Article Sidebar

Download
PDF
Statistic
Read Counter : 56 Download : 36

Main Article Content

Abstract

This study explores the synergistic effect of Internet of Things (IoT) and edge computing on the supply chain resilience through technological interaction channels. Based on dynamic capability theory and resource coordination theory, the study employs external data sources such as the World Bank Enterprise Survey, the China Industrial Enterprise Database, and the China Ministry of Industry and Information Technology to investigate the research question. Specifically, it uses panel data from 892 manufacturing and logistics enterprises spanning 2020-2024, employing hierarchical regression and simple slope analysis as the empirical methods. The empirical results show that the application level of either IoT technology or edge computing can significantly improve supply chain resilience, with remarkable synergistic effects when the two technologies are jointly adopted. Edge computing can further improve the efficiency of IoT applications by enabling higher application-level thresholds. Additionally, the synergistic effect between IoT technology and edge computing exhibits industrial heterogeneity in optimizing resilience-building efficiency: the manufacturing industry demonstrates a stronger synergistic effect than the logistics industry. This study formally validates the theoretical mechanism underlying technology application, encompassing real-time sensing, edge analysis, and rapid response. It thereby addresses a critical gap in the existing literature and theoretical framework concerning the "resilience-warning capability-response speed" model. 

Keywords

Supply chain resilience Internet of Things Edge computing Technology collaboration Dynamic capabilities

Article Details

How to Cite
Yu, Z., & Yu, Z. (2025). Research on resilience enhancement mechanism of intelligent supply chain in digital transformation context: synergistic effect of IoT empowerment and edge computing. Future Technology, 5(1), 324–336. Retrieved from https://fupubco.com/futech/article/view/638
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX
Bookmark and Share

