Does Corporate Venture Capital Suppress Technological Variation? Evidence from Pharmaceutical Firms’
Investments in Biotechnology Startups
FRANCISCO POLIDORO JR.
McCombs School of Business, University of Texas at Austin
1 University Station B6300, Austin, TX 78712
WEI YANG
University of Texas at Austin
ABSTRACT
Existing literature has highlighted the challenges that incumbent firms face when new technologies emerge
and emphasized the role of CVC investments in helping firms explore new technologies. However, while
demonstrating the effects of those investments in facilitating incumbent firms’ exploration of new technologies,
existing literature has thus far overlooked the possibility that these investments might shape the technological
trajectories of the recipient new ventures. In examining this tension, this study focuses on the influence that CVC
investments have on the search path that underlies new ventures’ inventive activities. More specifically, this study
proposes that these investments contribute to a new venture moving away from distant search and favoring activities
that are more aligned with the investing firm’s technologies, thus decreasing the technological distance between a new
venture and the investing firm. Moreover, this effect is attenuated by a new venture’s interorganizational
collaborations and by the size of the co-investing syndicate, and exacerbated by the investing firm's technological
capabilities. We test these hypotheses in the context of the biotechnology new ventures receiving CVC investment
from pharmaceutical firms between 1980 and 2015. The analysis adopts a matching approach to more sharply
distinguish between observations subject to treatment condition and those functioning as controls, thus allaying
endogeneity concerns. In contrast with prior research underlining the role of new ventures in increasing technological
variation and of CVC investments in helping firms explore a broader array technological opportunities, this study
reveals that, somewhat ironically, these investments contribute to suppressing the degree of technological variation that
investing firms could otherwise potentially learn from.
INTRODUCTION
Corporate venture capital (CVC) investments have become increasingly relevant to incumbents’ innovation
and adaptation in many technology-intensive sectors. In the process of technological change, new ventures are
oftentimes an important source of technological variation, becoming the locus of innovations that depart more radically
from existing technologies (Schumpeter, 1934; Tushman & Anderson, 1986; Anderson & Tushman,1990). In contrast,
established firms face substantial difficulties in adaptation, as their search and exploration of new technologies are
hindered by many internal obstacles stemmed from organizational inertia, rigidities of routines, and lack of
experiences and knowledge in those areas (Cohen & Levinthal, 1990; Christensen & Bower, 1996; Henderson &
Clark, 1990; Nelson & Winter, 1982; Tripsas, 1997; Tushman & Anderson, 1986). As minority equity investments in
new ventures, CVC helps firms overcome such tendencies to search locally by facilitating their access to a broader
array of technological options at their early stage (Dushnitsky & Lenox, 2005a; Park & Steensma, 2012). These
investments enable firms to assess emerging technologies long before they are introduced in product markets,
providing firms with the opportunity to either more swiftly respond to promising technologies or more smoothly
disengage from new technologies that turn out to be less fruitful than expected (Dushnitsky & Lenox, 2005b; Hallen,
Katila, & Rosenberger, 2014; Tong & Li, 2011). Yet, despite the great strides that scholars have made in establishing
CVC investments as important vehicles for firms to explore new technological opportunities, the literature has thus far
overlooked the possibility that these investments may reshape the technological trajectory of recipient new ventures.
Examining such possibility is conceptually relevant to a more comprehensive understanding of technological
change and incumbents’ adaptation in emerging technological fields. On the one hand, CVC investments are meant for
promoting more technological variation in the era of ferment following technological discontinuities. Although new
ventures may have achieved preliminary innovation by the time they receive the investment from established firms,
they still need to rely on external sources for refinement of the new technologies, innovation of complementary
technologies, as well as search of optimal applications on the product market. Corporate investments, by giving more
resources to new ventures, may help new ventures bring the technological opportunities to fruition, thus ultimately
increasing technological variation in the market (Chemmanur, Loutskina, & Tian, 2014; Pahnke, Katila, & Eisenhardt,
2015). On the other hand, although overlooked by the existing studies, such investments can also influence new
1
ventures to adjust the direction of their efforts in subsequent innovation taking into account the technologies and
resources of the investing firms. The resulting similarities between new ventures’ subsequent innovation and
incumbents’ existing knowledge could defeat the original purpose of promoting technological variation.
