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How Venture Capital Firms Choose Syndication Partners: The Moderating Effects of Institutional Uncertainty and Investment Preference

Published online by Cambridge University Press:  27 July 2021

Lu Zheng Open the ORCID record for Lu Zheng [Opens in a new window] ,
Likun Cao ,
Jie Ren ,
Xibao Li ,
Ximing Yin Open the ORCID record for Ximing Yin [Opens in a new window]  and
Jin Chen
Lu Zheng
Affiliation:
Tsinghua University, China
Likun Cao
Affiliation:
University of Chicago, USA
Jie Ren*
Affiliation:
Tsinghua University, China
Xibao Li
Affiliation:
Tsinghua University, China
Ximing Yin
Affiliation:
Beijing Institute of Technology, China
Jin Chen
Affiliation:
Tsinghua University, China
*
Corresponding author: Jie Ren ([email protected])
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Abstract

This study investigates how venture capital firms (VCs) choose syndication partners. Exponential random graph models of Chinese VC syndication networks from 2006 to 2013 show that the homophily mechanism does not always determine VCs’ partner selection. In selecting partners, VCs have to strike a balance between reducing uncertainty and mobilizing heterogeneous resources. Therefore, decisions about partners depend on institutional uncertainty and VCs’ investment preferences. While VCs that focus on traditional business in an immature market are more likely to form homogeneous syndications, their peers that prefer to invest in innovative companies and that can rely on a stable market tend to syndicate with heterogeneous partners.

摘要

本研究关注风险投资公司如何选择联合投资伙伴。通过对中国风险投资公司从2006年到2013年的联合投资网络建立指数随机图模型，我们发现风险投资并不总是选择同质性的联合投资伙伴。在选择合作伙伴时，风险投资公司需要在减少不确定性和调动异质性资源之间寻找平衡。联合投资伙伴的选择取决于制度的不确定性和风险投资的投资偏好。制度不确定性高时，投资传统业务的风险投资更可能选择同质的联合投资伙伴，制度不确定性低时，倾向于投资创新企业的风险投资更可能选择异质的联合投资伙伴。

Аннотация

Это исследование изучает, как венчурные компании (ВК) выбирают партнеров для объединения в синдикаты. Методы экспоненциальных случайных графов для моделирования сетей синдикации китайских венчурных компаний в период с 2006 по 2013 годов показывают, что механизм гомогенности не всегда определяет выбор партнеров для венчурных компаний. При выборе партнеров венчурные компании должны соблюдать баланс между снижением степени неопределенности и мобилизацией разнообразных ресурсов. Следовательно, решения о выборе партнеров зависят от институциональной неопределенности и инвестиционных преференций венчурных компаний. В то время как венчурные компании, которые сосредоточены на традиционном бизнесе на незрелом рынке, с большей вероятностью образуют однородные синдикаты, их коллеги, которые предпочитают инвестировать в инновационные компании и могут полагаться на стабильный рынок, как правило, объединяются в синдикаты с разнородными партнерами.

Resumen

Este estudio investiga cómo las empresas de capital de riesgo (VCs por sus iniciales en inglés) eligen sus socios de sindicación. Los modelos grafos aleatorios de las redes de sindicación de empresas de capital de riesgo chinas entre el 2006 y el 2013 muestran que los mecanismos de homofilia no siempre determinan la selección de socios por parte de las empresas de capital de riesgo. En la selección de socios las empresas de capital de riesgo tienen que encontrar un equilibrio entre reducir la incertidumbre y la movilización de recursos heterogéneos. Mientras que las empresas de capital de riesgo que se enfocan en negocios tradicionales en un mercado inmaduro son más propensas a formar sindicaciones homogéneas, sus pares que prefieren invertir en compañías innovadoras y que pueden confiar en un mercado estable tienden a sindicarse con socios heterogéneos.

Keywords

exponential random graph modelshomophilyinstitutional uncertaintyinvestment preferenceVC syndications风险投资联合投资同质性异质性指数随机图模型投资偏好制度不确定性модели экспоненциальных случайных графовгетерофилиягомофилияинституциональная неопределенностьинвестиционные преференциисиндикаты венчурных компанийmodelos grafos aleatorios exponencialesheterofiliahomofiliaincertidumbre institucionalsindicación de empresas de capital de riesgo
Type
Article
Information
Management and Organization Review , Volume 18 , Issue 3 , June 2022 , pp. 463 - 490
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of The International Association for Chinese Management Research

