TECHNOLOGICAL DIVERSIFICATION, CUMULATIVENESS AND VENTURE CAPITAL EXIT: M&A VERSUS IPO

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1 Frontiers of Entrepreneurship Research Volume 27 Issue 1 CHAPTER I. ENTREPRENEURSHIP FINANCING Article TECHNOLOGICAL DIVERSIFICATION, CUMULATIVENESS AND VENTURE CAPITAL EXIT: M&A VERSUS IPO Marianna Makri University of Miami, USA Marc Junkunc University of Miami, USA, mjunkunc@miami.edu Jonathan T. Eckhardt University of Wisconsin, USA Recommended Citation Makri, Marianna; Junkunc, Marc; and Eckhardt, Jonathan T. (2007) "TECHNOLOGICAL DIVERSIFICATION, CUMULATIVENESS AND VENTURE CAPITAL EXIT: M&A VERSUS IPO," Frontiers of Entrepreneurship Research: Vol. 27: Iss. 1, Article 1. Available at: This Paper is brought to you for free and open access by the Entrepreneurship at Babson at Digital Knowledge at Babson. It has been accepted for inclusion in Frontiers of Entrepreneurship Research by an authorized administrator of Digital Knowledge at Babson. For more information, please contact digitalknowledge@babson.edu.

2 Makri et al.: TECHNOLOGICAL DIVERSIFICATION, CUMULATIVENESS AND VENTURE CAPITAL TECHNOLOGICAL DIVERSIFICATION, CUMULATIVENESS AND VENTURE CAPITAL EXIT: M&A VERSUS IPO Marianna Makri, University of Miami, USA Marc Junkunc, University of Miami, USA Jonathan T. Eckhardt, University of Wisconsin, USA ABSTRACT Venture capitalists that specialize in providing funds to privately held firms generate their greatest returns from firms that go public. However, we argue that the technology regime of an industry affects the extent of knowledge asymmetries between different types of owners and subsequently the mode of exit for venture capitalists. More specifically, we suggest that the degree of technological diversification and technological cumulativeness of an industry will have a positive effect on the likelihood that a venture capital firm will exit its investment in a technology firm via a merger or an acquisition as opposed to taking it public. INTRODUCTION Venture capitalists that specialize in providing funds to privately held firms generate their greatest returns from firms that go public. A Venture Economics (1988) study finds that a $1 investment in a firm that goes public provides an average cash return of $1.95 beyond the initial investment with an average holding period of 4.2 years. The next best alternative, an investment in an acquired firm yields a cash return of only 40 cents over a 3.7 year mean holding period (Gompers & Lerner, 1999: 23). While research suggests that an IPO is by far the most profitable exit strategy for venture capitalists, we find that in some industries, venture capitalists chose an M&A over an IPO. We seek to explain this phenomenon by examining how the technology regime of the industry a venture-backed technology firm operates in affects this decision. Investors face many hazards when investing in new companies but uncertainty is compounded when firms operate in technology-intensive industries (Carpenter, Pollock & Leary, 2003; Stuart, Hoang & Hybels, 1999). In such industries, investors and analysts lack technological knowledge while the current owners of the firm have access to extensive information regarding not only the internal operations of the firm but also its innovation potential. In firms characterized by technological knowledge, even if investors have complete access to information regarding the firm they may still be unable to interpret such information. Put differently, even if owners are compelled to provide accurate and complete information on the firm s activities, investors may not have the capability to interpret such information if it requires an understanding of the firms technological capabilities (Sanders & Boivie, 2004; Cohen & Dean, 2005). In this study we argue that the technology regime of an industry affects the extent of knowledge asymmetries between owners and venture capitalists and subsequently the mode of exit for the latter. More specifically, we suggest that the degree of technological diversification and technological cumulativeness of an industry (Malerba & Orsenigo, 2000) will have a positive effect on the likelihood that a venture capital firm will exit its investment in a young technology firm via a merger or an acquisition (M&A) as opposed to going public through an IPO. Further, we argue that firm age, firm sales, the size of the VC fund as well as the amount already invested in the young firm will affect the exit decision. Frontiers of Entrepreneurship Research

