This study aims at identifying potential industry-University-research institution collaborations partners (IURC) efficaciously and analyzes the conditions and dynamics in the IURC process, based on knowledge potential and the knowledge spillover theory. Furthermore, a new identification method is constructed that takes into account the law of scientific research cooperation and economic factors. The method utilizes multisource data, combining bibliometric and econometrics analyses to achieve the network core of the existing collaboration network, and institution competitiveness in the innovation chain. Empirical analysis of the genetic engineering vaccine field shows that throughout the distribution characteristics of creative technologies from different institutions, the analysis based on the innovation chain can identify more complementarities between institutions. Compared to previous studies, this study emulates the real conditions of IURC. The rule of technological innovation can be better revealed, potential partners of IURC can be more easily identified, and the conclusion has a higher value in consultation. In particular, diverse informative indices can assist researchers in deriving appropriate partners for research and development cooperation.
Author(s): Haiyun Xu, Kun Dong, Ling Wei, Chao Wang, Shu Fang
Organization(s): Chengdu Documentation and Information Center, CAS; University of Chinese Academy of Sciences
Source: Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining