Skip to main content
SpringerLink
Log in

Exploring new knowledge through research collaboration: the moderation of the global and local cohesion of knowledge networks

  • Published:
The Journal of Technology Transfer Aims and scope Submit manuscript

Abstract

Research collaboration has long been suggested as an effective way to obtain innovative outcomes. Nevertheless, relatively little is known about whether and how different research collaboration strategies inspire or inhibit firms in the exploration of new knowledge. Drawing upon the research collaboration literature and social network theory, this study examines the effects of two specific collaboration strategies (i.e., collaborating widely and collaborating deeply) on new knowledge exploration by recognizing the moderating roles of the local and global cohesion of knowledge networks. We test our hypotheses by using a manually collected sample of 730 Chinese vehicle or parts manufacturers during the period between 1985 and 2011. The empirical results suggest the positive effects of research collaboration breadth and collaboration depth on new knowledge exploration and that the global cohesion of intra-organizational knowledge networks magnifies the effect of collaboration breadth, while local cohesion negatively moderates the effect of collaboration depth on new knowledge exploration. These findings jointly indicate that a research collaboration strategy in combination with the structure of a knowledge base is crucial for obtaining novel knowledge.

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

Similar content being viewed by others

Notes

  1. For instance, as Powell, Koput and Smith-Doerr (1996) noted, “obtaining access to new markets and technologies, pooling complementary skills, risk sharing, speeding products to market” are four of the main benefits of firm involvement in collaboration.

  2. As is shown in the Methodology section, we measured the independent variables in the former period (from 1985 through 2006), and we measured the dependent variable in the latter period (from 2007 through 2011).

  3. The three inter-temporal patterns are persistent collaboration, recently formed collaboration, and recently discontinued collaboration.

  4. Some recent studies focused on the sector level knowledge networks (e.g. Guan and Liu 2016).

  5. The ten industries are the automotive, steel, information and communication, logistics, textile, equipment manufacturing, ferrous metal, light industry, petrochemical, and shipbuilding industries. More details can be obtained from the following website: http://finance.sina.com.cn/focus/10chanye/.

  6. For details about the PISP, please refer to the following website: http://www.chinaip.com.cn/.

  7. IPC is a hierarchical patent classification system, within which classification terms consist of symbols such as A01B 1/00. The first letter is the “section symbol”. The following two-digit numbers are the “class symbol”. The four-digit letter makes up the “subclass”. The subclass is then followed by a one-to-three-digit “group” number, an oblique stroke and a number of at least two digits that represent a “main group” or “subgroup”. More details can be obtained from the following website: http://www.wipo.int/classifications/ipc/en/.

  8. There is a possibility that a firm may have one IPC class at the four-digit level but more IPC classes at the five- or six-digit level.

  9. We collected the patent data from PISP during April through June in 2015.

  10. For a specific cooperative patent, the collaboration depth between the focal firm and its partner i equals to 1/(n-1) when they jointly applied for a patent with the other n-2 actors.

  11. The detailed calculation of weighted density can be obtained in the “Appendix”.

  12. We calculated the local cohesion with the consideration of tie strength as well by using the weighted overall clustering coefficient of a firm’s knowledge network.

  13. For details about BYD, please refer to the following website: http://www.byd.com/indexglobal.html.

  14. For details about Chery, please refer to the following website: http://www.cheryinternational.com/.

  15. Following similar studies (e.g. Berchicci 2013; Grimpe and Kaiser 2010, Kafouros et al. 2015), we do not introduce the interactions between the moderators and squared terms.

  16. In our study, a total of 53 firms whose collaboration depth is greater than 1 accounted for 7.3% of the whole sample.

  17. We thank one reviewer who points this out.

  18. We calculated these statistics using data collected from various issues of Statistic Yearbook of Automobile Industry at http://tongji.cnki.net/kns55/Dig/dig.aspx.