3 Frontiers of Entrepreneurship Research, Vol. 27 [2007], Iss. 1, Art. 1 THEORETICAL BACKGROUND AND HYPOTHESES The Role of Venture Capitalists and Initial Public Offerings In the most recent two decades management and finance scholars have come to great understanding about the role of venture capitalists in the creation of new firms (Barry, et al., 1990), the structure and governance of venture capital organizations (Sahlman, 1990), and essentially the overall venture capital cycle as a phenomenon, from start to finish (Gompers and Lerner, 1999). In the cumulative knowledge about venture capital, scholars have established how venture capitalists and their organizations actively participate in the oversight of private firms through board of director positions (Lerner, 1995), the staging of the infusion of venture capital in investment rounds (Gompers, 1995), the establishment of certain control rights (Kaplan and Stromberg, 2002), and frequent VC-CEO interaction (Sapienza and Gupta, 1994). All of these mechanisms developed as a result of potential agency problems, such as moral hazard and adverse selection, due to asymmetric information in the marketplace surrounding the types of firms seeking venture capital, often being early stage, innovation-based or technology-driven companies. An initial public offering, or IPO, is a corporate action whereby a firm sells, for the first time, its common stock to the public in order to raise capital and to create liquidity for its current shareholders (Ritter and Welch, 2002), including venture capitalists, who supported the company throughout its development. Venture capitalists are often substantial investors taking on concentrated equity positions, who actively influence the IPO process by preparing firms to optimize their use of public investment capital as well as help them time their entry to the market (Gompers and Lerner, 1999). Market conditions are crucial in determining whether the firm should undertake an IPO or alternatively, seek a merger or an acquisition by an established firm. In the case of biotechnology, Lerner (1994) found that in a sample of 350 private venture-backed biotechnology firms, seasoned venture capitalists appear particularly adept at taking companies public near market peaks. He found that between 1978 and 1992 venture capitalists took their biotech companies to the public markets (IPO) when values were high and employed further private equity financings rather, when values were lower (Lerner, 1994). Thus, from prior literature it is clear that not only do venture capitalists play an active role in the initiation and development of young firms, but also in the exit strategies for investors and themselves from these firms. An alternative exit strategy for venture capitalists is to seek a merger or acquisition by an established firm. In high velocity industries, young technology-based firms can be attractive acquisition targets because they can be an important source of technological inputs for established firms (Leonard-Barton, 1985; McEvily, Eisenhardt and Prescott, 2004; Kale and Puranam, 2004). Acquiring such firms allows established technology intensive firms to avoid the time consuming, path dependent and uncertain processes of internally accumulating technological resources and can provide acquirers opportunities for developing more radical innovations (Dierickx and Cool, 1989; Steensma and Fairbank, 1999). Put differently, in high technology industries, M&As can be a lucrative alternative to an IPO for young technology firms because these firms can provide complementary technologies to established firms in the industry thus demanding substantial acquisition premiums. Technology Diversification, Cumulativeness and the M&A Decision Potentially important in determining an appropriate course of action by venture capitalists, as this paper explores, are the conditions of the industry in which the venture capitalist s portfolio firm competes. Prior literature has established that inter-industry differences in the sources of technological opportunities contribute to explanations of cross-industry variation in R&D intensity and technological advance (Klevorick, et al., 1995), and suggested that technology regimes influence the appropriateness of new firm formation as a mode of exploitation both theoretically (Winter, 1984) and empirically (Shane, 2001). Further, industries vary in their technological opportunity conditions as well as the degree of cumulativeness of technological knowledge (Malerba & Orsenigo, 1997). Technological opportunity Posted at Digital Knowledge at Babson 2

