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How Does Inter-Organizational Cooperation Impact Organizations’ Scientific Knowledge Generation? Evidence from the Biomass Energy Field

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  • Liu Li

    (School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China)

  • Chaoying Tang

    (School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China)

Abstract

Previous studies have demonstrated that accessing external knowledge is important for organizations’ knowledge generation. The main purpose of this study is to investigate how the diversity and amount of organizations’ external scientific knowledge influence their scientific knowledge generation. We also consider the moderating effect of the redundant industrial scientific knowledge and the amount of technical knowledge from external technical cooperators. The social network analysis method is used to establish both ego- and industrial-scientific cooperation network, and ego-technical cooperation network in order to analyze the external scientific knowledge and technical knowledge. The empirical analysis is based on patent and article data of 106 organizations in the biomass energy industry (including firms, universities and research institutes), and the results show that organizations’ structural holes and degree centrality of scientific cooperation network have positive effects on their scientific knowledge generation. In addition, organizations’ degree centrality of technical cooperation network positively moderates the relationship between their degree centrality of scientific cooperation network and scientific knowledge generation. Furthermore, density of industrial scientific cooperation network decreases the positive effect of organizations’ structural holes on their scientific knowledge generation, while it strengthens the positive effect of degree centrality of scientific cooperation network on their scientific knowledge generation. Academic contributions and practical suggestions are discussed.

