Abstract
The traditional liquor industry is facing a new requirement of promoting high-quality development by technological innovation in China. Cross-regional collaborative innovation among enterprises is one of the key measures. In order to explore how liquor enterprises make proper use of collaborative innovation, this paper analyzes the impact of enterprises’ innovation models and capabilities on collaborative innovation performance from the perspective of knowledge collaboration. Based on the sample of the Chinese liquor invention patents, this paper mainly uses the backward citation data to evaluate enterprises’ independent R &D capability and knowledge search intensity, and carries out a regression test. The results show that the relationship between enterprises’ independent R &D capability and collaborative cross-regional innovation performance is an inverted U-shaped curve; enterprises which search for more dissimilar knowledge may have lower cross-regional collaborative innovation performance. Besides, older enterprises and listed enterprises may have higher collaborative innovation performance. Finally, this paper puts forward some suggestions that large liquor enterprises should undertake the innovation path of independent R &D and consider more export-oriented open innovation; small and medium-sized enterprises can take a high degree of inward external knowledge acquisition and actively strive for cooperative R &D with large enterprises.
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Acknowledgements
This work was supported by National Natural Science Foundation of China [grant number 71904137], Education Department of Sichuan Province [grant number CJZB21-01] and Sichuan University [grant number 2021CXC25].
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Zhang, H., Yang, X., Huang, Z. (2022). Influence Mechanism of Cross-Regional Collaborative Innovation Performance of Chinese Liquor Enterprises—Based on Knowledge Collaboration. In: Xu, J., Altiparmak, F., Hassan, M.H.A., García Márquez, F.P., Hajiyev, A. (eds) Proceedings of the Sixteenth International Conference on Management Science and Engineering Management – Volume 2. ICMSEM 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 145. Springer, Cham. https://doi.org/10.1007/978-3-031-10385-8_16
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