References

  1. D. Ivanov, "Transformation of supply chain resilience research through the COVID-19 pandemic," International Journal of Production Research, vol. 62, no. 23, pp. 8217-8238, 2024.
  2. X. Shi, W. Liu, and M. K. Lim, "Supply chain resilience: new challenges and opportunities," International Journal of Logistics Research and Applications, vol. 27, no. 12, pp. 2485-2512, 2024.
  3. B. Huo, D. Li, and M. Gu, "The impact of supply chain resilience on customer satisfaction and financial performance: A combination of contingency and configuration approaches," Journal of Management Science and Engineering, vol. 9, no. 1, pp. 38-52, 2024.
  4. A. Cinti, M. R. Marcone, A. Sabatini, and V. Temperini, "Enhancing supply chain resilience through the supply network approach," Journal of business & industrial marketing, vol. 40, no. 4, pp. 858-876, 2025.
  5. S. A. Hosseini Shekarabi, R. Kiani Mavi, and F. Romero Macau, "Supply chain resilience: A critical review of risk mitigation, robust optimisation, and technological solutions and future research directions," Global Journal of Flexible Systems Management, pp. 1-55, 2025.
  6. Y. Guo, F. Liu, J.-S. Song, and S. Wang, "Supply chain resilience: A review from the inventory management perspective," Fundamental Research, vol. 5, no. 2, pp. 450-463, 2025.
  7. N. Ishii and M. Ohba, "Quantitative evaluation of an information network in a supply chain," International Journal of Production Economics, vol. 261, p. 108889, 2023.
  8. I. Vlachos and G. Graham, "The internet of things in supply chain management: past, present, and future–a systematic literature review and implementation framework," International Journal of Production Research, pp. 1-31, 2025.
  9. V. Varriale, A. Cammarano, F. Michelino, and M. Caputo, "Sustainable supply chains with blockchain, IoT and RFID: A simulation on order management," Sustainability, vol. 13, no. 11, p. 6372, 2021.
  10. M. R. Karim, D. C. Rodgers, and M. A. Hossain, "The Role of Internet of Things (IoT) in Real-Time Supply Chain Monitoring," International Journal of Research and Innovation in Social Science, vol. 8, no. 10, pp. 1800-1816, 2024.
  11. M. Akbari, "Revolutionizing supply chain and circular economy with edge computing: Systematic review, research themes and future directions," Management Decision, vol. 62, no. 9, pp. 2875-2899, 2024.
  12. Q. He, H. Zhao, Y. Feng, Z. Wang, Z. Ning, and T. Luo, "Edge computing-oriented smart agricultural supply chain mechanism with auction and fuzzy neural networks," Journal of Cloud Computing, vol. 13, no. 1, p. 66, 2024.
  13. M. Ghobakhloo, M. Iranmanesh, B. Foroughi, M.-L. Tseng, D. Nikbin, and A. A. Khanfar, "Industry 4.0 digital transformation and opportunities for supply chain resilience: a comprehensive review and a strategic roadmap," Production planning & control, vol. 36, no. 1, pp. 61-91, 2025.
  14. G. Zhang, Y. Yang, and G. Yang, "Smart supply chain management in Industry 4.0: the review, research agenda and strategies in North America," Annals of operations research, vol. 322, no. 2, pp. 1075-1117, 2023.
  15. E. Pessot, A. Zangiacomi, I. Marchiori, and R. Fornasiero, "Empowering supply chains with Industry 4.0 technologies to face megatrends," Journal of Business Logistics, vol. 44, no. 4, pp. 609-640, 2023.
  16. N. Zhao, J. Hong, and K. H. Lau, "Impact of supply chain digitalization on supply chain resilience and performance: A multi-mediation model," International journal of production economics, vol. 259, p. 108817, 2023.
  17. J. He, M. Fan, and Y. Fan, "Digital transformation and supply chain efficiency improvement: an empirical study from a-share listed companies in China," Plos one, vol. 19, no. 4, p. e0302133, 2024.
  18. H. Jing and Y. Fan, "Digital transformation, supply chain integration and supply chain performance: Evidence from Chinese manufacturing listed firms," Sage Open, vol. 14, no. 3, p. 21582440241281616, 2024.
  19. A. Alzahrani and M. Z. Asghar, "Intelligent risk prediction system in IoT-based supply chain management in logistics sector," Electronics, vol. 12, no. 13, p. 2760, 2023.
  20. S. Asaithambi, S. Nallusamy, J. Yang, S. Prajapat, G. Kumar, and P. S. Rathore, "A secure and trustworthy blockchain-assisted edge computing architecture for industrial internet of things," Scientific Reports, vol. 15, no. 1, p. 15410, 2025.
  21. S. Bag, A. Telukdarie, J. C. Pretorius, and S. Gupta, "Industry 4.0 and supply chain sustainability: framework and future research directions," Benchmarking: An International Journal, vol. 28, no. 5, pp. 1410-1450, 2021.
  22. C. Pechlivanis, "Implementing IoT Technology in Practice: Monitoring the Supply Chain for Sustainable Operation," WSEAS Transactions on Systems, vol. 22, pp. 349-359, 2023.
  23. Z. Rehman, N. Tariq, S. A. Moqurrab, J. Yoo, and G. Srivastava, "Machine learning and internet of things applications in enterprise architectures: Solutions, challenges, and open issues," Expert Systems, vol. 41, no. 1, p. e13467, 2024.
  24. M. I. Hossain, S. Talapatra, P. Saha, and H. Belal, "From theory to practice: leveraging digital twin technologies and supply chain disruption mitigation strategies for enhanced supply chain resilience with strategic fit in focus," Global Journal of Flexible Systems Management, vol. 26, no. 1, pp. 87-109, 2025.
  25. G. S. Balan, V. S. Kumar, and S. A. Raj, "Machine Learning and Artificial Intelligence Methods and Applications for Post-Crisis Supply Chain Resiliency and Recovery," Supply Chain Analytics, p. 100121, 2025.
  26. D.-H. Kim, G.-Y. Kim, and S. D. Noh, "Digital Twin-Based Prediction and Optimization for Dynamic Supply Chain Management," Machines, vol. 13, no. 2, p. 109, 2025.
  27. C. Li and H. Chen, "Machine Learning Based Supply Chain Risk Prediction and Management," in Proceeding of the 2024 5th International Conference on Computer Science and Management Technology, 2024, pp. 842-847.
  28. R. U. Attah, B. M. P. Garba, I. Gil-Ozoudeh, and O. Iwuanyanwu, "Enhancing supply chain resilience through artificial intelligence: Analyzing problem-solving approaches in logistics management," International Journal of Management & Entrepreneurship Research, vol. 5, no. 12, pp. 3248-3265, 2024.
  29. K. Sallam, M. Mohamed, and A. W. Mohamed, "Internet of Things (IoT) in supply chain management: challenges, opportunities, and best practices," SMIJ, vol. 2, no. 2, p. 32, 2023.
  30. A. Al-Banna, M. Yaqot, and B. Menezes, "Roadmap to digital supply chain resilience under investment constraints," Production & Manufacturing Research, vol. 11, no. 1, p. 2194943, 2023.