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Evaluating Supply Chain Risks in The Moroccan Automotive Industry: A Multi-Criteria Decision-Making Approach

Open Access
|Feb 2025

References

  1. K.E. Stecke, S. Kumar, Sources of Supply Chain Disruptions, Factors That Breed Vulnerability, and Mitigating Strategies, Journal of Marketing Channels, vol. 16, no 3, pp. 193–226, juin 2009, doi: 10.1080/10466690902932551.
  2. M.V.C. Fagundes, E.O. Teles, S.A.B. Vieira De Melo, F.G.M. Freires, Supply chain risk management modelling: A systematic literature network analysis review, IMA Journal of Management Mathematics, vol. 31, no 4, pp. 387–416, sept. 2020, doi: 10.1093/imaman/dpaa019.
  3. D. Fatima-Zahra, F. Abderrahim, Influence de la pandemie du COVID-19 sur la logistique et le transport au Maroc.
  4. R. Mohammed, B. Maroua, B. Chaimaa, L’impact du COVID-19 sur la chaine logistique hospitalière au Maroc, Quel effet a eu cette crise sanitaire sur les échanges internationaux?, Technical Sciences, no 1, 2020.
  5. Morocco’s Economy Has Come Under Pressure from Supply Shocks, World Bank. Consulté le: 11 mai 2024. [En ligne]. Disponible sur: https://www.worldbank.org/en/news/press-release/2023/02/14/morocco-s-economy-has-comeunder-pressure-from-supply-shocks
  6. RF. Canal de Suez: Quel a été l’impact du blocage sur l’économie mondiale?, Maritime News. Consulté le: 11 mai 2024. [En ligne]. Disponible sur: https://maritimenews.ma/7-science/9412-canal-de-suezquel-a-ete-l-impact-du-blocage-sur-l-economie-mondiale
  7. Ait Ali, Abdelaaziz, The Russia-Ukraine War and Food Security in Morocco, p. 34/22, 2022.
  8. Transport & Logistics sector Morocco.
  9. L’usine automobile PSA de Kenitra au Maroc à l’arrêt pour 15 jours, Le Desk. Consulté le: 11 mai 2024. [En ligne]. Disponible sur: https://mobile.ledesk.ma/live-content/lusine-automobile-psa-de-kenitra-au-maroclarret-pour-15-jours/
  10. Grève dans l’usine PSA de Kenitra au Maroc, L’Anticapitaliste. Consulté le: 11 mai 2024. [En ligne]. Disponible sur: https://lanticapitaliste.org/actualite/international/grevedans-lusine-psa-de-kenitra-au-maroc
  11. A. Amachraa, Morocco’s Rise In The Global Automotive Industry.
  12. R. Echrigui, A. Moghar, M. Hamiche, The impact of the automotive industry on the moroccan economy, EJEFR, vol. 5, no 2, juin 2021, doi: 10.46827/ejefr.v5i2.1100.
  13. T. Hahn, G.V. Auktor, The effectiveness of Morocco’s industrial policy in promoting a national automotive industry. in Discussion paper/German Development Institute, no. 2017, 27. Bonn: Deutsches Institut für Entwicklungspolitik GmbH, 2017.
  14. M. Salhi, Y. Chater, A. Maurady, The impact of safety culture dimensions on workplace accidents: an application in the Moroccan automotive industry, Int J Occup Saf Health, vol. 14, no 1, pp. 107–116, janv. 2024, doi: 10.3126/ijosh.v14i1.55669.
  15. P. Pakdeenarong, T. Hengsadeekul, Supply chain risk management of organic rice in Thailand, 10.5267/j.uscm, p. 165–174, 2020, doi: 10.5267/j.uscm.2019.7.007.
  16. Y. Wang, H.X., Hao Research on the supply chain risk assessment of the fresh agricultural products based on the improved toptsis algorithm, Chemical Engineering Transactions, vol. 51, pp. 445–450, juill. 2016, doi: 10.3303/CET1651075.
  17. S. Paul, G. Kabir, S.M. Ali, G. Zhang, Examining transportation disruption risk in supply chains: A case study from Bangladeshi pharmaceutical industry, Research in Transportation Business & Management, vol. 37, p. 100485, déc. 2020, doi: 10.1016/j.rtbm.2020.100485.
