Research on The Impact of Intelligent Manufacturing on‎Enterprise ESG Performance:‎ Empirical EvidenceOf Economics from China

  • Authors

    • Chen Xu University of Finance and Economics, Ulaanbaatar, Mongolia and College of Economic and Management, Chifeng University, Chifeng, Inner Mongolia, China
    • Batkhuyag Ganbaatar University of Finance and Economics, Ulaanbaatar, Mongolia
    https://doi.org/10.14419/m0f0bq97

    Received date: January 3, 2026

    Accepted date: January 19, 2026

    Published date: January 23, 2026

  • Intelligent Manufacturing; ESG Performance; Difference-In-Differences; Green Innovation; ‎Resource Allocation Efficiency; Corporate Sustainability; Chi-na

  • Abstract

    Background: The integration of intelligent manufacturing technologies and corporate ‎sustainability has emerged as a critical research frontier in the era of Industry 4.0. While ‎Environmental, Social, and Governance (ESG) performance increasingly shapes corporate ‎valuation and stakeholder relations, the economic mechanisms through which intelligent ‎manufacturing influences ESG outcomes remain theoretically underdeveloped and empirically ‎underexplored, particularly in emerging market contexts where institutional environments ‎differ substantially from developed economies.‎

    Methods: Exploiting China's Intelligent Manufacturing Pilot Demonstration Projects (IMPP) ‎as a quasi-natural experiment, this study employs a staggered difference-in-differences (DID) ‎design with 18,426 firm-year observations from 2,149 Chinese A-share manufacturing ‎companies during 2009-2023. We examine direct effects using two-way fixed effects models, ‎investigate mediating mechanisms through the Baron-Kenny approach supplemented by Sobel ‎tests, and explore heterogeneous effects across ownership structures, pollution intensities, and ‎competitive environments using split-sample analysis with Chow tests for coefficient equality.‎

    Results: Intelligent manufacturing significantly enhances enterprise ESG performance (β = ‎‎0.245, p < 0.01), representing a 5.3% improvement relative to the sample mean. This finding ‎demonstrates robust consistency across parallel trend tests, placebo simulations (500 ‎iterations), propensity score matching (PSM-DID), and instrumental variable (IV-2SLS) ‎estimations. Mechanism analysis reveals three significant transmission channels: green ‎innovation (mediating 24.6% of total effect, β = 0.186, p < 0.01), resource allocation ‎efficiency (16.6%, β = 0.142, p < 0.01), and synergistic governance (7.9%, β = 0.098, p < ‎‎0.05). Heterogeneity analysis demonstrates significantly stronger effects for non-state-owned ‎enterprises (β = 0.312 vs. 0.168, χ² = 8.45, p < 0.01), heavy-polluting industries (β = 0.356 vs. ‎‎0.186, χ² = 12.67, p < 0.01), and high-competition markets (β = 0.298 vs. 0.152, χ² = 5.23, p < ‎‎0.05). Sub-dimensional analysis reveals that environmental performance benefits most ‎substantially (β = 0.324), followed by social (β = 0.218) and governance (β = 0.142) ‎dimensions.‎

    Conclusions: This study establishes intelligent manufacturing as an economically significant ‎pathway for enhancing corporate ESG performance in emerging markets, with heterogeneous ‎effects contingent upon ownership structure, industrial characteristics, and competitive ‎dynamics. These findings advance theoretical understanding of technology-sustainability ‎linkages, provide empirical foundations for evidence-based industrial policy design, and offer ‎practical guidance for managers navigating the dual imperatives of technological ‎transformation and sustainable development‎.

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  • How to Cite

    Xu, C., & Ganbaatar, B. (2026). Research on The Impact of Intelligent Manufacturing on‎Enterprise ESG Performance:‎ Empirical EvidenceOf Economics from China. International Journal of Accounting and Economics Studies, 13(1), 423-435. https://doi.org/10.14419/m0f0bq97