of the observable means by which we can examine the support provided by CVCs to private companies. Hence, I use the presence of a product market alliance between one or more CVCs and the private company as a proxy for the support provided by CVCs. In this section, I examine the factors that influence the likelihood of product market alliances between CVCs and private 16

19 companies. Specifically, I test whether CVCs are more likely to provide support by means of product related alliances to complementary companies than non-complementary companies. Panels A and B of Table 5 provide the distribution of product market alliances across levels of complementarity. The results indicate that complementary CVC-private company pairs are more likely to result in product market alliances with CVCs. Panel C provides the results of the Pearson chi-squared test for the independence between the degree of complementarity and the likelihood of product market alliance. The statistical test rejects the null hypothesis of independence between complementarity and the likelihood of product market alliance at the 1% significance level, with CVCs being more likely to have product market alliance with complementary private companies. Furthermore, univariate tests indicate that corporate investors are more likely to have product/technology development and marketing/distribution agreements with complementary companies. These results, however, could be due to other factors such as industry and age of the company. That is, while these univariate results are suggestive, they could be driven by other factors. Hence, I attempt to control for such factors in a multivariate framework. The sample statistics indicate that CVC-private company pairs in some industries are more likely to result in product market alliances. In addition, Gompers and Lerner (1998) report that CVCs invest in later stage companies. Hence, I expect older companies to be more likely to have product market alliances with CVCs. Therefore, I estimate a logistic regression with product market alliance as the dependent variable and complementarity as the main independent variable, controlling for age and industry of the company, and present the results in Table 6. The dummy variable, product market alliance, takes the value 1 if the private company and the CVC have any product 17

20 market alliance, 0 otherwise. Similarly, the dummy variable complementary takes the value 1 if the private company and the CVC are complements. Model A estimates the influence of complementary between the private company and the CVC on the likelihood of product market alliance between them. The coefficient for the complementarity dummy is positive and significant at the 1% level. The implied probability of the private company having a product market alliance with the CVC increases by 40% due changing complementarity from 0 to 1 (with other explanatory variables at their means). This result indicates that CVCs are 40% more likely to have product market alliances with complementary companies. This is consistent with the univariate results and hypothesis III, which implies that gains from complementarity provide CVCs additional incentive to provide support to complementary companies. In order to test hypothesis IV, on the effect of increase in complementarity on the likelihood of product market alliances, I break down the complementarity variable into two levels, weak complementarity and strong complementarity. Model B reports the results of the logistic regression of likelihood of successful exits on the levels of complementarity and the control variables. The coefficient of strong complementarity is greater than the coefficient of weak complementarity implying that strongly complementary companies are more likely to have product market alliance than weakly complementary companies. The implied probability of the private company having a product market alliance with the CVC increases by 38.3% and 46.72% respectively due to weak complementarity and strongly complementary (with other explanatory variables at their means). The increase in the likelihood of product market alliance from weakly complementary companies to strongly complementary companies, however, is not statistically significant. 18

21 The results discussed above, are consistent with the hypothesis that complementarity provides CVCs with incentives to provide support to companies in which they invest. Nevertheless, these results do not completely explain the relation between complementarity and the likelihood of successful exits. The entrepreneur would gain from the complementarity if the increase in the likelihood of a product market alliance led to improvement in the performance of the private company. So I examine the influence of product market alliances on the performance of the firm in the following section. 6. Are product market alliances with CVCs valuable to the entrepreneur? In this section, I examine whether the product market alliances are valuable to the entrepreneur. Specifically, I study the impact of product market alliances on the likelihood of successful exit by the private company. Panels A and B of Table 7 report the distribution of status of companies across those that have product market alliance with the CVCs and those that do not. These results indicate that companies with product market alliances with CVCs are more likely to have successful exits. Panel C of Table 7 provides the results of Pearson s Chi-squared test for independence between likelihood of successful ext and the existence of product market alliances. These results of the statistical test reject the null hypothesis of independence between successful exit and the presence of the product market alliance (p=.00). Companies that have product market alliances with the CVCs are more likely to have an IPO or get acquired. In Table 8, I examine the relation between the likelihood of successful exit and the existence of product market alliances with the CVC in a multivariate framework controlling for the industry and age of the company. 19

