Emergency Management

Emergency Management

A Framework for Enhancing Supply Chain Resilience through Disruptive Technologies

Document Type : Original Article

Authors
Hassan Torabi 1
ََAmirreza Taghiloo 2
Mohammadreza Kholosi Aram 2
1 Assist. Prof., Dept. of Industrial Engineering, Faculty of Management and Industrial Engineering, Malek Ashtar University of Technology, Tehran, Iran.
2 MSc. Student in Business Administration, Dept. of Management, Faculty of Management and Industrial Engineering, Malek Ashtar University of Technology, Tehran, Iran.
Abstract
Modern supply chains face increasing challenges such as climate disruptions, crises of outbreak diseases, unexpected events, political and economic instability, and rapid technological developments. These challenges can lead to significant disruptions and risks to supply chain performance. To encounter these challenges, more resistant and resilient supply chains are needed. Disruptive technologies such as artificial intelligence, blockchain, and the Internet of Things have significant potential to improve supply chain resilience. These technologies can provide supply chains with greater visibility and transparency. Systematically reviewing previous studies and echoing the call, this research, which is developmental-applied, qualitative, and documentary regarding the purpose, nature of the data, and the methods of data and information collection tries to investigate the impact of the aforementioned disruptive technologies on the resilience of the defense supply chain with the method of meta-synthesizing the results. This method starts with the question and while searching the literature and evaluating the input, synthesizes the findings and reaches the reflection stage by presenting the results. In the first stage, the questions were asked based on the analysis of the synonyms. Then by searching the literature, evaluating the input, and synthesizing the findings, the results were obtained which indicate fact that the most important ways to improve the resilience of the supply chain through disruptive technologies include: "Prediction and risk management utilizing artificial intelligence algorithms", "increasing the transparency of blockchain as a distributed database", "improving performance and optimizing processes using artificial intelligence and the Internet of Things", and, "increasing the security of the supply chain network by blockchain". When integrated and applied to the supply chain, these technologies can significantly promote the resilience of supply chains.
Keywords
Supply Chain Resilience
Disruptive Technologies
Meta-Synthesis
Artificial Intelligence
Blockchain
Internet of Things
Subjects
  1. Wieland, A. (2021). Dancing the supply chain: Toward transformative supply chain management. Journal of Supply Chain Management, 57(1), 58-73.
  2. Sharma, K., Kumar, R., Kumar, A., Balabantaray, S. & Arora, M. (2024). A digital ecosystem for sustainable fruit supply chain in Uttarakhand: a comprehensive review. Environment, Development and Sustainability, 26(5), 13217-13252.
  3. Moslehi, S., & Reddy, T. A. (2018). Sustainability of integrated energy systems: A performance-based resilience assessment methodology. Applied energy, 228, 487-498.
  4. Negri, M., Cagno, E., Colicchia, C. & Sarkis, J. (2021). Integrating sustainability and resilience in the supply chain: A systematic literature review and a research agenda. Business Strategy and the environment, 30(7), 2858-2886.
  5. Bednarski, L., Roscoe, S., Blome, C. & Schleper, M. C. (2024). Geopolitical disruptions in global supply chains: a state-of-the-art literature review. Production Planning & Control, 1-27.
  6. Leng, J., Zhong, Y., Lin, Z., Xu, K., Mourtzis, D., Zhou, X. & Shen, W. (2023). Towards resilience in Industry 5.0: A decentralized autonomous manufacturing paradigm. Journal of Manufacturing Systems, 71, 95-114.
  7. Su, W. & Junge, S. (2023). Unlocking the recipe for organizational resilience: A review and future research directions. European Management Journal, 41(6), 1086-1105.

8.Garrido-Moreno, A., Martín-Rojas, R. & García-Morales, V. J. (2024). The key role of innovation and organizational resilience in improving business performance: A mixed-methods approach. International Journal of Information Management, 77, 102777.

9. Jiang, Y., Feng, T. & Huang, Y. (2024). Antecedent configurations toward supply chain resilience: The joint impact of supply chain integration and big data analytics capability. Journal of Operations Management, 70(2), 257-284.

10. Piprani, A. Z., Khan, S. A. R. & Yu, Z. (2024). Driving success through digital transformation: influence of Industry 4.0 on lean, agile, resilient, green supply chain practices. Journal of Manufacturing Technology Management.

11. Qiao, W., Ma, X., Liu, Y. & Deng, W. (2022). Resilience evaluation of maritime liquid cargo emergency response by integrating FRAM and a BN: A case study of a propylene leakage emergency scenario. Ocean Engineering, 247, 110584.

