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《山东大学学报(理学版)》 ›› 2026, Vol. 61 ›› Issue (8): 154-163.doi: 10.6040/j.issn.1671-9352.0.2025.033

• • 上一篇    

基于DEMATEL-ISM-MICMAC方法的供应链韧性影响因素分析

朱新建1,刘媛媛2,3,刘心缘2,3,李轩睿1,王彪2,3,宋宁宁1*   

  1. 1.山东省交通科学研究院, 山东 济南 250031;2.山东大学管理学院, 山东 济南 250100;3.山东省高等学校数智管理与决策模拟实验室, 山东 济南 250100
  • 发布日期:2026-08-12
  • 通讯作者: 宋宁宁(1991— ),女,工程师,硕士,研究方向为交通运输规划与管理. E-mail:songningning0405@163.com
  • 作者简介:朱新建(1994— ),男,工程师,硕士,研究方向为交通运输规划与管理. E-mail:1242713125@qq.com*通信作者:宋宁宁(1991— ),女,工程师,硕士,研究方向为交通运输规划与管理. E-mail:songningning0405@163.com
  • 基金资助:
    国家自然科学基金重点项目(72134004)

Analysis of supply chain resilience influencing factors based on the DEMATEL-ISM-MICMAC method

  1. 1. Shandong Provincial Transportation Science Research Institute, Jinan 250031, Shandong, China;
    2. Shandong University, Jinan 250100, Shandong, China;
    3. The Digitalized &
    Intelligent Management and Decision Simulation Laboratory of Colleges and Universities in Shandong Province, Jinan 250100, Shandong, China
  • Published:2026-08-12

摘要: 从复杂系统视角出发,构建以解释结构模型(interpretive structural modeling, ISM)为主,决策实验与评价实验室法(decision experiment and evaluation laboratory, DEMATEL)和交叉影响矩阵相乘法(cross-impact matrix multiplication, MICMAC)为辅的集成模型,旨在分析突发事件冲击下供应链韧性影响因素的相互作用。研究发现:物联网、大数据和区块链技术的应用是供应链韧性提高的主要驱动力因素,且区块链技术能弥补物联网和大数据的劣势,增强信息传输的可靠性。以区块链技术为核心,辅以风险偏好和内部供应链合作能力在根本上影响供应链的运作。

关键词: 突发事件, 供应链韧性, 影响因素

Abstract: Using a complex systems perspective, this paper develops an integrated model combining interpretive structural modeling(ISM), decision experiment and evaluation laboratory(DEMATEL), and cross-impact matrix multiplication(MICMAC)methods to analyze the interactions of resilience factors under such impacts. The study finds that IoT, big data, and blockchain technologies are key drivers for enhancing resilience, with blockchain improving the reliability of information transmission. Key factors influencing supply chain operations include blockchain technology, risk preference, and internal cooperation.

Key words: critical incident, supply chain resilience, influential factors

中图分类号: 