  19. We thank one of the reviewers who pointed this out.

References

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

    Article  Google Scholar 

  • Allen, J., James, A. D., & Gamlen, P. (2007). Formal versus informal knowledge networks in R&D: A case study using social network analysis. R&D Management, 37(3), 179–196.

    Article  Google Scholar 

  • Bammer, G. (2008). Enhancing research collaborations: Three key management challenges. Research Policy, 37(5), 875–887.

    Article  Google Scholar 

  • Battistella, C., De Toni, A. F., & Pillon, R. (2016). Inter-organisational technology/knowledge transfer: A framework from critical literature review. The Journal of Technology Transfer, 41(5), 1195–1234.

    Article  Google Scholar 

  • Becerra, M., Lunnan, R., & Huemer, L. (2008). Trustworthiness, risk, and the transfer of tacit and explicit knowledge between alliance partners. Journal of Management Studies, 45(4), 691–713.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Belsley, D. A. (1991). Conditioning diagnostics—Collinearity and weak data in regression. New York: John Wiley & Sons.

    Google Scholar 

  • Berchicci, L. (2013). Towards an open R&D system: Internal R&D investment, external knowledge acquisition and innovative performance. Research Policy, 42(1), 117–127.

    Article  Google Scholar 

  • Brennecke, J., & Rank, O. (2017). The firm’s knowledge network and the transfer of advice among corporate inventors—A multilevel network study. Research Policy, 46(4), 768–783.

    Article  Google Scholar 

  • Breschi, S., Lissoni, F., & Malerba, F. (2003). Knowledge-relatedness in firm technological diversification. Research Policy, 32(1), 69–87.

    Article  Google Scholar 

  • Burg, E., Berends, H., & Raaij, E. M. (2014). Framing and interorganizational knowledge transfer: A process study of collaborative innovation in the aircraft industry. Journal of Management Studies, 51(3), 349–378.

    Article  Google Scholar 

  • Calantone, R. J., Cavusgil, S. T., & Zhao, Y. (2002). Learning orientation, firm innovation capability, and firm performance. Industrial Marketing Management, 31(6), 515–524.

    Article  Google Scholar 

  • Carnabuci, G., & Bruggeman, J. (2009). Knowledge specialization, knowledge brokerage and the uneven growth of technology domains. Social Forces, 88, 607–641.

    Article  Google Scholar 

  • Carnabuci, G., & Operti, E. (2013). Where do firms’ recombinant capabilities come from? Intraorganizational networks, knowledge, and firms’ ability to innovate through technological recombination. Strategic Management Journal, 34(13), 1591–1613.

    Article  Google Scholar 

  • Chang, S.-J., Chung, C.-N., & Mahmood, I. P. (2006). When and how does business group affiliation promote firm innovation? A tale of two emerging economies. Organization Science, 17(5), 637–656.

    Article  Google Scholar 

  • Chen, C. J., Ding, Y., & Kim, C. F. (2010). High-level politically connected firms, corruption, and analyst forecast accuracy around the world. Journal of International Business Studies, 41(9), 1505–1524.

    Article  Google Scholar 

  • Choi, S. B., Lee, S. H., & Williams, C. (2011). Ownership and firm innovation in a transition economy: Evidence from China. Research Policy, 40(3), 441–452.

    Article  Google Scholar 

  • Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128–152.

    Article  Google Scholar 

  • Coleman, J. S. (1988). Social capital in the creation of human capital. American Journal of Sociology, 94, S95–S120.

    Article  Google Scholar 

  • Colombelli, A., Krafft, J., & Quatraro, F. (2013). Properties of knowledge base and firm survival: Evidence from a sample of French manufacturing firms. Technological Forecasting and Social Change, 80(8), 1469–1483.

    Article  Google Scholar 

  • Dahlander, L., & Gann, D. M. (2010). How open is innovation? Research Policy, 39(6), 699–709.