22 Model A estimates the relation between the presence of a product market alliance and the likelihood of a successful exit, using an IPO or an acquisition as the definition for successful exit by the company. The product market alliances dummy takes the value 1 if the company has any form of product market alliance with the CVC. The coefficient for the product market alliances dummy is positive and significant at the 1% level, which implies that private companies with product market alliances are more likely to have a successful exit. The implied probability of successful exit increases by 22.6% for the change in value of the product market alliance dummy from 0 to 1. This implies that entrepreneurial companies that have product market alliances with one or more of their corporate venture investors are 22.6% more likely to have a successful exit. I obtain even stronger results in models B, in which the dependent variable takes the value 1 if the company has gone public, has been acquired, or has filed registration statement with the SEC for an IPO, 0 otherwise. In model C and D, I examine the effect of product market alliance on likelihood of successful exits, controlling for the complementarity between the CVC and the private company. I find that the coefficient for product market alliance is positive and significant at the 2% level (p = 0.018), while the coefficient for complementarity is not significant. Similarly, results from models E and F, suggest that companies that convert complementary investments into product market alliances are more likely to have successful exits. These results are consistent with the inference that the likelihood of successful exit is driven by the product market alliances and not directly due to complementarity. Based on these results and those obtained in Section 5, it appears that complementarity influences the likelihood of product market support, which increases the likelihood of successful exit. Thus product market support is the channel through which complementarity influences the likelihood of successful exits of private companies. 20

23 Hence, this result provides an explanation for the positive relation between complementarity and likelihood of successful exit, documented by Gompers and Lerner (1998). Such positive relation between product market alliances and likelihood of successful exit is also consistent with the findings of other papers which document that strategic alliances create value in companies (Chan et al (1997)) and mitigate agency costs (Allen and Phillips (2000)). The results are also consistent with the hypothesis that entrepreneurial companies benefit from the certification effects of product market alliances with established companies (Stuart et al (1999) and Stuart (2000)). 6.1 Simultaneous equations Although results of product market alliances being positively related to the likelihood of successful exit in entrepreneurial companies is consistent with value added by corporate investors through these alliances, it is also consistent with the screening hypothesis. In particular, the CVCs might be more likely to have product market alliances with companies that are likely to succeed. In addition, the results obtained in the previous section suggest that the relation between complementarity and product market alliances is the direct effect that drives the positive relation between complementarity and successful exit by the private company. To account for these potential cross effects, I estimate systems of simultaneous equations using two-stage least squares. The first equation uses a dummy variable for the successful exit by the company as the dependent variable and the existence of product market alliances as the independent variable. In the second equation, the roles of these variables are reversed. Identifying independent variables include the complementarity dummy, industry dummies and age of the company. The results are presented in Table 9. 21

24 In model A, the successful exit variable takes the value 1 if the company has had an IPO or has been acquired, 0 otherwise. The results from the first equation show that the likelihood of successful exit is significantly influenced by the existence of product market alliances and not affected significantly by complementarity. The results concerning the likelihood of successful exit are consistent with those obtained in the previous section, based on single equations. Results from the second equation suggest that complementarity and the likelihood of successful exit significantly affect the existence of product market alliances. Thus, the screening effect does have an impact on a CVC having product market alliances, with companies that are more likely to have successful exits being more likely to have product market alliances. This effect, though, does not fully explain the positive relation between product market alliances and successful exits by the companies, as shown by results from the first equation. I obtain similar results in model B, in which the successful exit variable takes the value 1 if the company has had an IPO or has been acquired or has filed registration statement with the SEC, 0 otherwise. Therefore, we conclude that product market alliances are the means by which CVCs create value in complementary companies. 7. Conclusion While previous research has extensively documented the role of VCs, the role of CVCs in private companies is relatively unexplored. This issue gains importance as CVCs account for a significant amount of capital that has been invested in private firms in recent years. This paper attempts to fill this void by investigating the role of CVCs and the impact of complementarity and product market alliances on the success of private companies. This study is of particular 22

25 interest to economists, investors, VCs, and entrepreneurs who are considering the choice of various sources of venture capital. Based on a sample of 355 investments made by CVCs between 1995 and 1997, my main conclusions are as follows. First, complementary companies are more likely to have successful exits than non-complementary companies. This result is consistent with the theoretical prediction of Hellmann (2002) and empirical results of Gompers and Lerner (1998). Second, complementarity provides CVCs with incentive to provide more support to the private company in the form of product market alliances. Third, product market alliances increase the likelihood of private companies having successful exits and hence are valuable to the entrepreneurs. Finally, product market support is the channel through which complementarity influences the likelihood of successful exit. These results raise several interesting questions. First, what is the effect of the organizational design of the corporate venture investor? This paper does not consider the various organizational forms of corporate venture investors such as internal ventures (which are divisions of the parent company) and external ventures (which are structured to function independent of the parent company). It will be interesting to examine the effect of these structural forms of corporate venture programs on the complementarity of investments made by the corporate venture program. Second, is there an association between the organizational structure of the corporate venture investor and the type of support provided by them in entrepreneurial companies? Third, what is the longer-term impact of the support provided by CVCs in private companies? While I have examined short-term performance of the private firms using some proxies, the benefits of such alliances in the operational performance of the firm can be examined over a longer period in companies that go public through an IPO. 23

