The role of multicriteria decision making in the supply chain: Literature review
DOI:
https://doi.org/10.56294/dm2025619Keywords:
Multicriteria Decision-Making, Supply Chain, Industry 4.0 and Industry 5.0, Digital TwinsAbstract
Introduction: The evaluation of supply chain performance has gained significant relevance due to recent events that have transformed its operational dynamics, as well as the advent of Industry 5.0. This new era introduces advanced technologies, such as digital twins, which, when combined with multicriteria models, can identify and prioritize key factors to enhance performance evaluation. These tools have the potential to optimize strategic decision-making in an increasingly dynamic and competitive environment.
Methods: A systematic literature review was conducted following the PRISMA framework, analyzing 45 articles published between 2019 and 2024. The sources included scientific databases such as SCOPUS and Web of Science. The search employed terms related to multicriteria models, supply chain, Industry 4.0, and digital twins. Articles were selected based on predefined inclusion and exclusion criteria.
Results: Findings revealed that multicriteria methods are widely used to evaluate efficiency, sustainability, and resilience in supply chains. Additionally, digital twins emerged as key tools for real-time monitoring, risk management, and process simulation. However, technological, financial, and regulatory barriers were identified, hindering their practical implementation.
Conclusions: The combination of advanced technologies with multicriteria approaches represents a promising solution for improving supply chain performance. Future research should focus on developing hybrid models, promoting organizational training, and establishing international standards to ensure effective adoption. These initiatives will enable organizations to address the challenges of an increasingly complex global environment, strengthening the resilience and sustainability of supply chains.
References
1. Belhadi A, Kamble S, Fosso Wamba S, Queiroz MM. Building supply-chain resilience: an artificial intelligence-based technique and decision-making framework. Int J Prod Res. 2022 Jul 18;60(14):4487-507. DOI: https://doi.org/10.1080/00207543.2021.1950935
2. González-Hernández IJ, Armas-Alvarez B, Coronel-Lazcano M, Maldonado-López N, Vergara-Martínez O, Granillo-Macías R. Technological development in the industrial revolutions. Ingenio Concienc Scientific College of Super City Sahagún. 2021;8(16):41-52. DOI: https://doi.org/10.29057/escs.v8i16.7118
3. Sánchez Jiménez L. Control and monitoring of supply chain performance indicators [Internet] [Thesis]. [Nuevo León]: Autonomous University of Nuevo León; 2021. Available at: http://eprints.uanl.mx/22263/1/1080315308.pdf
4. Afaq Y, Manocha A. Blockchain and Deep Learning Integration for Various Applications: A Review. J Comput Inf Syst. 2 Jan 2024;64(1):92-105. DOI: https://doi.org/10.1080/08874417.2023.2173330
5. Nagy G, Szentesi S. Revolutionizing Production Logistics: Industry 5.0's Impact. Adv Logist Syst - Theory Pract. 2024;18(2):69-86. DOI: https://doi.org/10.32971/als.2024.019
6. Ivanov D. Conceptualization of a 7-element digital twin framework in supply chain and operations management. Int J Prod Res. Mar 18, 2024;62(6):2220-32. DOI: https://doi.org/10.1080/00207543.2023.2217291
7. Tao F, Cheng J, Qi Q, Zhang M, Zhang H, Sui F. Digital twin-driven product design, manufacturing and service with big data. Int J Adv Manuf Technol. 2018 Feb;94(9- 12):3563-76. DOI: https://doi.org/10.1007/s00170-017-0233-1
8. Melnyk LH, Kubatko OV, Dehtyarova IB, Dehtiarova IB, Matsenko OM, Rozhko OD. The effect of industrial revolutions on the transformation of social and economic systems. 2019; DOI: https://doi.org/10.21511/ppm.17(4).2019.31
9. Thomes P. Industry—Between Evolution and Revolution: A Historical Perspective. In: Handbook Industry 40: Law, Technology, Society. Springer; 2022. p. 1119-38. DOI: https://doi.org/10.1007/978-3-662-64448-5_58
10. Kumar K, Zindani D, Davim JP. Industry 4.0: developments towards the fourth industrial revolution. Springer; 2019. DOI: https://doi.org/10.1007/978-981-13-8165-2
11. Rozo-García F. Review of the technologies present in industry 4.0. Rev UIS Eng. 2020;19(2):177-91. DOI: https://doi.org/10.18273/revuin.v19n2-2020019
12. Petcu I, Barbu DC, Anghel M, Radu AF, Golea DG. Shaping the Future: Between Opportunities and Challenges of the Ongoing 4 Th and the Forthcoming 5 Th Industrial Revolution. ELearning Softw Educ. 2020;3. DOI: https://doi.org/10.12753/2066-026X-20-181
13. Hassoun A, Aït-Kaddour A, Abu-Mahfouz AM, Rathod NB, Bader F, Barba FJ, et al. The fourth industrial revolution in the food industry—Part I: Industry 4.0 technologies. Crit Rev Food Sci Nutr. 2023 Sep 10;63(23):6547-63. DOI: https://doi.org/10.1080/10408398.2022.2034735
14. Lei Z, Shi J, Luo Z, Wan J. Intelligent manufacturing from the perspective of industry 5.0: application review and perspectives. IEEE Access. 2024; DOI: https://doi.org/10.1109/ACCESS.2024.3496697
15. Ghobakhloo M, Mahdiraji HA, Iranmanesh M, Jafari-Sadeghi V. From Industry 4.0 digital manufacturing to Industry 5.0 digital society: a roadmap toward human-centric, sustainable, and resilient production. Inf Syst Front. 2024;1-33.
