Dual networks: how does knowledge network embeddedness affect firms' supply chain learning?

Purpose: To explore the mechanism that shapes firms' supply chain learning (SCL) practices, this study examines the relationship between firms' knowledge network embeddedness and their SCL practice in a supply chain network, as well as the moderating role of supply chain network cohesion in this relationship. Design/methodology/approach: Using patent application data and supply chain partner information from 869 listed firms between 2011 and 2020 in China, this study uses fixed-effect regression models to reduce endogeneity problems by controlling for individual heterogeneity effects that cannot be observed over time. Findings: Firms' knowledge network embeddedness has an inverted U-shaped effect on their SCL, and this non-linear relationship is conditional on supply chain network cohesion, which strengthens (weakens) the positive (negative) effect of knowledge network embeddedness on SCL. Practical implications: The findings show that managers can reconcile the downsides of knowledge network embeddedness on SCL by fostering greater supply chain network cohesion. Originality/value: Drawing from the network pluralism perspective, this study contributes to supply chain literature by extending the research context of the antecedents of SCL from a single-network setting to a dual-network setting. It extends the network pluralism perspective by showing that not only positive effects but also negative effects of network embeddedness can transfer from one network to another