Empowering Manufacturing Industry Chain Resilience through Digital-Intelligence Integration: A Resource Orchestration and Dynamic Capabilities Perspective

Abstract

In the context of escalating global supply chain disruptions, geopolitical fragmentation, and rapid technological change, enhancing the resilience of the manufacturing industry chain has become a critical strategic priority for major industrial economies. This study investigates the theoretical mechanisms and empirical impacts of Digital-Intelligence Integration (DI)—the deep, synergistic fusion of digital infrastructures and intelligent technologies—on manufacturing industry chain resilience. We establish an analytical framework drawing upon Dynamic Capabilities Theory and Resource Orchestration Theory to explain how DI builds systemic adaptive capacity. Using a balanced panel dataset of 31 Chinese provinces over the period 2011–2024, we construct comprehensive evaluation indices for DI and manufacturing resilience using the Quadratic Entropy Method, which incorporates time-dimension information entropy to ensure dynamic consistency. Utilizing a two-way fixed-effects panel model, our baseline regressions reveal that DI significantly promotes manufacturing industry chain resilience. This positive relationship remains robust across multiple verification tests, including the exclusion of the COVID-19 pandemic year, the exclusion of direct-controlled municipalities, one-period lagged independent variables, and alternative measurements of resilience. To address endogeneity, we employ two-stage least squares (2SLS) estimation using legacy post office density in 1984 and capital-to-coast geographic distance as external instruments. Sub-dimensional analyses show that the driving power of the industry chain receives the largest enhancement from DI, followed by stabilizing power and recovery power, as confirmed by Seemingly Unrelated Regression (SUR) Wald tests. Mechanism analysis indicates that DI fosters resilience through three main channels: stimulating breakthrough innovation, optimizing the business environment, and promoting industrial agglomeration. Geographic and development heterogeneity tests show that the resilience-enhancing effect of DI is most pronounced in the Central region, in high-DI adoption areas, and in regions with high levels of industrial agglomeration. These findings provide empirical support and policy implications for utilizing digital-intelligence technologies to secure supply chain stability and promote high-quality industrial development.