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Leveraging Industry 4.0 technologies for organizational sustainability performance in Chinese firms: an NRBV-mediated model advancing UN SDGs 9 and 12
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  • Published: 21 March 2026

Leveraging Industry 4.0 technologies for organizational sustainability performance in Chinese firms: an NRBV-mediated model advancing UN SDGs 9 and 12

  • Yan Gao1,2,
  • Jinlong Wang3,4,
  • Xiangtang Chen5,
  • Shouping Peng6 &
  • …
  • Sohaib Mustafa7 

Scientific Reports , Article number:  (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Environmental impact
  • Sustainability

Abstract

The rapid integration of Industry 4.0 technologies offers new pathways for Chinese manufacturers to reconcile operational efficiency with environmental stewardship. Grounded in the Natural Resource-Based View (NRBV), this study investigates how digital technologies, Artificial Intelligence/Machine Learning (AIA), Digital Twin Usage (DTU), IoT Integration (IOTI), and Green Technology Adoption (GTA), serve as strategic resources to enhance Sustainable Manufacturing Practices (SMP) and drive Organizational Sustainability Performance (OSP). Analyzing data from 719 firms through structural equation modeling (SEM), the findings reveal significant direct effects of AIA, DTU, GTA, and IOTI on SMP, with SMP fully mediating their impact on OSP. The study advances NRBV by demonstrating how digital technologies function as dynamic capabilities that reconfigure operational practices to achieve sustainability outcomes. Managers should prioritize integrated IoT networks for real‑time monitoring, AI/ML for predictive quality control, digital twins for lifecycle optimization, and green‑technology implementations for energy and material efficiency. While this study does not directly measure SDG-specific indicators, the observed improvements in resource efficiency, emissions reduction, lifecycle optimization, and eco-efficient production practices are conceptually consistent with the objectives of UN Sustainable Development Goals (SDG 9 and 12). Accordingly, SDG alignment should be interpreted as an inferential linkage grounded in firm-level sustainability outcomes rather than as direct evidence of SDG attainment.

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Data availability

The corresponding authors (J.W and S.P) will make the raw data supporting this article’s conclusions available upon request.

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Funding

This research was supported by the Shandong Provincial Education Science "14th Five-Year Plan" Research Project, Grant Number: 2023ZC048.

Author information

Authors and Affiliations

  1. College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, 310023, China

    Yan Gao

  2. Taizhou Vocational College of Science and Technology, Taizhou, 318020, China

    Yan Gao

  3. School of Education, Qufu Normal University, Qufu, 276826, China

    Jinlong Wang

  4. Weifang Engineering Vocational College, Qingzhou, 262500, China

    Jinlong Wang

  5. Library, Wenzhou University of Technology, Wenzhou, 325027, China

    Xiangtang Chen

  6. School of Economics and Trade Management, Wenzhou Vocational College of Science and Technology, Wenzhou, 325000, China

    Shouping Peng

  7. College of Economics and Management, Beijing University of Technology, Beijing, People’s Republic of China

    Sohaib Mustafa

Authors
  1. Yan Gao
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  2. Jinlong Wang
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  3. Xiangtang Chen
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  4. Shouping Peng
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Contributions

Conceptualization, Y.G. and S.M.; methodology, J.W.; software, S.P.; validation, Y.G. and X.C.; formal analysis, S.P.; investigation, Y.G.; resources, S.P., Y.G. and X.C.; data curation, S.M., S.P., Y.G. and X.C..; writing—original draft preparation, J.W.; writing—review and editing, J.W.; visualization. All authors have read and agreed to the published version of the manuscript.

Corresponding authors

Correspondence to Jinlong Wang or Shouping Peng.

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The authors declare no competing interests.

Institutional review board statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of Zhejiang University of Technology.

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Informed consent was obtained from all subjects involved in the study.

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Gao, Y., Wang, J., Chen, X. et al. Leveraging Industry 4.0 technologies for organizational sustainability performance in Chinese firms: an NRBV-mediated model advancing UN SDGs 9 and 12. Sci Rep (2026). https://doi.org/10.1038/s41598-026-42871-8

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  • Received: 26 April 2025

  • Accepted: 27 February 2026

  • Published: 21 March 2026

  • DOI: https://doi.org/10.1038/s41598-026-42871-8

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Keywords

  • Industry 4.0
  • Internet of Things (IoT) integration
  • AI/ML adoption
  • Digital twin usage
  • Green technology adoption
  • Sustainable manufacturing practices
  • Organizational sustainability performance
  • SDGs 9 and 12
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