4 Makri et al.: TECHNOLOGICAL DIVERSIFICATION, CUMULATIVENESS AND VENTURE CAPITAL conditions reflect the ease of innovating for a given amount of resources invested in innovation search and such conditions are more pervasive in industries where new knowledge can be applied to several products and markets as well as in industries with a potentially rich variety of technological solutions. Put differently, the degree of technological diversification in an industry would be associated with greater technological opportunities for incumbent firms. Cumulativeness conditions reflect an industry s tendency to generate new technological knowledge by incrementally building upon what has been previously done. The differences among industries in terms of the conditions discussed above have been associated with differences in terms of industry concentration. Malerba and Orsenigo (1997) argue that industries characterized by high levels of technological opportunities would show a tendency towards greater industry concentration. High technological opportunities would allow for the continuous entry of new innovators but established firms would most likely gain a substantial leap in their relative innovativeness thus leading to the elimination from the market of less successful competitors. In conditions of high levels of technological cumulativeness, established technological leaders have an advantage because they have already accumulated technological knowledge and capabilities. Thus, under such conditions new entrants will be limited. We argue that these differences among industries affect whether venture capitalists exit their technology-intensive venture-backed firms by taking them public (IPO) or by selling them to another firm (M&A). More specifically, we suggest that the degree of technological diversification and technological cumulativeness in an industry affects this decision. Because under conditions of high technological diversification and high technological cumulativeness an industry would tend to be more concentrated, M&As would be a more likely mode of exit than IPOs. Put differently, technological diversification and cumulativeness would be associated with greater industry consolidation which would imply a greater number of M&As in that industry. Formally stated: Hypothesis 1: The probability that a venture capital firm will exit via M&A will be positively associated with the degree of technological diversification of its industry. Hypothesis 2: The probability that a venture capital firm will exit via M&A will be positively associated with the degree of technological cumulativeness of its industry. Venture Backed Firm Age and the M&A Decision Past research has shown that firms are persistently competent in specializing in certain technological areas. Due to limited resources and bounded rationality firms tend to be selective in pursuing certain technology trajectories over others (Nerkar & Paruchuri, 2005). To meet the challenge of keeping up with the rapid pace of innovation and the increasing scope of knowledge needed to remain competitive, companies turn to external sources of knowledge (Rosenkopf & Nerkar, 2001). Drawing upon another firm s knowledge, resources and capabilities can lead to innovations that would not be feasible by working independently. Thus, founders of young technology firms while primarily searching to recombine new knowledge within their firms boundaries, at some point in the young firm s development, can increase their likelihood of survival and enrich their existing technology platforms by searching for knowledge created outside organizational boundaries. That said, it is reasonable to suggest that as the young technology firm matures, the likelihood it would grow via M&A increases because there is a greater probability that the firms existing technology platforms have reached a plateau and that the firm needs to break out of existing path dependencies in order to remain competitive. That probability however would diminish after a certain period of time because as the venture backed firm ages, it would be more difficult to find an acquirer. Waiting too long to exit may signal to the market that if the firm has not gone public it is because it does not have what it takes to be competitive. At that stage, it could become difficult to find an interested buyer or a buyer willing to pay a high acquisition premium. In turn, we Frontiers of Entrepreneurship Research

5 Frontiers of Entrepreneurship Research, Vol. 27 [2007], Iss. 1, Art. 1 would expect that venture capitalists may chose to wait until the IPO market turns hot again. Formally stated: Hypothesis 3: There is a curvilinear relationship between the probability that a venture capital firm will exit via M&A and firm age. Signaling and the M&A Decision Investing in young technology firms is inherently risky because of the nature of competition in the industries they operate in and because R&D is by nature an uncertain process with unforeseen twists and turns. Added to these hazards is the fact that such firms usually have short track records, and are years away from generating significant sales from their internal R&D. That said, the decision by investors or established firms to invest capital in a young technology firm is one laden with uncertainty, requiring they draw inferences about the firm s future performance (Nerkar & Paruchuri, 2005). One factor on which investors base their funding decisions involves signals of quality of the young firm. However, because the quality of these firms technology portfolios is for the most part unobservable, investors rely on observable