A Study of Methods to Identify Industry-University-Research Institution Cooperation Partners based on Innovation Chain Theory

doi:10.2478/jdis-2018-0008

Abstract

Abstract:

Purpose: This study aims at identifying potential industry-university-research collaboration (IURC) partners effectively and analyzes the conditions and dynamics in the IURC process based on innovation chain theory.Design/methodology/approach: The method utilizes multisource data, combining bibliometric and econometrics analyses to capture the core network of the existing collaboration networks and institution competitiveness in the innovation chain. Furthermore, a new identification method is constructed that takes into account the law of scientific research cooperation and economic factors.Findings: Empirical analysis of the genetic engineering vaccine field shows that through the distribution characteristics of creative technologies from different institutions, the analysis based on the innovation chain can identify the more complementary capacities among organizations.Research limitations: In this study, the overall approach is shaped by the theoretical concept of an innovation chain, a linear innovation model with specific types or stages of innovation activities in each phase of the chain, and may, thus, overlook important feedback mechanisms in the innovation process.Practical implications: Industry-university-research institution collaborations are extremely important in promoting the dissemination of innovative knowledge, enhancing the quality of innovation products, and facilitating the transformation of scientific achievements.Originality/value: Compared to previous studies, this study emulates the real conditions of IURC. Thus, the rule of technological innovation can be better revealed, the potential partners of IURC can be identified more readily, and the conclusion has more value.

Key words: Institutions collaboration, Collaboration network, Innovation chain, Industrial chain, Industry-university-research institutions

Haiyun, Xu, Wang Chao, Dong Kun, Luo Rui, Yue Zenghui, and Pang Hongshen. "A Study of Methods to Identify Industry-University-Research Institution Cooperation Partners based on Innovation Chain Theory." Journal of Data and Information Science, vol.3, no.2, 2018, pp.38-61. DOI: 10.2478/jdis-2018-0008