Suggested Citation

  • Liu Li & Chaoying Tang, 2020. "How Does Inter-Organizational Cooperation Impact Organizations’ Scientific Knowledge Generation? Evidence from the Biomass Energy Field," Sustainability, MDPI, vol. 13(1), pages 1-18, December.
    • Handle: RePEc:gam:jsusta:v:13:y:2020:i:1:p:191-:d:469252
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    as
    1. Guan, Jiancheng & Yan, Yan & Zhang, Jing Jing, 2017. "The impact of collaboration and knowledge networks on citations," Journal of Informetrics, Elsevier, vol. 11(2), pages 407-422.
    2. Wang, Jian, 2016. "Knowledge creation in collaboration networks: Effects of tie configuration," Research Policy, Elsevier, vol. 45(1), pages 68-80.
    3. Gersbach, Hans & Sorger, Gerhard & Amon, Christian, 2018. "Hierarchical growth: Basic and applied research," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 434-459.
    4. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    5. Simon Rodan & Charles Galunic, 2004. "More than network structure: how knowledge heterogeneity influences managerial performance and innovativeness," Strategic Management Journal, Wiley Blackwell, vol. 25(6), pages 541-562, June.
    6. Meihui Li & Na Luo & Yi Lu, 2017. "Biomass Energy Technological Paradigm (BETP): Trends in This Sector," Sustainability, MDPI, vol. 9(4), pages 1-28, April.
    7. Paul Muller & Julien Pénin, 2007. "Why do firms disclose knowledge and how does it matter?," Springer Books, in: Uwe Cantner & Franco Malerba (ed.), Innovation, Industrial Dynamics and Structural Transformation, pages 149-172, Springer.
    8. Hausman, Jerry & Hall, Bronwyn H & Griliches, Zvi, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," Econometrica, Econometric Society, vol. 52(4), pages 909-938, July.
    9. Choi, Hyundo & Shin, Jungwoo & Hwang, Won-Sik, 2018. "Two faces of scientific knowledge in the external technology search process," Technological Forecasting and Social Change, Elsevier, vol. 133(C), pages 41-50.
    10. Weishu Liu & Mengdi Gu & Guangyuan Hu & Chao Li & Huchang Liao & Li Tang & Philip Shapira, 2014. "Profile of developments in biomass-based bioenergy research: a 20-year perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(2), pages 507-521, May.
    11. Shu-Hao Chang, 2018. "A pilot study on the connection between scientific fields and patent classification systems," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 951-970, March.
    12. Angelina Roša (Rosha) & Natalja Lace, 2018. "The Open Innovation Model of Coaching Interaction in Organisations for Sustainable Performance within the Life Cycle," Sustainability, MDPI, vol. 10(10), pages 1-17, September.
    13. Rotolo, Daniele & Messeni Petruzzelli, Antonio, 2013. "When does centrality matter? Scientific productivity and the moderating role of research specialization and cross-community ties," MPRA Paper 53406, University Library of Munich, Germany.
    14. Melissa A. Schilling & Corey C. Phelps, 2007. "Interfirm Collaboration Networks: The Impact of Large-Scale Network Structure on Firm Innovation," Management Science, INFORMS, vol. 53(7), pages 1113-1126, July.
    15. Manzano-Agugliaro, F. & Alcayde, A. & Montoya, F.G. & Zapata-Sierra, A. & Gil, C., 2013. "Scientific production of renewable energies worldwide: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 18(C), pages 134-143.
    16. Popp, David, 2017. "From science to technology: The value of knowledge from different energy research institutions," Research Policy, Elsevier, vol. 46(9), pages 1580-1594.
    17. Justin Tan & Hongjuan Zhang & Liang Wang, 2015. "Network Closure or Structural Hole? The Conditioning Effects of Network–Level Social Capital on Innovation Performance," Entrepreneurship Theory and Practice, , vol. 39(5), pages 1189-1212, September.
    18. Akbar Zaheer & Geoffrey G. Bell, 2005. "Benefiting from network position: firm capabilities, structural holes, and performance," Strategic Management Journal, Wiley Blackwell, vol. 26(9), pages 809-825, September.
    19. Jiancheng Guan & Lanxin Pang, 2018. "Bidirectional relationship between network position and knowledge creation in Scientometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 201-222, April.
    20. Anil K. Gupta & Paul E. Tesluk & M. Susan Taylor, 2007. "Innovation At and Across Multiple Levels of Analysis," Organization Science, INFORMS, vol. 18(6), pages 885-897, December.
    21. Brooks, Harvey, 1994. "The relationship between science and technology," Research Policy, Elsevier, vol. 23(5), pages 477-486, September.
    22. Geert Duysters & Charmianne Lemmens, 2003. "Alliance Group Formation Enabling and Constraining Effects of Embeddedness and Social Capital in Strategic Technology Alliance Networks," International Studies of Management & Organization, Taylor & Francis Journals, vol. 33(2), pages 49-68, January.
    23. Manju K. Ahuja & Dennis F. Galletta & Kathleen M. Carley, 2003. "Individual Centrality and Performance in Virtual R& D Groups: An Empirical Study," Management Science, INFORMS, vol. 49(1), pages 21-38, January.
    24. Qingjun Zhao & Jiancheng Guan, 2013. "Love dynamics between science and technology: some evidences in nanoscience and nanotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 113-132, January.
    25. Chen, Kaihua & Zhang, Yi & Zhu, Guilong & Mu, Rongping, 2020. "Do research institutes benefit from their network positions in research collaboration networks with industries or/and universities?," Technovation, Elsevier, vol. 94.
    26. Panwar, N.L. & Kaushik, S.C. & Kothari, Surendra, 2011. "Role of renewable energy sources in environmental protection: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(3), pages 1513-1524, April.
    27. Andreas Schwab, 2007. "Incremental Organizational Learning from Multilevel Information Sources: Evidence for Cross-Level Interactions," Organization Science, INFORMS, vol. 18(2), pages 233-251, April.
    28. Audretsch, David B. & Bozeman, Barry & Combs, Kathryn L. & Feldman, Maryann & Link, Albert N. & Siegel, Donald S. & Stephan, Paula, 2002. "The Economics of Science and Technology," The Journal of Technology Transfer, Springer, vol. 27(2), pages 155-203, April.
    29. Saxena, R.C. & Adhikari, D.K. & Goyal, H.B., 2009. "Biomass-based energy fuel through biochemical routes: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(1), pages 167-178, January.
    30. Breschi, Stefano & Catalini, Christian, 2010. "Tracing the links between science and technology: An exploratory analysis of scientists' and inventors' networks," Research Policy, Elsevier, vol. 39(1), pages 14-26, February.
    31. R. J. W. Tussen & R. K. Buter & Th. N. van Leeuwen, 2000. "Technological Relevance of Science: An Assessment of Citation Linkages between Patents and Research Papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 47(2), pages 389-412, February.
    32. Perkmann, Markus & Walsh, Kathryn, 2008. "Engaging the scholar: Three types of academic consulting and their impact on universities and industry," Research Policy, Elsevier, vol. 37(10), pages 1884-1891, December.
    33. Huang, Mu-Hsuan & Yang, Hsiao-Wen & Chen, Dar-Zen, 2015. "Increasing science and technology linkage in fuel cells: A cross citation analysis of papers and patents," Journal of Informetrics, Elsevier, vol. 9(2), pages 237-249.
    34. Angela Hullmann & Martin Meyer, 2003. "Publications and patents in nanotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 58(3), pages 507-527, November.
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