In examining this tension, this study focuses the influence of CVC investments have on the search path that
underlies new ventures’ inventive activities. Based on evolutionary economics and the literature on organizations’
adaptive search (e.g., Nelson & Winter, 1982; Levinthal, 1997), we argue that CVC has the potential effect of
“localizing” what has been distant search - the new venture may favor paths that come closer to the investing firm
when continuing in the development of the technology. In terms of knowledge and information, such investments
facilitate the flow of information and knowledge from incumbents to new ventures through the routine interactions,
mentoring activities, and new ventures’ utilization of incumbents’ resources and complementary assets, such as
research facilities. Cognitively, corporate investments shape entrepreneur’s attention and the perceived uncertainty of
different technological options. As such influence of corporate investments originates from its ability to reshape new
ventures’ search process and shift entrepreneurs’ attention, we further propose that this effect is attenuated by a new
venture’s interorganizational collaborations and by the size of the co-investing syndicate, and exacerbated by the
investing firm's technological capabilities.
This study contributes to the evolutionary theory and research on entrepreneurship in the follow ways. First,
this study deepens the understanding of technological variation and incumbents’ search process for adaptation during
technological changes. Somewhat ironically, incumbents’ efforts of expanding the scope of search through investment
to new ventures may suppress variation, thus partly defeating the purpose of such efforts in the first place. Meanwhile,
the propositions of our study also shed lights on the potential advantage incumbents can leverage during technological
changes, explaining why, despite the difficulties, some incumbents can still survive radical technological changes.
Relying on their existing resources and knowledge, incumbents can exert influence on the technological development
by investing in new ventures with emerging technologies, naturalizing the threat from competence-destroying
discontinuities (Anderson & Tushman, 1990; Tushman & Anderson, 1986). Second, this study advances the
understanding of start-up innovation. Extending the existing studies that focus on CVC and the volume of start-up
innovation, we further propose that such external investment can also alter the direction of innovation in new ventures.
In addition to its theoretical contribution, such finding also enables entrepreneurs to be better informed of the possible
consequences to their ventures’ technological development when seeking CVC investment.
THEORY AND HYPOTHESES
Technological change presents great challenges to incumbent firms. Changes induced by competencedestroying discontinuities introduce new knowledge and technologies that threaten the technological and market
position of established firms (Tushman & Anderson 1986; Henderson & Clark, 1990). Lacking adequate knowledge
and experience in those remote areas, incumbents’ learning and adaptation is oftentimes hindered by their low
absorptive capacity to effectively assimilate the relevant new information knowledge and inability to recognize the
technological opportunities created by radical changes (Anderson & Tushman, 1990; Cohen & Lavinthal, 1990;
Tushman & Anderson 1986). Incumbents’ adaptation is also constrained by the existing routines and structures for the
operations on the previous technologies and markets, as well as the resulting path dependencies and organizational
inertia (Nelson & Winter, 1982; Henderson & Clark, 1990; Tripsas, 1997). All those obstacles reinforce incumbents’
tendencies of local search and lead to sub-optimal adaptation (Levinthal, 1997), causing incumbents fall behind the
development of new technologies.
To overcome those difficulties they encounter, established firms are increasingly utilizing CVC investments in
many high technology industries (Dushnitsky & Lenox, 2005b; Maula, Keil, & Zahra, 2013). Such investments
provide incumbents with opportunities to access and explore new technologies through the participation of investment
screening, due diligence and board membership (e.g. Dushnitsky & Lenox, 2005b; Katila et al., 2008; Maula et al.,
2013; Wadhwa & Kotha, 2006). Incumbents can also postpone learning under high technological uncertainties, while
access to the information and knowledge relevant to the failures experienced by new ventures’ failure within proximity
(Dushnitsky & Lenox, 2005b). In sum, such investments to new ventures allow incumbents to be timely informed of
emerging technologies (Maula et al., 2013), while bridging incumbent's existing domain with new technological
development initiated by entrepreneurial firms’ technologies.
