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

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.

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Publication Details

Journal
Sustainability
Published
2025-08-29
DOI
https://doi.org/10.3390/su17177813
Citations
2
Primary Topic
Supply Chain and Inventory Management
Type
article
Field-Weighted Citation Impact
4.57

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article

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

Jingyang Yan, Chao Gao, Yi Tan, Zhimin Du
2 citations
Sustainability
Supply Chain and Inventory Management
4.57
article

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

Jingyang Yan, Chao Gao, Yi Tan, Zhimin Du
article en
2 citations

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.

SustainabilityVol. 17(17)
Central South University of Forestry and Technology (CN), Central South University (CN), Chang'an University (CN), Technical University of Munich (DE)
Xi'an Social Science Fund
Openalex Percentile: Top 5%
Supply Chain and Inventory Management
4.57
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The Impact of Digital Supply Chain Management on Enterprise Total Factor Productivity: Evidence from a Quasi-Natural Experiment in China — Jingyang Yan, Chao Gao, et al. · Sustainability (2025) | TGRS Research Map | TGRS