Impact of Enterprise Innovation Network Characteristics on Relationship Learning: Mediating Effect of Absorptive Capacity
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Through analyzing the relationship among innovation network characteristics, enterprise absorptive capacity and relationship learning, this study constructs a theoretical model about the impact of enterprise innovation network characteristics on relationship learning, and further introduces absorptive capacity as a mediating variable to discuss the mechanism among them. Based on a sample data of 205 questionnaires, the empirical results show that the relationship strength and relationship quality of enterprise innovation network characteristics have positive impact on relationship learning. Three dimensions of absorptive capacity, namely, knowledge acquisition capacity, knowledge digestion capacity and knowledge application capacity, have positive effects on relationship learning. Among the characteristics of enterprise innovation network, network size, network centrality and relationship quality have positive influence on absorptive capacity of enterprises. Knowledge acquisition capacity, knowledge digestion capacity and knowledge application capacity play a partial mediating role in the influence of relationship strength and relationship quality on relationship learning.
KeywordsInnovation network characteristics Absorptive capacity Relationship learning
This work was supported by National Natural Science Foundation of China [grant number 71904137] and Ministry of Education of the People’s Republic of China [grant number 18YJC630227].
- 2.Chesbrough, H.W.: Open Innovation: The New Imperative for Creating and Profiting from Technology. Harvard Business Press, Brighton (2003)Google Scholar
- 7.Hongbin, D., Zhengbin, W.: An empirical study on the network structure’s impact to the firm growth performance: the intermediary role of exploitative learning and explorative learning. Nankai Bus. Rev. 14(3), 15–25 (2011). (in Chinese)Google Scholar
- 8.Ibarra, H.: Network centrality, power, and innovation involvement: determinants of technical and administrative roles. Acad. Manag. J. 36(3), 471–501 (1993)Google Scholar
- 15.Madani, F., Daim, T., Weng, C.: ‘Smart building’ technology network analysis: applying core-periphery structure analysis. Int. J. Manag. Sci. Eng. Manag. 12(1), 1–11 (2017)Google Scholar
- 16.Nan, G., Wei, J., Hu, H.: Analysis of the multi-agent’s relationship in collaborative innovation network for science and technology SEMs based on evolutionary game theory. Int. J. Inf. Tchnology Manag. 18(1), 1–15 (2019)Google Scholar
- 18.Rampersad, G., Quester, P., Troshani, I.: Developing and evaluating scales to assess innovation networks. Int. J. Technol. Intell. Plan. 5(4), 402–420 (2009)Google Scholar
- 19.Ren, S., Wu, J., Wang, L.W.: A study on network embeddedness and enterprise’s innovation performance: test of the moderating effect of network competence. R&D Manag. 23, 16–24 (2011). (in chinese)Google Scholar
- 25.Ye, Z., Zheng, J.: Network characteristics and corporate entrepreneurship of cluster enterprises: an empirical study based on entrepreneurial competence. Sci. Res. Manag. 35(1), 58–65 (2014). (in Chinese)Google Scholar