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Footnotes

ACCEPTED BY Senior Editor Lin Cui

References

REFERENCES

Anderson, P. W. 1999. Perspective: Complexity theory and organization science. Organization Science, 10(3): 216–232.CrossRefGoogle Scholar
Andrevski, G., Brass, D. J., & Ferrier, W. J. 2016. Alliance portfolio configurations and competitive action frequency. Journal of Management, 42(4): 811–837.CrossRefGoogle Scholar
Barabási, A. L., & Albert, R. 1999. Emergence scaling in random networks. Science, 286(5439): 509–512.CrossRefGoogle ScholarPubMed
Batjargal, B. 2007. Network triads: Transitivity, referral and venture capital decisions in China and Russia. Journal of International Business Studies, 38(6): 998–1012.CrossRefGoogle Scholar
Beckman, C. M., Haunschild, P. R., & Phillips, D. J. 2004. Friends or strangers? Firm-specific uncertainty, market uncertainty and network partner selection. Organization Science, 15(3): 259–275.CrossRefGoogle Scholar
Brander, J. A., Amit, R., & Antweiler, W. 2002. Venture capital syndication: Improved venture selection vs. the value-added hypothesis. Journal of Economics & Management Strategy, 11(3): 423–452.CrossRefGoogle Scholar
Burt, R. S. 1992. Structural holes. Cambridge, MA: Harvard University Press.CrossRefGoogle Scholar
Burt, R. S. 2005. Brokerage and closure: An introduction to social capital. Oxford, UK: Oxford University Press.Google Scholar
Burt, R. S. 2010. Neighbor networks: Competitive advantage local and personal. Oxford, UK: Oxford University Press.Google Scholar
Burt, R. S., & Burzynska, K. 2017. Chinese entrepreneurs, social networks, and guanxi. Management and Organization Review, 13(2): 221–260.CrossRefGoogle Scholar
Bylund, P. L., & McCaffrey, M. 2017. A theory of entrepreneurship and institutional uncertainty. Journal of Business Venturing, 32(5): 461–475.CrossRefGoogle Scholar
Chen, C. C., Chen, X.-P., & Huang, S. 2013. Chinese guanxi: An integrative review and new directions for future research. Management and Organization Review, 9(1): 167–207.CrossRefGoogle Scholar
Chowdhury, E. A. M., Tarek, R., & Mohammad, I. A. 2019. Intellectual capital efficiency and organizational performance in the context of the pharmaceutical industry in Bangladesh. Journal of Intellectual Capital, 20(6): 784–806.CrossRefGoogle Scholar
Cox, P. E., 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): 266–76.Google Scholar
Cui, L., & Jiang, F. 2012. State ownership effect on firms’ FDI ownership decisions under institutional pressure: A study of Chinese outward-investing firms. Journal of International Business Studies, 43(3): 264–284.CrossRefGoogle Scholar
Dayan, M., & Benedetto, C. A. D. 2010. The impact of structural and contextual factors on trust formation in product development teams. Industrial Marketing Management, 39(4): 691–703.CrossRefGoogle Scholar
Du, Q. 2016. Birds of a feather or celebrating differences? The formation and impacts of venture capital syndication. Journal of Empirical Finance, 39(Part A): 1–14.CrossRefGoogle Scholar
Durkheim, E. 1933. The division of labor in society (1893). Simpson, George, trans. New York, NY: Macmillan.Google Scholar
Ely, R. J., & Thomas, D. A. 2001. Cultural diversity at work: The effects of diversity perspectives on work group processes and outcomes. Administrative Science Quarterly, 46(2): 229–273.CrossRefGoogle Scholar
Flynn, F. J., Chatman, J. A., & Spataro, S. E. 2001. Getting to know you: The influence of personality on impressions and performance of demographically different people in organizations. Administrative Science Quarterly, 46(3): 414–442.CrossRefGoogle Scholar
Gell-Mann, M. 1995. What is complexity? Complexity, 1: 1.Google Scholar
Granovetter, M. 1985. Economic action and social structure: The problem of embeddedness. American Journal of Sociology, 91(3): 481–510.CrossRefGoogle Scholar
Gulati, R. 1999. Network location and learning: The influence of network resources and firm capabilities on alliance formation. Strategic Management Journal, 20(5): 397–420.3.0.CO;2-K>CrossRefGoogle Scholar
Guo, D., & Jiang, K. 2013. Venture capital investment and the performance of entrepreneurial firms: Evidence from China. Journal of Corporate Finance, 22: 375–395.CrossRefGoogle Scholar
Han, Y., & Zheng, E. 2016. Why Chinese firms perform differently in corporate social responsibility? The persistence of organizational imprints among state-owned enterprises. Management and Organizations Review, 12(3): 605–629.CrossRefGoogle Scholar