While facilitating the adaptation and learning of established firms, CVC also should influence the subsequent
innovation process of new ventures. The involvement of incumbents through such investment not only enables new
ventures to secure the financial capital necessary for subsequent development, but also to gain access to those
resources complementary that enable them to further refine and improve their innovation. Yet, empirical evidence on
the role of such investments in new venture innovation is limited. Moreover, as the only few relevant study all focuses
2
on the effect of such investment on the speed of innovation (e.g., Chemmanur et al. 2014; Pahnke et al., 2015), the
existing literature has largely overlooked the possibility that these investments might shape the technological
trajectories of the recipient new ventures
In this study, we probe into such possibility and argue that CVC investments trigger new ventures’ tendencies
to move away from distant search and favor activities that are more aligned with the investing firm’s technologies, thus
decreasing the technological distance between a new venture and the investing firm. In other words, corporate
investment influences the search processes guiding the inventive activities of those new ventures, reshaping what was
once a distance search process toward convergence to technological space of investing firm. First, corporate
investments shift start-ups’ resource viability allocation and entrepreneurs’ attention to the technological regimes
dominated by the incumbents. In particular, as new ventures often lack the complementary assets to profit from
innovation (Teece, 1986), they are motivated to seek corporate venture capital to obtain access to the resources of
incumbent firms that can be utilized as complementary assets. In addition, the convergence of technological
development of new ventures to incumbents also occurs as a result of maximizing the reputation and legitimacy
benefits associated with corporate venture capital.
Second, CVC magnifies the appeal of incumbent technologies and shapes entrepreneurs' perception about
technological capabilities. Corporate venture capital brings attention to incumbents' technologies. Entrepreneurs are
likely to pay more attention to the development of incumbents, so as to development technologies that can be favored
by corporate venture capital, for the purpose of subsequent financing or event ultimate acquisition (Tong & Li, 2011;
Gompers & Lerner, 2000). What’s more, such attention to incumbents' technologies shapes the search landscape of
new ventures during innovation (Levinthal, 1997). The attention and subsequent learning lead to better understanding
of the interdependencies of incumbents technologies, lowering the perceived uncertainties and motivating distant new
venture to achieve the long jump to incumbents' technological domains.
Hypothesis 1: The technological distance between a new venture and an incumbent firm diminishes
after that venture receives CVC investments from that firm.
As such influence of corporate investments originates from its ability to reshape new ventures’ search process
and shift entrepreneurs’ attention, we further probe the logic underlying main effect by looking at possible
contingencies that may alter those mechanisms. First, CVC usually operates as subsidiaries or sub-units of incumbents
firms, who do not have the direct technological knowledge or access to complementary assets (Souitaris, Zerbinati, &
Liu, 2012). Hence, CVC’s ability to converge new ventures' technological trajectories can be bounded by the number
of new ventures' direct collaborations with other firms during innovation (Toh & Polidoro, 2013). Compared with
direct collaborations, the indirect connections between incumbents and start-ups through CVC can generate smaller
resource sharing benefits from collaboration, communication and recombination of knowledge, as all of those actives
requires substantial trust between patterns (Ahuja, 2000). In addition, new ventures with direct access to other
knowledge sources are likely to move away from incumbent’s technologies when other trajectories through inter-firm
collaboration are available, because the social norms of trust and reciprocity through direct collaboration could
function as more effective defense mechanisms for knowledge appropriation.
Hypothesis 2: The more interorganizational collaborations a new venture has, the less that the
technological distance between a new venture and the firm diminishes after that venture receives CVC
investments from that firm.
In addition, the characteristics of investment can also affect CVC’s influence on technological
distance. More specifically, the presence of a large number of venture capitalists weakens the ability of
corporate venture capital to influence the perception of technological opportunities. Each of the venture
capitalists, with their resources and experiences, may provide new ventures with different technological
options. Hence, large investment syndications can expand the search scope of new ventures in the course of
innovation, diluting their attention to incumbents' technologies. Moreover, independent venture capitalists are
often more actively involved in the decision-making process of new ventures (Park & Steensma, 2012). As
independent venture capitalists often take active seats on the board, participate in the selection of management
team members and are with more frequent mentoring (Davila, Foster, & Gupta, 2003), their influences to
entrepreneurs are stronger and more immediate than those from corporate venture capital, who are found to be
more passive investors with less involvement in the daily activities of invested start-ups (Katila et al., 2008).
Hypothesis 3: The larger the co-investing syndicate, the less that the technological distance between a
new venture and the firm diminishes after that venture receives CVC investments from that firm.
The tendency of new ventures technological convergence can be accentuated by the incumbents’
technological strength. One of the major mechanisms that promote technological convergence is the access to
3
complementary assets. Incumbents' superior high technological capabilities indicate larger amount of
complementary assets accumulated through the development of such capabilities. High technological
capabilities also lead to incumbents' superior innovation performance, which increases the appeal of their
technologies while decreasing the perceived risks. In addition, the risk of convergence is further lowered as
new ventures expect better technological and facility support from incumbents with high technological
capabilities (Chemmanur et al., 2014; Katila et al., 2008), further strengthening invested start-ups’ tendencies
to venture into incumbents’ knowledge and technologies in subsequent innovation.
