Skip to main content
SpringerLink
Log in

Community-level characteristics and member firms’ invention: evidence from university–industry innovation community in China

  • Published:
Scientometrics Aims and scope Submit manuscript

Abstract

Increased attention has been drawn to the phenomenon of community-based innovation; however, researchers have mainly emphasized firm-centric communities, paying little attention to non-firm members. This study focuses on university–industry (U–I) innovation communities to address this gap. Using China’s joint patent application data from 2000 to 2017, we construct a U–I collaboration network, identified existing U–I innovation communities, and reveal community-level characteristics of birth, expansion, maturity, and self-renewal in a lifecycle framework. The results suggest that average geographical distance negatively affects firm invention production and within-community knowledge diversity positively affects firm innovation. The effects of dynamic attributes indicate that U–I community membership turnover affects member firm’s patent production in an inverse U-shaped manner. In addition, a firm’s within-community network position exerts a moderating effect on the relation between community membership dynamics and firm innovation. In theoretical terms, this study combines innovation community and social network theories, using a lifecycle framework to examine the influence of the specified characteristics in facilitating member firms’ invention productivity. Finally, this study discusses the practical implications for U–I community stakeholders and policymakers.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Adner, R., & Kapoor, R. (2016). Innovation ecosystems and the pace of substitution: Re-examining technology S-curves. Strategic Management Journal, 37(4), 625–648.

    Article  Google Scholar 

  • Agrawal, A. K. (2001). University-to-industry knowledge transfer: Literature review and unanswered questions. International Journal of Management Reviews, 3(4), 285–302.

    Article  Google Scholar 

  • Ahuja, G. (2000). Collaboration networks, structural holes, and innovation: A longitudinal study. Administrative Science Quarterly, 45(3), 425–455.

    Article  Google Scholar 

  • Aktamov, S., & Zhao, Y. (2014). Impact of network centrality positions on innovation performance of the firm: Evidence from China automobile industry. Business Management and Strategy, 5(1), 164–178.

    Article  Google Scholar 

  • Belderbos, R., Carree, M., Lokshin, B., & Sastre, J. F. (2015). Inter-temporal patterns of R&D collaboration and innovative performance. The Journal of Technology Transfer, 40(1), 123–137.

    Article  Google Scholar 

  • Bell, G. G. (2005). Clusters, networks, and firm innovativeness. Strategic Management Journal, 26(3), 287–295.

    Article  Google Scholar 

  • Blondel, V. D., Guillaume, J.-L., Lambiotte, R., & Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008(10), P10008.

    Article  MATH  Google Scholar 

  • Bommert, B. (2010). Collaborative innovation in the public sector. International Public Management Review, 11(1), 15–33.

    Google Scholar 

  • Boschma, R. A. (2005). Proximity and innovation: A critical assessment. Regional Studies, 39(1), 61–74.

    Article  Google Scholar 

  • Bramwell, A., Hepburn, N., & Wolfe, D. A. (2012). Growing innovation ecosystems: University-industry knowledge transfer and regional economic development in Canada. University of Toronto.

    Google Scholar 

  • Bruyaka, O., & Durand, R. (2012). Sell-off or shut-down? Alliance portfolio diversity and two types of high-tech firms exit. Strategic Organization, 10(1), 7–30.

    Article  Google Scholar 

  • Catalini, C., Fons-Rosen, C., & Gaule, P. (2020). How do travel costs shape collaboration? Management Science, 66(8), 3340–3360.

    Article  Google Scholar 

  • Chen, C.-J., Lin, B.-W., Lin, J.-Y., & Hsiao, Y.-C. (2018). Technological diversity, knowledge flow and capacity, and industrial innovation. Technology Analysis and Strategic Management, 30(12), 1365–1377.

    Article  Google Scholar 

  • Chen, D.-N., & Liang, T.-P. (2016). Knowledge diversity and firm performance: An ecological view. Journal of Knowledge Management, 20(4), 671–686.

    Article  Google Scholar 

  • Clarysse, B., Wright, M., Bruneel, J., & Mahajan, A. (2014). Creating value in ecosystems: Crossing the chasm between knowledge and business ecosystems. Research Policy, 43(7), 1164–1176.

    Article  Google Scholar 

  • Dahl, A., Lawrence, J., & Pierce, J. (2011). Building an innovation community. Research-Technology Management, 54(5), 19–27.

    Article  Google Scholar 

  • Dahlander, L., & Frederiksen, L. (2012). The core and cosmopolitans: A relational view of innovation in user communities. Organization Science, 23(4), 988–1007.

    Article  Google Scholar 

  • de Vasconcelos Gomes, L. A., Facin, A. L. F., Salerno, M. S., & Ikenami, R. K. (2018). Unpacking the innovation ecosystem construct: Evolution, gaps and trends. Technological Forecasting and Social Change, 136, 30–48.

    Article  Google Scholar 

  • Dedehayir, O., Makinen, S. J., & Ortt, J. R. (2018). Roles during innovation ecosystem genesis: A literature review. Technological Forecasting and Social Change, 136, 18–29.

