Complexity (Jan 2024)

R&D Partner Diversity, Ambidextrous Learning, and Innovation Quality of Firms

  • Zhongtao Zhao,
  • Zhaofeng Yu,
  • Yunwei Li,
  • Jing Tian

DOI
https://doi.org/10.1155/2024/7187690
Journal volume & issue
Vol. 2024

Abstract

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R&D partner diversity (RPD) is crucial for enhancing a firm’s innovation level, with innovation quality being a pivotal indicator of the firm’s overall capacity for innovation. However, the relationship between RPD and innovation quality has received little attention in the literature. This paper aims to unravel the influence of RPD on innovation quality and the underlying mechanisms. We conduct empirical research utilizing data from 463 publicly listed Chinese manufacturing companies to achieve this goal. Using a negative binomial model for data analysis, we find that RPD has a positive impact on the quality of innovation. The micromechanism analysis reveals that both exploratory learning and exploitative learning play a mediating role in the relationship between RPD and innovation quality. Furthermore, we discover that the strength of the relationship between RPD and innovation quality varies depending on the types of R&D partners and corporate ownership. Specifically, firms that collaborate with universities, competitors, users, or research institutes strengthen the positive effect, whereas forming alliances with other entities within the same group mitigates it. RPD has a more significant positive influence on the quality of innovation in non-state-owned enterprises compared to state-owned enterprises. These findings are robust to a battery of sensitivity tests, which provide valuable insights for firms seeking to enhance their innovation quality by fostering diverse R&D partnerships.