26 In addition, current literature proposes a few competing rationales for syndication among venture capital investors. The difference in the institutional features between CVCs and VCs will enable us to examine these rationales for syndication of venture capital investments. I intend to explore these issues in future research. 24

27 References Allen J.W and Phillips G.M, Corporate equity ownership, Strategic Alliances and Product Market relationships. Journal of Finance 54, Barry, C., Muscarella, C., Peavy III and Vetsuypens, M., The Role of venture capitalists in the creation of public companies: Evidence from the going public process. Journal of Financial Economics 27, Baker, M., and Gompers, P., Executive ownership and control in newly public firms: The role of venture capitalists. Unpublished working paper, Harvard University. Baker, M., and Gompers, P., The Determinants of board structure and function at the initial public offering. Unpublished working paper, Harvard University. Christopher, A., 2000, Corporate venture capital: moving to the head of the class, Venture Capital Journal November 1. Chan, S.H., Kensinger, J.W., Keown A.J., and Martin, J.D., Do strategic alliances create value? Journal of Financial Economics 46, Gompers, P., and Lerner, J., The determinants of corporate venture capital success: organizational structure, incentives and complementarities. Unpublished working paper, NBER. Gompers, P., and Lerner, J., An analysis of compensation in the U.S. venture capital partnership. Journal of Financial Economics 51, Hellmann, T., Theory of strategic venture investing. Forthcoming in Journal of Financial Economics. Hellmann, T., and Puri, M., The Interaction between product market and financing strategy: The role of venture capital. Review of Financial Studies 13, Hellmann, T., and Puri, M., Venture capital and the professionalization of start-up firms: empirical evidence. Forthcoming in Journal of Finance. Kale, P., Singh, H. and Permlutter, H., Learning and protection of proprietary assets in strategic alliances: Building relational capital. Strategic Management Journal 21, Kaplan, J., 1995, Startup: A silicon valley adventure, Houghton Mifflin Company. Lerner, J., Venture capitalist and the oversight of private firms. Journal of Finance 50, Lerner, J., Did Microsoft deter software innovation? Unpublished working paper, Harvard University. 25

28 Maula and Murray, Corporate venture capital and creation of US public companies: The impact of sources of venture capital on the performance of portfolio companies, strategy in the entrepreneurial millennium. John Wiley & Sons. Mowery D.C, J.E. Oxley and B.S. Silverman, Strategic alliances and interfirm knowledge transfer. Strategic Management Journal 17, Sahlman, W., The structure of governance of venture capital organizations. Journal of Financial Economics 27, Stuart T.E., Interorganizational alliances and the performance of firms: A study of growth and innovation rates in high-technology industry. Strategic Management Journal. Stuart, T.E., H. Hoang and R.C. Hybel, Interorganizational endorsements and the performance of entrepreneurial ventures. Administrative Science Quarterly 44,

29 Table 1: Sample Description This table provides description of the sample of 355 investments in 242 companies with 292 unique CVC-private firm pairs collected from SDC s VentureXpert database during the sample period Panel A reports the status of companies, CVC -private company pairs and investments in the sample. Panel B reports the distribution of unique CVC-private company pairs across degrees of complementarity. The complementarity measure is assigned based on the industries of the companies and the CVC firm, using the industry classification provided in the Corporate Technology (CorpTech) Directory. The CVC and the private company are defined as substitutes if their industry codes match at all the three levels. If the industry codes match only at the first two levels, then they are defined to be strong complements. If the industry codes match only at the first level then they are defined as weak complements. If the industry codes do not match even at the first levels, complementarity is assigned based on the profiles of the company. If a company is not assigned to any of these categories, I define complementarity as none. If a profile for the company cannot be obtained, I code complementarity as not available. Panel C describes the types of product market alliances between the CVC firm and private company. The product market alliances between the private company and the CVC are obtained by searching the Dow Jones News Retrieval Services. Panel A: Companies, associations, and investments in the sample Current Status Companies % CVC-Private Company pair % Investments % Went Public Through IPO Acquired In Registration Merged Alive Company Bankrupt Other Total Panel B: Degree of Complementarity Complementarity Type CVC-Private Company pair % Substitute None Weak Complements Strong Complements Not Available Total Panel C: Description of Product Market Alliances Product Market Alliance Type Number of Alliances % Product development & Integration Technology Development Distribution & Marketing Customer/Supplier Others None Total