    Article  Google Scholar 

  • Dhanaraj, C., & Parkhe, A. (2006). Orchestrating innovation networks. Academy of Management Review, 31(3), 659–669.

    Article  Google Scholar 

  • Drivas, K., & Economidou, C. (2015). Is geographic nearness important for trading ideas? Evidence from the us. The Journal of Technology Transfer, 40(4), 629–662.

    Article  Google Scholar 

  • Gloor, P. A. (2006). Swarm creativity: Competitive advantage through collaborative innovation networks. Oxford University Press.

    Book  Google Scholar 

  • Goerzen, A., & Beamish, P. W. (2005). The effect of alliance network diversity on multinational enterprise performance. Strategic Management Journal, 26(4), 333–354.

    Article  Google Scholar 

  • Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology, 78(6), 1360–1380.

    Article  Google Scholar 

  • Granstrand, O. (1998). Towards a theory of the technology-based firm. Research Policy, 27(5), 465–489.

    Article  Google Scholar 

  • Greve, H. R., Baum, J. A., Mitsuhashi, H., & Rowley, T. J. (2010). Built to last but falling apart: Cohesion, friction, and withdrawal from interfirm alliances. Academy of Management Journal, 53(2), 302–322.

    Article  Google Scholar 

  • Guan, J., & Zhao, Q. (2013). The impact of university-industry collaboration networks on innovation in nano-biopharmaceuticals. Technological Forecasting and Social Change, 80(7), 1271–1286.

    Article  Google 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.

    Article  Google Scholar 

  • Gulati, R., & Gargiulo, M. (1999). Where do interorganizational networks come from? American Journal of Sociology, 104(5), 1439–1493.

    Article  Google Scholar 

  • Gulati, R., Puranam, P., & Tushman, M. (2012). Meta-organization design: Rethinking design in interorganizational and community contexts. Strategic Management Journal, 33(6), 571–586.

    Article  Google Scholar 

  • Hausman, J., & Griliches, H. Z. (1984). Econometric models for count data with an application to the patents - R&D relationship. Econometrica, 52(4), 909–938.

    Article  Google Scholar 

  • Hervas-Oliver, J. L., Sempere-Ripoll, F., & Boronat-Moll, C. (2021). Technological innovation typologies and open innovation in SMEs: Beyond internal and external sources of knowledge. Technological Forecasting and Social Change, 162, 120338.

    Article  Google Scholar 

  • Hong, W., & Su, Y.-S. (2013). The effect of institutional proximity in non-local university-industry collaborations: An analysis based on Chinese patent data. Research Policy, 42(2), 454–464.

    Article  Google Scholar 

  • Huggins, R., & Prokop, D. (2017). Network structure and regional innovation: A study of university-industry ties. Urban Studies, 54(4), 931–952.

    Article  Google Scholar 

  • Jensen, P. H., Palangkaraya, A., & Webster, E. (2015). Trust and the market for technology. Research Policy, 44(2), 340–356.

    Article  Google Scholar 

  • Laursen, K., Reichstein, T., & Salter, A. (2011). Exploring the effect of geographical proximity and university quality on university-industry collaboration in the United Kingdom. Regional Studies, 45(4), 507–523.

    Article  Google Scholar 

  • Laursen, K., & Salter, A. (2006). Open for innovation: The role of openness in explaining innovation performance among UK manufacturing firms. Strategic Management Journal, 27(2), 131–150.

    Article  Google Scholar 

  • Lin, B.-W., & Chen, J.-S. (2005). Corporate technology portfolios and R&D performance measures: A study of technology intensive firms. R&D Management, 35(2), 157–170.

    Article  Google Scholar 

  • Lin, Y., & Wu, L.-Y. (2014). Exploring the role of dynamic capabilities in firm performance under the resource-based view framework. Journal of Business Research, 67(3), 407–413.

    Article  Google Scholar 

  • Lynn, L. H., Reddy, N. M., & Aram, J. D. (1996). Linking technology and institutions: The innovation community framework. Research Policy, 25(1), 91–106.

    Article  Google Scholar 

  • Moore, J. F. (1993). Predators and prey: A new ecology of competition. Harvard Business Review, 71(3), 75–86.

    Google Scholar 

  • Newman, M. E. (2004). Fast algorithm for detecting community structure in networks. Physical Review E, 69(6), 066133.

    Article  Google Scholar 

  • Newman, M. E., & Girvan, M. (2004). Finding and evaluating community structure in networks. Physical Review E, 69(2), 026113.

    Article  Google Scholar 

  • Paci, R., & Usai, S. (2000). Technological enclaves and industrial districts: An analysis of the regional distribution of innovative activity in Europe. Regional Studies, 34(2), 97–114.

    Article  Google Scholar 

  • Park, H., Ree, J. J., & Kim, K. (2013). Identification of promising patents for technology transfers using TRIZ evolution trends. Expert Systems with Applications, 40(2), 736–743.