  18. Supply Chain Risk Factors and Corporate Repute in Pharma Industry of Thailand, SRP, vol. 11, no 04, juin 2020, doi: 10.31838/srp.2020.4.16.
  19. A.C. Cagliano, A. De Marco, S. Grimaldi, et C. Rafele, An integrated approach to supply chain risk analysis, Journal of Risk Research, vol. 15, no 7, pp. 817–840, août 2012, doi: 10.1080/13669877.2012.666757.
  20. M. Junaid, Y. Xue, M.W. Syed, Construction of Index System for Risk Assessment in Supply Chains of Automotive Industry, vol. 9, no 4, 2020.
  21. S. Cao, K. Bryceson, et D. Hine, An Ontology-based Bayesian network modelling for supply chain risk propagation, IMDS, vol. 119, no 8, pp. 1691–1711, sept. 2019, doi: 10.1108/IMDS-01-2019-0032.
  22. S. Mukherjee, S.S. Padhi, Sourcing decision under interconnected risks: an application of mean–variance preferences approach, Ann Oper Res, vol. 313, no 2, pp. 1243–1268, juin 2022, doi: 10.1007/s10479-021-04485-3.
  23. R. Sukwadi, A. Caesar, An integrated approach for supply chain risk management, Engineering Management in Production and Services, vol. 14, no 1, p. 38–48, mars 2022, doi: 10.2478/emj-2022-0004.
  24. L. Wang, A multi-level fuzzy comprehensive assessment for supply chain risks, IFS, vol. 41, no 4, pp. 4947–4954, nov. 2021, doi: 10.3233/JIFS-189981.
  25. M.F. Blos, S.L. Hoeflich, E.M. Dias, H.-M. Wee, A note on supply chain risk classification: discussion and proposal, International Journal of Production Research, vol. 54, no 5, pp. 1568–1569, mars 2016, doi: 10.1080/00207543.2015.1067375.
  26. M.S. Shahbaz, R.Z. RM Rasi, M.F. Bin Ahmad, A novel classification of supply chain risks: Scale development and validation, JIEM, vol. 12, no 1, p. 201, avr. 2019, doi: 10.3926/jiem.2792.
  27. V.V. Shenoi, T.N. S. Dath, C. Rajendran, Supply chain risk management in the Indian manufacturing context: a conceptual framework.
  28. H. Rogers, M. Srivastava, K.S. Pawar, J. Shah, Supply chain risk management in India – practical insights, International Journal of Logistics Research and Applications, vol. 19, no 4, pp. 278–299, juill. 2016, doi: 10.1080/13675567.2015.1075476.
  29. R.W. Monroe, J.M. Teets, P.R. Martin, Supply chain risk management: an analysis of sources of risk and mitigation strategies, IJAMS, vol. 6, no 1, p. 4, 2014, doi: 10.1504/IJAMS.2014.059291.
  30. S. Fazli, R. Kiani Mavi, et M. Vosooghidizaji, Crude oil supply chain risk management with DEMATEL-ANP, Oper Res Int J, vol. 15, no 3, pp. 453–480, oct. 2015, doi: 10.1007/s12351-015-0182-0.
  31. M. Shekarian, M. Mellat Parast, An Integrative approach to supply chain disruption risk and resilience management: a literature review, International Journal of Logistics Research and Applications, vol. 24, no 5, pp. 427–455, sept. 2021, doi: 10.1080/13675567.2020.1763935.
  32. P. Trkman, M.P.V. de Oliveira, K. McCormack, Value-oriented supply chain risk management: you get what you expect, Industrial Management & Data Systems, vol. 116, no 5, pp. 1061–1083, juin 2016, doi: 10.1108/IMDS-09-2015-0368.
  33. J. Liu, F. Liu, H. Zhou, Y. Kong, An Integrated Method of Supply Chains Vulnerability Assessment, Scientific Programming, vol. 2016, pp. 1–10, 2016, doi: 10.1155/2016/2819238.
  34. F.E. Essaber, R. Benmoussa, R. De Guio, S. Dubois, A Hybrid Supply Chain Risk Management Approach for Lean Green Performance Based on AHP, RCA and TRIZ: A Case Study, Sustainability, vol. 13, no 15, p. 8492, juill. 2021, doi: 10.3390/su13158492.
