What affects new venture firm’s innovation more in corporate venture capital?

What affects new venture firm’s innovation more in corporate venture capital?

Journal Pre-proof What affects new venture firm’s innovation more in corporate venture capital? Jun-You Lin PII: S0263-2373(20)30021-9 DOI: https:...

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Journal Pre-proof What affects new venture firm’s innovation more in corporate venture capital?

Jun-You Lin PII:

S0263-2373(20)30021-9

DOI:

https://doi.org/10.1016/j.emj.2020.01.004

Reference:

EMJ 1981

To appear in:

European Management Journal

Received Date:

24 October 2018

Accepted Date:

30 January 2020

Please cite this article as: Jun-You Lin, What affects new venture firm’s innovation more in corporate venture capital?, European Management Journal (2020), https://doi.org/10.1016/j.emj. 2020.01.004

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier.

Journal Pre-proof Journal Title: European Management Journal Editor-in-Chief: Professor Minas Kastanakis Paper Title: What affects new venture firm’s innovation more

in corporate venture capital? ● Author Name: 1. First Author: Jun-You Lin, Associate Professor, Department of Management and Information, National Open University. Tel.: +886-2-22829355 ext 7612 E-mail address: [email protected] Reference website: http://mi.nou.edu.tw/teacher_cont.aspx?id=fK776UqITag= Biographical note: Dr. Jun-You Lin is an associate professor at the Department of Management and Information, National Open University, Taipei, Taiwan. He received his doctorate in the Graduate Institute of Business Administration, College of Management, National Taiwan University, Taipei, Taiwan. His current research interests include innovation management and entrepreneurship. His current research interests include innovation management and entrepreneurship. He has published papers in Journal of Technological Forecasting and Social Change, Journal of Technology Transfer, Journal of Engineering and Technology Management, Management Decision, Technology Analysis & Strategic Management, International Journal of Technology Management, Journal of Business-to Business Marketing, Service, Industrial Journal, and other journals. ● Corresponding Author: Author Name: Jun-You Lin Correspondence address: 172, Chung-Cheng Road, Lu-Chow District, New Taipei City 247, Taiwan, ROC. Tel.: +886-2-22829355 ext 7612 Mobile phone: +886-922332215 E-mail address: [email protected]

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What affects new venture firm’s innovation more in corporate venture capital? Jun-You Lin1 Abstract Although corporate venture capital (CVC) is a potential source of innovation, few studies have directly examined the impact of a parent company’s knowledge and resources on a new venture firm’s innovation performance. This article investigates the impact of experience with parent’s alliance and investment intensity on the extent to which new ventures in the U.S. use their parents’ knowledge and financial resources for their innovation activities at the inception of the CVC relationship over a 44-year period. Our findings suggest that ventures with alliance experience draw more on collaboration knowledge and relational capital, while investment intensity also increases innovation. At a low level of investment complexity, the use of alliance experience and investment intensity is positively related to innovation performance. However, when a parent company has high investment complexity for innovation performance, investment intensity and alliance experience are less effective. Our results, thus, unveil the CVC backing associated with the innovation of new venture firms. Keywords: investment intensity, alliance experience, investment complexity, innovation performance

1Corresponding

author: Department of Management and Information, National Open University,

Tel.:+886-2-2282-9355ext7612

E-mail address:[email protected] 2

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What affects new venture firm’s innovation more in corporate venture capital? Abstract Although corporate venture capital (CVC) is a potential source of innovation, few studies have directly examined the impact of a parent company’s knowledge and resources on a new venture firm’s innovation performance. This article investigates the impact of experience with parent’s alliance and investment intensity on the extent to which new ventures in the U.S. use their parents’ knowledge and financial resources for their innovation activities at the inception of the CVC relationship over a 44-year period. Our findings suggest that ventures with alliance experience draw more on collaboration knowledge and relational capital, while investment intensity also increases innovation. At a low level of investment complexity, the use of alliance experience and investment intensity is positively related to innovation performance. However, when a parent company has high investment complexity for innovation performance, investment intensity and alliance experience are less effective. Our results, thus, unveil the CVC backing associated with the innovation of new venture firms. Keywords: investment intensity, alliance experience, investment complexity, innovation performance

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1. INTRODUCTION New ventures often lack the resources and expertise to innovate on their own. Assisting their parent companies, offers a way for them to access complementary experience and resources to increase the likelihood of innovation success. A corporate venture capital (CVC) investment is typically the first type of relationship that new ventures form with industry incumbents. CVC investments, whereby parent companies take minority equity stakes in private startups (Dushnitsky & Lenox, 2006; Kim et al., 2019), have increased dramatically over the past few decades. Many studies have explored the industry- and firm-level characteristics that promote CVC investments (Basu, Wadhwa, & Kotha, 2016). Empirical studies identifying the factors that explain the performance of these new ventures have yielded some results. For example, previous research has shown that some entrepreneurs’ technical and managerial experience, size of venture team, and their human and social resource endowments have a divergent influence (Aspelund, Berg-Utby, & Skjevdal 2005; Dushnitsky & Lenox, 2005b; 2006; García-Carbrera et al., 2019). However, the alliance experience and investment intensity are usually a complement to, and sometimes a substitute for, the new venture’s own R&D. Research indicates that established parent companies are more likely to enter into an investment relationship with a new venture firm, and benefit each other. When the experience with parent’s alliance and finance resource are novel and significant (Katila et al., 2008; Gulati, 2007; Stuart, 2000), they also tend to harvest innovation opportunities. Overall, parent companies are a good source of innovation or to realize that a venture firm’s innovation needs to come from both external and internal sources. From the new venture perspective, then, investment relationships with parent companies are strategic, not just (or even primarily) financial transactions. Although such links open up innovation opportunities for new venture firms, we examine the experience and investment links that form between new ventures and parent companies, when new ventures build on parent company experience and investment. To fill this research gap, we propose that two issues must be considered, as they can enhance our comprehension of the effect of alliance experience, finance resources and the

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investment complexity on the innovation performance of a new venture firm. This study explores the CVC contents by categorizing parent’s resource heterogeneity into two dimensions, and then examines their effects on the innovation performance of new venture firms, and then explores the role of parent’s investment complexity in explaining the relationship between parent’s resource heterogeneity and new venture’s innovation. Our primary contribution is to the CVC literature. By identifying experience and investment links as an influential innovation antecedent and exploring relevant boundary conditions to their influence, we respond to the call by researchers to improve the understanding of who makes new venture firms’ innovation build on parent company alliance and investments of CVC relationships (Basu, Phelps, & Kotha 2011; Wadhwa & Kotha; 2006). We also show that new ventures’ insight into the innovation tendencies of potential new venture firms gained through investment complexity is a significant contingency that influences innovation. As such, our study responds to the call for more research on the resource heterogeneity of parent companies (Dushnitsky & Shaver, 2009; Kim et al., 2019; Pahnke, et al., 2015; Pahnke, McDonald, Wang, & Hallen, 2015) and more broadly contributes to research on the linkage between new ventures and parent companies. In addition, although investment complexity has been found to encourage new venture’s innovation by serving as a variety of investment of parent company in the CVC relationship, this article contributes to our understanding of the moderating roles of parent’s investment complexity. Investment complexity may exert either a positive or a negative effect on the parent’s resources–performance relationship, depending upon the value of the investment complexity. While prior studies recognize that the symmetry of contingency arguments suggests a nonmonotonic effect of investment complexity (Murray et al., 2005), the literature streams on new venture’s innovation sourcing and parent investment complexity have largely remained separate. Our research extends these studies by addressing the moderating role of investment complexity in relation to the innovation of a new venture firm. Prior studies suggest that CVC investments can be a powerful tool that allows parent investors to tap into the knowledge held by new venture firms and access new innovation developments (Benson & Ziedonis, 2009; Chesbrough, 2003; Dushnitsky & Lenox, 2005a;