    Article  Google Scholar 

  • Petruzzelli, A. M. (2011). The impact of technological relatedness, prior ties, and geographical distance on university-industry collaborations: A joint-patent analysis. Technovation, 31(7), 309–319.

    Article  Google Scholar 

  • Ponds, R., Van Oort, F., & Frenken, K. (2007). The geographical and institutional proximity of research collaboration. Papers in Regional Science, 86(3), 423–443.

    Article  Google Scholar 

  • Protogerou, A., Caloghirou, Y., & Lioukas, S. (2012). Dynamic capabilities and their indirect impact on firm performance. Industrial and Corporate Change, 21(3), 615–647.

    Article  Google Scholar 

  • Reagans, R., & Zuckerman, E. W. (2001). Networks, diversity, and productivity: The social capital of corporate R&D teams. Organization Science, 12(4), 502–517.

    Article  Google Scholar 

  • Rodan, S., & Galunic, C. (2004). More than network structure: How knowledge heterogeneity influences managerial performance and innovativeness. Strategic Management Journal, 25(6), 541–562.

    Article  Google Scholar 

  • Rohrbeck, R., Holzle, K., & Gemunden, H. G. (2009). Opening up for competitive advantage—How Deutsche Telekom creates an open innovation ecosystem. R&D Management, 39(4), 420–430.

    Article  Google Scholar 

  • Schilling, M. A., & Phelps, C. C. (2007). Interfirm collaboration networks: The impact of large-scale network structure on firm innovation. Management Science, 53(7), 1113–1126.

    Article  MATH  Google Scholar 

  • Srivastava, M. K., Gnyawali, D. R., & Hatfield, D. E. (2015). Behavioral implications of absorptive capacity: The role of technological effort and technological capability in leveraging alliance network technological resources. Technological Forecasting and Social Change, 92, 346–358.

    Article  Google Scholar 

  • Su, Y.-S., Zheng, Z.-X., & Chen, J. (2018). A multi-platform collaboration innovation ecosystem: The case of China. Management Decision, 56(1), 125–142.

    Article  Google Scholar 

  • Sytch, M., & Tatarynowicz, A. (2014). Exploring the locus of invention: The dynamics of network communities and firms’ invention productivity. Academy of Management Journal, 57(1), 249–279.

    Article  Google Scholar 

  • Sytch, M., Tatarynowicz, A., & Gulati, R. (2012). Toward a theory of extended contact: The incentives and opportunities for bridging across network communities. Organization Science, 23(6), 1658–1681.

    Article  Google Scholar 

  • Torre, A., & Rallet, A. (2005). Proximity and localization. Regional Studies, 39(1), 47–59.

    Article  Google Scholar 

  • Wang, C., Rodan, S., Fruin, M., & Xu, X. (2014). Knowledge networks, collaboration networks, and exploratory innovation. Academy of Management Journal, 57(2), 484–514.

    Article  Google Scholar 

  • Wang, J., & Yang, N. (2019). Dynamics of collaboration network community and exploratory innovation: The moderation of knowledge networks. Scientometrics, 121(2), 1067–1084.

    Article  Google Scholar 

  • Wei, L., & Dang, X. (2017). Study on the emergence of technological innovation network community structure and effect on ambidexterity innovation in asymmetric perspective. Operations Research and Management Science, 26(10), 188–199.

    Google Scholar 

  • West, J., & Lakhani, K. R. (2008). Getting clear about communities in open innovation. Industry and Innovation, 15(2), 223–231.

    Article  Google Scholar 

  • Ye, Y., De Moortel, K., & Crispeels, T. (2020). Network dynamics of Chinese university knowledge transfer. The Journal of Technology Transfer, 45, 1228–1254.

    Article  Google Scholar 

  • Yeniyurt, S., & Carnovale, S. (2017). Global supply network embeddedness and power: An analysis of international joint venture formations. International Business Review, 26(2), 203–213.

    Article  Google Scholar 

  • Yu, G. J., & Lee, J. (2017). When should a firm collaborate with research organizations for innovation performance? The moderating role of innovation orientation, size, and age. The Journal of Technology Transfer, 42(6), 1451–1465.

    Article  Google Scholar 

  • Zahra, S. A., & Nambisan, S. (2011). Entrepreneurship in global innovation ecosystems. AMS Review, 1(4), 4–17.

    Article  Google Scholar 

  • Zhang, S., Zhang, N., Zhu, S., & Liu, F. (2020). A foot in two camps or your undivided attention? The impact of intra-and inter-community collaboration on firm innovation performance. Technology Analysis and Strategic Management, 32, 753–768.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Statistics and Mathematics, Central University of Finance and Economics, Beijing, China

    Wenjing Wang

  2. School of Government, Central University of Finance and Economics, Beijing, China

    Yiwei Liu

Authors
  1. Wenjing Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yiwei Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yiwei Liu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, W., Liu, Y. Community-level characteristics and member firms’ invention: evidence from university–industry innovation community in China. Scientometrics 126, 8913–8934 (2021). https://doi.org/10.1007/s11192-021-04157-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-021-04157-w

Keywords

Search

Navigation