attributes thought to reflect the innovation potential of these firms (Stuart et al., 1999). Some of these attributes are the credibility and experience of the VC firms funding these young technology companies and also the total amount already invested in the young firm. Put differently, the characteristics of the VC firm serve as indicators of quality of the knowledge and technology generated by these young technology firms. The amount already invested in the young firm can serve as a signal to investors that there are already a number of investors who have shown confidence in the firm s innovation potential. Put differently, all else equal, we expect that the amount invested would be associated with a greater probability of an IPO versus an M&A because the confidence of the market in the firm would be high if the firm has already received capital greater than the average for other firms in that industry. Further, a young technology firm that already has established a track record of sales is more likely to engender investor s confidence, all else equal. Formally stated: Hypothesis 4a: The probability that a venture capital firm will exit via M&A will be negatively associated with total amount invested. Hypothesis 4b: The probability that a venture capital firm will exit via M&A will be negatively associated with prior sales. Finally, a large VC firm is more likely to have a larger network and history of deals. Importantly, scholars have found evidence that network ties are important for launching new high-technology ventures (Shane & Cable, 2002), that interorganizational networks affect entrepreneurial ventures ability to acquire the resources necessary for growth in the case of biotechnology (Stuart, et al., 1999), and further that the venture capital process itself depends on strong and embedded relations among the relevant actors resulting in industrial and geographic spatial patterns of investment shaped through co-investment and syndication networks (Sorenson and Stuart, 2001). Thus, do to the inherent social and network ties, the larger the VC fund, the more likely it is that the firm will be able to locate an appropriate merger candidate or acquirer in the world of specialized knowledge where network ties are so important. Stated formally: Hypothesis 4c: The probability that a venture capital firm will exit via M&A will be positively associated with the size of the VC firm. Posted at Digital Knowledge at Babson 4

6 Makri et al.: TECHNOLOGICAL DIVERSIFICATION, CUMULATIVENESS AND VENTURE CAPITAL DATA COLLECTION, METHODS AND MEASUREMENT We used Thomson Financial s SDC Platinum VentureXpert database to screen for all venture capital transactions. SDC Platinum is a financial transactions database which covers capital market, M&A, and private equity activity in the US and internationally, and includes substantial numbers of venture capital transactions as far back as the 1960 s (data was originally part of Venture Economics). The database has been used for years as a primary research tool among academics studying venture capital transactions. We then reduced our sample to those firms which had their last venture capital transaction between the years of 1990 and 1999, in order to correspond to our patent database variable constructs, as described below. The sample was then reduced further to high technology companies only, excluding transactions in non-high tech sectors as classified by SDC (e.g. Industrial/Engergy, Financial Services, Consumer Related, Business Services, etc.). From the 4,450 firms remaining we then selected only those firms which had an exit via IPO, merger or acquisition, excluding all those that were still active venture capital investments or had gone bankrupt, and were left with a sample of 1,675 unique firms. Although firms often have more than one venture capital transaction, for our analysis we constructed a firm level database so that each observation is a particular portfolio company which received venture capital investment. Descriptive statistics for these firms, and regarding their transactions, are shown in Table 1 reported by industry groups. While SDC classifies companies into five primary high-technology industries, we aggregated such information into three industries: Computers and, Drugs and Medical, and Semiconductors. Such aggregation was necessary because we wanted to combine SDC data with patent related information from the National Bureau of Economic Research (NBER) Patent Citations Data File constructed by Hall, Jaffe & Trajtenberg (2001). The U.S. Patent and Trademark Office (USPTO) categorizes technologies into 417 main (3-digit) patent classes (Hall et al., 2001). Hall et al., (2001) aggregated these 417 classes into 36 two-digit technological subcategories, which in turn are further aggregated into 6 main categories. We were able to combine SDC data with NBER data by industries because both databases contain