Harris, J. K. 2013. An introduction to exponential random graph modeling. Thousand Oaks, CA: Sage Publications.Google Scholar
Harrison, D. A., Price, K. H., Gavin, J. H., & Florey, A. T. 2002. Time, teams and task performance: Changing effects of surface- and deep-level diversity on group functioning. Academy of Management Journal, 45(5): 1029–1045.CrossRefGoogle Scholar
Hearnshaw, E. J., & Wilson, M. M. 2013. A complex network approach to supply chain network theory. International Journal of Operations & Production Management, 33(4): 442–469.CrossRefGoogle Scholar
Hillman, A. J., Withers, M. C., & Collins, B. J. 2009. Resource dependence theory: A review. Journal of Management, 35(6): 1404–1427.CrossRefGoogle Scholar
Hochberg, Y. V., Ljungqvist, A., & Yang, L. U. 2007. Whom you know matters: Venture capital networks and investment performance. The Journal of Finance, 62(1): 251–301.CrossRefGoogle Scholar
Hochberg, Y. V., Ljungqvist, A., & Yang, L. U. 2010. Networking as a barrier to entry and the competitive supply of venture capital. The Journal of Finance, 65(3): 829–859.CrossRefGoogle Scholar
Hunter, D. R., Handcock, M. S., Butts, C. T., Goodreau, S. M., & Morris, M. 2008. ERGM: A package to fit, simulate and diagnose exponential-family models for networks. Journal of Statistical Software, 24(3): nihpa54860.CrossRefGoogle ScholarPubMed
Kozlowski, A. C., Taddy, M., & Evans, J. A. 2019. The geometry of culture: Analyzing the meanings of class through word embeddings. American Sociological Review, 84(5): 905–949.CrossRefGoogle Scholar
Lee, R., & Wellman, B. 2012. Networked: The new social operating system. Boston, MA: MIT Press.Google Scholar
Lerner, J. 1994. The syndication of venture capital investments. Financial Management, 23(3): 16–27.CrossRefGoogle Scholar
Lerner, J., Leamon, A., & Hardymon, G. F. 2012. Venture capital, private equity and the financing of entrepreneurship. Hoboken, NJ: John Wiley & Sons.Google Scholar
Lin, L. 2020. Contractual innovation in China's venture capital market. European Business Organization Law Review, 21(1): 101–138.CrossRefGoogle Scholar
Lin, N., Ensel, W. M., & Vaughn, J. C. 1981. Social resources and strength of ties–structural factors in occupational–status attainment. American Sociological Review, 46(4): 393–403.CrossRefGoogle Scholar
Lorenz, E. N. 1963. Deterministic nonperiodic flow. Journal of the Atmospheric Sciences, 20(2): 130–141.2.0.CO;2>CrossRefGoogle Scholar
Luo, J., Rong, K., Yang, K., Guo, R., & Zou, Y. 2019. Syndication through social embeddedness: A comparison of foreign, private and state-owned venture capital firms. Asia Pacific Journal of Management, 36(2): 499–527.CrossRefGoogle Scholar
Lusher, D., Koskinen, J., & Robins, G. 2013. Exponential random graph models for social networks: Theory, methods, and applications. New York, NY: Cambridge University Press.Google Scholar
McPherson, M., Smith-Lovin, L., & Cook, J. M. 2001. Birds of a feather: Homophily in social networks. Annual Review of Sociology, 27(1): 415–444.CrossRefGoogle Scholar
Meyer, K. E. 2015. Context in management research in emerging economies. Management and Organization Review, 11(3): 369–377.CrossRefGoogle Scholar
Meyer, J. W., & Rowan, B. 1977. Institutionalized organizations: Formal structure as myth and ceremony. American Journal of Sociology, 83(2): 340–363.CrossRefGoogle Scholar
Murrell, P. 2005. Institutions and firms in transition economies. New York, NY: Springer US.CrossRefGoogle Scholar
Opper, S., & Nee, V. 2015. Network effects, cooperation, and entrepreneurial innovation in China. Asian Business & Management, 14(4): 283–302.CrossRefGoogle Scholar
Pathak, S. D., Day, J. M., Nair, A., Sawaya, W. J., & Kristal, M. M. 2007. Complexity and adaptivity in supply networks: Building supply network theory using a complex adaptive systems perspective. Decision Sciences, 38(4): 547–580.CrossRefGoogle Scholar
Perera, S., Bell, M. G., & Bliemer, M. C. 2018. Network science approach to modelling emergence and topological robustness of supply networks: A review and perspective. Applied Network Science, 2(33): ArXiv, abs/1803.09913.Google Scholar
Petkova, A., Wadhwa, A., Yao, X., & Jain, S. 2013. Reputation and decision making under ambiguity: A study of U.S. venture capital firms’ investments in the emerging clean energy sector. Academy of Management Journal, 57(2): 422–448.CrossRefGoogle Scholar
Podolny, J. M. 1994. Market uncertainty and the social character of economic exchange. Administrative Science Quarterly, 39(3): 458–483.CrossRefGoogle Scholar