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Lorenzo & Vrande, 2019; Wadhwa & Basu, 2013). Such research provides substantial evidence of the benefits of CVC investments for parent companies. For example, CVC investments lead to increased significant innovative output (Dushnitsky & Lenox, 2005b; Dushnitsky & Lenox, 2006; Wadhwa & Kotha, 2006), and enhance explorative learning (Schildt, Maula, & Keil, 2005). However, as the parent-sided view is probably incomplete in the CVC investment literature, relatively little is known about how CVC investments generate benefits for the ventures within an investment portfolio (Cumming, 2010; Lorenzo & Vrande, 2019). Prior studies suggest that CVC-backed ventures are more likely to go public, to have higher IPO values than those with VC backing, and are particularly beneficial for new ventures that require specialized complementary assets (Gompers & Lerner, 2004; Maula & Murray, 2002; Park & Steensma, 2012). Notably, new venture firms are not just selling a piece of equity in a financial transaction but rather, absorbing, learning from, and assisting parents for access to promising alliance experience and investment intensity that may accelerate their own innovation development (Wadhwa & Kotha, 2006). The benefits of CVC are not solely financial. Scholars have recently started to investigate the innovation outcomes of CVC-backed new ventures and found that they typically develop more innovations than VC-backed ventures (Alvarez-Garrido & Dushnitsky, 2016; Pahnke, Katila, et al., 2015). The alliance experience and investment intensity are usually a complement to, and sometimes a substitute for, the new venture’s own R&D. When the alliance experience and finance resource are novel and significant (Stuart, 2000), they tend to harvest innovation opportunities. Finally, this study provides an understanding of whether and to what extent ventures access and use parent companies’ tangible and intangible resources. This is important because although new ventures are often admired for their organizational innovativeness, they are likely to be constrained in terms of the alliance experience and financial resources that are available to them, which threatens their chances of innovation (e.g., Carbrera et al., 2019; Lorenzo & Vrande, 2019). In fact, not all ventures have the resources needed to seek, manage, and leverage technology development (Dushnitsky & Shaver, 2009), which creates decisional trade-offs for new ventures in allocating their limited resources to capture innovation opportunities. Thus, we take a question-driven approach and ask how experience with parent’s alliance and investment intensity in a CVC setting can represent,

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individually and jointly with investment complexity, opportunities to tap into parents’ tangible and intangible assets for a new venture’s innovation. 2. THEORY AND HYPOTHESES 2.1 Theoretical development As new venture firms have insufficient resources, experience and knowledge are required to continue their innovation; their capacity to learn from parent companies is important in maintaining a competitive advantage (Almeida et al., 2003; Lorenzo & Vrande, 2019). New venture firms often need additional resources to innovate, which makes them more likely to turn to their parent companies to gain access to complementary resources and financial assets (e.g., Katila et al., 2008). Access to these resources and assets has been shown to significantly increase the performance of corporate-backed new ventures (e.g., Alvarez-Garrido & Dushnitsky, 2016; Lorenzo & Vrande, 2019). Moreover, the relational and investment capital held by parent companies are attractive sources of innovation for new ventures, which often innovate by building on their parent companies’ tangible and intangible assets (Kim et al., 2017). Thus, our model combines the perspectives of resource dependence (Pfeffer & Salancik, 1978; 2003) and resource-based theory (Harrison et al., 1991; Wernerfelt, 1984). The logic of resourcebased theory explains that investment from parent companies allows a new venture firm to capitalize on its innovation; resource dependence theory stresses the alliance experience for reducing failures and threats in new venture firms by managing the uncertainties of innovation. Both theories focus on how knowledge sharing and resource investment affect innovation outcomes. 2.1.1 Resource dependence theory Resource dependence theory offers insights into which collaborative strategies organizations will use, and how the use of these strategies varies over time. When the transfer of knowledge and innovation are uncertain and problematic, organizations attempt to establish strategic alliances or CVC investment linkages to obtain knowledge resources and to avoid organizational constraints (Pfeffer & Salancik, 1978; 2003). Resource dependence theory has two axioms. The first is that new venture firms are constrained by, and depend on, other organizations that control critical resources for them.

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The second is that resource dependence theorists have suggested that managers make strategic choices given the constraints in a strategic alliance to reduce and manage innovation uncertainty (Hrebeniak & Joyce, 1985). A new venture firm has discretion over how to structure interorganizational investment relationships to manage innovation uncertainties. In CVC investment, a parent company contributes the knowledge and resources necessary for the new venture firm’s innovation success that the other firm cannot. The firm will gain power relative to other firms and assert greater control over the new venture. It also implies that a parent’s control will focus on the activities of the new venture firm to which it contributes knowledge and resources (Harrigan & Newman, 1990; Lecraw, 1984; Yan & Gray, 1994). Resource dependence theory focuses on the effects of factors pertaining to the way in which new venture firms should organize to innovate in a dynamic environment. According to the theory, a firm should reduce its dependence on other firms for pivotal or crucial resources, and manage its boundaries to reduce environmental uncertainties (Pfeffer & Salancik, 1978). In this study, this theory could explain not only why new venture firms adopt experience with a parent’s alliance, but also why such a strategy’s effect on innovation performance may be contingent on the complexity of the investment. 2.1.2 Resource-based theory Resources include all tangible assets, capabilities, experiences, processes, and knowledge controlled by the firms (Barney 1991). In the case of new venture firms, frequently described from the resource-based perspective (Barney, 1991; 1997; Teece et al., 1997; Wernerfelt, 1984), researchers argue that the innovation of these ventures is closely associated with the knowledge and resources of their parent companies. The resource-based theory explains the importance of investment intensity from parent companies as an opportunity to capitalize on the strengths of a new venture firm’s innovation. New venture firms face knowledge and resource constraints because of their liability of newness (Atuahene-Gima, Li, & De Luca 2006) and deal with the innovation nature of the technology dynamic (Harrison et al., 2001). Resource-based theory creates interdependency and facilitates the formation, development, and investment effectiveness

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of CVC. Furthermore, accessing financial resources through market mechanisms is not always easy in the early stage of a new venture. CVC investment can be used to attract financial resources due to their technological flexibility and potential to reduce innovation risk. The resource-based CVC formation argument suggests that new venture firms combine the parent’s resources and maximize innovation by pooling and using valuable resources that a new venture firm cannot create by itself (Ainuddin et al., 2007; Das & Teng, 1998; Hu et al., 1995; Ireland et al., 2002). CVC investment provides synergistic benefits from alliance experience and financial resource when based on complementarity and assistance. Resource dependence theory and resource-based theory have suggested that new venture firms depend on a parent company to supply the knowledge and resources to manage and reduce innovation uncertainties (Barringer & Harrison, 2000; Harrison et al., 2001). Resource-based theory has been categorized based on the tangible and intangible assets that include a firm’s alliance experience and financial resources. In combining these two theoretical perspectives, we argue that innovation sourcing from alliance experience and investment intensity would help new venture firms obtain collaboration knowledge and financial resources. Both are related to the new venture firm’s innovation performance. 2.2 Alliance experience and innovation performance Alliances offer benefits such as access to capital, knowledge, new markets, and the ability to share the risks of uncertain endeavors. Alliances can be of fundamental importance to the innovation of entrepreneurial firms. However, because entrepreneurial firms hold limited resources and because of their lack of legitimacy, new venture firms find it challenging to engage in alliances (Blevins & Ragozzino, 2018). In this study, alliance experience is defined as the number of repetitions in the learning-by-collaboration process between new venture firms and their parent company. These collaborative mechanisms are often portrayed in resource dependence theory as devices that combine the relationship between the parent and the new venture firm, thus providing an important basis for understanding the effective innovation management of recognizing opportunities and exploiting critical heterogeneous resources and capability (Ireland et al., 2002; Mowery et al., 1988).

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While our hypotheses addressed alliance experience needs from the perspective of the new venture firm’s innovation, relationship formation is bilateral, meaning that the interests of both parties are relevant and appropriate to CVC tie formation. New venture firms are likely to be especially interested in relationships that involve alliance with parents, because having excess resources from a parent can be a rationale for a new venture firm to be interested in CVC investment relationship (Penrose, 1959). Providing alliance collaboration may be particularly appealing to new venture firms because technology development decisions are often intertwined with innovation choices at the early stage (Pisano, 1989). New venture firms may prefer more alliance relationships because external technology resources are often expensive and slow to create, and sometimes uniquely available with parent collaboration (Schilke, 2014). This argument builds on the resource dependence with the parent company, an iterative process of organizational knowledge creation, retention, and transfer (Pfeffer & Salancik, 1978). As a result, acquiring and applying knowledge through more alliance with parents may enhance the development of innovation. Unfortunately, new venture firms may lack reputation, and its capacity to bear the transaction costs associated with alliance formation – which can include ex ante search and due diligence costs as well as ex post contractual and litigation costs (e.g., Gulati & Singh, 1998; Reuer et al., 2002). The ability of new venture firms to engage in alliance activity may be inhibited by their inherent characteristics, have fewer resources to offer to a collaboration partner (e.g., Mowery et al., 1996), and be poorly connected (Chung, Singh, & Lee, 2000). Using parent’s alliance relationship while innovating helps confer guarantee and legitimacy, which is important for their innovation development. These experiences also enhance a new venture’s visibility and reputation as a trustworthy partner. Thus, because of enhanced alliance management skills along with greater ability to learn a parent’s knowledge sources, new venture firms with more experience with parent’s alliances are more capable of using the opportunities for knowledge exchange (Kavusan et al., 2016). Accordingly, our main prediction is that new venture firms will be more likely to innovate with more alliance experience with parents. A new venture firm’s innovation may be reinforced by the parent company’s inclination to form alliances, because of the