firm/security CUSIP number identifiers. These two databases however, do not use the same classification of high-technology industries at the subcategory level. This required that we use the broader level of aggregation available to enable an accurate matching of industries. As a result, our data was classified into the three main industries described above. As can be seen in Table 1, 1077 of the 1675 transactions are in Computers &, 442 are in Drugs & Medical and 156 are in Semiconductors. Interestingly, venture-backed firms in the Semiconductors industry tend to exit via IPO more so than firms in the other two industry groups. Also, it takes them longer to exit and consequently by the time of exit they are more mature than firms in the other industries. It is also important to note that all three industries are highly diversified in terms of technology. In terms of technology cumulativeness however, Computers & appear to be more patent intensive. Independent Variables Technological Diversification: The measure of technological diversification has been constructed based on a Herfindahl index of concentration (Hall et al., 2001; Garcia-Vega, 2006) using NBER patent data. With 36 technological subcategories indexed by j=1,.., 36, if the ith firm has Ni patents in a given year, each patent can be assigned to a technological subcategory. Let Nij denote the number of patents that the ith firm holds in subcategory j. A Herfindahl index of concentration can then be obtained for each firm and year. Subtracting this value from 1 gives us the technological diversification. Thus, if a firm s patents belong to a wide range of technology classes that measure will be closer to one whereas if most patents are concentrated in a few classes it will be close to zero. Frontiers of Entrepreneurship Research

7 Frontiers of Entrepreneurship Research, Vol. 27 [2007], Iss. 1, Art. 1 While our technological diversification measure was constructed using Hall et al. s (2001) 36 technological subcategories, we had to aggregate such information based on the three industries described earlier for to create an industry measure of technological diversification for each firm representing the industry within which it operates. Technological Cumulativeness: As discussed earlier, technological cumulativeness reflects an industry s tendency to generate new technological knowledge by incrementally building upon what has been previously done. At the firm level, such measure can be constructed as the number of patents in a firm s portfolio. Patent counts, is a direct measure of innovation quantity (e.g. Griliches, 1995, 1998) and has been used extensively to indicate innovation productivity (Hitt, Hoskisson, Ireland & Harrison, 1991; Mowery et al., 1998; Sorensen & Stuart, 2001; DeCarolis & Deeds, 1999; Hall et al., 2001). Using the NBER database, we aggregated the total number of patents in each of the three industries during to create an industry measure of technological cumulativeness for each firm representing the industry within which it operates. Age, Size, Sales and Prior Investment: We considered several variables to examine additional factors influencing the probability that a venture capital firm would exit via M&A versus IPO. For instance, we consider the age of the venture backed firm at the time of the transaction (in years) as well as the time it took for the young firm to reach the transaction stage. Additionally, we account for the total amount invested in each venture backed firm, the size of the VC fund that invested in the firm, the number of VC firms that invested in the young technology firm, as well as the total number of rounds via which the VC backed firm received capital. Finally, we take into account net sales for the most recent year available. Statistical Analysis We employ a logit random effects model for examining the effect of technological diversification and technological cumulativeness on the likelihood that venture capitalists would exit their firms via M&A. The dependent variable is Situation Type = 0 for M&A and 1 for IPO. In all models we include the industry dummy variables as discussed earlier (semiconductor is the excluded industry dummy). The following expression summarizes the logit models in Table 3 where i represents the i th corporate action and t represents the year in which the i th corporate action took place. The model is estimated including a random effects panel specification over a 10 year period ( ). A logit random effects design is appropriate because we have a number of observations over a 10 year period which belong to different groups (industries): Pr (M&A = 0) i,t = a 1 Industry it + a 2 Age at Event it + a 3 Time to Event it + a 4 Age at Event it Squared + a 5 Time to Event it Squared + a 6 Amount Invested it + a 7 No Of Firms Investing in the Company it + a 8 Fund Size it + a 9 No Rounds Received it + a 10 Sales it + a 11 Technology