  35. M. Er Kara, S.Ü. Oktay Fırat, A. Ghadge, A data mining-based framework for supply chain risk management, Computers & Industrial Engineering, vol. 139, p. 105570, janv. 2020, doi: 10.1016/j.cie.2018.12.017.
  36. A. Sibevei, A. Azar, M. Zandieh, S.M. Khalili, M. Yazdani, Developing a Risk Reduction Support System for Health System in Iran: A Case Study in Blood Supply Chain Management, IJERPH, vol. 19, no 4, p. 2139, févr. 2022, doi: 10.3390/ijerph19042139.
  37. A. Ghadge, S. Dani, M. Chester, R. Kalawsky, A systems approach for modelling supply chain risks, Supply Chain Management: An International Journal, vol. 18, no 5, pp. 523–538, juill. 2013, doi: 10.1108/SCM-11-2012-0366.
  38. Faculty of Engineering, Mahidol University, Nakhon Pathom, Thailand, D. Sumrit, et S. Srisawad, Fuzzy failure mode and effect analysis model for operational supply chain risks assessment: an application in canned tuna manufacturer in Thailand, Logforum, vol. 18, no 1, pp. 77–96, mars 2022, doi: 10.17270/J.LOG.2022.645.
  39. P. Senna, A. Reis, I.L. Santos, A.C. Dias, O. Coelho, A systematic literature review on supply chain risk management: is healthcare management a forsaken research field?, BIJ, vol. 28, no 3, pp. 926–956, mars 2021, doi: 10.1108/BIJ-05-2020-0266.
  40. S. Anwar, T. Djatna, Sukardi, P. Suryadarma, Modelling supply chain risks and their impacts on the performance of the sago starch agro-industry, IJPPM, vol. 71, no 6, pp. 2361–2392, juin 2022, doi: 10.1108/IJPPM-10-2020-0556.
  41. F.R. Azmi, A. Abdullah, E.R. Cahyadi, H. Musa, J.R. Sa’ari, Type of Risk in Halal Food Supply Chain: A Review, vol. 9, no 4, 2020.
  42. A. Samvedi, V. Jain, F.T.S. Chan, Quantifying risks in a supply chain through integration of fuzzy AHP and fuzzy TOP-SIS, International Journal of Production Research, vol. 51, no 8, pp. 2433–2442, avr. 2013, doi: 10.1080/00207543.2012.741330.
  43. C.R. Vishnu, R. Sridharan, P.N.R. Kumar, Supply chain risk management: models and methods, Supply chain risk management.
  44. A. Alora, M.K. Barua, An integrated structural modelling and MICMAC analysis for supply chain disruption risk classification and prioritisation in India.
  45. J.R. Macdonald, C.W. Zobel, S.A. Melnyk, S.E. Griffis, Supply chain risk and resilience: theory building through structured experiments and simulation, International Journal of Production Research, vol. 56, no 12, pp. 4337–4355, juin 2018, doi: 10.1080/00207543.2017.1421787.
  46. M. Kumar, P. Basu, B. Avittathur, Pricing and sourcing strategies for competing retailers in supply chains under disruption risk, European Journal of Operational Research, vol. 265, no 2, pp. 533–543, mars 2018, doi: 10.1016/j.ejor.2017.08.019.
  47. K. Kauppi, A. Longoni, F. Caniato, M. Kuula, Managing country disruption risks and improving operational performance: risk management along integrated supply chains, International Journal of Production Economics, vol. 182, pp. 484–495, déc. 2016, doi: 10.1016/j.ijpe.2016.10.006.
  48. K. Govindan, M.B. Jepsen, Supplier risk assessment based on trapezoidal intuitionistic fuzzy numbers and electre TRIC: A case illustration involving service suppliers, Journal of the Operational Research Society, vol. 67, no 2, pp. 339–376, févr. 2016, doi: 10.1057/jors.2015.51.
  49. S. Kumar Sharma, S. Sharma, Developing a Bayesian Network Model for Supply Chain Risk Assessment, Supply Chain Forum: An International Journal, vol. 16, no 4, pp. 50–72, janv. 2015, doi: 10.1080/16258312.2015.11728693.
