Search Frictions, Ownership Relations, and Innovation Collaboration:An Analysis Based on Selection Mechanism
LIU Bocong, XU Wan, LI Lei
School of Economics, Nankai University; Institute of New Structural Economics, Peking University; Center for Transnationals' Studies / The Laboratory for Economic Behaviors and Policy Simulation, Nankai University
Summary:
As a critical component of the innovation system, collaborative innovation serves as a common approach to improving innovation efficiency and driving economic growth. However, this topic has received relatively limited attention in the academic literature. This study develops a two-sided random search-and-matching model with firm heterogeneity to examine the determinants of innovation-output quality and partner selection in collaborative R&D, focusing on search frictions and equity linkages. Based on the model, three hypotheses are proposed. First, due to the presence of search frictions, the “productivity threshold” required for an innovating firm to collaborate with a non-equity-affiliated firm is higher than that for collaborating with an equity-affiliated partner. This selection mechanism implies that although innovating firms engage in a larger number of collaborative R&D projects with equity-affiliated firms, the innovation outcomes generated from collaborations with non-equity-affiliated partners tend to be of higher quality. Second, regardless of whether the partner is equity-affiliated, innovating firms consistently select collaborators with similar innovation capabilities. Third, innovating firms prefer non-equity-affiliated partners of comparable firm size, whereas firm size does not influence partner choice when collaboration occurs within equity-affiliated relationships. Empirically, the study tests these hypotheses using collaborative patent data from Chinese industrial enterprises. Equity affiliations are identified via the “relationship mapping” function of Qichacha (a Chinese enterprise information platform); firms' innovation capabilities are measured by their patent application counts in the collaboration field; and firm size is proxied by the percentile rank of their main business revenue within the industry. The empirical results strongly support the theoretical predictions concerning the role of search frictions in shaping partner selection and collaborative outcomes. Furthermore, the analysis extends the research framework by examining the economic consequences of collaborative innovation from the perspective of firms' operational decisions. The findings reveal that collaborative R&D generates substantial knowledge spillovers, guiding firms' subsequent innovation trajectories toward the technological fields associated with their joint patents. At the same time, collaborative innovation enhances firms' innovation performance, production efficiency, and operating outcomes. After participating in collaborative projects, firms exhibit higher total patent application counts, increased total factor productivity, and larger main business revenue compared with independent-innovation firms in the control group. Finally, the paper investigates the sources of post-collaboration growth in firms' patenting activities. The results show that the improvement in innovation performance is primarily driven by an increase in jointly filed patents, while the number of independently filed patents declines. This pattern is particularly pronounced in collaborations with equity-affiliated firms. The potential contributions of this study are as follows. From a research perspective, this paper is the first to introduce the concept of equity affiliation into the analysis of inter-firm patent collaboration. By integrating a theoretical model with empirical evidence, it offers an in-depth examination of search-matching patterns in collaborative innovation, the quality of collaborative outcomes, and the extent to which such collaborations achieve the social optimum. Regarding the theoretical model, this paper embeds equity affiliation into a random search-and-matching framework and demonstrates how such affiliations generate heterogeneous sorting patterns across firms with respect to technological accumulation and firm size. The model further shows that these observed collaboration patterns are endogenously driven by firms' bargaining power and search costs, thereby offering a novel theoretical explanation for the differential probabilities of collaboration and heterogeneous quality of innovation outcomes between equity-affiliated and non-affiliated firms. Empirically, this study is the first to investigate, using Chinese micro-level enterprise data, how participation in collaborative innovation projects influences firms' subsequent innovation trajectories and overall performance. It also innovatively measures knowledge spillovers arising from collaboration by analyzing patent abstract texts. This approach provides stronger and more credible empirical evidence on whether collaborative innovation truly generates knowledge spillovers that enhance firms' innovative capabilities, thereby deepening our understanding of the strategic importance of collaboration in corporate innovation and business operations.