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accessibility of complementary resources from the parent and the enhanced visibility to prospective funded ventures (Dushnitsky & Lavie, 2010). In sum, the reinforcement perspective suggests that the pursuit of alliance experience with a parent beyond the new venture firm’s boundaries, as reflected in the knowledge resource complementarity and network resource visibility mechanisms, can explain a positive association between alliance experience and the venture firm’s innovation in a CVC setting. Thus, we predict: Hypothesis 1: Alliance experience with parent company has a positive relationship with a new venture firm’s innovation performance. 2.3 Investment intensity and innovation performance As new venture firms are often subject to the threat of early failure and liabilities of newness (Lorenzo & Vrande, 2019), building on parents’ financial resources can be a critical element of their innovation activities. The resource-based view suggests that the rationale for CVC investment is the innovation-creation potential of financial resources that are to be used in R&D or technology development (Barney, 1991; Grant, 1991; Wernerfelt, 1984). In terms of CVC structure, the funding resource investment of a parent company determines a new venture firm’s innovation performance. Investment intensity refers to the actual cumulative investment of programs divided by total known amount invested in the focal new venture firm. It is used to evaluate the financial input of parent companies in venture firms. We test whether such a main effect exists through the second hypothesis. In this study, we propose that investment intensity can increase a new venture firm’s innovation in four ways. The due-diligence process provides the new venture firm a unique opportunity to revise its operations, business plan, and invention progress even prior to committing capital. This includes a background check of the founders and key management team in addition to discussions with key technology development. Investment intensity may experience economies of scale and scope in managerial efforts that allow a new venture firm to perform superior due diligence at lower cost, and helps to generate expertise about advancing the innovation quality of a new venture firm (Chesbrough, 2003). Indeed, before a parent’s investment funding, the due diligence activities related to business plans, technology resources, proposed products, and market prospects give the new venture firm a unique opportunity to learn about a parent’s innovation.

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In many instances, new venture firms solicit corporate investment (Dushnitsky & Lenox, 2005b). Parent companies need to evaluate a venture firm’s outcome responses to its actions, and draw generalizations about the causal relations between the effects and the results after making an equity commitment (Dushnitsky & Lenox, 2005a; Wadhwa & Kotha, 2006; Yang et al., 2009). The due diligence process allows the new venture to learn everything prior to committing capital (Dushnitsky & Lenox, 2005b). Such evaluations and generalizations are tested and adjusted over repeated actions and involvement, so that new venture firms can revise their course of action in ways that increase the probability of securing desired innovation outcomes (Van de Ven & Polley, 1992). The more the parent company invests in a specific venture firm, the more intention and attention will be placed in that firm. Parent companies make a greater involvement to new venture firms to ensure innovation performance. In addition, after high investment intensity, a typical investment decision follows a sequence of initial screening, information gathering, risk assessment, and the evaluation of target entrepreneurial companies. Investment intensity enhances innovation performance by extending new venture firms’ technology domains when the parent companies are established in diverse technology segments. It gives a venture firm’s managers new insights into a parent’s financial resources. Intense investment activity helps new venture firms overcome financial obstacles in a changing competitive environment, and drives new venture firms to take advantage of better innovation growth opportunities (Lin & Lee, 2011). High parent investment also prompts new venture firms to establish and manage relationships to achieve resource reliability, stability, and predictability. Through the use of CVC investment, new venture firms can respond to innovation uncertainty by spreading the risk with high investment intensity. High investment intensity allows the new venture firm to possess superior resource adaptation and adjustments under innovation uncertainty. Finally, greater investment intensity reflects the importance of the new venture firm to the parent companies. A new venture firm can require and expand the availability of a parent company’s financial resources. Once the investment round has taken place, a new venture firm can learn from its parent companies. Corporate investors often secure board seats, or at least board observation rights, which provide consultative support for ventures’ key activities and technologies (Dushnitsky & Lenox, 2005b). New venture firms have

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instituted specific organizational routines to encourage and funnel learning from parents at the postinvestment stage. These linkages give the new venture firm access to a broader pool of inputs of R&D human capital than what is available in the new venture firm. The new venture firm may use new R&D human capital to support, complement, or augment its R&D capabilities (Chesbrough & Tucci, 2003). It has long been recognized that learning is contingent upon close interaction between firms’ personnel that accommodates rich channel and knowledge flows. Thus, investment intensity provides a powerful stimulus to the development of innovation performance. Resource investment from the parent company enhances synergies by facilitating the shift funds to meet R&D needs and the cross-leveraging of innovation opportunities (Lin & Lee, 2011). This may allow the new venture firm to tap into rich sources required to be an effective innovation source. This leads to the following hypothesis. Hypothesis 2: Investment intensity from a parent company has a positive relationship with a new venture firm’s innovation performance. 2.4 Investment complexity as a contingency As new venture firms are not self-sufficient in terms of the knowledge and resources that they need, these firms are forced to enter into investment relations with the parent companies in their environment. Resource dependence theorists have suggested that managers make strategic choices within constraints (Pfeffer & Salancik, 1978), but they have discretion over how to arrange organizational relationships to conduct innovation uncertainties (Oliver, 1990). Many researchers consider complexity to be an important factor in major strategic decisions, such as the decision to seek CVC investment. CVC investment presents a significant managerial challenge, given the complexities and uncertainties of syndicated managing programs across organizational boundaries. Investment complexity refers to the account of parent companies’ engagement in syndication for investing a new venture firm listed in each CVC investment program. Investment complexity may moderate the effect of the alliance experience effect and subsequent innovation performance. In developing hypotheses investigating contingency relationships, researchers have warned that contingency arguments have symmetrical effects. The symmetrical property of contingency arguments suggests a nonmonotonic effect of alliance experience on innovation performance over the range of the investment

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complexity, instead of the usual assumption of a constant effect (Murray et al., 2005; Schoonhoven, 1981). We attribute these effects to the following observations. A parent’s investment complexity may enhance the likelihood of collaboration formation, by making it easier for new venture firms to search for and identify a parent’s attractive knowledge. From a new venture perspective, parent companies whose investment complexity new ventures are building on are likely to have technology development capabilities, the breadth of knowledge absorption, and alliance channels specifically applicable to the respective new venture innovation. Indeed, the parent’s investment complexity is an effective means for new ventures to accumulate knowledge about a prospective innovation. As capability conduits, investment complexity delivers private, reliable information with rich details on the quality, and competence of a new venture firm’s innovation (Gulati & Gargiulo, 1999). Thus, when investment complexity is low, the new venture firm that takes advantage of alliance experience to gain access to a parent’s innovation capability tends to enjoy greater innovation performance. When a parent’s investment is highly complex, it may reduce the effect of the venture’s alliance benefits and its subsequent innovation. High investment complexity among coinvestors generates a greater need for interorganizational coordination. The alliance relationship needs to be accommodated through diverse means of coordination and is difficult to manage. When investing with greater complexity, it is hard to pursue a common investment objective; there is a need to reconcile goal incongruity, unfairness, and the competing interests of co-parents’ companies (Kang & Jindal, 2015). Indeed, the investment complexity of CVC activities incurs incremental costs that outweigh marginal benefits, leading to negative effect innovation performance of this focal venture firm (Cho & Authurs, 2018). In addition, high investment complexity may lead to a more adverse selection as a low-quality parent company (Dushnitsky & Shavor, 2009). This problem is most pronounced for CVC investments because high-quality new venture firms hesitate to establish alliances and share information about their key technology with parent companies for fear that those new venture firms may expropriate their innovation outcomes (Dushnitsky & Lenox, 2006). The investment complexity might hinder the processing of information and the ability to draw inferences from knowledge generated through alliance with its parent. We believe

