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.
Author(s): Haiyun Xu, Chao Wang, Kun Dong, Rui Luo, Zenghui Yue, Hongshen Pang
Source: Journal of Data and Information Science