    Article  Google Scholar 

  • Dechezlepretre, A., Neumayer, E., & Perkins, R. (2015). Environmental regulation and the cross-border diffusion of new technology: Evidence from automobile patents. Research Policy, 44(1), 244–257.

    Article  Google Scholar 

  • Dibiaggio, L., Nasiriyar, M., & Nesta, L. (2014). Substitutability and complementarity of technological knowledge and the inventive performance of semiconductor companies. Research Policy, 43(9), 1582–1593.

    Article  Google Scholar 

  • Dittrich, K., & Duysters, G. (2007). Networking as a means to strategy change: The case of open innovation in mobile telephone. Journal of Product Innovation Management, 24(6), 510–521.

    Article  Google Scholar 

  • Dodgson, M., Gann, D., & Salter, A. (2006). The role of technology in the shift towards open innovation: The case of Procter & Gamble. R&D Management, 36(3), 333–346.

    Article  Google Scholar 

  • Dushnitsky, G., & Shaver, J. M. (2009). Limitations to interorganizational knowledge acquisition: The paradox of corporate venture capital. Strategic Management Journal, 30(10), 1045–1064.

    Article  Google Scholar 

  • Dyer, J. H., & Nobeoka, K. (2000). Creating and managing a high-performance knowledge-sharing network: The Toyota case. Strategic Management Journal, 21(3), 345–367.

    Article  Google Scholar 

  • Dyer, J. H., & Singh, H. (1998). The relational view: Coopearative strategy and sources of interorganizational competitive advantage. Academy of Management Review, 23(4), 660–679.

    Article  Google Scholar 

  • Echambadi, R., & Hess, J. D. (2007). Mean-centering does not alleviate collinearity problems in moderated multiple regression models. Marketing Science, 26(3), 438–445.

    Article  Google Scholar 

  • Enkel, E., Gassmann, O., & Chesbrough, H. (2009). Open R&D and open innovation: Exploring the phenomenon. R&D Management, 39(4), 311–316.

    Article  Google Scholar 

  • Fan, G., Wang, X. L., & Zhu, H. P. (2006). Marketization index in China: The regional process report Beijing: Ecomonic Science Press (in Chinese).

  • Fleming, L., & Sorenson, O. (2001). Technology as a complex adaptive system: Evidence from patent data. Research Policy, 30(7), 1019–1039.

    Article  Google Scholar 

  • Fleming, L., & Sorenson, O. (2004). Science as a map in technological search. Strategic Management Journal, 25(8/9), 909–928.

    Article  Google Scholar 

  • Fu, X. (2012). How does openness affect the importance of incentives for innovation? Research Policy, 41(3), 512–523.

    Article  Google Scholar 

  • Gao, G. Y., Murray, J. Y., Kotabe, M., & Lu, J. (2010). A “strategy tripod” perspective on export behaviors: Evidence from domestic and foreign firms based in an emerging economy. Journal of International Business Studies, 41(3), 377–396.

    Article  Google Scholar 

  • Garcia-Vega, M. (2006). Does technological diversification promote innovation?: An empirical analysis for European firms. Research Policy, 35(2), 230–246.

    Article  Google Scholar 

  • Grant, R. M. (1996). Toward a knowledge-based theory of the firm. Strategic Management Journal, 17(S2), 109–122.

    Article  Google Scholar 

  • Grimpe, C., & Kaiser, U. (2010). Balancing internal and external knowledge acquisition: The gains and pains from R&D outsourcing. Journal of Management Studies, 47(8), 1483–1509.

    Article  Google Scholar 

  • Guan, J., & Liu, N. (2016). Exploitative and exploratory innovations in knowledge network and collaboration network: A patent analysis in the technological field of nano-energy. Research Policy, 45(1), 97–112.

    Article  Google Scholar 

  • Gulati, R., & Gargiulo, M. (1999). Where do interorganizational networks come from? American Journal of Sociology, 104(5), 1438–1439.