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that the high investment complexity arising from the exposure to, on average, high investment risk contexts, diminishes a new venture firm’s ability to apply and assess the value of lessons from the past alliance. As managers perceive a higher likelihood of a potential uncertain intervention by the corporate investors that is detrimental to the innovation interests of the new venture firm, their confidence in the beneficial outcomes with parent’s alliance dealing with investment risk is likely to be lower. In summary, investment complexity will limit the ability of new venture firms to acquire venture-parent alliance benefits, thereby confronting innovation difficulties. Based on these arguments, this study hypothesizes a negative relationship between alliance experience and innovation performance with high investment complexity. These arguments lead to the following hypotheses: H3: The impact of alliance experience on the new venture firm’s innovation performance is nonmonotonic over the range of investment complexity. H3a: When investment complexity is low, increases in alliance experience by the parent company tend to positively influence a new venture firm’s innovation performance. H3b: When investment complexity is high, increases in alliance experience by the parent company tends to negatively influence a new venture firm’s innovation performance. Most new venture firms lack the financial resources to develop the constituents related to the innovations. In the CVC industry, syndication is one of the most familiar and significant forms of investment (Wright & Lockett, 2003). Empirical findings on the effect of investment complexity on investment intensity range from positive to negative. The contradictory findings of the effect of complexity on the innovation of a new venture may be due to the different types of levels faced by parent companies. Sutcliffe and Zaheer (1998) have stressed that complexity is an uncertain construct in that it may come from a variety of sources, and different types of complexity may have different implications for innovation development. To capture the effects of complexity on the investment intensity– innovation performance relationship, it is necessary to investigate different levels of complexity separately. We expect investment complexity to moderate the relationship between investment intensity and innovation performance. We attribute these positive and negative effects to the following.

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When investment complexity is low, the new venture firm can benefit by upgrading its innovation capability by sourcing financial resources from a parent’s investment. In addition, a new venture firm may learn about novel experiences from a board of directors as well as by using dedicated liaisons (Dushnitsky & Lenox, 2005b; Dushnitsky & Shaver, 2009). Syndication coinvestors could share expertise, possibly leading to better decisions on whether and how to invest in new venture firms (Yang et al., 2009). Syndication with new venture firms provides opportunities for capability development. The emphasis relies on financial investment from parent companies to generate synergy within sharing or combining of physical capital (Yang et al., 2014). Over time, the intensity of learning-byinvesting allows them to integrate resources to make them problem-focused, setting the R&D stage with diverse new venture innovation subjects. Thus, when there is a low level of investment complexity, the new venture firm that is most likely to gain access to parent’s funding resources tends to improve innovation performance. However, increasing investment complexity might lead to diminishing returns. When a parent company’s investment is highly complicated, it is not as easy for the new venture firm to rely on its investment intensity. A high level of investment complexity arises from the difficulties associated with coordinating many coinvestors (Phene & Tallman, 2012). Studies of investment complexity point to the effect of conflict, redundancy, or competitive overlap among parent companies in the portfolio (Gomes-Casseres, 1996). In addition, investment complexity complicates the development of CVC investment performance agreement, given that it is more difficult to define new CVC programs that meet the requirements of all the coinvestors. A critical limitation on innovation created by a new venture firm is that each parent company makes it more difficult to increase the investment amount and implement the reciprocity mechanism (Garcia-Canal & Sanchez-Lorda, 2007; Hoffmann, 2007). Given the complex nature of investment, parent companies face situations that are more ambiguous, it is difficult for parent companies to evaluate the appropriate investment amount, thus contributing to diminished innovation performance. The need for disparate routines and practices from investment complexity and intensity increases the cost and limits the innovation benefits of new venture firms. The associated complexity exerts significant pressures on the new venture firm's limited resources, leading to a saturation

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effect (Belderbos et al., 2018; Gomes-Casseres, 1996; Heimeriks & Duysters, 2007). Thus, unexpected innovation outcomes are hard to predict. Therefore, when CVC investments are complex, their performance is often viewed as uncertain because of their unstable returns and ambiguous strategic benefits due to the low appropriability of intellectual property rights and their use (Mayer & Salomon, 2006). Therefore, a new venture firm with high investment complexity is usually associated with more outcome than investment certainty because the former have not reached certain milestones. Based on these arguments, at high level of investment complexity, the present study hypothesizes a negative moderating relationship between investment intensity and innovation performance, reflecting the variety of costs of simultaneous investing by different kinds of corporate investors. Thus, investment intensity may make a new venture firm’s innovation more difficult. Therefore, it is hypothesized that: H4: The impact of investment intensity on the new venture firm’s innovation performance is nonmonotonic over the range of investment complexity. H4a: When investment complexity is low, increases in investment intensity by the parent company tends to positively influence the new venture firm’s innovation performance. H4b: When investment complexity is high, increases in investment intensity by the parent company tends to negatively influence the new venture firm’s innovation performance. 2.5 Theoretical model CVC activities construct a reciprocal relationship between a parent company and a new venture firm, bringing many benefits to both sides (Allen & Hevert, 2007; Miller & Camp, 1985; Stuart et al., 1999). Some of these activities are financially focused, with established companies seeking higher returns on their investments by targeting younger and growing entrepreneurial venture firms. Other CVC investments promote organizational learning about emerging technologies (Yang et al., 2009). Faced with persistent and radical changes in their innovation environments, the new venture firms have used CVC investments to establish innovation advantage, making it an important research topic (Dushnitsky & Lenox, 2005a; Powell et al., 1996; Stuart, 2000; Yang et al., 2009). Moreover, in viewing CVC investment as a complex social system, this study contends that parent companies’ inherent parent’s investment-specific attributes help a new

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venture firm’s innovation. Parent companies tend to view CVC deals strategically, as a window on innovation technology and an opportunity to learn (Dushnitsky & Lenox, 2006; Kim et al., 2019). Alliance experience and investment intensity from the parent company adjust and improve new venture firm’s future actions and may influence the development of innovation. They help them adjust and improve their future actions when they repeatedly engage in an activity (Jimenez et al., 2018; Levitt & March, 1988). In addition, we propose that the effect of alliance experience and investment intensity on innovation performance of new venture firms is moderated by investment complexity. We expect new venture firms to profit from a parent’s tangible and intangible resources to varying degrees depending on parent’s investment complexity. When investment complexity is low, increases in alliance experience and investment intensity from the parent company have a positive effect on a new venture’s innovation; in a highly complex investment environment, internal conflicts, weak incentives, and unstrained information asymmetries may erode innovation. Intended outcomes are hard to predict and inferences about causes and effects are difficult to generate. Thus, with greater investment complexity, it is more difficult for new venture firms to innovate. To the best of our knowledge, few studies have directly examined the innovation sourcing–performance relationships for new venture firms. Figure 1 presents our conceptual framework. We answer two research questions. Does an increase in the experience with a parent’s alliance and investment intensity enhance innovation performance? What is the role of investment complexity in explaining this relationship? A positive relationship (Hypotheses 1 and 2) and a moderated relationship (Hypotheses 3, 3a, 3b and 4, 4a, 4b) are hypothesized. Insert Figure 1 3. RESEARCH METHODS 3.1 Research Setting and Sample The unit of analysis is the new venture firm. To test the hypotheses, we construct a sample using the SDC VentureXpert database, Standard and Poor’s Compustat and the U.S. Patent and Trademark Office (USPTO) database. We focused on global firms that are publicly traded to obtain data on CVC investments and firm’s finance data. The objective

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of this study is to explore the effects of alliance experience and investment intensity on the innovation performance; we constructed a large panel of public firms (1968–2012). Our sample contains information on firms’ CVC activity collected from VentureXpert database, which have been used by previous studies (e.g., Dushnitsky & Lennox, 2005a, 2005b; Yang et al., 2009) and which contains detailed information on private equity investments (Gompers & Lerner, 2004). Financial information about public parent companies and new venture firms from Standard and Poor’s Compustat database, and patent data is extracted from USPTO database through PatentGuider, a software program designed to acquire patent data from around the world. SDC VentureXpert database is offered by Venture Economics, a division of Thomson Financial, is a leading source of global private equity intelligence and famous in researches about the venture capital industry. Because of its richness and reliability, it has been used in numerous academic studies about venture capital (Bygrave, 1989; Gompers, 1995; Dushnitsky & Lenox, 2005a; 2005b). The follow-up data and variable augmentation are based on this list. The VentureXpert database contains a comprehensive coverage of investment, CVC portfolio size, CVC age, exit, and performance activity in the private equity industry and provides us with the population of all private equity investments done by parent companies and new venture firms (Dushnitsky & Lenox, 2006; Yang et al., 2014). The venture lists of all ventures searched from VentureXpert have been used in prior CVC studies (Dushnitsky & Lenox, 2005b; Yang et al., 2014): Non-Financial Corp Affiliate or Subsidiary Partnership, Venture/PE Subsidiary of Non-Financial Corp., Venture/PE Subsidiary of Other Companies NEC, Venture/PE Subsidiary of Service Providers, Direct Investor/Non-Financial Corp, and Direct Investor/Service Provider. This step will define the corporate-backed venture units. The investing fund must be the primary shareholder to manifest the influence from single CVC investment parent companies. In this study, the parent company makes the largest cumulative investment in the new venture firm. Besides, all parent companies and new venture firms having IPO before our research are required to ensure financial data are accessible. To compensate for the small sample size, this research will collect 5 observation years for each firm because of our stricter data sieving criteria. In addition, because of a time lag between a CVC investment and the innovation performance, a 1-year time lag has