References

[1]	Arundel A., &Geuna A. (2004). Proximity and the use of public science by innovative European firms. Economics of Innovation & New Technology, 13(6), 559-580.
[2]	Bamfield P. (2006). Research and development in the chemical and pharmaceutical industry. John Wiley & Sons.
[3]	Barber M.J. (2007). Modularity and community detection in bipartite networks. Physical Review E Statistical Nonlinear & Soft Matter Physics, 76(2), 066102.
[4]	Baxter G., Dorogovtsev S., Goltsev A., & Mendes J. (2012). Handbook of Optimization in Complex Networks. Optimization, 57, 229-252. https://doi.org/10.1007/978-1-4614-0754-6.
[5]	Blondel V.D., Guillaume J.L., Lambiotte R., & Lefebvre E. (2008). Fast unfolding of communities in large networks. Journal of statistical mechanics, (10), 155-168.
[6]	Bruneel J., d’Este P., & Salter A. (2010). Investigating the factors that diminish the barriers to university-industry collaboration. Research Policy, 39(7), 858-868.
[7]	Cai X., Xiao Y.F., & Zeng F.R. (2001). Research on knowledge-innovation-chain. Soft Science, 15(1), 2-4.
[8]	Cai X. (2002). Innovation, innovation cluster, innovation chain and their enlightenment. R&D Management, 14(6), 35-39.
[9]	Cao J., Fan D.C., & Tang X.X. (2010). Research on the evaluation of technology innovation performance based on industry-university-research cooperation. Science& Technology Progress and Policy, 27(7), 114-118.
[10]	Clements C.J., &Wesselingh S.L. (2005). Vaccine presentations and delivery technologies-what does the future hold? Expert Review of Vaccines, 4(3), 281.
[11]	Cohen W.M., Nelson R.R., & Walsh J.P. (2002). Links and impacts: the influence of public research on industrial R&D. Management science, 48(1), 1-23.
[12]	D’Este P., &Patel P. (2007). University-industry linkages in the UK: What are the factors underlying the variety of interactions with industry? Research policy, 36(9), 1295-1313.
[13]	Fischer M., J?hn H., Teich T. (2004). Optimizing the selection of partners in production networks. Robotics & Computer-Integrated Manufacturing, 20(6), 593-601.
[14]	Huang M.D., Li W.W., & Huang J. (2017). Research on the present situation and countermeasures of the industry-university-research cooperation in China. Science & Technoloyg Progress and Policy, 34(19), 22-27.
[15]	Huang S.J. (2014). China Industrial Cluster Innovation Development Report: Learning Mechanism in Cluster Network 2011-2012. Economic management publishing house.
[16]	Incites. (2015). InCitesTM quick strat guide of InCitesTM database. .
[17]	Kogut B., &Chang S.J. (1991). Technological capabilities and Japanese foreign direct investment in the United States. Review of Economics and Statistics, 73(3), 401-413.
[18]	Mohnen P., &Hoareau C. (2003). What type of enterprise forges close links with universities and government labs? Evidence from CIS 2. Managerial and decision economics, 24(2-3), 133-145.
[19]	Larson E.V., &Brahmakulam I.T. (2001). Building a New Foundation for Innovation. Rand Corporation.
[20]	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.
[21]	Leydesdorff L., &Etzkowitz H. (1996). Emergence of a Triple Helix of university-industry-government relations. Science & public policy, 23(5), 279-286.
[22]	Liang Y.M. (2007). A new strategy on the bilateral technical cooperation. Guangzhou. (Jinan University M.S. dissertation)
[23]	Li W.H., Wang C.H., & An N. (2008). Analysis of the relationship and mode between Subject and object of industry-unniversity-research cooperation based on innovation system. Science and Technology Management Research, 28(6), 4-5.
[24]	Park I., Jeong Y., Yoon B., & Mortara L. (2015). Exploring potential R&D collaboration partners through patentanalysis based on bibliographic coupling and latent semantic analysis. Technology Analysis & Strategic Management, 27(7), 759-781.
[25]	Newman M.E. (2003). The structure and function of complex networks. SIAM review, 45(2), 167-256.
[26]	Newman M.E., &Girvan M. (2004).Finding and evaluating community structure in networks. Physical Review E Statistical Nonlinear & Soft Matter Physics, 69(2), 026113.
[27]	Qing T., &Liu S. (2016). Construction of industry-university-research cooperation innovation system in Chengdu. China Journal of Commerce, (29), 135-137.
[28]	Reuters T. (2015). Thomson Data Analyzer.
[29]	Reuters T. (2015). Derwent innovations index.Thomson Reuters.
[30]	Santoro M.D., &Gopalakrishnan S. (2000). The institutionalization of knowledge transfer activities within industry-university collaborative ventures. Journal of engineering and technology management, 17(3-4), 299-319.
[31]	Shen H.Data show the conversion rate of scientific and technological achievements in China is less than 30%, China Economic Net. Retrieved from .
[32]	Slotte V., &Tynj?l? P. (2003). Industry-university collaboration for continuing professional development. Journal of Education & Work, 16(4), 445-464.
[33]	Solesvik M.Z., &Encheva S. (2010). Partner selection for interfirm collaboration in ship design. Industrial Management & Data Systems, 110(5), 701-717.
[34]	Tang Y.L., Song G.C., & Liang W.C. (2005). Research progress and applicaton of genetic engineering vaccines. Jilin Journal of Animal husbandry and veterunary medicine, 12, 18-20.
[35]	Timmers P. (2002). Building effective public R&D programs. Portland International Conference on Management of Engineering and Technology, 1999. Technology and Innovation Management. Picmet. IEEE, 2, 591-597.
[36]	Wang T.C., &Chen Y.H. (2007). Applying consistent fuzzy preference relations to partnership selection. Omega, 35(4), 384-388.
[37]	Wang X.F., Wang Z.N., Huang Y., Liu Y.Q., Zhang J., Heng X.F., & Zhu D.H. (2017). Identifying R&D partners through subject-action-object semantic analysis in a problem & solution pattern. Technology Analysis and Strategic Management, 1-14.
[38]	Wen F.F. (2012). Study on patent collaboration patterns based on co-inventorship bibliometrics. Wuhan University.
[39]	Xie K.F., &Liu H.L. (2006). Game analysis of R&D entities basesd on industry-unniversity-research institute cooperation. Science of Science and management of S. &T., 27(10), 27-30.
[40]	Xu H.Y., Qi Y., Yue Z.H., & Fang S. (2015). Measurment methods and application research of triple helix model in collaborative innovation management. Journal of the China Society for Scientific and Technical Information, 34(3), 236-246.
[41]	Xu H.Y., Wang C., Dong K., Wei L., & Pang H.S. (2017). Methods to identify potential industry-university-research institutions cooperation partners based on the knowledge spillovers effects in the Innovation chain. Journal of the China Society for Scientific and Technical Information, 36(7), 682-694.
[42]	Yoon B., &Song B. (2014). A systematic approach of partner selection for open innovation. Industrial Management & Data Systems, 114(7), 1068-1093.
[43]	Yue Z.H., Xu H.Y., & Fang S. (2015). Modeling knowledge diffusion in scientific collaboration network based on structural parameters. Journal of the China Society for Scientific and Technical Information, 34(5), 471-483.
[44]	Zhang L. (2012). Choice of Partners for the Cooperative Innovation of Industries, Universities and Research Institutes by Game Analysis. Science and Technology Management Research, (19), 218-223.
[45]	Zheng Y.L. (2015). Study on formation mechanism of generic technology cooperative R&D based on evolutinary game theory. Chongqing. (Chongqing University Ph.D. dissertation)