[1]李俊青、袁博和张雪莹,2025,《中国上市企业股权网络结构与技术创新——基于风险分担与风险传染的视角》,《金融研究》第8期,第151~168页。 [2]刘慧龙、苗小雨和王一飞,2025《共同机构持股的创新信息扩散效应》,《金融研究》第6期,第171~188页。 [3]龙小宁、刘灵子和张靖,2023,《企业合作研发模式对创新质量的影响——基于中国专利数据的实证研究》,《中国工业经济》第10期,第174~192页。 [4]孙天阳和成丽红,2020,《协同创新网络与企业出口绩效——基于社会网络和企业异质性的研究》,《金融研究》第3期,第96~114页。 [5]Allen, T. 2014. “Information Frictions in Trade”, Econometrica, 82(6): pp.2041~2083. [6]Asgari, N., K. Singh, and W. Mitchell. 2017. “Alliance Portfolio Reconfiguration Following a Technological Discontinuity: Alliance Portfolio Reconfiguration and Discontinuities”, Strategic Management Journal, 38(5): pp.1062~1081. [7]Becker, G.S. and K.M. Murphy. 1992. “The Division of Labor, Coordination Costs, and Knowledge”, The Quarterly Journal of Economics, 107(4): pp.1137~1160. [8]Belderbos, R., B. Cassiman, D. Faems, B. Leten, and B.V. Looy. 2014. “Co-Ownership of Intellectual Property: Exploring the Value-Appropriation and Value-Creation Implications of Co-Patenting with Different Partners”, Research Policy, 43(5): pp.841~852. [9]Bloom, N., L. Garicano, R. Sadun, and J. Van Reenen. 2014. “The Distinct Effects of Information Technology and Communication Technology on Firm Organization”, Management Science, 60(12): pp.2859~2885. [10]Bonneton, N. and C. Sandmann. 2025. “Non-Stationary Search and Assortative Matching”,Econometrica, 93(5): pp.1635~1662. [11]Boudreau, K.J., T. Brady, I. Ganguli, P. Gaule, E. Guinan, A. Hollenberg, and K.R. Lakhani. 2017. “A Field Experiment on Search Costs and the Formation of Scientific Collaborations”, The Review of Economics and Statistics, 99(4): pp.565~576. [12]Burdett, K. and M.G. Coles. 1997. “Marriage and Class”, The Quarterly Journal of Economics, 112(1): pp.141~168. [13]Cassiman, B. and R. Veugelers. 2002. “R&D Cooperation and Spillovers: Some Empirical Evidence from Belgium”, American Economic Review, 92(4): pp.1169~1184. [14]Castellani, D., A. Perri, and V.G. Scalera. 2022. “Knowledge Integration in Multinational Enterprises: The Role of Inventors Crossing National and Organizational Boundaries”, Journal of World Business, 57(3): pp.101290. [15]De Faria, P., F. Lima, and R. Santos. 2010. “Cooperation in Innovation Activities: The Importance of Partners”, Research Policy, 39(8): pp.1082~1092. [16]Diamond, P.A. 1971. “A Model of Price Adjustment”, Journal of Economic Theory, 3(2): p.156~168. [17]Diamond, P.A. 1982. “Wage Determination and Efficiency in Search Equilibrium”, The Review of Economic Studies, 49(2): pp.217~227. [18]Eaton, J., D. Jinkins, J.R. Tybout, and D. Xu, 2022. “Two-Sided Search in International Markets”, NBER Working Paper, No.29684. [19]Eeckhout, J. and P. Kircher. 2010. “Sorting and Decentralized Price Competition”, Econometrica, 78(2): pp.539~574. [20]Granovetter, M. 1985. “Economic Action and Social Structure: The Problem of Embeddedness”, American Journal of Sociology, 91(3): pp.481~510. [21]Gulati, R. and M. Gargiulo. 1999. “Where Do Interorganizational Networks Come From?”, American Journal of Sociology, 104(5): pp.1439~1493. [22]Hagedoorn, J., A.N. Link, and N.S. Vonortas. 2000. “Research Partnerships”, Research Policy, 29(4~5): pp.567~586. [23]Hall, B.H., A.B. Jaffe, and M. Trajtenberg. 2001. “The NBER Patent Citation Data File: Lessons, Insights and Methodological Tools”, NBER Working Paper, No.8498. [24]Howell, S.T. 2020. “Reducing Information Frictions in Venture Capital: The Role of New Venture Competitions”, Journal of Financial Economics, 136(3): pp.676~694. [25]Jajja, M.S.S., V.R. Kannan, S.A. Brah, and S.Z. Hassan. 