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been preserved between independent and dependent variables (Dushnitsky & Lenox, 2005a; Hall & Zedonis, 2001). An automated, matching algorithm and hand checking is used to link the VentureXpert data with the Compustat data set. The final sample consists of 855 firm-year observations, where investments were done by 111 public parent companies from 1968 to 2012. 3.2 Measures Dependent variable. Innovation performance. We use two measures of new venture firm innovation performance. Our first measure is number of patents granted. Patents are available in a consistent and longitudinal manner, and are validated by examiners based on invention novelty (Belderbos et al., 2018). Patents are also a prime determinant of new venture firms’ ability to attract a parent direct investment (Shan & Song, 1997). If parent companies are interested in a new venture’s innovation skills, the number of patents granted is widely used to evaluate innovation performance. Accordingly, innovation performance is operationalized as the number of patents granted to a new venture firm during the focal year. It is used to measure the new venture firm’s recent innovation activity. Patent data are collected from the U.S. Patent and Trademark Office. This study defines innovation performance as the ability to identify exceptionally promising new venture firms that are likely to generate numerous patents. To measure the impact of innovation performance, we used patent applied diversity as the innovation performance of a new venture firm (Garcia-Vega, 2006). It is possible to use the one minus Herfindahl index (HHI) of new patents that applied different patent classes in a given year. The HHI has been used extensively in the literature of strategic management to measure innovative diversity. In this study, we follow Hall’s (2005) study and use the HHI to indicate the patent portfolio concentration of technology fields within a new venture firm. J

Nj 2

Typically, the computational formula is defined as HHI = ∑j = 1( N ) , for a set of N patents falling into J classes, with Nj patents in each class (Nj ≥ 0, j=1,...,J ) we use 1 minus HHI as the proxy of the innovation performance. The higher the 1 minus HHI, the higher the innovation performance. As suggested by Dushnitsky and Lenox (2005a), we use a 1-year lagged effect of CVC parent’s investment intensity and alliance activity on the innovation 18

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performance of the new venture firm. Independent variables Alliance experience: Firms often differ in their ability to deal with alliances or joint ventures. Research demonstrates that alliance experience enables the new venture firm to recognize opportunities, assess partner potential, management cooperation and transfer of tacit knowledge over organizational boundaries (Hoang & Rothaermel, 2005; Phene & Tallman, 2012; Steensma & Lyles 2000). The management of strategic alliances or joint ventures may positively influence a new venture firm’s innovation performance. To allow for this effect, we created a variable, alliance experience, which is the number of repetitions in the learning-by-collaboration process. We operationalized this variable as the number of strategic alliances or joint ventures formed between the parent and venture firm given first and last investment year for a CVC program (Schilke & Goerzen, 2010). Investment intensity: Investment intensity is commonly used to evaluate the resource input of parent company in the new venture firm (Dushnitsky & Lenox, 2015b; Yang et al., 2014). Financial resources can be a source of new venture firm’s innovation advantage, even though they are not themselves unique or difficult to imitate. New venture firms that have high investment intensity are more likely to have slack resources, enabling them to leverage their R&D expenses and make value‐creating investments for future development when some of these value‐creating investments can be directed toward supporting innovation progress. Clearly, for innovation to be successful, they require adequate levels of financial investment and support, which will be available if the new venture firm has adequate distributable investment funds (Bierly III et al., 2009). In this study, investment intensity is the engagement in syndication for learning-by-investing. It is measured by the actual cumulative investment of programs divided by total known amount invested in the focal new venture firm. It is used to evaluate the financial input of parent companies in venture firms (Allen & Hevert, 2007; Dushnitsky & Lenox, 2005a, 2006). The more invested the parent company is in a venture firm, the importance of venture firm to parent company is greater, and the more resource and attention that venture firm will receive. Investment complexity: Multipartner investors have significant implications for CVC governance owing to higher coordination and appropriation concerns (Phene & Tallman, 2012). The SDC VentureXpert database lists the participants in CVC investment programs.

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In this study, investment complexity is measured by the account of parent companies’ engagement in syndication for investing a new venture firm listed in each CVC investment program. Control variables Patent stock: The parent company and new venture firm’s patent stock might influence how parent investors select and perceive the value added to the new venture firm, so we controlled for the parent company and new venture firm’s stock of knowledge, operationalized as organization i’s stock of prior patents (Patent Stock), to capture the capacity to absorb new knowledge (Yang et al., 2014). Age at IPO: Because capabilities develop over time, older firms acquire more resource endowments, and therefore, influence their innovative behaviors. Parent company and venture firm’s age are related to resources, experiences, and capabilities. Innovative knowledge embodied in organizational capabilities necessitates the passage of time because learning requires repetition and experimentation (Barney, 1991; Fortune & Mitchell, 2012; Teece et al., 1997). In this study, we control parent company and new venture firm’s age for the number of years from the IPO year of firm i to the year before the observation of the dependent variable. We acquire these data from the Compustat database. Productivity: We measure a firm's productivity by dividing its total assets by the number of employees. Productivity measures how a parent company and a new venture firm hire its employees to generate total assets and is considered a highly reliable indicator of the economic value that a firm produces (Bae & Gargiulo, 1998). Therefore, productivity, as a measure of overall performance, is more influential in internal R&D investments and marketing activities than are indicators that are focused on specific functional performance. Country patent: The richness of country innovation’s knowledge base caused by country patent effects allowed the parent company and new venture firm to enjoy innovation productivity (McGahan & Porter, 1997; Tsai, 2009). Industrial effects: Industry determines the environmental dynamism and growth rates, influencing the number of new business opportunities (Bierwerth et al., 2009). Research demonstrates that parent companies in different industries vary in their pursuit of CVC investment, underlining the importance of considering industry as a core boundary

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condition, when studying the investment-innovation relationship. We controlled for the variability of the intercept across industries using industry-specific dummy variables through the parent’s Standard Industrial Classification (SIC) code. Year effects: This study uses the SDC VentureXpert database, Standard and Poor’s Compustat and USPTO database for diverse parent companies’ and new venture firms’ data and across a long time span. To capture any time-varying factors homogeneously and heterogeneously affecting all sample firms, year effects should take into account possible general macroeconomic conditions and external economic shocks. In this study, to account for variances of CVC investment and new venture firm’s innovation in different time periods, a set of dummies to control 5-years window effect to account for possible environmental changes that could influence independent variables (Schildt et al., 2005). 3.3 Model and Estimation In this study, to evaluate the way in which alliance experience, Investment intensity, and complexity affects the new venture’s innovation performance, the patent production function is adopted. Two dependent variables are: the number of patents granted to new ventures and patent applied diversity. As the patent granted is a nonnegative integer, the count data model provides an adequate estimating technique (Ahuja & Lampert, 2001; Hausman, et al., 1984), the Poisson regression, and zero-inflated Poisson regression. In addition, we estimate the patent applied diversity models by using the fixed-effects and ML random-effects panel regression. The empirical models that we estimate are specified as Innovation performance = f (Alliance experience, Investment intensity, Investment complexity, Control variables) The Poisson model has a restriction that mean equals to variable, but this condition is difficult to hold because of the over-dispersion problem. To solve this problem, heterogeneity-consistent standard errors can be used. In the fixed-effects model, we assume that all firm differences are captured by differences in the intercept parameter. The intercepts are fixed parameters that could be estimated directly using the least squares estimator; the random-effects model using the GLS estimator allows us to control for the time invariant component of the error term without removing the term itself. In other words,