16. Jabir I. MCDM and Logistics and Transportation. 2020;
17. Riadh H. Contribution of logistics diagnosis to cost minimization: The case of a subsidiary of the automotive industry. J Sustain Dev Transp Logist. 2018;3(3):55-68. DOI: https://doi.org/10.14254/jsdtl.2018.3-3.4
18. Torres Vergara JI. Multicriteria model for the evaluation of the performance of the resilient and sustainable supply chain [Thesis]. [Nuevo León]: Autonomous University of Nuevo León; 2021.
19. Christopher M. Logistics and supply chain management. Pearson Uk; 2022.
20. Agarwala N. Promoting Circular Economy in the shipping industry. J Int Marit Saf Environ Aff Shipp. 2 Oct 2023;7(4):2276984. DOI: https://doi.org/10.1080/25725084.2023.2276984
21. Henao CAR, Serna OLL. Data envelopment analysis and its applications in sustainability. Ingeniare. 2021;(31):11-9.
22. Bhushan N, Rai K. Strategic decision-making. In: Strategic Decision Making: Applying the Analytic Hierarchy Process. Springer; 2004. p. 3-10. DOI: https://doi.org/10.1007/978-1-85233-864-0_1
23. Quintero AG, Serranomoya ED, Von CMH. Multicriteria methods and processes for evaluation. Blue Moon. 2013;(36):285-306.
24. Silva-López GC, Solís-Centurión M, Recalde-Ramírez JL, López MM. Application of the analytical hierarchy process (AHP) in the selection of logistics technology. In: IV Argentine Symposium on Industrial Informatics and Operational Research (SIIIO 2021)- JAIIO 50 (Virtual mode). 2021.
25. Chakraborty S. TOPSIS and Modified TOPSIS: A comparative analysis. Decis Anal J. 2022;2:100021. DOI: https://doi.org/10.1016/j.dajour.2021.100021
26. Khan AU, Ali Y. Analytical hierarchy process (AHP) and analytical network process methods and their applications: a twenty year review from 2000-2019: AHP & ANP techniques and their applications: Twenty years review from 2000 to 2019. Int J Anal Hierarchy Process. 2020;12(3). DOI: https://doi.org/10.13033/ijahp.v12i3.822
27. Jovčić S, Průša P, Dobrodolac M, Švadlenka L. A proposal for a decision-making tool in third-party logistics (3PL) provider selection based on multi-criteria analysis and the fuzzy approach. Sustainability. 2019;11(15):4236. DOI: https://doi.org/10.3390/su11154236
28. Lambora A, Gupta K, Chopra K. Genetic algorithm-A literature review. In: 2019 international conference on machine learning, big data, cloud and parallel computing (COMITCon). IEEE; 2019. p. 380-4. DOI: https://doi.org/10.1109/COMITCon.2019.8862255
29. Sahoo P, Saraf PK, Uchil R. Identification of challenges to Industry 5.0 adoption in Indian manufacturing firms: an emerging economy perspective. Int J Comput Integr Manuf. :1- 26. DOI: https://doi.org/10.1080/0951192X.2024.2382186
30. Taherdoost H, Brard A. Analyzing the process of supplier selection criteria and methods. Procedia Manuf. 2019;32:1024-34. DOI: https://doi.org/10.1016/j.promfg.2019.02.317
31. Apeji UD, Sunmola FT. Sustainable supply chain visibility assessment and proposals for improvements using fuzzy logic. J Model Manag. 2023;18(3):701-26. DOI: https://doi.org/10.1108/JM2-08-2021-0181
32. Imran N, Mubarik MS, Naghavi N, Khan SA. An application of multi-criteria data management approach for prioritization of unwarranted causes of delay in international shipments. Int J Integr Supply Manag. 2022;15(3):233-52. DOI: https://doi.org/10.1504/IJISM.2022.124440
33. Dimitriou D, Sartzetaki M. Performance assessment modeling for managing transport enterprises based on modified fuzzy TOPSIS analysis. Oper Res. 2022;22(5):6037-53. DOI: https://doi.org/10.1007/s12351-022-00719-9