    Article  Google Scholar 

  • Guler, I., & Nerkar, A. (2012). The impact of global and local cohesion on innovation in the pharmaceutical industry. Strategic Management Journal, 33(5), 535–549.

    Article  Google Scholar 

  • Hanneman, R. A., & Riddle, M. (2005). Introduction of social network methods Rivreside. CA: University of California at Riverside.

    Google Scholar 

  • Hansen, M. T., & Nohria, N. (2004). How to build collaborative advantage. Mit Sloan Management Review, 46(1), 22–30.

    Google Scholar 

  • Harvey, S., & Kou, C. Y. (2013). Collective engagement in creative tasks. The role of evaluation in the creative process in groups. Administrative Science Quarterly, 58(3), 346–386.

    Article  Google Scholar 

  • Henisz, W. J., Zelner, B. A., & Guillén, M. F. (2005). The worldwide diffusion of market-oriented infrastructure reform, 1977–1999. American Sociological Review, 70(6), 871–897.

    Article  Google Scholar 

  • Holloway, S. S., & Parmigiani, A. (2016). Friends and profits don’t mix: The performance implications of repeated partnerships. Academy of Management Journal, 59(2), 460–478.

    Article  Google Scholar 

  • Howells, J., Ramlogan, R., & Cheng, S. L. (2012). Innovation and university collaboration: Paradox and complexity within the knowledge economy. Cambridge Journal of Economics, 36(3), 703–721.

    Article  Google Scholar 

  • Hülsheger, U. R., Anderson, N., & Salgado, J. F. (2009). Team-level predictors of innovation at work: A comprehensive meta-analysis spanning three decades of research. Journal of Applied Psychology, 94(5), 1128–1145.

    Article  Google Scholar 

  • Inkpen, A. C., & Tsang, E. W. (2005). Social capital, networks, and knowledge transfer. Academy of Management Review, 30(1), 146–165.

    Article  Google Scholar 

  • Janowicz-Panjaitan, M. K., & Noorderhaven, N. G. (2009). Trust, calculation, and interorganizational learning of tacit knowledge: An organizational roles perspective. Organization Studies, 30(10), 1021–1044.

    Article  Google Scholar 

  • Joshi, A. M., & Nerkar, A. (2011). When do strategic alliances inhibit innovation by firms? Evidence from patent pools in the global optical disc industry. Strategic Management Journal, 32(11), 1139–1160.

    Article  Google Scholar 

  • Kafouros, M., Wang, C., Piperopoulos, P., & Zhang, M. (2015). Academic collaborations and firm innovation performance in China: The role of region-specific institutions. Research Policy, 44(3), 803–817.

    Article  Google Scholar 

  • Katz, J. S., & Martin, B. R. (1997). What is research collaboration? Research Policy, 26(1), 1–18.

    Article  Google Scholar 

  • Knudsen, T., & Srikanth, K. (2014). Coordinated exploration: Organizing joint search by multiple specialists to overcome mutual confusion and joint myopia. Administrative Science Quarterly, 59(3), 409–441.

    Article  Google Scholar 

  • Kuhn, T. S. (1996). The structure of scientific revolution. Chicago: University of Chicago Press.

    Book  Google Scholar 

  • Lant, T. K. (1992). Aspiration level adaptation: An empirical exploration. Management Science, 38(5), 623–644.

    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 

  • Laursen, K., & Salter, A. J. (2014). The paradox of openness: Appropriability, external search and collaboration. Research Policy, 43(5), 867–878.

    Article  Google Scholar 

  • Lavie, D. (2006). The competitive advantage of interconnected firms: An extension of the resource-based view. The Academy of Management Review, 31(3), 638–658.

    Article  Google Scholar 

  • Lehmann, E. E., & Menter, M. (2016). University–industry collaboration and regional wealth. The Journal of Technology Transfer, 41(6), 1284–1307.