12. Iftikhar, A., Ali, I., Arslan, A. & Tarba, S. (2024). Digital innovation, data analytics, and supply chain resiliency: A bibliometric-based systematic literature review. Annals of Operations Research, 333(2), 825-848.

  1. Ambulkar, S., Blackhurst, J. & Grawe, S. (2015). Firm's resilience to supply chain disruptions: Scale development and empirical examination. Journal of operations management, 33, 111-122.
  2. Michelman, P. & Sheffi, Y. (2007). Building a resilient supply chain. Business Review.
  3. Craighead, C. W., Blackhurst, J., Rungtusanatham, M. J. & Handfield, R. B. (2007). The severity of supply chain disruptions: design characteristics and mitigation capabilities. Decision sciences, 38(1), 131-156.
  4. Ivanov, D. & Dolgui, A. (2021). A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0. Production Planning & Control, 32(9), 775-788.
  5. Craven, M., Liu, L., Mysore, M. & Wilson, M. (2020). COVID-19: Implications for business. McKinsey & Company, 8.
  6. Sarkis, J. (2020). Supply chain sustainability: learning from the COVID-19 pandemic. International Journal of Operations & Production Management, 41(1), 63-73.
  7. Handfield, R. B., Graham, G. & Burns, L. (2020). Corona virus, tariffs, trade wars and supply chain evolutionary design. International Journal of Operations & Production Management, 40(10), 1649-1660.
  8. Paul, S. K. & Chowdhury, P. (2021). A production recovery plan in manufacturing supply chains for a high-demand item during COVID-19. International Journal of Physical Distribution & Logistics Management, 51(2), 104-125.
  9. 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, 57(3), 829-846.
  10. Linton, T. & Vakil, B. (2020). Coronavirus is proving we need more resilient supply chains. Harvard business review, 5(5), 121-129.
  11. Dubey, R., Gunasekaran, A., Childe, S. J., Bryde, D. J., Giannakis, M., Foropon, C. & Hazen, B. T. (2020). Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations. International journal of production economics, 226, 107599.
  12. Hendricks, K. B., Singhal, V. R. & Zhang, R. (2009). The effect of operational slack, diversification, and vertical relatedness on the stock market reaction to supply chain disruptions. Journal of operations management, 27(3), 233-246.
  13. Dubey, R., Ali, S. S., Aital, P. & Venkatesh, V. G. (2014). Mechanics of humanitarian supply chain agility and resilience and its empirical validation. International Journal of Services and Operations Management, 17(4), 367-384.
  14. Toorajipour, R., Sohrabpour, V., Nazarpour, A., Oghazi, P. & Fischl, M. (2021). Artificial intelligence in supply chain management: A systematic literature review. Journal of Business Research, 122, 502-517.
  15. Riahi, Y., Saikouk, T., Gunasekaran, A. & Badraoui, I. (2021). Artificial intelligence applications in supply chain: A descriptive bibliometric analysis and future research directions. Expert Systems with Applications, 173, 114702.

28- پارسا، خادم، رضایی، محمودزاده و ابراهیم. (2024). بررسی الزامات زنجیره تأمین دفاعی تاب‌آور با تأکید بر فناوری‌های نوظهور صنعت 4. فصلنامه آماد و فناوری دفاعی, 6(4), 11-40.‎

  1. Aghaee, M. & Jazini, A. (2023). A Hybrid Model of Agile and Resilient Logistics in Police Organizations Using the Thematic Analysis Method. Industrial Management Studies, 21(68), 121-152.
  2. Phadnis, S. (2024). A review of research on supply chain adaptability: Opening the black box. Journal of Business Logistics, 45(1), e12370.
  3. Ponomarov, S. Y. & Holcomb, M. C. (2019). Understanding the concept of supply chain resilience. The international journal of logistics management, 20(1), 124-143.

32- رحیمی، راد، عباس، عالم تبریز و موتمنی. (2018). ارائه مدل ساختاری تفسیری زنجیره تأمین تاب‌آور در صنایع دفاعی ایران. فصلنامه مدیریت نظامی، 18(71), 31-70.‎

  1. Rajesh, R. (2016). Forecasting supply chain resilience performance using grey prediction. Electronic Commerce Research and Applications, 20, 42-58.
  2. Hohenstein N. O., Feisel E., Hartmann E. & Giunipero L. (2015) "Research on the phenomenon of supply chain resilience: a systematic review and paths for further investigation"; International Journal of Physical Distribution & Logistics Management, 45(1/2).
  3. Gupta, S., Modgil, S., Meissonier, R. & Dwivedi, Y. K. (2021). Artificial intelligence and information system resilience to cope with supply chain disruption. IEEE Transactions on Engineering Management.
  4. Belhadi, A., Mani, V., Kamble, S. S., Khan, S. A. R. & Verma, S. (2024). Artificial intelligence-driven innovation for enhancing supply chain resilience and performance under the effect of supply chain dynamism: an empirical investigation. Annals of Operations Research, 333(2), 627-652.