Diversification it + a 12 Technology Cumulativeness it + constant term DATA ANALYSIS AND RESULTS Table 2 presents descriptive statistics and correlations for the variables included in the analyses. On average, across all three industries, it takes approximately 6 years for a venture-backed firm to reach a point where it goes public or is acquired by another firm. Further, on average these firms receive approximately five rounds of funding from six investment firms. Table 3 presents the results of the logit specification, testing the effects of technology diversification and cumulativeness on the probability that a venture capital firm would exit its investment via M&A. The results suggest that technological diversification and technological cumulativeness are negatively and significantly associated with the likelihood that the VC firm will exit via IPO (p<0.001 respectively) thus Posted at Digital Knowledge at Babson 6

8 Makri et al.: TECHNOLOGICAL DIVERSIFICATION, CUMULATIVENESS AND VENTURE CAPITAL positively associated with the probability that the VC firm will exit via M&A. This provides strong support for Hypotheses 1 and 2. Table 4 presents the results for examining the effects of firm age (Hypothesis 3), total prior investment (Hypothesis 4a), firm sales (Hypothesis 4b), and VC fund size (Hypothesis 4c) on the likelihood that a venture capital firm would exit its investment via M&A. As expected, there is a curvilinear relationship between Age at Event and the likelihood that a firm will be acquired. More specifically, the squared term for Age at Event is negative and significant (p<0.01) thus providing support for Hypothesis 3. Amount invested as well as sales generated by the firm are positively and significantly associated with the probability that the VC firm will exit via IPO (p<0.001). This suggests that prior capital invested in the firm, and prior sales generated by the firm, reduce uncertainty for public investors and increase the likelihood to go IPO. Consequently, the probability of an M&A decreases, providing support for Hypotheses 4a and 4b. Finally, the size of the VC fund invested in the firm is negatively and significantly (p<0.01) associated with the likelihood of an IPO, hence positively associated with the likelihood of an M&A. This finding suggests that Hypothesis 4c is supported. DISCUSSION AND CONCLUDING REMARKS In this study we seek to shed light on a phenomenon suggesting that while an IPO is the most profitable exit strategy for venture capitalists, in some industries, an M&A is the preferred mode of exit. We pose that the technology regime of the industry a venture-backed technology firm operates in affects this decision. More specifically, we suggest that the probability that a VC firm will exit via M&A and consequently that the venture-backed firm will grow via M&A, will be positively associated with the degree of technological diversification and technological cumulativeness of its industry. Further, we argue that as the young technology firm matures, the likelihood it would grow via M&A increases and that likelihood is positively associated with the size of the VC firm. Finally, we suggest that the probability that a venture-backed firm will grow via M&A will be negatively associated with total amount invested in the firm as well as with prior sales. We tested our hypotheses using a sample of 1675 venture capital transactions from in the computers, drugs, and semiconductors industries. The statistical results support our main thesis namely that the degree of technological diversification and technological cumulativeness of an industry (Malerba & Orsenigo, 2000) will have a positive effect on the likelihood that a venture capital firm investing in a young technology firm will exit via a merger or an acquisition (M&A) as opposed to going public through an IPO. Further, we found support for the argument that firm age, the size of the VC firm as well as the amount already invested in the young firm affect the exit decision. Study Limitations This study has certain limitations leaving room for further research on the topic. First, the firms in our venture capital dataset do not contain standard SIC classifications and hence we are left with the broadest of industry classifications in order to match with our patent dataset in applying our measures of technological diversification and technological cumulativeness. Although our results are statistically significant and robust to our tests, much finer industry distinctions could be made in future research which may shed further light on the phenomenon and result in clearer managerial implications. Secondly, prior literature has shown that IPO decisions are linked closely to financial market conditions, for example in the case of biotechnology firms (Lerner, 1994). Although we find significance in our hypothesized correlations, there may be alternative market explanations as to why firms favor M&A versus IPO for which we have not controlled. To the extent such market conditions are correlated with our hypothesized explanations this could be confounding our results. To partially mitigate this factor we have used a random effects model taking into consideration the year of each firm s exit transaction. Frontiers of Entrepreneurship Research