  50. M. Yazdani, E.D.R.S. Gonzalez, P. Chatterjee, A multi-criteria decision-making framework for agriculture supply chain risk management under a circular economy context, MD, vol. 59, no 8, pp. 1801–1826, août 2021, doi: 10.1108/MD-10-2018-1088.
  51. S. Carpitella, I. Mzougui, J. Izquierdo, Multi-criteria risk classification to enhance complex supply networks performance, OPSEARCH, vol. 59, no 3, pp. 769–785, sept. 2022, doi: 10.1007/s12597-021-00568-8.
  52. J. Hou, X. Zhao, Toward a supply chain risk identification and filtering framework using systems theory, APJML, vol. 33, no 6, pp. 1482–1497, juin 2021, doi: 10.1108/APJML-05-2020-0342.
  53. S. Althaf, C.W. Babbitt, Disruption risks to material supply chains in the electronics sector, Resources, Conservation and Recycling, vol. 167, p. 105248, avr. 2021, doi: 10.1016/j.resconrec.2020.105248.
  54. S. Roscoe, H. Skipworth, E. Aktas, F. Habib, Managing supply chain uncertainty arising from geopolitical disruptions: evidence from the pharmaceutical industry and brexit, IJOPM, vol. 40, no 9, pp. 1499–1529, mai 2020, doi: 10.1108/IJOPM-10-2019-0668.
  55. F. Jianying, Y. Bianyu, L. Xin, T. Dong, M. Weisong, Evaluation on risks of sustainable supply chain based on optimized BP neural networks in fresh grape industry, Computers and Electronics in Agriculture, vol. 183, p. 105988, avr. 2021, doi: 10.1016/j.compag.2021.105988.
  56. E. Benedito, C. Martínez-Costa, S. Rubio, Introducing Risk Considerations into the Supply Chain Network Design, Processes, vol. 8, no 6, p. 743, juin 2020, doi: 10.3390/pr8060743.
  57. S. Mithun Ali, Md. A. Moktadir, G. Kabir, J. Chakma, Md. J.U. Rumi, Md. T. Islam, Framework for evaluating risks in food supply chain: Implications in food wastage reduction, Journal of Cleaner Production, vol. 228, pp. 786–800, août 2019, doi: 10.1016/j.jclepro.2019.04.322.
  58. S. Anwar, T. Djatna, Sukardi, P. Suryadarma, Modelling supply chain risks and their impacts on the performance of the sago starch agro-industry, IJPPM, vol. 71, no 6, pp. 2361–2392, juin 2022, doi: 10.1108/IJPPM-10-2020-0556.
  59. A. Deiva Ganesh, P. Kalpana, Future of artificial intelligence and its influence on supply chain risk management – A systematic review, Computers & Industrial Engineering, vol. 169, p. 108206, juill. 2022, doi: 10.1016/j.cie.2022.108206.
  60. M.M. Parast, N. Subramanian, An examination of the effect of supply chain disruption risk drivers on organizational performance: evidence from Chinese supply chains, SCM, vol. 26, no 4, pp. 548–562, mai 2021, doi: 10.1108/SCM-07-2020-0313.
  61. H. Jiao, W. Ding, Y. Shi, N. Zhao, B. Wang, Supply chain risk assessment model based on cloud model with subjective preference weight allocation algorithm, IDT, vol. 14, no 2, pp. 133–142, juill. 2020, doi: 10.3233/IDT-180001.
  62. X. Lei, C.A. MacKenzie, Assessing risk in different types of supply chains with a dynamic fault tree, Computers & Industrial Engineering, vol. 137, p. 106061, nov. 2019, doi: 10.1016/j.cie.2019.106061.
  63. M.N. Khan, P. Akhtar, Y. Merali, Strategies and effective decision-making against terrorism affecting supply chain risk management and security: A novel combination of triangulated methods, IMDS, vol. 118, no 7, pp. 1528–1546, sept. 2018, doi: 10.1108/IMDS-09-2017-0449.
