Dynamic Selection of Key Innovation Partners in Open Innovation Ecosystems: A Collaborative Innovation Field Approach for Sustainable Development
ABSTRACT Innovation consortiums, as a new collaborative innovation model within the open innovation ecosystem, play a significant role in breakthroughs in key core technologies in China and in improving enterprises' technological innovation levels. However, identifying key resource‐matching partners is the primary challenge that innovation consortiums face in achieving sustainable innovation. This paper employs resource dependence theory and field theory to propose a method for identifying and dynamically selecting innovative partners: potential partners of leading enterprises are identified through association rules, evaluated and ranked using the R‐TOPSIS model, and finally selected by constructing a collaborative innovation field. Through the case study of the data of China Zhaotai Medical Company (Company Z), the applicability and effectiveness of this method were further verified. This research study makes a dual contribution. Theoretically, it enriches the literature on open innovation ecosystems and collaborative innovation by integrating resource dependence and field theories within the context of Chinese practices. Methodologically, it offers a novel, dynamic framework for partner selection in an innovation consortium. By facilitating the effective integration of key resources over time, this approach directly supports the sustainable development of such a consortium, enabling them to tackle complex technological challenges aligned with broader socio‐economic goals persistently.
Authors
- Jiayi Jia
- Yijiang Zhou
- Yongzeng Lai (ORCID: https://orcid.org/0000-0002-1039-7019)
- Lin Li (ORCID: https://orcid.org/0000-0002-1022-5313)
- Zheng Yang (ORCID: https://orcid.org/0009-0007-3992-3346)
Institutions
- Hunan University (CN)
- Hunan University of Technology (CN)
- Wilfrid Laurier University (CA)
Publication Details
- Journal
- Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration
- Published
- 2026-05-21
- DOI
- https://doi.org/10.1002/cjas.70070
- Primary Topic
- Innovation and Knowledge Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Hunan Province