    Article  Google Scholar 

  • Leiponen, A., & Helfat, C. E. (2010). Innovation objectives, knowledge sources, and the benefits of breadth. Strategic Management Journal, 31(2), 224–236.

    Article  Google Scholar 

  • Levin, R. C., Klevorick, A. K., Nelson, R. R., & Winter, S. G. (1987). Appropriating the returns from industrial research and development. Brookings Papers on Economic Activity, 3, 783–831.

    Article  Google Scholar 

  • Levinthal, D. A., & March, J. G. (1993). The myopia of learning. Strategic Management Journal, 14(S2), 95–112.

    Article  Google Scholar 

  • Levitt, B., & March, J. (1988). Organizational learning. Annual Review of Sociology, 14, 319–340.

    Article  Google Scholar 

  • Li, D., & Ireland, R. D. (2008). Friends, acquaintances, or strangers? Partner selection in R&D alliances. Academy of Management Journal, 51(2), 315–334.

    Article  Google Scholar 

  • Li, J., Strange, R., Ning, L., & Sutherland, D. (2016). Outward foreign direct investment and domestic innovation performance: Evidence from China. International Business Review, 25, 1010–1019.

    Article  Google Scholar 

  • Li, J., Sutherland, D., Ning, L., & Wang, Y. (2014). Firm ownership, industrial structure, and regional innovation performance in China’s provinces. Technology Analysis & Strategic Management, 26(9), 1001–1022.

    Article  Google Scholar 

  • Lipparini, A., Lorenzoni, G., & Ferriani, S. (2014). From core to periphery and back: A study on the deliberate shaping of knowledge flows in interfirm dyads and networks. Strategic Management Journal, 35(4), 578–595.

    Article  Google Scholar 

  • Liu, J., & Tylecote, A. (2009). Corporate governance and technological capability development: Three case studies in the Chinese auto industry. Industry and Innovation, 16, 525–544.

    Article  Google Scholar 

  • Long, J. S. (1997). Regression models for categorical and limited dependent variables. Thousand Oaks, CA: Sage Publications.

    Google Scholar 

  • March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87.

    Article  Google Scholar 

  • Mcfadyen, M. A., & Cannella, A. A. (2004). Social capital and knowledge creation: Diminishing returns of the number and strength of exchange. Academy of Management Journal, 47(5), 735–746.

    Google Scholar 

  • Miller, D. J., Fern, M. J., & Cardinal, L. B. (2007). The use of knowledge for technological innovation within diversified firms. Academy of Management Journal, 50(2), 307–326.

    Article  Google Scholar 

  • Mishra, A., Chandrasekaran, A., & MacCormack, A. (2015). Collaboration in multi-partner R&D projects: The impact of partnering scale and scope. Journal of Operations Management, 33–34, 1–14.

    Article  Google Scholar 

  • Nahapiet, J., & Ghoshal, S. (1998). Social capital, intellectual capital, and the organizational advantage. Academy of Management Review, 23(2), 242–266.

    Article  Google Scholar 

  • Nerkar, A. (2003). Old is gold? The value of temporal exploration in the creation of new knowledge. Management Science, 49(2), 211–229.

    Article  Google Scholar 

  • Nickerson, J. A., & Zenger, T. R. (2004). A knowledge-based theory of the firm–The problem-solving perspective. Organization Science, 15(6), 617–632.

    Article  Google Scholar 

  • Nooteboom, B. (2009). A cognitive theory of the firm: Learning, governance and dynamic capabilities. Cheltenham: Edward Elgar Publishing.

    Book  Google Scholar 

  • Parker, H. (2012). Knowledge acquisition and leakage in inter-firm relationships involving new technology-based firms. Management Decision, 50(9), 1618–1633.

    Article  Google Scholar 

  • Parker, H., & Brey, Z. (2015). Collaboration costs and new product development performance. Journal of Business Research, 68(7), 1653–1656.