  64. P. Kumar Tarei, G. Kumar, M. Ramkumar, A Mean-Variance robust model to minimize operational risk and supply chain cost under aleatory uncertainty: A real-life case application in petroleum supply chain, Computers & Industrial Engineering, vol. 166, p. 107949, avr. 2022, doi: 10.1016/j.cie.2022.107949.
  65. R. Rostamzadeh, M.K. Ghorabaee, K. Govindan, A. Esmaeili, H.B.K. Nobar, Evaluation of sustainable supply chain risk management using an integrated fuzzy TOPSISCRITIC approach, Journal of Cleaner Production, vol. 175, pp. 651–669, févr. 2018, doi: 10.1016/j.jclepro.2017.12.071.
  66. Y. Cao, W. Wei, L. Huang, H. Qiao, J. Du, Research on supply chain risk coping strategy based on fuzzy logic, IFS, vol. 37, no 4, pp. 4537–4546, oct. 2019, doi: 10.3233/JIFS-179287.
  67. C. Bode, S.M. Wagner, Structural drivers of upstream supply chain complexity and the frequency of supply chain disruptions, Journal of Operations Management, vol. 36, no 1, pp. 215–228, mai 2015, doi: 10.1016/j.jom.2014.12.004.
  68. S. Aghajanian, R.I. Shevchenko-Perepy, An Empirical Procurement Risk Management Framework in Supply Chain Networks: A Hybrid Approach, IEMS, vol. 17, no 4, pp. 730–744, déc. 2018, doi: 10.7232/iems.2018.17.4.730.
  69. X. Zhang, B. Sun, X. Chen, X. Chu, J. Yang, An approach to evaluating sustainable supply chain risk management based on BWM and linguistic value soft set theory, IFS, vol. 39, no 3, pp. 4369–4382, oct. 2020, doi: 10.3233/JIFS-200372.
  70. Dematerialization of Customs procedures: Feedback from Moroccan Customs, WCO News. Consulté le: 11 mai 2024. [En ligne]. Disponible sur: https://mag.wcoomd.org/magazine/wco-news-94/dematerialization-of-customs-procedures-morocco/
  71. A. Av, Customs and excise administration.
  72. K. Khan, A. Keramati, A Framework for Smart Supply Chain Risk Assessment: An Empirical Study, International Journal of Information Systems and Supply Chain Management, vol. 16, no 1, pp. 1–17, janv. 2023, doi: 10.4018/IJISSCM.316167.
  73. Failure Mode and Effect Analysis (FMEA), in Service Design for Six Sigma, Hoboken, NJ, USA: John Wiley & Sons, Inc., 2005, pp. 241–261. doi: 10.1002/0471744719.ch11.
  74. N. Rezki, M. Mansouri, Improving supply chain risk assessment with artificial neural network predictions, AL, vol. 10, no 04, pp. 645–658, déc. 2023, doi: 10.22306/al.v10i4.444.
  75. H.S. Kilic, S.K. Canbakis, M. Karabas, S. Koseoglu, E. Unal, Z.T. Kalender, Integrated Supply Chain Risk Assessment Methodology Based on Modified FMEA, JRACR, vol. 13, no 2, juin 2023, doi: 10.54560/jracr.v13i2.359.
  76. A. Nalhadi, A. Kurniasari, N. Djamal, S. Suryani, S. Supriyadi, Supply chain risk assessment of cotton shirt production uses the house of risk method, J. Phys.: Conf. Ser., vol. 1381, no 1, p. 012060, nov. 2019, doi: 10.1088/1742-6596/1381/1/012060.
  77. G.C. Dias, C.T. Hernandez, U.R. de Oliveira, Supply chain risk management and risk ranking in the automotive industry, Gest. Prod., vol. 27, no 1, p. e3800, 2020, doi: 10.1590/0104-530x3800-20.
  78. I. Mzougui, S. Carpitella, A. Certa, Z.E. Felsoufi, Assessing Supply Chain Risks in the Automotive Industry through a Modified MCDM-Based FMECA, p. 22, 2020.
  79. M.A.T. Dvaipayana, I.K. Sriwana, Prambudia, Design of supply chain risk mitigation system using house of risk and Fuzzy AHP methods in precast concrete, Sinergi, vol. 28, no 1, p. 93, déc. 2023, doi: 10.22441/sinergi.2024.1.010.