  • C934
[1] Christopher M, Peck H. Building the Resilient Supply Chain[J]. The International Journal of Logistics Management, 2004, 15(2):1-14.
[2] Kamalahmadi M, Parast M M. A review of the literature on the principles of enterprise and supply chain resilience:Major findings and directions for future research[J]. International Journal of Production Economics, 2016, 171:116-133.
[3] 盛昭瀚,王海燕,胡志华. 供应链韧性: 适应复杂性 - 基于复杂系统管理视角[J]. 中国管理科学,2022,30(11):1-7. Sheng Zhaohan, Wang Haiyan, Hu Zhihua. Supply chain resilience: adapting to complexity-based on the per- spective of complex system thinking[J]. Chinese Journal of Management Science, 2022, 30(11):1-7.
[4] Ali A, Mahfouz A, Arisha A. Analysing supply chain resilience: integrating the constructs in a concept mapping framework via a systematic literature review[J]. Supply Chain Management: An International Journal, 2017, 22(1):16-39.
[5] Wieland A, Wallenburg C M. The influence of relational competencies on supply chain resilience: a relational view[J]. International Journal of Physical Distribution & Logistics Management, 2013, 43(4):300-320.
[6] Kazancoglu I, Ozbiltekin-PM, Kumar MS, et al. Role of flexibility, agility and responsiveness for sustainable supply chain resilience during COVID-19[J]. Journal of Cleaner Production, 2022, 362:132431.
[7] Gligor D, Feizabadi J, Russo I, et al. The triple-a supply chain and strategic resources: developing competitive advantage[J]. International Journal of Physical Distribution & Logistics Management, 2020, 50(2):159-190.
[8] Eckstein D, Goellner M, Blome C, et al. The performance impact of supply chain agility and supply chain adapt- ability: the moderating effect of product complexity[J]. International Journal of Production Research, 2015, 53(10):3028-3046.
[9] Aslam H, Blome C, Roscoe S, et al. Dynamic supply chain capabilities: How market sensing, supply chain agility and adaptability affect supply chain ambidexterity[J]. International Journal of Operations & Production Management, 2018, 38(12):2266-2285.
[10] Ivanov D. Viable supply chain model: integrating agility, resilience and sustainability perspectives-lessons from and thinking beyond the COVID-19 pandemic[J]. Annals of operations research, 2022, 319(1):1411-1431.
[11] Khorasani S T, Almasifard M. The development of a green supply chain dual-objective facility by considering different levels of uncertainty[J]. Journal of Industrial Engineering International, 2018, 14(3):593-602.
[12] Hafezalkotob A, Zamani S. A multi-product green supply chain under government supervision with price and demand uncertainty[J]. Journal of Industrial Engineering International, 2019, 15(1):193-206.
[13] Aldrighetti R, Battini D, Ivanov D. Efficient resilience portfolio design in the supply chain with consideration of preparedness and recovery investments[J]. Omega, 2023, 117:102841.
[14] Dubey R, Gunasekaran A, Childe S J, et al. Empirical investigation of data analytics capability and organizational flexibility as complements to supply chain resilience[J]. International Journal of Production Research, 2021, 59(1):110-128.
[15] Ivanov D, Dolgui A. Low-Certainty-Need(LCN)supply chains: a new perspective in managing disruption risks and resilience[J]. International Journal of Production Research, 2019, 57(15-16):5119-5136.
[16] Christopher M, Mena C, Khan O, et al. Approaches to managing global sourcing risk[J]. Supply Chain Management: An International Journal, 2011, 16(2):67-81.
[17] Ji Ting, Xu Xiaoping, Yan Xiaoming, et al. The production decisions and cap setting with wholesale price and revenue sharing contracts under cap-and-trade regulation[J]. International Journal of Production Research, 2020, 58(1):128-147.
[18] Luo Ruiling, Zhou Li, Song Yang, et al. Evaluating the impact of carbon tax policy on manufacturing and remanufacturing decisions in a closed-loop supply chain[J]. International Journal of Production Economics, 2022, 245:108408
[19] Yang Yuefeng, Xu Xuerong. Post-disaster grain supply chain resilience with government aid[J]. Transportation Research Part E: Logistics and Transportation Review, 2015, 76:139-159.
[20] Chu C Y, Park K, Kremer G E. A global supply chain risk management framework: An application of text-mining to identify region-specific supply chain risks[J]. Advanced Engineering Informatics, 2020, 45:101053.
[21] Wang Qiang, Zhang Min, Li Rongrong. Does COVID-19 reduce international cooperation in supply chain research between the US and China?[J]. Benchmarking: An International Journal, 2023, 30(3):697-712.
[22] Pettit T J, Fiksel J, Croxton K L. Ensuring supply chain resilience: development of a conceptual framework[J]. Journal of business logistics, 2010, 31(1):1-21.
[23] Scholten K, Schilder S. The role of collaboration in supply chain resilience[J]. Supply Chain Management: An International Journal, 2015, 20(4):471-484.
[24] Pandey A K, Daultani Y, Pratap S. Blockchain technology enabled critical success factors for supply chain resilience and sustainability[J]. Business Strategy and the Environment, 2024, 33(2):1533-1554.
[25] Lopes J A B, Chiappetta C J, Hingley M, et al. Sustainability of supply chains in the wake of the coronavirus(COVID-19/SARS-CoV-2)pandemic: lessons and trends[J]. Modern Supply Chain Research and Applications, 2020, 2(3):117-122.