    Article  Google Scholar 

  • Phelps, C., Heidl, R., & Wadhwa, A. (2012). Knowledge, networks, and knowledge networks: A review and research agenda. Journal of Management, 38(4), 1115–1166.

    Article  Google Scholar 

  • Pollitte, W. A., Miller, J. C., & Yaprak, A. (2015). Returns to US firms from strategic alliances in China: A knowledge-based view. Journal of World Business, 50(1), 144–148.

    Article  Google Scholar 

  • Powell, W. W., Koput, K. W., & Smith-Doerr, L. (1996). Interorganizational collaboration and the locus of innovation: Networks of learning in biotechnology. Administrative Science Quarterly, 41(1), 116–145.

    Article  Google Scholar 

  • Quintana-García, C., & Benavides-Velasco, C. A. (2008). Innovative competence, exploration and exploitation: The influence of technological diversification. Research Policy, 37(3), 492–507.

    Article  Google Scholar 

  • Rodríguez-Pose, A., & Crescenzi, R. (2008). Research and development, spillovers, innovation systems, and the genesis of regional growth in Europe. Regional Studies, 42(1), 51–67.

    Article  Google Scholar 

  • Rosenkopf, L., & Nerkar, A. (2001). Beyond local search: Boundary-spanning, exploration, and impact in the optical disk industry. Strategic Management Journal, 22(4), 287–306.

    Article  Google Scholar 

  • Rosenkopf, L., & Padula, G. (2008). Investigating the microstructure of network evolution: Alliance formation in the mobile communications industry. Organization Science, 19(5), 669–687.

    Article  Google Scholar 

  • Savino, T., Messeni Petruzzelli, A., & Albino, V. (2017). Search and recombination process to innovate: A review of the empirical evidence and a research agenda. International Journal of Management Reviews, 19(1), 54–75.

    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  Google Scholar 

  • Schotter, A., & Beamish, P. W. (2011). General manager staffing and performance in transitional economy subsidiaries: A subnational analysis. International Studies of Management & Organization, 41(2), 55–87.

    Article  Google Scholar 

  • Shi, W. S., Sun, S. L., & Peng, M. W. (2012). Sub-National Institutional Contingencies, Network positions, and IJV partner selection. Journal of Management Studies, 49(7), 1221–1245.

    Article  Google Scholar 

  • Sidhu, J. S., Commandeur, H. R., & Volberda, H. W. (2007). The multifaceted nature of exploration and exploitation: Value of supply, demand, and spatial search for innovation. Organization Science, 18(1), 20–38.

    Article  Google Scholar 

  • Sørensen, J. B., & Stuart, T. E. (2000). Aging, obsolescence, and organizational innovation. Administrative Science Quarterly, 45(1), 81–112.

    Article  Google Scholar 

  • Stuart, T. E., & Podolny, J. M. (1996). Local search and the evolution of technological capabilities. Strategic Management Journal, 17(S1), 21–38.

    Article  Google Scholar 

  • Terjesen, S., & Patel, P. C. (2017). In search of process innovations: The role of search depth, search breadth, and the industry environment. Journal of Management, 43(5), 1421–1446.

    Article  Google Scholar 

  • Tödtling, F., Lehner, P., & Kaufmann, A. (2009). Do different types of innovation rely on specific kinds of knowledge interactions? Technovation, 29(1), 59–71.

    Article  Google Scholar 

  • Trajtenberg, M. (1990). A penny for your quotes: Patent citations and the value of innovations. Rand Journal of Economics, 21(1), 172–187.

    Article  Google Scholar 

  • Van Echtelt, F. E. A., Wynstra, F., Van Weele, A. J., & Duysters, G. (2008). Managing supplier involvement in new product development: A multiple-case study. Journal of Product Innovation Management, 25(2), 180–201.