Hypothesis 4: The stronger a firm’s technological capability, the more that the technological distance
between a new venture and the firm diminishes after that venture receives CVC investments from that
firm.
METHOD
We empirically test our proposed hypotheses in the context of biotechnology new ventures receiving CVC
investments from pharmaceutical companies. This setting is appropriate for the test of our hypotheses for several
reasons. First, the development of biotechnology induces significant technological change and creates considerable
technology uncertainties that require incumbents’ constant adaptation and innovation. Second, the field of
biotechnology is characterized by the co-existence of large pharmaceutical incumbents and a large amount of
entrepreneurial new ventures (Gaba & Meyer, 2008; Wadhwa & Kotha, 2006), making the considerations of CVC and
its technological consequences particularly relevant. Indeed, as figure 1 shows, CVC investment takes up to 12% of all
investment in new ventures in the biotechnology sector, the highest amount all the six industry categories according to
the data from VentureXpert.
We collected the CVC investment data are obtained through VentureXpert database and new ventures’ interfirm collaboration through alliances from SDC Platinum. Incumbent firms’ financial data was gathered from
COMPUSTAT database. We are in the process of collecting the patent data for measuring technological convergence
from the United States Patent and Trademark Office (USPTO).
Research design
Empirically examining the causal effect of CVC on new ventures’ technological convergence presents
challenges of endogeneity. While the literature on CVC usually adopts conventional panel data regression analyses
(e.g. Tong & Li, 2011; Dushnitsky & Lenox, 2005b), such method that usually focuses on the likelihood of CVC
investment or incumbents’ innovation may not be appropriate when examining the post-investment technological
development of new ventures due to high endogeneity between investment and innovation of start-ups (Chemmanur et
al., 2014). In particular, CVC was attracted to certain new ventures because of their unique technological features and
tendencies, and such features can also lead technological convergence, confounding the effect of CVC in that regard.
In order to derive a more definite casual conclusion, we constructed a matched sample that is with the same
independent venture capitalists and similar technological characteristics, approximating a quasi-experiment design in
which CVC investment can be argued as a treatment that is randomly assigned. We first identified the investment
made to the new ventures of the category of “biotechnologies” that are labeled as “corporate investment” in
VentureXpert to construct the “treated” group, in which CVC can be regarded as the treatment to the ventures’
technological development. We then located all the independent venture capitalists that appear in syndicates and use
all the syndicates without any CVC participation as to construct the control group, in which the treatment of CVC is
absent. To future enhance the randomization of CVC as the treatment, we performed Coarsened Exact Match (CEM)
based on the investment amount, syndicate size and time of investment. As shown in figure 2 and 3, the final sample
consists of 545 investment made to 264 new ventures through 364 syndicates from 1980 to 2016, 203 of which
involved 261 investments by 122 CVCs and 161 syndicates as control group involves 284 investments by 149 IVCs.
Figure 4 reports the frequency of CVC investment by the major incumbent plays.
***Insert Figure 1- Figure 3 Here ***
Measurement and analysis
We measure CVC investment in the context of a venture capital syndication, namely, whether the investment
syndication involved in the new venture has corporate venture capitalists as members. Following existing traditions,
Technological capabilities of incumbents is measured by the citation-weighted patent counts of the incumbent firms to
measure the technological capabilities (Dushnitsky & Lenox, 2005b). Start-up’s inter-firm collaborations is measured
by the number of research alliances formed within a focal year. Syndicate size is measured by the count of venture
capital firms listed as investors at a given time. In addition to quasi-experiment design with an approximation of
randomized treatment of corporate venture capital, we will also consider control variables related to the characters of
4
the incumbent, the new venture and the investment to reduce unobserved heterogeneity. Table 1 and table 2 report
descriptive statistics of variables and t-tests between the treated and control group.