37- محمدحسین کریمی گوارشکی، اکبر رحیمی و فریبا طالبی.1402."ارائه مدل ساختاری تفسیری جامع موانع ‏‏تاب‏آوری زنجیره تأمین".95- شماره 23 -بهار و تابستان 1402- دو فصلنامه علمی و پژوهشی.

38- عابدی جعفری، عابد، و امیری. (2019). فراترکیب، روشی برای سنتز مطالعات کیفی. روش‌شناسی علوم انسانی، 25(99), 73-87.‎

39- درخشی خواجه، جبارزاده و یونس. (2020). توسعه مدل علّی عوامل تأثیرگذار بر تاب‌آوری زنجیره تأمین. نشریه علمی مدیریت زنجیره تأمین، 22(68), 56-73.‎

40- پارسا، خادم، رضایی، محمودزاده و ابراهیم. (2024). بررسی الزامات زنجیره تأمین دفاعی تاب‌آور با تأکید بر فناوری‌های نوظهور صنعت 4. فصلنامه آماد و فناوری دفاعی، 6(4), 11-40.‎

  1. Sepehri, K. J., Mohtadi, M. M. & GHASEMI, N. Y. (2023). Identification and ranking of effective key criteria in supply chain resilience (case study: Isar Support Company).

[42] Rahimi, A., Boshehri, A. & Jafarian, A. (2021). Providing a Resilience Supply Chain Model in PANHA Company. Journal of Industrial Management Studies, 19 (63), 85-124.

43- محمدی فاتح، اصغر و مهدوی، علی،1402، شناسایی و طبقه‌بندی کاربردهای فناوری‌های شالوده شکن در جنگ‌های آینده (موردمطالعه: ارتش جمهوری اسلامی ایران)، اولین همایش ملی فرماندهی و مدیریت در جنگ‌های آینده، تهران

  1. Ahmed, T., Karmaker, C. L., Nasir, S. B., Moktadir, M. A. & Paul, S. K. (2023). Modeling the artificial intelligence-based imperatives of industry 5.0 towards resilient supply chains: A post-COVID-19 pandemic perspective. Computers & Industrial Engineering, 177, 109055.
  2. Belhadi, A., Mani, V., Kamble, S. S., Khan, S. A. R. & Verma, S. (2024). Artificial intelligence-driven innovation for enhancing supply chain resilience and performance under the effect of supply chain dynamism: an empirical investigation. Annals of Operations Research, 333(2), 627-652.
  3. Zamani, E. D., Smyth, C., Gupta, S. & Dennehy, D. (2023). Artificial intelligence and big data analytics for supply chain resilience: a systematic literature review. Annals of Operations Research, 327(2), 605-632.
  4. Gupta, S., Modgil, S., Meissonier, R. & Dwivedi, Y. K. (2021). Artificial intelligence and information system resilience to cope with supply chain disruption. IEEE Transactions on Engineering Management.
  5. Dash, R., McMurtrey, M., Rebman, C. & Kar, U. K. (2019). Application of artificial intelligence in automation of supply chain management. Journal of Strategic Innovation and Sustainability, 14(3).
  6. Sullivan, Y. & Wamba, S. (2022). Artificial intelligence, firm resilience to supply chain disruptions, and firm performance.
  7. Modgil, S., Singh, R. K. & Hannibal, C. (2022). Artificial intelligence for supply chain resilience: learning from Covid-19. The International Journal of Logistics Management, 33(4), 1246-1268.
  8. Min, H. (2019). Blockchain technology for enhancing supply chain resilience. Business Horizons, 62(1), 35-45.
  9. Al-Talib, M., Melhem, W. Y., Anosike, A. I., Reyes, J. A. G. & Nadeem, S. P. (2020). Achieving resilience in the supply chain by applying IoT technology. Procedia Cirp, 91, 752-757.

  • Receive Date 21 July 2024
  • Revise Date 20 November 2024
  • Accept Date 16 November 2024