    Article  Google Scholar 

  • von Hippel, E. (1988). The sources of innovation. New York: Oxford University Press.

    Google Scholar 

  • Walsh, J. P., Lee, Y.-N., & Nagaoka, S. (2016). Openness and innovation in the US: Collaboration form, idea generation and implementation. Research Policy, 45(8), 1660–1671.

    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 

  • Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Yang, H., Phelps, C., & Steensma, H. K. (2010). Learning from what others have learned from you: The effects of knowledge spillovers on originating firms. The Academy of Management Journal, 53(2), 371–389.

    Article  Google Scholar 

  • Yayavaram, S., & Ahuja, G. (2008). Decomposability in knowledge structures and its impact on the usefulness of inventions and knowledge-base malleability. Administrative Science Quarterly, 53(2), 333–362.

    Article  Google Scholar 

  • Yayavaram, S., & Chen, W.-R. (2015). Changes in firm knowledge couplings and firm innovation performance: The moderating role of technological complexity. Strategic Management Journal, 36, 377–396.

    Article  Google Scholar 

  • Zahra, S. A., & George, G. (2002). Absorptive capacity: A review, reconceptualization, and extension. Academy of Management Review, 27(2), 185–203.

    Article  Google Scholar 

  • Zhang, Y., Li, H., Li, Y., & Zhou, L.-A. (2010). FDI spillovers in an emerging market: The role of foreign firms’ country origin diversity and domestic firms’ absorptive capacity. Strategic Management Journal, 31(9), 969–989.

    Google Scholar 

  • Zheng, Y., & Yang, H. (2015). Does familiarity foster innovation? The impact of alliance partner repeatedness on breakthrough innovations. Journal of Management Studies, 52(2), 213–230.

    Article  Google Scholar 

  • Zhou, K. Z., & Li, C. B. (2012). How knowledge affects radical innovation: Knowledge base, market knowledge acquisition, and internal knowledge sharing. Strategic Management Journal, 33(9), 1090–1102.

    Article  Google Scholar 

Download references

Acknowledgements

We thank Yapu Zhao for his helpful comments and discussions. We are especially grateful to the Editor Barry Bozeman and three anonymous reviewers for their insightful comments and encouragement. Seminar participants of College of Business Administration at Hunan University provided helpful suggestions. Earlier version of this paper is presented at the International Conference on Innovation Studies (ICIS) at Tsinghua University in 2017. This research is sponsored by grants from the National Natural Science Foundation of China (Grant Nos: 71502056, 71673082, 71233002). All errors are ours.

Author information

Authors and Affiliations

  1. College of Business Administration, Hunan University, No.11, Lushan South Road, Changsha, 410082, Hunan, China

    Luyun Xu, Jian Li & Xin Zhou

Authors
  1. Luyun Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jian Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xin Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jian Li.

Appendix

Appendix

To better understand the measurement of weighted density, an example is given to illustrate how weighted density is calculated. If a firm’s knowledge network is as follows (the matrix in Table 3), the weighted density (WD) of the firm’s knowledge network then can be calculated as:

Table 3 An example of a firm’s knowledge network in the form of symmetric matrix
Full size table
$$ WD = \frac{(16 + 12 + 12 + 12 + 12 + 8 + 1 + 1 + 1)}{{\frac{5(5 - 1)}{2}}} = \frac{75}{10} = 7.5 $$

By constrast, the pure density neglects the frequency of this co-occurrence and thus the pure density (PD) of the firm’s knowledge network can be calculated as:

$$ PD = \frac{9}{{\frac{5(5 - 1)}{2}}} = \frac{9}{10} = 0.9. $$

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xu, L., Li, J. & Zhou, X. Exploring new knowledge through research collaboration: the moderation of the global and local cohesion of knowledge networks. J Technol Transf 44, 822–849 (2019). https://doi.org/10.1007/s10961-017-9614-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10961-017-9614-8

Keywords

JEL Classification

Search

Navigation