34. Gupta A, Singh RK, Mangla SK. Evaluation of logistics providers for sustainable service quality: Analytics based decision making framework. Ann Oper Res. 2022;315(2):1617-64. DOI: https://doi.org/10.1007/s10479-020-03913-0
35. Fuller A, Fan Z, Day C, Barlow C. Digital twin: Enabling technologies, challenges and open research. IEEE Access. 2020;8:108952-71. DOI: https://doi.org/10.1109/ACCESS.2020.2998358
36. de Prada C, Galán-Casado S, Pitarch JL, Sarabia D, Galán A, Gutiérrez G. Digital twins in the process industry. Rev Iberoam Automática E Ind. 2022;19(3):285-96. DOI: https://doi.org/10.4995/riai.2022.16901
37. Gupta S. Digital Twins: Advancements in Theory, Implementation, and Applications. SpringerNature;
38. Nambisan S, Wright M, Feldman M. The digital transformation of innovation and entrepreneurship: Progress, challenges and key themes. Res Policy. 2019;48(8):103773. DOI: https://doi.org/10.1016/j.respol.2019.03.018
39. Haddaway NR, Page MJ, Pritchard CC, McGuinness LA. PRISMA2020: An R package and Shiny app for producing PRISMA 2020-compliant flow diagrams, with interactivity for optimized digital transparency and Open Synthesis. Campbell Syst Rev 2022 Jun 1;18(2):e1230. DOI: https://doi.org/10.1002/cl2.1230
40. Hsu CH, Wu JZ, Zhang TY, Chen JY. Deploying Industry 5.0 drivers to enhance sustainable supply chain risk resilience. Int J Sustain Eng 2024;17(1):1-28. DOI: https://doi.org/10.1080/19397038.2024.2327381
41. Yin L, Li T, Li G, Besklubova S, Zhong RY, Zhao S. Cyber-physical internet based intelligent operation platform for off-site construction supply chain management. Enterp Inf Syst. 2024;18(6):2346743. DOI: https://doi.org/10.1080/17517575.2024.2346743
42. Fatorachian H, Kazemi H. Impact of Industry 4.0 on supply chain performance. Prod Plan Control. 2021 Jan 2;32(1):63-81. DOI: https://doi.org/10.1080/09537287.2020.1712487
43. Bakhshi S, Ghaffarianhoseini A, Ghaffarianhoseini A, Najafi M, Rahimian F, Park C, et al. Digital twin applications for overcoming construction supply chain challenges. Auto Const. Nov 2024;167:105679. DOI: https://doi.org/10.1016/j.autcon.2024.105679
44. Holopainen M, Saunila M, Ukko J. Enhancing the order-to-delivery process with real-time performance measurement based on digital visualization. Prod Manuf Res. Dec 31, 2023;11(1):2217237. DOI: https://doi.org/10.1080/21693277.2023.2217237
45. Ivanov D, Dolgui A. A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0. Prod Plan Control. 2021;32(9):775-88. DOI: https://doi.org/10.1080/09537287.2020.1768450
46. Hahn GJ. Industry 4.0: a supply chain innovation perspective. Int J Prod Res 2020;58(5):1425-41. DOI: https://doi.org/10.1080/00207543.2019.1641642
47. Ghobakhloo M, Mahdiraji HA, Iranmanesh M, Jafari-Sadeghi V. From Industry 4.0 digital manufacturing to Industry 5.0 digital society: a roadmap toward human-centric, sustainable, and resilient production. Inf Syst Front. 2024;1-33. DOI: https://doi.org/10.1007/s10796-024-10476-z
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Alejandra Holguin Avila , Luis Asunción Pérez Domínguez , Roberto Romero Lopez , David Luviano Cruz (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
The article is distributed under the Creative Commons Attribution 4.0 License. Unless otherwise stated, associated published material is distributed under the same licence.