*** Insert Table 1, Table 2 and Figure 4 - Figure 6 Here ***
We use fixed effect differences-in-differences model to estimate the effect of proposed hypotheses in the
matched sample. The model allows for estimations of the treatment effect of CVC on technological convergence while
controlling for the firm fixed effect and other variables listed above. We estimate the effect of corporate venture
investment in five years as the following (Chemmanur et al., 2014):
5
𝑡𝑒𝑐ℎ_𝑐𝑜𝑣𝑔𝑖,𝑡 =
𝑠
𝛽1𝑠 ∑ 𝑎𝑓𝑡𝑒𝑟𝑖,𝑡
𝑠=1
5
𝑠
+ 𝛽2𝑠 ∑ 𝑎𝑓𝑡𝑒𝑟𝑖,𝑡
∗ 𝑐𝑣𝑐𝑖 + 𝑩𝑿𝒊𝒕 + 𝜇𝑖 + 𝜖𝑖𝑡
𝑠=1
𝑠
In which 𝑎𝑓𝑡𝑒𝑟𝑖,𝑡
indicates the whether by the time t the treated group has received corporate venture capital
investment for s years, 𝑩𝑿𝒊𝒕 represents the effect of all other independent and control variables, and 𝜇𝑖 represents the
firm fixed effects. Hypothesis 2 to Hypothesis 4 will be tested by sub-sample analysis using samples with 1 standard
deviation below and above the mean of proposed boundary conditions. Robustness tests will be performed using
different time span for measuring innovation and corporate investment. Figure 5 and figure 6 show the sample
selection of treated and control group in the model and the predicted effects.
DISCUSSION
By examining how CVC alters the search process in the recipient new ventures’ inventive activities and thus
affecting the technological variation in emerging technological field, our study makes the following contributions.
First, our study deepens the understanding of the consequences of incumbents’ adaptation efforts. In most of the
existing studies on CVC, such investments are widely regarded as an instrument that aids incumbents’ adaptation and
learning of new technologies (Dushnitsky & Lenox, 2005a; Maula et al., 2013; ). It is argued that the investments to
new ventures, the major force that drives the knowledge creation in emerging technological areas, facilitate
incumbents’ access to the knowledge underlying a variety of new technologies, enabling incumbents to overcome the
internal obstacles that hinder adaptation (e.g., Christensen & Bower, 1996; Henderson & Clark, 1990; Nelson &
Winter, 1982; Tripsas, 1997; Tushman & Anderson, 1986). Our study, in contrast, uncovers that such investment may
not achieve such intended purpose of adaptation as it shapes the scope of technological variation. That is, despite the
promote technological diversity and in turn the distant search for incumbents, CVC localizes the search process within
relevant new ventures to the knowledge base of incumbents’ existing technologies during their subsequent innovative
activities. Such converging tendencies on the side of start-ups may suppress the degree of technological variation that
investing firms could otherwise potentially learn from.
Second, our study advances the research on start-up innovation and entrepreneurship. Conceptually, this study
uncovers detailed processes through which new venture's technological development is influenced by their incumbent
competitors during technological changes. As shown in our study, investments from established firms can shift new
ventures’ locus of innovation by directing the search from distant search and frequent bricolage to a more specific path
closer to the existing technological trajectories of incumbents. In addition, by exploring the change of innovation
trajectory, this study shed lights on how external influences can shape the emergence of routines and the formulation
of path-dependencies critical to the knowledge creation and resource accumulation at the early stage of a start-up
development. While conventional wisdom that routines and inertia are rooted in dynamics internal to an organization,
this study shows that routines and organizational inertia can be externally induced at the early stage of organizational
development, under the influence of external investors.
The last but not the least, this study contributes to the literature on the evolution technological change. While
existing literature has extensively discussed the evolution of radical technological changes (Abernathy & Utterback,
1978; Anderson & Tushman, 1990; Suarez & Utterback, 1995; Tushman & Anderson, 1986), the detailed mechanisms
underlying the emergence of dominant design during such process remain underexplored. Through the case of CVC
investment to new ventures, our study reveals that the very efforts of established firms could affect the selection of
dominant design. Our findings of recipient new ventures’ tendencies to align subsequent innovation with incumbents’
existing technologies illustrate the process in which variation diminishes as new ventures move away from distant
search in the ferment period followed by radical technological changes, becoming localized to specific sub-domains,
precluding the emergence of dominant designs.
5
REFERENCES
Abernathy, W. J., & Utterback, J. M. 1978. Patterns of industrial innovation. Technology review, 80(7), 40-47.
Ahuja, G. 2000. Collaboration networks, structural holes, and innovation: A longitudinal study. Administrative science
quarterly, 45(3): 425-455.
Ahuja, G., & Katila, R. 2001. Technological acquisitions and the innovation performance of acquiring firms: A longitudinal study.
Strategic management journal, 22(3): 197-220.
Anderson, P., & Tushman, M. L. 1990. Technological discontinuities and dominant designs: A cyclical model of technological
change. Administrative science quarterly: 604-633.
