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Background: The COVID-19 pandemic exposed vulnerabilities in global supply chains, highlighting the urgent need for resilience and sustainability. As businesses recover and adapt, selecting sustainable suppliers has become crucial to ensure long-term environmental, social, and economic stability. Sustainable supplier selection not only supports these goals but also enhances competitive advantage in a rapidly changing business landscape. This study was initiated to address these post-pandemic challenges, providing a systematic evaluation of suppliers based on sustainability using multi-criteria decision-making (MCDM) methods. It aims to assess the effectiveness of MEREC and CoCoSo methods in supporting sustainable supplier selection, offering insights and strategic guidance for businesses. To this end, it develops a novel approach integrating these methods that facilitates effective and sustainable supplier selection in the context of post-pandemic supply chain challenges. Methods: The study evaluates seven suppliers against five key criteria relevant to sustainable supply chains: environmental sustainability, social responsibility, cost, delivery time, and supplier reliability. The MEREC method is employed to assign weights to each criterion, establishing their relative importance in the supplier selection process. Following this, the CoCoSo method ranks the suppliers based on these weighted criteria, facilitating the identification of the most suitable supplier for sustainability-focused objectives. The combined use of MEREC and CoCoSo enables a robust and balanced approach to multi-criteria decision-making. Results: The MEREC analysis indicates that environmental sustainability and cost are the most critical criteria in sustainable supplier selection. Using the CoCoSo method, suppliers are ranked according to their performance across the criteria, with the top supplier offering the optimal sustainability balance. The findings support the use of these methods to prioritize suppliers aligned with sustainability goals, emphasizing the flexibility of CoCoSo in supplier ranking and the accuracy of MEREC in weight calculation. Conclusion: This study demonstrates the advantages of integrating the MEREC and CoCoSo methods in sustainable supplier selection processes. Its findings could guide businesses looking to optimize sustainability-focused decision-making processes in supply chain management. Future studies could expand the scope of this research by including more criteria and alternatives, and the approach could be adapted for sustainable supply chain practices in various industries. Such studies would contribute to global supply chain sustainability by supporting companies in fulfilling their environmental and social responsibilities.
Wydawca
Czasopismo
Rocznik
Tom
Strony
63--72
Opis fizyczny
Bibliogr. 26 poz., tab.
Twórcy
autor
- Sciences Department of Business Administration, İzmir Bakırçay University Faculty of Economics and Administrative, İzmir, Turkey
Bibliografia
- 1. Azadnia, A.H., Ghadimi, P., & Wong, K.Y. 2015. Sustainable supplier selection and order lot-sizing: an integrated multi-objective decision-making process. International Journal of Production Economics, 166, 324-332. https://doi.org/10.1016/j.ijpe.2015.02.013
- 2. Büyüközkan, G., & Çifçi, G. 2012. Evaluation of the green supply chain management practices: An integrated fuzzy multi-criteria decision-making approach. Journal of Cleaner Production, 47, 345-354. https://doi.org/10.1016/j.jclepro.2012.06.012
- 3. Cevik, M., et al. 2022. Evaluating green technology suppliers using MEREC. Environmental Technology and Innovation. https://dx.doi.org/10.1007/s40747-023-01032-4
- 4. Cheng, R., Fan, J., & Wu, M. 2023. A dynamic multi-attribute group decision-making method with R-numbers based on MEREC and CoCoSo method. Complex & Intelligent Systems. https://doi.org/10.1007/s40747-023-01032-4
- 5. Detwal, P.K., Agrawal, R., Samadhiya, A., Kumar, A., & Garza-Reyes, J.A. 2024. Research developments in sustainable supply chain management considering optimization and industry 4.0 techniques: a systematic review. Benchmarking: An International Journal, 314, 1249-1269. https://doi.org/10.1108/BIJ-01-2023-0055
- 6. Demirkaya, F., et al. 2023. Sustainable transportation planning with CoCoSo. Transportation Research Part D. https://dx.doi.org/10.1007/s40747-023-01032-4
- 7. Golgeci, I., et al. 2023. Decision making for environmental management through MEREC. Journal of Environmental Management. https://dx.doi.org/10.1007/s40747-023-01032-4
- 8. Govindan, K., Khodaverdi, R., & Jafarian, A. 2013. A fuzzy multi-criteria approach for measuring sustainability performance of a supplier based on triple bottom line approach. Journal of Cleaner Production, 47, 345-354. https://doi.org/10.1016/j.jclepro.2013.01.027
- 9. Govindan, K., Soleimani, H., & Kannan, D. 2015. Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future. European Journal of Operational Research, 2403, 603-626. https://doi.org/10.1016/j.ejor.2014.07.012
- 10. Gungor, N., & Can, B. 2022. Sustainable supplier assessment in fashion using CoCoSo. Fashion Supply Chain Sustainability. https://dx.doi.org/10.1007/s40747-023-01032-4
- 11. Hammou, I.A., Salah, O., & Hebaz, A. 2022. The impact of lean & green supply chain practices on sustainability: literature review and conceptual framework. LogForum, 181.