[26] Esmaeilian B, Sarkis J, Lewis K, et al. Blockchain for the future of sustainable supply chain management in Industry 4.0[J]. Resources, Conservation and Recycling, 2020, 163:105064.
[27] Ahmad R W, Salah K, Jayaraman R, et al. Blockchain and COVID-19 pandemic: Applications and challenges[J]. Cluster Computing, 2023:1-26.
[28] Khan S A, Mubarik M S, Kusi-sarpong S, et al. Blockchain technologies as enablers of supply chain mapping for sustainable supply chains[J]. Business Strategy and the Environment, 2022, 31(8):3742-3756.
[29] Manupati V K, Schoenherr T, Ramkumar M, et al. A blockchain-based approach for a multi-echelon sustainable supply chain[J]. International Journal of Production Research, 2020, 58(7):2222-2241.
[30] Bai Chunguang, Sarkis J. A supply chain transparency and sustainability technology appraisal model for blockchain technology[J]. International Journal of Production Research, 2020, 58(7):2142-2162.
[31] Wamba S F, Dubey R, Gunasekaran A, et al. The performance effects of big data analytics and supply chain am- bidexterity: The moderating effect of environmental dynamism[J]. International Journal of Production Economics, 2020, 222:107498.
[32] Cavalcante I M, Frazzon E M, Forcellini F A, et al. A supervised machine learning approach to data-driven simulation of resilient supplier selection in digital manufacturing[J]. International Journal of Information Management, 2019, 49:86-97.
[33] Annosi M C, Brunetta F, Bimbo F, et al. Digitalization within food supply chains to prevent food waste. Drivers, barriers and collaboration practices[J]. Industrial Marketing Management, 2021, 93:208-220.
[34] Dubey R, Bryde D J, Dwivedi Y K, et al. Dynamic digital capabilities and supply chain resilience: The role of government effectiveness[J]. International Journal of Production Economics, 2023, 258:108790.
[35] Fosso Wamba S, Gunasekaran A, Dubey R, et al. Big data analytics in operations and supply chain management[J]. Annals of Operations Research, 2018, 270:1-4.
[36] Ivanov D, Dolgui A. Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak[J]. International Journal of Production Research, 2020, 58(10):2904-2915.
[37] Bi Z, Jin Y, Maropoulos P, et al. Internet of things(IoT)and big data analytics(BDA)for digital manufacturing(DM)[J]. International Journal of Production Research, 2023, 61(12):4004-4021.
[38] Graves S C, Tomlin B T, Willems S P. Supply chain challenges in the post-Covid Era[J]. Production and Operations Management, 2022, 31(12):4319-4332.
[39] Elleuch H, Dafaoui E, Elmhamedi A, et al. Resilience and vulnerability in supply chain: literature review[J]. IFAC- PapersOnLine, 2016, 49(12):1448-1453.
[40] Chowdhury M M H, Quaddus M. Supply chain resilience:conceptualization and scale development using dynamic capability theory[J]. International Journal of Production Economics, 2017, 188:185-204.
[41] 田丹,唐加福,闫玉. 企业弹性的测度与判别研究[J]. 系统工程理论与实践,2022,42(5):1233-1244. Tian Dan, Tang Jiafu, Yan Yu. The measurement and discriminant analysis of enterprise resilience[J]. Systems Engineering - Theory & Practice, 2022, 42(5):1233-1244.
[42] Pettit T J, Croxton K L, Fiksel J. Ensuring supply chain resilience: development and implementation of an assessment tool[J]. Journal of Business Logistics, 2013, 34(1):46-76.
[43] 马潇宇,黄明珠,杨朦晰. 供应链韧性影响因素研究: 基于SEM与fsQCA方法[J]. 系统工程理论与实践,2023,43(9):2484-2501. Ma Xiaoyu, Huang Mingzhu, Yang Mengxi. Research on the influencing factors of supply chain resilience: Based on SEM and fsQCA[J]. Systems Engineering - Theory & Practice, 2023, 43(9):2484-2501.
[44] Tang C S. Robust strategies for mitigating supply chain disruptions[J]. International Journal of Logistics Research and Applications, 2006, 9(1):33-45.
[45] Gabus A, Fontela E. World problems, an invitation to further thought within the framework of DEMATEL[R]. Battelle Geneva Research Centre, Geneva, Switzerland, 1972.
[46] 李广利,严一知,刘文琦,等. 基于DEMATEL-ISM的矿工不安全情绪形成因子研究[J]. 中国安全科学学报,2021,31(7):30-37. Li Guangli, Yan Yizhi, Liu Wenqi, et al. Research on formation factors of miners unsafe emotions based on DEMATEL-ISM[J]. China Safety Science Journal, 2021, 31(7):30-37.
[47] Warfield J N. Societal systems planning, policy and complexity[J]. Cybernetics and System, 1978, 8(1):113-115.
[48] Mathiyazhagan K, Govindan K, Noorulhaq A, et al. An ISM approach for the barrier analysis in implementing green supply chain management[J]. Journal of Cleaner Production, 2013, 47:283-297.
[49] Lan Z, Pau K, Mohd YH, et al. Hierarchical topological model of the factors influencing adolescents non-suicidal self-injury behavior based on the DEMATEL-TAISM method[J]. Scientific reports, 2022, 12(1):17238.
[50] Kannan G, Pokharel S, Sasi KP. A hybrid approach using ISM and fuzzy TOPSIS for the selection of reverse logistics provider[J]. Resources, Conservation and Recycling, 2009, 54(1):28-36.
[51] Mohanty M. Assessing sustainable supply chain enablers using total interpretive structural modeling approach and fuzzy-MICMAC analysis[J]. Management of Environmental Quality: An International Journal, 2018, 29(2):216-239.
[52] Mandal A, Deshmukh S G. Vendor selection using interpretive structural modelling(ISM)[J]. International journal of operations & production management, 1994, 14(6):52-59.
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