Ego-network embeddedness, stability of supply chain network and innovation performance

The purpose of this paper is to explores the impact of supply chain network membership mobility on the relationship between network embeddedness and innovation performance from a dynamic perspective by introducing supply chain network stability. Utilizing annual report data from 2399 China-listed manufacturing firms (2019-2021), this study constructs a supply chain ego-network. Empirical tests are conducted to examine dynamic network membership changes, and spatial autocorrelation analysis is used for pre-testing. The study reveals a nonlinear relationship between supply chain network embeddedness and innovation performance. Network stability significantly moderates this relationship, and network embeddedness influences innovation performance through a transmission mechanism of absorptive capacity. This study constructs supply chain network distance weight matrix to assess the spatial autocorrelation of knowledge spillovers and provides a pre-testing. It provides a mechanistic perspective on the dual impact of supply chain network embeddedness and network stability on innovation performance, considering the changes in the composition of members in the dynamic supply chain network. The study implies that firms can optimize their network embeddedness to boost innovation, tailored to their industry characteristics. Additionally, by determining their supply chain stability, firms can enhance their innovation performance.