2017. “Linkages between Firm Innovation Strategy, Suppliers, Product Innovation, and Business Performance: Insights from Resource Dependence Theory”, International Journal of Operations & Production Management, 37(8): pp.1054~1075. [26]Kamien, M.I., E. Muller, and I. Zang. 1992. “Research Joint Ventures and R&D Cartels”, The American Economic Review, 82(5): pp.1293~1306. [27]Lavie, D. 2007. “Alliance Portfolios and Firm Performance: A Study of Value Creation and Appropriation in the U.S. Software Industry”, Strategic Management Journal, 28(12): pp.1187~1212. [28]Li, D., L. Eden, M.A. Hitt, and R.D. Ireland. 2008. “Friends, Acquaintances, or Strangers? Partner Selection in R&D Alliances”, Academy of Management Journal, 51(2): pp.315~334. [29]Li, D., Z. Yang, P. Ma, and H. Chen. 2022. “Cooperation and Competition among Subsidiaries in a Business Group: Their Impacts on Innovation”, Management Decision, 60(6): pp.1662~1682. [30]McCall, J.J. 1970. “Economics of Information and Job Search”, The Quarterly Journal of Economics, 84(1): pp.113~126. [31]Mellewigt, T., A. Thomas, I. Weller, and E.J. Zajac. 2017. “Alliance or Acquisition? A Mechanisms‐Based, Policy‐Capturing Analysis”, Strategic Management Journal, 38(12): pp.2353~2369. [32]Mortensen, D.T. 1982. “Property Rights and Efficiency in Mating, Racing, and Related Game”, The American Economic Review, 72(5): pp.968~979. [33]Oxley, J.E. 1997. “Appropriability Hazards and Governance in Strategic Alliances: A Transaction Cost Approach”, The Journal of Law, Economics, and Organization, 13(2): pp.387~409. [34]Ozdemir, S., J. Carlos Fernandez de Arroyabe, V. Sena, and S. Gupta. 2023. “Stakeholder Diversity and Collaborative Innovation: Integrating the Resource-Based View with Stakeholder Theory”, Journal of Business Research, 164: p.113955. [35]Reuer, J.J. and R. Ragozzino. 2011. “The Choice between Joint Ventures and Acquisitions: Insights from Signaling Theory”, Organization Science, 23(4): pp.1175~1190. [36]Schilke, O. and A. Goerzen. 2010. “Alliance Management Capability: An Investigation of the Construct and Its Measurement”, Journal of Management, 36(5): pp.1192~1219. [37]Shi, S. 2001. “Frictional Assignment. I. Efficiency”, Journal of Economic Theory, 98(2): pp.232~260. [38]Shi, S. 2005. “Frictional Assignment, Part II: Infinite Horizon and Inequality”, Review of Economic Dynamics, 8(1): pp.106~137. [39]Shimer, R. 2005. “The Assignment of Workers to Jobs in an Economy with Coordination Frictions”, Journal of Political Economy, 113(5): pp.996~1025. [40]Shimer, R. and L. Smith. 2000. “Assortative Matching and Search”, Econometrica, 68(2): pp.343~369. [41]Stigler, G.J. 1961. “The Economics of Information”, Journal of Political Economy, 69(3): pp.213~225. [42]Su, J., F. Zhang, D. Wang, S. Sindakis, Y. Xiao, and E. Herrera-Viedma. 2023. “Examining the Influence of Knowledge Spillover on Partner Selection in Knowledge Alliances: The Role of Benefit Distribution”, Computers & Industrial Engineering, 180: pp.109245. [43]Xu, S., F. Wu, and E. Cavusgil. 2013. “Complements or Substitutes? Internal Technological Strength, Competitor Alliance Participation, and Innovation Development”, Journal of Product Innovation Management, 30(4): pp.750~762.