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the fixed-effects model assumes that the strata differ in their conditional means, while the random-effects model assumes that the strata differ in their conditional variances. To take a robustness check, we use a random-effects model with the maximum likelihood estimator and fit it to the population-averaged estimator (Wooldridge, 2013). We adopt a 1-year lagged specification, examining the association between a previous year’s values of our independent variables and this year’s innovation performance, patents granted and patent applied diversity, in an effort to mitigate concerns of reverse causality (Dushnitsky & Lenox, 2005b). Country patents, industry effects, and year effects alleviate concerns that innovative turbulent change is driving our results. The inclusion of patent stock, age at IPO, and productivity help control for the possibility that affects new venture firm’s innovation in CVC. 4. RESULTS We estimated the hypothesized relationships using moderated Poisson, zeroinflated Poisson, fixed- and ML random effects linear regression models. The dependent variable is the new venture firm’s innovation performance. We regressed innovation performance on the independent, moderator, and control variables, and the interaction between the independent and each of the moderator variables. Table 1 presents the descriptive statistics and correlation coefficients for the variables considered in this study. The variance inflation factors associated with each predictor ranged from 2.75 to 1.07 with a mean of 1.79. The effects of multicollinearity are within acceptable limits. None of the correlations are high enough to raise concerns about any serious multicollinearity among the variables (Hair et al., 1998). Insert Table 1 Tables 2 and 3 display the results of the hierarchical moderated regressions for the main and moderated effects on the new venture’s innovation performance. The Poisson regression and zero-inflated Poisson regression analyses provide the results for similar specifications that are estimated for each innovation variable. We also used the fixed- and ML random effects of the panel data-generalized regression models that generated similar results. Estimates in various specifications are similar, suggesting the estimated results are robust in tables 2 and 3. Models 1-3 in table 2 test our 4 hypotheses on the direct and moderated effects; models 4-6 are the same specifications for alternative zero-inflated

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Poisson regression analysis. Models 1-6 in table 3 are the same specifications for the alternative performance variable. When data on all new venture firms are considered, models 1 and 4, baseline for analysis, are restricted to the effects of all control variables. Models 2 and 5 include alliance experiencet-1 to evaluate hypothesis 1. Similarly, models 2 and 5 include investment intensityt-1 to test hypothesis 2. To test hypotheses 3 and 4, in addition to alliance experiencet-1 and investment intensityt-1, models 3 and 6 are the full models that include all variables. We introduce additional independent variables: investment complexityt-1 and the interaction terms with alliance experiencet-1 and investment intensityt-1. Although not reported in Tables 2 and 3, all models include industry and year dummy variables to control unobserved heterogeneity and time-varying factors. As shown by the LR  2 and F statistics in Tables 2 and 3, all 12 models for the Poisson, zero-inflated Poisson, fixed, and ML random effects are statistically significant (p<0.001). Direct effects: Hypothesis 1 posits a positive relationship between alliance experiencet-1 and innovation performance. The results for models 2 and 5 in Tables 2 and 3 show that the coefficients for alliance experiencet-1 are positive and statistically significant. The coefficients for alliance experiencet-1 are statistically significant (β = 0.515, p<0.05; β = 1.882, p<0.001; β = 0.198, p<0.01; β = 0.177, p<0.01) for the Poisson, zeroinflated Poisson, fixed, and ML random effects regression models. These relationships support hypothesis 1, indicating that the relationship between alliance experiencet-1 and innovation performance is positive. Hypothesis 2 states that investment intensityt-1 has a positive effect on innovation performance. The results for models 2 and 5 in Tables 2 and 3 indicate that the coefficients for investment intensityt-1 are positive and statistically significant (β = 0.564, p<0.05; β = 1.318, p<0.001; β = 0.371, p<0.001; β = 0.338, p<0.001). Therefore, the results are consistent with our expectation, presented in hypothesis 2, of the positive relationship between investment intensityt-1 and innovation performance. Alliance experiencet-1 and investment intensityt-1 are both positively related to innovation performance. Higher levels of alliance experiencet-1 and investment intensityt-1 from parent companies are related to higher innovation performance. Moderator effects: H3 hypothesizes that investment complexityt-1 has a moderating effect on the relationship between alliance experiencet-1 and innovation performance. The

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result shows that investment complexityt-1 is a significant moderator (β = -0.026, p<0.05; β = -0.111, p<0.001; β = -0.011, p<0.01; β = -0.019, p<0.05); thus, H3 is supported. Schoonhoven (1981, 363) has warned that “Merely inspecting the signs and magnitudes of regression coefficients is insufficient analysis for contingency hypotheses.” Hence, we conduct further analyses to identify any differences in the relationship between the alliance experiencet-1 (predictor variable) and the innovation performance (dependent variable) over the range of the investment complexityt-1 (moderator variable). As recommended by Aiken and West (1991) and Murry et al. (2005), the analysis is performed by computing the partial derivative of innovation performance in the Poisson regression equation for alliance experiencet-1 using the following partial differentiation equation:∂𝑌 ∂𝑋= 0.313–0.026 (investment complexityt-1), where X = alliance experiencet-1 and Y = innovation performance. The value of ∂𝑌 ∂𝑋 is ≥ 0 when the value of investment complexityt-1 is ≤ 12.038. It means that the effect of alliance experiencet-1 on innovation performance is positive when investment complexityt-1 is ≤ 12.038 (i.e., measured to be higher than average = 7.300), but is negative when investment complexityt-1 is ≥ 12.038. Therefore, the derivative hypotheses (i.e., H3a and H3b) are supported. The result shows that 84.21% of new venture firms has a value below the cutoff point of 12.038 for investment complexityt-1, and 15.79% of new venture firms above it. H4 hypothesize that the moderating effect of investment complexityt-1 is significant in the relationship between investment intensityt-1 and innovation performance. The result showed that the coefficient is significant (β = -0.291, p<0.001; β = -0.153, p<0.001; β = 0.021, p<0.1; β = -0.026, p<0.05). The partial differentiation equation in Poisson regression is: ∂𝑌 ∂𝑋 = 0.313–0.026 (investment complexityt-1). The value of ∂𝑌 ∂𝑋 is ≥ 0 when the value of investment complexityt-1 is ≤ 8.100. It means that the effect of investment intensityt-1 on innovation performance is positive when investment complexityt-1 is ≤ 8.100 (i.e., measured to be higher than average = 7.300). Thus, H4 and its related hypotheses, H4a–H4b are supported. The data show that 67.25% of new venture firms has a value below the cutoff point of 8.100 for investment complexityt-1, and 32.75% of new venture firms above it. Thus, taken together, the results indicate that investment complexityt-1 has a negative moderating effect both on alliance experience and on investment intensityt-1. Estimates of various specifications in tables 2 and 3 show similar

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results, suggesting the estimated results are robust. Insert Table 2 & Table 3 To depict the moderation effects, we used marginal plots. Unlike simple slopes, they show the strength and significance of the effect of alliance experiencet-1 and investment intensityt-1 on innovation performance for each value of the moderator (investment complexityt-1) (Kopmann et al., 2015). The solid lines in figures 2 and 3 represent the effect over the whole range of the moderator values. The dashed lines represent 95% confidence intervals. Conforming to what we observed from the estimated coefficient in figures 2 and 3, the marginal effect of alliance experiencet-1 and investment intensityt-1 go down and eventually turn negative when investment complexityt-1 rises from 0 to 40. Fig. 2 shows that alliance experiencet-1 is negatively and significantly related to innovation performance if investment complexityt-1 for damages realization is above 12.038, which is still higher than the mean in this sample (7.300). A similar effect can be observed regarding the investment complexityt-1 for investment intensityt-1. In high level of investment complexityt-1 (considerably higher than the sample mean of 7.300), the effect of investment intensityt-1 becomes significantly negative. Comparing the relationships in figures 2 and 3, it shows that lower levels of investment complexityt-1 are critical for alliance experiencet-1 and investment intensityt-1 on innovation performance. The best-performing new venture firms pursue alliance experiencet-1 and investment intensityt-1 in the context of investment complexityt-1. The best performance results in low level of investment complexityt-1. These findings support hypotheses H3, H3a, H3b and H4, H4a, H4b. Insert Figure 2 Insert Figure 3 The main results from the empirical analysis are as follows. Alliance experiencet-1 and investment intensityt-1 exert a strong effect on a new venture firm’s innovation performance. These two variables signal a new venture firm’s innovation sourcing for CVC investment. Thus, greater alliance experiencet-1 and investment intensityt-1 from parent company might create more opportunities to obtain novel innovation for the new venture firm. 5. DISCUSSION AND IMPLICATIONS 5.1 Theoretical contributions