Podolny, J. M. 2001. Networks as the pipes and prisms of the market. American Journal of Sociology, 107(1): 33–60.CrossRefGoogle Scholar
Popli, M., & Ladkani, R. M. 2020. Value constraining or value enabling? The impact of business group affiliation on post-acquisition performance by emerging market firms. Management and Organization Review, 16(2): 261–291.CrossRefGoogle Scholar
Powell, W. W., Packalen, K., & Whittington, K. 2012. Organizational and institutional genesis: The emergence of high-Tech clusters in the life sciences. In Padgett, J. F. & Powell, W. W. (Eds.), The emergence of organizations and markets: 379. Princeton, NJ: Princeton University Press.Google Scholar
Powell, W. W., White, D. R., Koput, K. W., & Owen-Smith, J. 2005. Network dynamics and field evolution: The growth of inter-organizational collaboration in the life sciences. American Journal of Sociology, 110(4): 1132–1205.CrossRefGoogle Scholar
Ring, P. S., & van de Ven, A. H. 1994. Developmental processes of cooperative inter-organizational relationships. Academy of Management Review, 19(1): 90–118.CrossRefGoogle Scholar
Robins, G., Pattison, P., Kalish, Y., & Lusher, D. 2007. An introduction to exponential random graph (p*) models for social networks. Social Networks, 29(2): 173–191.CrossRefGoogle Scholar
Robson, M. J., Katsikeas, C. S., & Bello, D. C. 2008. Drivers and performance outcomes of trust in international strategic alliances: The role of organizational complexity. Organization Science, 19(4): 647–665.CrossRefGoogle Scholar
Schumpeter, J. A. 1934. The theory of economic development. New York, NY: Springer US.Google Scholar
Shi, F., Teplitskiy, M., Duede, E. M., & Evans, J. A. 2019. The wisdom of polarized crowds. Nature Human Behavior, 3: 329–336.CrossRefGoogle ScholarPubMed
Snijders, T. A. B. 2017. Stochastic actor-oriented models for network dynamics. Annual Review of Statistics and Its Application, 4: 343–363.CrossRefGoogle Scholar
Snijders, T. A. B., Pattison, P. E., Robins, G. L., & Handcock, M. S. 2010. New specifications for exponential random graph models. Sociological Methodology, 36(1): 99–153.CrossRefGoogle Scholar
Sorenson, O., & Stuart, T. E. 1999. Syndication networks and the spatial distribution of venture capital investments. American Journal of Sociology, 106(6): 1546–1588.CrossRefGoogle Scholar
Sorenson, O., & Stuart, T. E. 2008. Bringing the context back in: Settings and the search for syndicate partners in venture capital investment networks. Administrative Science Quarterly, 53(2): 266–294.CrossRefGoogle Scholar
Stark, D. 2009. The sense of dissonance. Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar
Steen, E. V. D. 2010. Culture clash: The costs and benefits of homogeneity. Management Science, 56(10): 1718–1738.CrossRefGoogle Scholar
Swidler, A. 1986. Culture in action: Symbols and strategies. American Sociological Review, 51(2): 273–286.CrossRefGoogle Scholar
Ter Wal, A. L. J., Oliver, A., Jörn, B., & Sandner, P. G. 2016. The best of both worlds: The benefits of open-specialized and closed-diverse syndication networks for new ventures’ success. Administrative Science Quarterly, 61(3): 393–432.CrossRefGoogle ScholarPubMed
Thurner, S., Peter, Klimek., & Hanel, R. 2018. Introduction to the theory of complex systems. Oxford, UK: Oxford University PressCrossRefGoogle Scholar
Wang, X., Fan, G., & Yu, J. 2017. NERI index of marketization of Chinas’ provinces 2016 report (Chinese edition). Beijing, China: Social Sciences Academic Press.Google Scholar
Wang, X., Fan., G., & Zhu, H. 2007. Marketization in China: Progress and contribution to growth. In Garnaut, R. & Song, L. (Eds.), China: Linking markets for growth: 30–44. Canberra: ANU E Press.Google Scholar
Yang, S., Keller, F., & Zheng, L. 2017. Social network analysis: Methods and examples. Thousand Oaks, CA: Sage Publication Inc.CrossRefGoogle Scholar
Zhang, L., Gupta, A. K., & Hallen, B. L. 2017. The conditional importance of prior ties: A group-level analysis of venture capital syndication. Academy of Management Journal, 60(4): 1360–1386.CrossRefGoogle Scholar
Zhelyazkov, P. I., & Gulati, R. 2016. After the break-up: The relational and reputational consequences of withdrawals from venture capital syndicates. Academy of Management Journal, 59(1): 277–301.CrossRefGoogle Scholar
Zheng, L., Cao, L., Ren, J. 2019. Venture capital background and high-tech firms' long-term success: evidence from survival analysis. Journal of Hehai University, 21(01): 51–60+106.Google Scholar