The Impact of Digital Supply Chain Management on Enterprise Total Factor Productivity: Evidence from a Quasi-Natural Experiment in China

Jingyang Yan, Chao Gao (), Yinan Tan and Zhimin Du ()
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Jingyang Yan: School of Economics and Management, Central South University of Forestry & Technology, Changsha 410004, China
Chao Gao: Department of Public Administration, School of Humanities, Chang’an University, Xi’an 710061, China
Yinan Tan: Engineering Research Center of Highway Infrastructure Digitalization, Ministry of Education, Xi’an 710064, China
Zhimin Du: Department of Public Administration, School of Humanities, Chang’an University, Xi’an 710061, China

Sustainability, 2025, vol. 17, issue 17, 1-16

Abstract: Digital supply chain management (DSCM) has emerged as a critical driver of enterprise performance in the modern economy, yet empirical evidence on its causal impact on productivity remains limited. This study examines how DSCM adoption affects total factor productivity (TFP) by leveraging China’s supply chain innovation pilot program as a quasi-natural experiment. Using a difference-in-differences approach with propensity score matching, the analysis employs a comprehensive dataset of 2843 Chinese A-share listed companies from 2013 to 2022; the analysis reveals that DSCM adoption leads to an average TFP increase of 14.1%. This positive effect strengthens over time, demonstrating a clear dynamic of organizational learning. Mediation analysis indicates that this productivity enhancement operates through two primary channels: innovation capability enhancement (accounting for approximately 35% of the total effect) and cost efficiency improvement (21%). Crucially, heterogeneity analysis reveals that the positive effects of DSCM are significantly more pronounced in supply-chain-intensive industries, such as manufacturing, and for firms with higher R&D intensity. The findings provide robust causal evidence on the productivity effects of DSCM, offering valuable insights into its underlying mechanisms and key boundary conditions for both enterprise strategy and digital transformation policy.

Keywords: digital supply chain management; total factor productivity; difference in differences; innovation capability; quasi-natural experiment; cost efficiency; heterogeneity (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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