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We explore the relationship between CVC investment and new venture firm innovation by analyzing a sample of 865 public new venture firms over a 42-year period. This finding is robust for different specifications to control for unobserved heterogeneity and the inclusion of new venture firm’s innovation performance. Theoretical contributions and managerial implications of our study are discussed in the next session. Although many studies have explored the industry- and firm-level attributes that promote CVC investment (e.g., Dushnitsky & Lenox, 2005a; Katila et al., 2008; Tong & Li, 2011), there has been limited consideration of experience with parent’s alliance and investment intensity on new venture firm’s innovation. A new venture firm may create and obtain more R&D synergies with a parent company than with those that lack alliance experience (Belderbos et al., 2018; Cho & Authurs, 2018; Cohen & Levinthal., 1990; Jimenez et al., 2018). Alliance with a parent’s experience is also beneficial to innovation performance in terms of knowledge application, guarantee, legitimacy, sharing risks, and development costs as evidenced by their positive influence on innovation (Chung, Singh, & Lee, 2000; Dushnitsky & Lavie, 2010; Kavusan et al., 2016; Reuer et al., 2002; Schilke, 2014). Similarly, investment intensity is beneficial to innovation capability in terms of a sequence of initial screening, information gathering, risk assessment, R&D need, consultative support, and the evaluation of target entrepreneurial companies (Chesbrough, 2003; Dushnitsky & Lenox, 2005b; Lin & Lee, 2011; Yang et al., 2009). By identifying knowledge and resource links as two important antecedents of the new venture firm’s innovation in the early stage, we respond to the call by Basu et al. (2011) and Basu et al. (2016) to study the relational antecedents of the CVC investment relationship. In doing so, our study complements prior research suggesting that alliance learning and financial investment from parents are two important determinants of subsequent new venture’s innovation in the context of CVC. More importantly, we show that insight into parent companies’ opportunistic propensities garnered by new ventures through investment complexity is a crucial moderator of their innovation performance. Prior research on CVC and new venture formation strategy has focused on the capability of parent companies and their innovation or finance performance (Dushnitsky & Shaver, 2009). We also contribute to the CVC literature by emphasizing the necessity of examining the symmetrical property of

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contingency arguments. More specifically, the combination of alliance experience and investment complexity occurs in new venture firms that draw less effect on experienceinnovation relationship in high level of investment complexity. Moreover, after investment intensity and high investment complexity interact, the venture innovates less in the investment-innovation relationship. We therefore offer a different perspective of bounded rationality arguments that there is a nonmonotonic effect of alliance experience and investment intensity on innovation performance over the range of investment complexity (Murray et al., 2005; Schoonhoven, 1981). Consequently, investment complexity substantiates any fears on the part of parent companies that their resources might be misappropriated through CVC investment; new venture firms are likely to perceive complex equity links as a threat rather than as an indication of opportunities for innovation. In sum, this study addresses a topic that we do not yet fully understand: how parent companies contribute to new venture firms’ innovation performance? Prior work has argued that CVCs bring investment benefits to new venture firms (Davila, Foster, & Gupta, 2003; Dimov & Shepherd, 2005; Blevins & Ragozzino, 2018). While prior work has focused on the link between CVCs’ properties to liquidity events, such as IPOs and acquisitions (Dushnitsky & Shaver, 2009), our interest is in new ventures’ innovation. New ventures often acquire resources from their parent companies to foster innovation development and success. Researchers have been most interested in equity investments in the CVC setting (Lorenzo & Vrande, 2019), and have studied the impact of entrepreneurs’ heterogeneity of experience in technical and managerial areas, size of venture team, and entrepreneurs’ human and social resources endowments on performance (Aspelund, BergUtby, & Skjevdal 2005; García-Carbrera et al., 2019). We look at whether these three attributes – alliance experience, investment intensity, and complexity – could function as channels through which new ventures can access and use a parent company’s tangible and intangible assets. Our results thus unveil the CVC backing associated with the alliance experience, investment intensity, and combined moderating role of a parent’s investment complexity in determining new venture firms' innovation performance. 5.2 Managerial implications

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The possible influence of experience with a parent’s alliance and investment intensity on a new venture firm’s innovation in a CVC setting has been traditionally gone unnoticed. In turn, practitioners have established separate organizational management routines for managing alliance partners and the new venture firm of CVC investments, yet increasingly recognize that the experience with a parent’s alliance and financial investment decisions may be intertwined with the new venture firm’s innovation. Our study examines the broader phenomenon of interdependence among alliance experience, investment intensity, complexity, and innovation performance, assuming that alliances experience and financial investment may be two innovation precursors of CVC investment in a target venture firm. We reveal an inherent association between parents’ resource-innovation relationships in CVC investment. Venturing activity might satisfy parent companies’ inclination toward introducing innovations by accessing an increasingly important source of knowledge – competent new venture firms (Dushnitsky & Lenox, 2005a; 2005b). The results of this study provide important insights for entrepreneurship scholars studying the CVC relationship to obtain a richer view of a new venture’s innovation. Scholars often portray new venture firms as passive participants in CVC relationships with parent companies and have not considered entrepreneurs as key innovators (Katila et al., 2008). In response, we take the side of the new venture firm entrepreneur. Little research takes the new venture firm’s innovation perspective on corporate investment relationships. Rather, the parent companies are viewed as the powerful, resource-rich, and highly desirable alliance experienced partner that dominates the decision to form a CVC investment relationship (Keil et al., 2008). It is important to determine the optimal level of complexity for CVC investment. Our findings confirm the moderating effects and reveal the conditions under which alliance experiences an investment intensity work. We point to the importance of a thorough evaluation of the new venture firm’s investment complexity. Our findings suggest that, at low levels of investment complexity, the new venture firm would ally with the parent company to develop a new knowledge base to supplement its limited capabilities with its parents’ technological expertise and knowledge in obtaining innovation performance. Sources of innovation do not reside exclusively inside new venture firms but are commonly found in the collaboration between new venture firms and parent companies (Powell et al.,

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1996). New venture firms would seek more alliance experiences and investment intensity that would provide the needed innovation (Ahuja, 2000). Alliance experience and investment intensity allow the new venture firm to leverage a parent’s knowledge resources. In addition, specialized experience and skills that result from social interaction unique to the new venture firm are more likely to lead to innovation advantages. However, at higher levels of investment complexity, the parent’s sourcing – innovation performance relationship was a negative one. Indeed, high investment complexity may destroy the continued relevance of a relationship; therefore, both alliance experience and investment intensity are less effective. Because of coordination and conflict management, high investment complexity leads to less-defined and more ambiguous innovation property rights, creating the potential for opportunism, shirking, and free-riding by coinvestors. Empirical evidence supports the hypothesized contingent effects (Garcia-Canal & Sanchez-Lorda; 2007; Gomes-Casseres, 1996; Heimeriks & Duysters, 2007; Hoffmann, 2007). Thus, the low level of investment complexity is likely to increase the benefits and lessen the costs. Given the critical role of these two innovation sourcing channels as vehicles for accessing parents’ knowledge and financial assets, as well as the investment complexity with parent companies, managers of new ventures would benefit from a better understanding of the extent to which these two innovation sourcing channels, individually and in combination with investment complexity, might contribute to the acquisition of a parent’s knowledge and resources for new venture firms’ innovation. 6. LIMITATIONS AND FUTURE RESEARCH Despite the contributions of our study to new venture firm’s innovation, there are some limitations to consider with regard to future research. The first is that this study uses the SDC VentureXpert database, Standard and Poor’s USPTO database from 1968 to 2012. Forty-two years may be too long a period, even though we have included year dummies in 5 firm years to control its effect. The second limitation is that we recognize three interrelated experience and resource flows within the CVC network. This study focuses both on parents’ experience and investment on new venture firm’s innovation performance, but also on existing knowledge

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between parents and from the new venture firm to the parents. Future research may examine the entire network of CVC activities, empirical insights into these questions would provide a more complete picture of the new venture firm-parents learning interactive phenomenon. Future researchers could also examine different investment patterns and stages where there are potential benefits for performance output. Given the lack of archival data, the study used global firms that are publicly traded to capture financial returns associated with CVC investments. Although this measure is in line with the literature (Yang et al., 2009), the IPO data reduce the variation of the dependent and independent variables; thus future research should supplement the objective measures, such as survey or interview managers of new venture firms and parent companies to capture the nature of new venture firm’s innovation. Similarly, measuring innovation performance by the use of secondary data is problematic, because successful innovation capabilities are usually embedded in an organization and protected from outsiders. Researchers have acknowledged the limitations of archival patent data in measuring innovation (Zahra et al., 2006). In conclusion, despite these limitations, both practitioners and scholars have proposed that CVC may provide a valuable avenue to access this pool of knowledge (Chesbrough, 2003; Dushnitsky & Lenox, 2005b). Through CVC investment, new venture firms may open an innovation window onto the parent’s experiences and resources. The findings of a positive relationship not only contributes to the understanding of the strategic benefits of a new venture firm’s innovation, but also advances the impact of alliance experience and investment intensity on innovation performance. In addition, a corporate investor's investment complexity moderates the relationship among alliance experience, investment intensity, and innovation performance. These insights from our results may guide new venture firms’ innovation to consider the impact of investment complexity.

