Disentangling the Intelligentization–Carbon Emission Nexus within China’s Logistics Sector: An Econometric Approach

Abstract

Amidst the global pursuit of environmental sustainability, the concurrent trends of decarbonization and intelligentization have emerged as critical strategic priorities. However, the interplay between these phenomena, particularly within the logistics sector, remains an underexplored area. This study investigates the complex dynamics between logistics intelligentization and decarbonization across 29 provinces in China from 2006 to 2019, providing a fresh perspective on a globally relevant issue. By employing Differential GMM, Systematic GMM, and instrumental variable-based GMM models, we evaluate the impact of logistics intelligence on carbon emissions while effectively addressing endogeneity issues inherent in the empirical analysis. Our findings reveal that the advancement of intelligent logistics correlates positively with increased carbon emissions, highlighting a significant incompatibility between decarbonization objectives and intelligentization efforts within the logistics sector. Additionally, we identify mediating pathways—specifically scale, structure, and technology effects—and moderating mechanisms that influence this relationship. These insights underscore the need for policymakers to establish environmental standards for intelligent technology adoption and to promote initiatives that reconcile intelligentization with sustainability goals. Ultimately, our study provides critical guidance for promoting sustainable and smart industrial growth in the logistics sector.