9 Frontiers of Entrepreneurship Research, Vol. 27 [2007], Iss. 1, Art. 1 Finally, our theoretical arguments rely on the notion that firms are specialized and thus contain specialized knowledge resources, and that these knowledge resources operate within certain industry technological regimes. However, presently we do not have any firm level measures of specialized knowledge, or industry measures, but rely instead on the industry measures that are available with regards to technological diversification and cumulativeness. In a sense we are only looking at one side of the coin, the industry technological regime, but do not have information on the degree or nature of the specialization at the firm level, or even industry proxies of this for the firms operating within the industry regimes. Perhaps future researchers can find new ways of getting to these more refined elements of study. Concluding Remarks Strategic management and entrepreneurship researchers have not adequately studied how the technology regime of an industry and the knowledge asymmetries between owners and investors, affect the mode of exit of venture capital firms. The technology regimes of the industry a young technology firm operates in and the associated knowledge asymmetries are an important concept for venture capitalists to consider because they affect the valuation of the firms they represent and subsequently their exit strategies. CONTACT: Marc Junkunc; mjunkunc@miami.edu; (T): ; (F): ; University of Miami, School of Business Administration, Jenkins Bldg, 412A, 5250 University Drive, Coral Gables, FL REFERENCES Barry, C. B., C. J. Muscarella, J. W. Peavy, & M. R. Vetsuypens. (1990), The Role of Venture Capital in the Creation of Public Companies, Journal of Financial Economics, 27: Carpenter, M., T. Pollock, & M. Leary. (2003) Testing a Model of Reasoned Risk Taking: Governance, the Experience of Principals and Agents and Global Strategy in High-Technology IPO firms. Srategic Management Journal, 24: Cohen, B. & T. Dean. (2005) Information Asymmetry and Investor Valuation of IPOs: Top Management Team Legitimacy as a Capital Market Signal. Strategic Management Journal, 26: DeCarolis, D. M., & D. Deeds. (1999). The Impact of Stocks and Flows of Organizational Knowledge on Firm Performance: An Empirical Investigation of the Biotechnology Industry. Strategic Management Journal, 20: Dierickx I, & K. Cool. (1989). Asset Stock Accumulation and Sustainability of Competitive Advantage. Management Science 35(12). Garcia-Vega, M. (2006) Does Technological Diversification Promote Innovation? An Empirical Analysis for European Firms. Research Policy, 35: Gompers, P. (1995) Optimal Investment, Monitoring, and the Staging of Venture Capital. Journal of Finance, 50(5): Gompers, P., & J. Lerner. (1999). The Venture Capital Cycle. Cambridge, MA: MIT Press. Griliches, Z. (1998) R&D and productivity: The Econometric Evidence. Chicago: University of Chicago Press. Griliches, Z. (1995) R&D and Productivity: Econometric Results and Measurement Issues. Oxford: Blackwell. Hall, B. H., A. B. Jaffe, & M. Tratjenberg. (2001) The NBER Patent Citation Data File: Lessons, Insights and Methodological Tools. NBER Working Paper Hitt, M. A., R. E. Hoskisson, D. R. Ireland & S. J. Harrison. (1991) Effects of Acquisitions on R&D. Academy of Management Journal. 34: Posted at Digital Knowledge at Babson 8

10 Makri et al.: TECHNOLOGICAL DIVERSIFICATION, CUMULATIVENESS AND VENTURE CAPITAL Kale P, & P. Puranam. (2004) Choosing Equity Stakes in Technology Sourcing Relationships: An Integrative Framework. California Management Review 46(3): Kaplan, S., & P. Strömberg. (2002) Financial contracting theory meets the real world: An empirical analysis of venture capital contracts, Working Paper: University of Chicago School of Business. Chicago, IL. Klevorick, A., R. Levin, R. Nelson, & S. Winter. (1995) On the Sources and Significance of Interindustry Differences in Technological Opportunities. Research Policy, 25: Leonard-Barton D. (1985) Experts as Negative Opinion Leaders in the Diffusion of a Technological Innovation. Journal of Consumer Research(11 March): Lerner, J., (1995) Venture Capitalists and the Oversight of Private Firms. Journal of Finance, L(1): Lerner, J., (1994) Venture Capitalists and the Decision to Go Public. Journal of Financial Economics, 35: Malerba, F., & L. Orsenigo. (2000) Knowledge, Innovative Activities, and Industrial Evolution. Industrial and Corporate Change, 9(2): Malerba, F., & L. Orsenigo. (1997) Technological Regimes and Sectoral Patterns of Innovative Activities. Industrial and Corporate Change, 6(1): McEvily S. K., K. M. Eisenhardt, & J. E. Prescott. (2004) The Global Acquisition, Leverage, and Protection of Technological Competencies. Strategic Management Journal 25(8/9): 713. Mowery, D. C., J. E. Oxley, & B. S. Silverman. (1998) Technological Overlap and Interfirm Cooperation: Implications for the Resource View of the Firm. Research Policy, 27: Nerkar, A., & S. Paruchuri. (2005) Evolution of R&D Capabilities: The Role of Knowledge Networks Within a Firm. Management Science. 