ISSN: 2226-3624
Open access
This study investigates the impact of digital transformation (DT) on supply chain efficiency (SCE) in Chinese listed manufacturing firms using panel data from 2014–2023. Employing two-way fixed-effects and instrumental variable models, results show that DT significantly improves SCE. Mediation analysis reveals that this effect operates through two key mechanisms: enhancing technology development rate (TDR) and improving operational management efficiency (OME). Robustness checks with alternative variables confirm the consistency of the findings. The study highlights the strategic value of integrating digital tools into innovation and management processes, offering empirical evidence for policy support and enterprise decision-making to foster end-to-end digital adoption in manufacturing supply chains.
Ahmed, A. M., Sharif, N. A., Ali, M. N., & Hágen, I. (2023). Effect of Firm Size on the Association between Capital Structure and Profitability. Sustainability, 15(14), Article 14. https://doi.org/10.3390/su151411196
Ahmed, M. S., Vivek, S. D., & Chabukswar, R. D. (2025). Emerging Disruptive Technologies (EDTs) and Contemporary Supply Chains. In M. S. Mubarik & S. A. Khan (Eds.), Smart Supply Chain Management: Design, Methods and Impacts (pp. 29–52). Springer Nature. https://doi.org/10.1007/978-981-96-1333-5_3
Alonge, E. O., Eyo-Udo, N. L., Ubanadu, B. C., Daraojimba, A. I., Balogun, E. D., & Ogunsola, K. O. (2021). Real-Time Data Analytics for Enhancing Supply Chain Efficiency. International Journal of Multidisciplinary Research and Growth Evaluation., 2(1), 759–771. https://doi.org/10.54660/.IJMRGE.2021.2.1.759-771
Areo, G. (2024). The Impact of Artificial Intelligence on Supply Chain Optimization in SMEs.
Ayomide, A. S., & Ozurumba, E. (2024). ARTIFICIAL INTELLIGENCE IN ADVANCED PROCESS OPTIMIZATION AND SMART MANUFACTURING SYSTEMS. 08(11).
Chan, W. H., Fok, C. K., Liu, L., & Wei, L. (2023). Retailers’ Inventory Turnover and Suppliers’ Investment Efficiency. Available at SSRN 4545555.
Chukwudi, N. (2024). Impact of Digitalization on Firm Performance in the Manufacturing Sector: A Case Study of Nigeria. International Journal of Strategic Management, 3(1), Article 1. https://doi.org/10.47604/ijsm.2480
Feng, C., & Ali, D. A. (2024a). IMPROVING THE ORGANIZATIONAL EFFICIENCY OF MANUFACTURING ENTERPRISES - THE ROLE OF DIGITAL TRANSFORMATION, RESOURCE PLANNING (ERP), AND BUSINESS PRACTICES. Journal of Law and Sustainable Development, 12(3), e2439–e2439. https://doi.org/10.55908/sdgs.v12i3.2439
Feng, C., & Ali, D. A. (2024b). LEVERAGING DIGITAL TRANSFORMATION AND ERP FOR ENHANCED OPERATIONAL EFFICIENCY IN MANUFACTURING ENTERPRISES. Journal of Law and Sustainable Development, 12(3), e2455–e2455. https://doi.org/10.55908/sdgs.v12i3.2455
Ferrari, A. (2023). Inventories, demand shocks propagation and amplification in supply chains. ArXiv. Org, 2205.03862.
Fu, S., Ge, Y., Hao, Y., Peng, J., & Tian, J. (2024). Energy supply chain efficiency in the digital era: Evidence from China’s listed companies. Energy Economics, 134, 107597. https://doi.org/10.1016/j.eneco.2024.107597
Ghazal, S., Aziz, T., Tabash, M. I., & Drachal, K. (2024). The Linkage between Corporate Research and Development Intensity and Stock Returns: Empirical Evidence. Journal of Risk and Financial Management, 17(5), Article 5. https://doi.org/10.3390/jrfm17050180
Ha, L. T., Huong, T. T. L., & Thanh, T. T. (2022). Is digitalization a driver to enhance environmental performance? An empirical investigation of European countries. Sustainable Production and Consumption, 32, 230–247. https://doi.org/10.1016/j.spc.2022.04.002
Hao, X., Li, Y., Ren, S., Wu, H., & Hao, Y. (2023). The role of digitalization on green economic growth: Does industrial structure optimization and green innovation matter? Journal of Environmental Management, 325, 116504. https://doi.org/10.1016/j.jenvman.2022.116504
He, J., Fan, M., & Fan, Y. (2024). Digital transformation and supply chain efficiency improvement: An empirical study from a-share listed companies in China. PLOS ONE, 19(4), e0302133. https://doi.org/10.1371/journal.pone.0302133
Ivanov, D., Dolgui, A., & Sokolov, B. (2019). The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics. International Journal of Production Research. https://www.tandfonline.com/doi/abs/10.1080/00207543.2018.1488086
Jiang, R., Su, Z., Hu, S., Yin, H.-T., & Chang, C.-P. (2024). How firm’s perception of economic policy uncertainty influences innovation quality. Economics of Innovation and New Technology, 0(0), 1–18. https://doi.org/10.1080/10438599.2024.2354442
Li, S. (2025). The Impact of Digital Transformation on ESG: Evidence from the Listed Companies in China. Advances in Economics, Management and Political Sciences, 162(1), 168–177. https://doi.org/10.54254/2754-1169/2025.20390
Liu, C., Cai, W., Zhang, C., & Wei, F. (2023). Data-driven intelligent control system in remanufacturing assembly for production and resource efficiency. The International Journal of Advanced Manufacturing Technology, 128(7), 3531–3544. https://doi.org/10.1007/s00170-023-12080-y
Liu, M., Yang, H., & Zheng, S. (2024). Index construction and application of digital transformation in the insurance industry: Evidence from China. PLOS ONE, 19(1), e0296899. https://doi.org/10.1371/journal.pone.0296899
Liu, Y., & He, Z. (2024). Synergistic industrial agglomeration, new quality productive forces and high-quality development of the manufacturing industry. International Review of Economics & Finance, 94, 103373. https://doi.org/10.1016/j.iref.2024.103373
Maheshwari, S., & Naik, D. R. (2024). Efficiency in Operations of NASDAQ Listed Technology Companies from 2011 to 2023. Journal of Risk and Financial Management. https://doi.org/10.3390/jrfm17050205
Mansour, M., Al Zobi, M. K., Al-Naimi, A., & Daoud, L. (2023). The connection between Capital structure and performance: Does firm size matter? Investment Management & Financial Innovations, 20(1), 195.
