Whom You Connect With Matters: Innovation Collaboration Network Centrality and Innovative Productivity in Chinese Cities

Cui Zhang, Dandan Zhang, Yu Pan and Yanzhen Wang

Growth and Change, 2025, vol. 56, issue 1

Abstract: This paper introduces eigenvector centrality to capture partner heterogeneity and examines its impact on urban innovation. By constructing and empirically testing a co‐invention patent database of Chinese cities over the period from 2014 to 2018, we find that eigenvector centrality has a positive effect on urban innovation. Technology breadth and technology depth increases are two important underlying mechanisms. A counterfactual analysis shows that laggard cities with low levels of innovation can increase their innovative productivity by establishing collaborative links with other cities, especially with well‐connected cities, which indicates the potential gains from policies that improve the inter‐city innovation collaboration network structure. And this result is further confirmed by the comparative analysis of Erdos and Chifeng.

Date: 2025
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