51(5): Ritter, J. R., and I. Welch. (2002) A Review of IPO Activity, Pricing, and Allocations. The Journal of Finance, LVII(4); Rosenkopf, L., & A. Nerkar. (2001) Beyond Local Search: Boundary-Spanning, Exploration, and Impact in the Optical Disk Industry. Strategic Management Journal, 22: Sahlman, W. (1990) The Structure and Governance of Venture Capital Organizations. Journal of Financial Economics, 27: Sanders, G., & S. Boivie. (2004). Sorting Things Out: Valuation of New Firms in Uncertain Markets. Strategic Management Journal, 25: Sapienza, H. J., & A. K. Gupta. (1994) Impact of Agency Risks and Task Uncertainty on Venture Capitalist-CEO Interaction. Academy of Management Journal, 37(6): Shane, S., (2001) Technology Regimes and New Firm Formation, Management Science, 47(9): Shane, S., & D. Cable. (2002) Network Ties, Reputation, and the Financing of New Ventures. Management Science, 48(3): Shane, S., & T. E. Stuart. (2002) Organizational Endowments and the Performance of University Startups, Management Science, 48 (1): Sorenson, O. & T. E. Stuart. (2001) Syndication Networks and the Spatial Distribution of Venture Capital Investments. American Journal of Sociology, 106(6): Steensma H. K., & J. Fairbank. (1999) Internalizing External Technology: A Model of Governance Mode Choice and an Empirical Assessment. Journal of High Technology Management Research 10(1): 1. Stuart, T. E., H. Hoang & R. C. Hybels. (1999) Interorganizational Endorsements and the Performance of Entrepreneurial Ventures, Administrative Science Quarterly, 44: Venture Economics. (1988) Exiting Venture Capital Investments. Needham: Venture Economics. Winter, S. G. (1984) Schumpeterian Competition in Alternative Technological Regimes. Journal of Economic Behavior and Organization, 4: Frontiers of Entrepreneurship Research

11 Frontiers of Entrepreneurship Research, Vol. 27 [2007], Iss. 1, Art. 1 Table 1 Technological Diversification Industry N Mean Std. Dev Std. Error Mean Computers & Drugs & Medical Semiconductors Situation Type (IPO=1 M&A=0) Computers & Drugs & Medical Semiconductors Time to Event Computers & Drugs & Medical Semiconductors Age at Event Computers & Drugs & Medical Semiconductors Amount Invested Computers & Drugs & Medical Semiconductors Sales Computers & Drugs & Medical Semiconductors Technological Cumulativeness Computers & Drugs & Medical Semiconductors Rounds Received Computers & Drugs & Medical Semiconductors Fund Size Computers & Drugs & Medical Semiconductors Posted at Digital Knowledge at Babson 10

12 Makri et al.: TECHNOLOGICAL DIVERSIFICATION, CUMULATIVENESS AND VENTURE CAPITAL Table 2: Descriptive Statistics & Correlations Mean Std Dev Age at Event Time to Event *** 1.00 Amount Invested *** Sales *** 0.14*** Fund Size ** *** Rounds Received *** 0.54*** 0.21*** ** 1.00 No. Firms Invest in Company *** 0.44*** 0.29*** *** 0.64*** 1.00 Tech Diverse * 0.07** -0.11*** ** ** 1.00 Tech Cumulative * -0.11*** ** *** 0.76*** Frontiers of Entrepreneurship Research

13 Frontiers of Entrepreneurship Research, Vol. 27 [2007], Iss. 1, Art. 1 Table 3 Logit Regression Coefficients Hypothesis 1 Dependent Variable= Exit Type (IPO=1, M&A=0) Logit Regression Coefficients Hypothesis 2 Dependent Variable= Exit Type (IPO=1, M&A=0) β/ Std. Error β/ Std. Error Constant 2.09 *** * Computers & ** * Drugs & Medical *** * Time to Event *** *** Age at Event 4.21 *** 4.52 *** Time to Event Squared 4.20 *** 4.53 *** Age at Event Squared ** *** Amount Invested (log) 2.89 ** 3.43 *** Sales (log) 7.19 *** 6.74 *** Fund Size (log) ** ** Rounds Received * * Number of Firms Invested in the Company Technological Diversification *** Technological Cumulativeness *** Chi-squared *** *** Log Likelihood p< 0.10 * p< 0.05 ** p< 0.01 *** p< N=908 for both models Posted at Digital Knowledge at Babson 12

14 Makri et al.: TECHNOLOGICAL DIVERSIFICATION, CUMULATIVENESS AND VENTURE CAPITAL Table 4 Logit Regression Coefficients Hypotheses 3 & 4a, 4b, 4c Dependent Variable= Exit Type (IPO=1, M&A=0) β/ Std. Error Constant *** Computers & ** Drugs & Medical Time to Event *** Age at Event 4.14 *** Time to Event Squared 4.72 *** Age at Event Squared ** Amount Invested (log) 4.43 *** Sales (log) 6.49 *** Fund Size (log) ** Rounds Received ** Number of Firms Invested in the Company 1.83 Chi-squared *** Log Likelihood p< 0.10 * p< 0.05 ** p< 0.01 *** p< N=908 Frontiers of Entrepreneurship Research