Negi, S. (2020). Supply chain efficiency framework to improve business performance in a competitive era. Management Research Review, 44(3), 477–508. https://doi.org/10.1108/MRR-05-2020-0272
Nour, S., & Arbussà, A. (2024). Driving innovation through organizational restructuring and integration of advanced digital technologies: A case study of a world-leading manufacturing company. European Journal of Innovation Management, ahead-of-print(ahead-of-print). https://doi.org/10.1108/EJIM-02-2024-0156
Owusu-Berko, L. (2025). Advanced supply chain analytics: Leveraging digital twins, IoT and blockchain for resilient, data-driven business operations.
Patil, D. (2024). Artificial Intelligence-Driven Predictive Maintenance In Manufacturing: Enhancing Operational Efficiency, Minimizing Downtime, And Optimizing Resource Utilization (SSRN Scholarly Paper 5057406). Social Science Research Network. https://doi.org/10.2139/ssrn.5057406
Prabha, B., SHAHU, R., VT, S., VASOYA, A., SATHUA, J., MOHAPATRA, M. R., KALIAPPAN, S., & TIWARI, M. (2024). IoT based Data-Driven Methodology for Real Time Production Optimization and Supply Chain Visibility in Smart Manufacturing and Logistics.
Qureshi, M. R. N. M. (2022). Evaluating Enterprise Resource Planning (ERP) Implementation for Sustainable Supply Chain Management. Sustainability, 14(22), Article 22. https://doi.org/10.3390/su142214779
Sun, B., Zhang, Y., Zhu, K., Mao, H., & Liang, T. (2024). Is faster really better? The impact of digital transformation speed on firm financial distress: Based on the cost-benefit perspective. Journal of Business Research, 179, 114703. https://doi.org/10.1016/j.jbusres.2024.114703
Tripathi, V., Chattopadhyaya, S., Mukhopadhyay, A., Saraswat, S., Sharma, S., Li, C., & Rajkumar, S. (2022). Development of a data-driven decision-making system using lean and smart manufacturing concept in industry 4.0: A case study. Mathematical Problems in Engineering, 2022(1), 3012215.
Uche Nweje & Moyosore Taiwo. (2025). Leveraging Artificial Intelligence for predictive supply chain management, focus on how AI- driven tools are revolutionizing demand forecasting and inventory optimization. International Journal of Science and Research Archive, 14(1), 230–250. https://doi.org/10.30574/ijsra.2025.14.1.0027
Wang, Q., Yuan, S., Ostic, D., & Pan, L. (2023). Supply chain finance and innovation efficiency: An empirical analysis based on manufacturing SMEs. PLOS ONE, 18(7), e0286068. https://doi.org/10.1371/journal.pone.0286068
Wang, X., Kumar, V., Kumari, A., & Kuzmin, E. (2022). Impact of Digital Technology on Supply Chain Efficiency in Manufacturing Industry. In V. Kumar, J. Leng, V. Akberdina, & E. Kuzmin (Eds.), Digital Transformation in Industry (pp. 347–371). Springer International Publishing. https://doi.org/10.1007/978-3-030-94617-3_25
Wang, Z., Lin, S., Chen, Y., Lyulyov, O., & Pimonenko, T. (2023). Digitalization Effect on Business Performance: Role of Business Model Innovation. Sustainability, 15(11), Article 11. https://doi.org/10.3390/su15119020
Wu, F., Hu, H., Lin, H., & Ren, X. (2021). Enterprise digital transformation and capital market performance: Empirical evidence from stock liquidity. Management World, 37(7), 130–144.
Yang, B., Xu, J., Dai, Y., Zhang, Y., & Geng, P. (2025). Commodity financialization and firm investment:Implications for market efficiency and economic stability in emerging markets. International Review of Economics & Finance, 99, 103957. https://doi.org/10.1016/j.iref.2025.103957
Yang, M., Fu, M., & Zhang, Z. (2021). The adoption of digital technologies in supply chains: Drivers, process and impact. Technological Forecasting and Social Change, 169, 120795. https://doi.org/10.1016/j.techfore.2021.120795
Zhao, N., Hong, J., & Lau, K. H. (2023). Impact of supply chain digitalization on supply chain resilience and performance: A multi-mediation model. International Journal of Production Economics, 259, 108817. https://doi.org/10.1016/j.ijpe.2023.108817
Guangxia, M., & Jaafar, H. (2025). Digital Transformation’s Impact on Supply Chain Efficiency: Evidence from China’s Listed Manufacturing Firms. International Journal of Academic Research in Economics and Management Sciences, 14(2), 1-15.
Copyright: © 2025 The Author(s)
Published by HRMARS (www.hrmars.com)
This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at: http://creativecommons.org/licences/by/4.0/legalcode