Management or technology? Firms’ embeddedness in dual talent flow networks and their innovation performance

Abstract

This paper examines the complex relationship between different types of talent flow networks and firms’ innovation. Based on the social network theory and human capital theory, we divide the talent flow networks into “management talent flow networks” and “technical talent flow networks”. The paper then investigates the potential interacting effect and matching effect between the two types of networks when they influence the innovation of firms. The empirical results, which draw from LinkedIn (China) resume data show that: (1) in both management talent flow networks and technical talent flow networks, higher degree of centrality and larger structural hole indexes can enhance firms’ innovation performance; (2) there is significant interacting effect between management talent flow networks and technical talent flow networks in their influence on firms’ innovation. That is, the interaction between firms’ centrality in management talent flow networks and technical talent flow networks, and the interaction between firms’ structural hole indexes in the two networks can both enhance their innovation performance; (3) there is also noteworthy matching effect between the two network types. That is, firms with balanced degree centrality (high-high, or low-low) and balanced structural hole indexes (high-high, or low-low) in management talent flow networks and technical talent flow networks exhibit better innovation performance than those with imbalanced degree centrality (high-low, or low-high) and structural hole indexes (high-low, or low-high) in the two networks. This paper contributes to the classification research on talent flow networks, and deepens our understanding of the complex influencing mechanism between talent flow networks and firms’ innovation. Moreover, it provides managerial implications for firms to improve innovation performance via talent flow management.