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

嵌入性 供应链 业务 供应链网络 知识转移 产业组织 营销 知识管理 供应链管理 微观经济学 经济 计算机科学 社会学 人类学
作者
Ji Yan,Zihao Yu,Kiran Fernandes,Yu Xiong
出处
期刊:International Journal of Operations & Production Management [Emerald Publishing Limited]
卷期号:43 (8): 1277-1303 被引量:20
标识
DOI:10.1108/ijopm-08-2022-0507
摘要

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.
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