References: Ahuja, G., 2000. The duality of collaboration: inducements and opportunities in the formation of interfirm linkages. Strategic Management Journal 21(3): 317-343. Ahuja, G., Lampert, C., 2001. Entrepreneurship in the large corporation: a longitudinal study of how established firms create break through inventions. Strategic

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Investment complexity H3 Alliance experience Investment intensity

H4

H1 H2 New venture firm’s innovation performance

Control variables 1. Firm level 2. Country level - Parent patent stock - Venture patent stock - Parent age at IPO - Venture age at IPO - Parent productivity - Venture productivity 2. Country level - Parent country patent - Venture country patent 3. Industrial effect 4. Year effect

Figure 1. Research framework.

40

Table 1. Correlation and Descriptive Statistics a Variable 1. Innovation performance: patent granted 2. Innovation performance:

1

2

3

4

5

6

7

8

9

10

11

12

13

1.00

-0.14

1.00

3. Alliance experience

-0.02

-0.03

1.00

4. Investment intensity

-0.01

0.06

-0.02

1.00

5. Investment complexity

0.12

-0.04

-0.53

0.16

1.00

6. Parent patent stock

0.01

0.06

-0.18

-0.08

0.02

1.00

7. Venture patent stock

0.73

-0.24

0.02

-0.02

0.06

0.01

1.00

8. Parent age at IPO

0.03

-0.11

0.18

-0.08

-0.12

0.01

0.13

1.00

9. Venture age at IPO

-0.03

0.04

0.13

-0.08

-0.10

-0.02

-0.01

0.89

1.00

10. Parent productivity

-0.04

-0.06

0.09

-0.02

-0.11

-0.08

-0.03

0.04

0.06

1.00

11. Venture productivity

-0.03

-0.11

0.13

-0.04

-0.12

0.00

0.00

0.01

-0.06

0.21

1.00

12. Parent country patent

-0.10

0.06

-0.30

-0.02

0.04

0.16

-0.05

-0.05

-0.06

0.08

0.19

1.00

13. Venture country patent

0.08

0.08

-0.19

0.11

0.06

0.04

0.14

0.09

0.01

-0.07

-0.16

0.30

1.00

Mean

1.93

0.64

0.16

0.46

7.30

3896.15

13.17

.8.05

5.83

1143.42

2102.40

7131.34

123580.8

Standard deviation

7.48

0.29

0.47

0.25

5.31

7240.96

36.92

8.39

7.46

3257.71

12330.99

3782.96

63189.74

1.07

2.04

1.64

1.11

1.32

1.99

2.152

1.63

1.62

2.75

2.37

patent applied diversity

VIF

50

a

N=855 (two-tailed t-tests). Correlations with absolute value greater than 0.10 are significant at ** p  .01 , those greater than 0.12 are

significant at *** p  .001 .

51

Journal Pre-proof Table 2. Poisson and zero-inflated Poisson regression model for new venture firm’s innovation performance b Poisson estimation Variables Constant

M1

M2

-0.767

-2.280

**

Zero-inflated Poisson estimation M3

M4

M5

M6

-1.226

-0.220

-1.794



-0.911

Independent variables Alliance experiencet-1

0.515

*

Investment intensityt-1

0.564

*



0.313

1.882

1.831

***

1.318

***

-0.021

0.137

***

0.070

**

*

-0.115

***

-0.111

***

-0.153

***

2.357

***

***

-0.441

Moderator variable Investment complexityt-1

0.080

***

Interactions Alliance experiencet-1 

**

-0.036

Investment complexityt-1

-0.026

Investment intensityt-1 

-0.291

Investment complexityt-1

***

Control variables 0.106

4

Parent patent stock ( x1 0 ) Venture patent stock Parent age at IPO Venture age at IPO 5

Parent productivity ( x1 0 ) 5

Venture productivity ( x1 0 ) 4

Parent country stock ( x1 0 )

5.840

( x1 0 )

0.105

0.102

0.053

0.011

***

0.014

***

0.014

***

0.011

***

0.012

***

0.012

***

-0.061

***

-0.093

***

-0.088

***

-0.111

***

-0.102

***

-0.098

***

0.064

***

0.104

***

0.090

***

0.073

***

0.133

***

0.125

***

3.110

-8.350

-3.450

-25.100

-1.290

-0.587

-0.050

-2.780

-0.615

***

0.024

***

-1.111

***

1.290

-1.101

Venture country stock 4

0.012

0.131

***

-1.217

***

0.164

**

-18.500

*

-0.592 -0.295



***

-1.551

***

***

0.118

-3.060

***

-1.461

***

0.126

Industrial dummies

yes

yes

yes

yes

yes

yes

Year dummies

yes

yes

yes

yes

yes

yes

52

***

Journal Pre-proof Log-likelihood

-1125.234

LR 𝑐ℎ𝑖2

3100.58

Pseudo 𝑅2 b

-960.156

***

2301.65

0.579

N=855



p  .10

*

p  .05

**

-923.531

***

0.545

p  .01

***

***

2374.90

-835.602 1219.66

***

-751.629 1370.85

***

-741.725 1390.66

***

0.563

p  .001 , Two-tailed t-tests.

Table 3. Fixed and ML random effects linear model for new venture firm’s innovation performance c

Fixed Effects M1

Variables Constant

1.057

M2

***

0.660

ML random Effects M3

M4

*

0.601

*

**

0.201

***

0.504

M5

***

M6

0.891

**

0.812

**

**

0.177

**

0.179

**

***

0.338

***

0.493

***

0.014

**

1.339

Independent variables Alliance experiencet-1

0.198

Investment intensityt-1

0.371

Moderator variable Investment complexityt-1

0.005

0.012

*

0.005

Interactions Alliance experiencet-1 

-0.011

Investment complexityt-1

**

Investment intensityt-1  Investment complexityt-1

-0.011

**

-0.021



-0.010

*

-0.019

*

-0.026

*

Control variables 6

Parent patent stock ( x1 0 ) 4

Venture patent stock ( x1 0 ) Parent age at IPO

3.530

-0.656 -0.021

Venture age at IPO



***

0.008 5

Parent productivity ( x1 0 ) 6

Venture productivity ( x1 0 )

2.690 -1.010

*

4.290

-0.526

-0.156

4.120

-0.024

***

0.021 *

***

**

1.570 -8.900

***

53

-0.024

*

3.770

0.110

***

0.022

**

1.430 -8.760

*

***

-0.021

***

*

4.410

-0.307

0.124

4.230

-0.023

***

-0.023

**

0.018

0.006

0.017

0.752

-0.202

-0.070

***

-6.490

*

*** **

-0.596 ***

-6.430

***

Journal Pre-proof 4.780

6

Parent country stock ( x1 0 ) 7

Venture country stock ( x1 0 )

-6.030

7.880

7.740

4.480

0.760

-1.140

-20.070

*

8.290

8.260

-10.310

-12.900

Industrial dummies

yes

yes

yes

yes

yes

yes

Year dummies

yes

yes

yes

yes

yes

yes

27.632

37.916

40.237

Within R2

0.248

0.303

0.309

Between R2

0.004

0.008

0.005

Overall R2

0.116

0.147

0.159

Log likelihood F values

7.15

***

7.24

***

LR  2

7.05

***

85.530 c

N=855



p  .10

*

p  .05

**

p  .01

***

***

p  .001 , Two-tailed t-tests.

54

104.330

***

108.970

***

Journal Pre-proof

Figure 2. Marginal effect of alliance experience depending on investment complexity (the dashed lines represent 95% confidence intervals).

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Journal Pre-proof

Figure 3. Marginal effect of investment intensity depending on investment complexity.

56