- 12. Karaca, E., et al. 2023. Partner selection in manufacturing using MEREC. Sustainable Manufacturing Review. https://dx.doi.org/10.1007/s40747-023-01032-4
- 13. Keshavarz Ghorabaee, M., Zavadskas, E.K., & Amiri, M. 2016. The fuzzy best-worst method [BWM] for supplier selection. Information Sciences, 359-360, 57-68. https://doi.org/10.1016/j.ins.2016.05.006
- 14. Kilic, M., & Cebeci, U. 2021. Using CoCoSo Method in Sustainable Smart City Infrastructure Planning. Journal of Urban Planning and Development, 1474, 04021064.
- 15. Kilic, O., & Cebeci, T. 2021. CoCoSo for smart city infrastructure. Urban Planning and Development. https://dx.doi.org/10.1007/s40747-023-01032-4
- 16. Ojeda-Benitez, S., & Ramírez-Barreto, M.E. 2020. Sustainable Supply Chain Management—A Literature Review on Emerging Economies. Sustainability, 1217, 6972. https://doi.org/10.3390/su12176972
- 17.Ozkan, A., & Demir, I. 2022. Prioritization of Renewable Energy Projects using CoCoSo. Renewable and Sustainable Energy Reviews, 154, 111747.
- 18. Ozkan, H., & Demir, A. 2022. Renewable energy project prioritization using CoCoSo. Energy Systems. https://dx.doi.org/10.1007/s40747-023-01032-4
- 19. Sener, L., & Tekin, E. 2021. CoCoSo in healthcare facility selection. Healthcare Management Science. https://dx.doi.org/10.1007/s40747-023-01032-4
- 20. Tas, M., et al. 2023. Evaluating recycling programs with CoCoSo. Waste Management and Recycling. https://dx.doi.org/10.1007/s40747-023-01032-4
- 21. Yazdani, M., Zarate, P., Zavadskas, E., & Turskis, Z. 2019. A combined compromise solution CoCoSO method for multi-criteria decision-making problems. Management Decision. https://doi.org/10.1108/MD-05-2017-0458
- 22. Yildiz, A., & Kirca, M. 2022. Application of MEREC Method in Supplier Selection for Sustainability. Journal of Cleaner Production, 321, 129035.
- 23. Yildiz, T., & Kirca, O. 2022. Objective supplier selection using MEREC method. International Journal of Supply Chain Management. https://dx.doi.org/10.1007/s40747-023-01032-4
- 24. Yilmaz, H., & Kaplan, M. 2020. MEREC in renewable energy project evaluation. Renewable Energy Research Journal. https://dx.doi.org/10.1007/s40747-023-01032-4
- 25. Yilmaz, S., & Kaplan, B. 2020. MEREC in Renewable Energy Project Assessment. Renewable Energy, 156, 877-886.
- 26. Zhu, Q., Sarkis, J., & Lai, K. 2013. Institutional-based antecedents and performance outcomes of internal and external green supply chain management practices. Journal of Purchasing and Supply Management, 192, 106-117. https://doi.org/10.1016/j.pursup.2012.12.001
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-db74ff8c-2194-41c5-9c13-a30fff63c35a
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