  80. R. Guo, Z. Wu, Social sustainable supply chain performance assessment using hybrid fuzzy – AHP-DEMATEL-VIKOR: a case study in manufacturing enterprises, Environ Dev Sustain, vol. 25, no 11, pp. 12273–12301, nov. 2023, doi: 10.1007/s10668-022-02565-3.
  81. I. Masudin, R.W. Wardana, M.W.T. Wijayanti, D.P. Restuputri, Usability website evaluation for fresh food product in sme’s online business with fuzzy AHP-topsis integration, AEJ, vol. 13, no 3, pp. 71–79, août 2023, doi: 10.11113/aej.v13.19159.
  82. R.M. Mouhoumed, Ö. Ekmekcioğlu, E.E. Başakın, M. Özger, Integrated Fuzzy AHP-TOPSIS Model for Assessing Managed Aquifer Recharge Potential in a Hot Dry Region: A Case Study of Djibouti at a Country Scale, Water, vol. 15, no 14, p. 2534, juill. 2023, doi: 10.3390/w15142534.
  83. T.K.L. Nguyen, T.L.H. Nguyen, T.L. Ngo, B.A. Hoang, H.H. Le, T.T.H. Tran, An Integrated Approach of Fuzzy Analytic Hierarchy Process and Super Slack-Based Measure for the Logistics Industry in Vietnam, Sustainability, vol. 15, no 16, p. 12654, août 2023, doi: 10.3390/su151612654.
  84. S.E. Helmy, G.H. Eladl, M. Eisa, Fuzzy analytical hierarchy process (fahp) using geometric mean method to select best processing framework adequate to big data. Vol., no 1, p. 20, 2005.
  85. A.G. Abdullah, M.A. Shafii, S. Pramuditya, T. Setiadipura, K. Anzhar, Multi-criteria decision making for nuclear power plant selection using fuzzy AHP: Evidence from Indonesia, Energy and AI, vol. 14, p. 100263, oct. 2023, doi: 10.1016/j.egyai.2023.100263.
  86. S.H. Anbarkhan, A Fuzzy-TOPSIS-Based Approach to Assessing Sustainability in Software Engineering: An Industry 5.0 Perspective, Sustainability, vol. 15, no 18, pp. 13844, sept. 2023, doi: 10.3390/su151813844.
  87. T. Althaqafi, Cultivating Sustainable Supply Chain Practises in Electric Vehicle Manufacturing: A MCDM Approach to Assessing GSCM Performance, WEVJ, vol. 14, no 10, p. 290, oct. 2023, doi: 10.3390/wevj14100290.
  88. S.W. Chisale, H.S. Lee, Evaluation of barriers and solutions to renewable energy acceleration in Malawi, Africa, using AHP and fuzzy TOPSIS approach, Energy for Sustainable Development, vol. 76, p. 101272, oct. 2023, doi: 10.1016/j.esd.2023.101272.
  89. A. Tubis, S. Werbińska-Wojciechowska, Fuzzy topsis in selecting logistic handling operator: case study from Poland, Transport, vol. 38, no 1, pp. 12–30, avr. 2023, doi: 10.3846/transport.2023.17074.
  90. O.I.S. El Dardery, I. Gomaa, A.R.M. Rayan, Frendy, G.E. Khayat, S.H. Sabry, Using Fuzzy TOPSIS and Balanced Scorecard for Kaizen Evaluation, Business Systems Research Journal, vol. 14, no 1, pp. 112–130, sept. 2023, doi: 10.2478/bsrj-2023-0006.
  91. M. Ahani, H. R. Bahrami, M. Rostami, Determining and ranking dimensions of knowledge management implementation using Hicks model and fuzzy TOPSIS Technique, msl, vol. 3, no 2, pp. 721–730, févr. 2013, doi: 10.5267/j.msl.2012.11.023.
  92. S.H. Kia, A. Danaei, M. Oroei, An application of fuzzy TOP-SIS on ranking products: A case study of faucet devices, 10.5267/j.dsl, p. 43–48, 2014, doi: 10.5267/j.dsl.2013.08.004.
DOI: https://doi.org/10.2478/mspe-2025-0013 | Journal eISSN: 2450-5781 | Journal ISSN: 2299-0461
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