Benson, D., & Ziedonis, R. H. 2009. Corporate venture capital as a window on new technologies: Implications for the performance
of corporate investors when acquiring startups. Organization Science, 20(2): 329-351.
Chemmanur, T. J., Loutskina, E., & Tian, X. 2014. Corporate venture capital, value creation, and innovation. Review of Financial
Studies: hhu033.
Christensen, C. M., & Bower, J. L. 1996. Customer power, strategic investment, and the failure of leading firms. Strategic
management journal, 17(3): 197-218.
Cohen, W. M., & Levinthal, D. A. 1990. Absorptive capacity: a new perspective on learning and innovation. Administrative
science quarterly, 35(1).
Dushnitsky, G., & Lenox, M. J. 2005a. When do firms undertake R&D by investing in new ventures? Strategic management
journal, 26(10): 947-965.
Dushnitsky, G., & Lenox, M. J. 2005b. When do incumbents learn from entrepreneurial ventures?: Corporate venture capital and
investing firm innovation rates. Research Policy, 34(5): 615-639.
Gaba, V., & Meyer, A. D. 2008. Crossing the organizational species barrier: How venture capital practices infiltrated the
information technology sector. Academy of Management Journal, 51(5): 976-998.
Hallen, B. L., Katila, R., & Rosenberger, J. D. 2014. How do social defenses work? A resource-dependence lens on technology
ventures, venture capital investors, and corporate relationships. Academy of Management Journal, 57(4): 1078-1101.
Henderson, R. M., & Clark, K. B. 1990. Architectural innovation: The reconfiguration of existing product technologies and the
failure of established firms. Administrative science quarterly: 9-30.
Katila, R., Rosenberger, J. D., & Eisenhardt, K. M. 2008. Swimming with sharks: Technology ventures, defense mechanisms and
corporate relationships. Administrative science quarterly, 53(2): 295-332.
Levinthal, D. A. 1997. Adaptation on rugged landscapes. Management science, 43(7), 934-950.
Maula, M. V., Keil, T., & Zahra, S. A. 2013. Top management’s attention to discontinuous technological change: Corporate
venture capital as an alert mechanism. Organization Science, 24(3): 926-947.
Nelson, R. R., & Winter, S. G. 1982. An evolutionary theory of economic change: Harvard University Press.
Pahnke, E. C., Katila, R., & Eisenhardt, K. M. 2015. Who takes you to the dance? How partners’ institutional logics influence
innovation in young firms. Administrative science quarterly, 60(4): 596-633.
Park, H. D., & Steensma, H. K. 2012. When does corporate venture capital add value for new ventures? Strategic management
journal, 33(1): 1-22.
Schumpeter, J. A. 1934. Capitalism, socialism and democracy. New York: Harper & Row
Souitaris, V., Zerbinati, S., & Liu, G. 2012. Which iron cage? Endo-and exoisomorphism in corporate venture capital programs.
Academy of Management Journal, 55(2): 477-505.
Suarez, F. F., & Utterback, J. M. 1995. Dominant designs and the survival of firms. Strategic management journal, 16(6): 415430.
Teece, D. J. 1986. Profiting from technological innovation: Implications for integration, collaboration, licensing and public policy.
Research Policy, 15(6): 285-305.
Toh, P. K., & Polidoro, F. 2013. A competition‐based explanation of collaborative invention within the firm. Strategic
management journal, 34(10): 1186-1208.
Tong, T. W., & Li, Y. 2011. Real options and investment mode: Evidence from corporate venture capital and acquisition.
Organization Science, 22(3): 659-674.
Tripsas, M. 1997. Unraveling the process of creative destruction: Complementary assets and incumbent survival in the typesetter
industry. Strategic management journal, 18(s 1): 119-142.
Tushman, M. L., & Anderson, P. 1986. Technological discontinuities and organizational environments. Administrative science
quarterly: 439-465.
Wadhwa, A., & Kotha, S. 2006. Knowledge creation through external venturing: Evidence from the telecommunications
equipment manufacturing industry. Academy of Management Journal, 49(4): 819-835.
Yang, Y., Narayanan, V., & Zahra, S. 2009. Developing the selection and valuation capabilities through learning: The case of
corporate venture capital. Journal of Business Venturing, 24(3): 261-273
6
APPENDIX
30
20
10
0
Frequency
40
50
Figure 2. Sample Investments to Biotechnology Ventures by Year
1980
1990
2000
year
7
2010
2020