Strategic supplier selection for renewable energy supply chain under green capabilities (fuzzy BWM-WASPAS-COPRAS approach)

Masoomi, Behzad; Sahebi, Iman Ghasemian; Fathi, Masood; Yıldırım, Figen; Ghorbani, Shahryar

doi:10.1016/j.esr.2022.100815

Cited by 100 publications

(41 citation statements)

References 82 publications

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“…The COPRAS approach was used by Rani et al [64] to solve the SSS for a trading organization in India. Masoomi et al [65] devised a fuzzy COPRAS strategy for strategic supplier selection in the renewable energy supply chain based on green capabilities. Kumari and Mishra [66] proposed a multi-criteria COPRAS technique for intuitionistic fuzzy sets based on parametric measures: application of green supplier selection.…”

Section: Literature Review On Proposed Methodologymentioning

confidence: 99%

A Two-Stage Multi-Criteria Supplier Selection Model for Sustainable Automotive Supply Chain under Uncertainty

Dang

Nguyen

et al. 2022

Axioms

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Sustainable supplier selection (SSS) is gaining popularity as a practical method to supply chain sustainability among academics and practitioners. However, in addition to balancing economic, social, and environmental factors, the emergence of the COVID-19 pandemic has affected the selection of long-term suppliers to ensure sustainable supply chains, recover better from the pandemic and effectively respond to any future unprecedented crises. The purpose of this study is to assess and choose a possible supplier based on their capability to adapt to the COVID-19 epidemic in a sustainable manner. For this assessment, a framework based on multi-criteria decision making (MCDM) is provided that integrates spherical fuzzy Analytical Hierarchical Process (SF-AHP) and grey Complex Proportional Assessment (G-COPRAS), in which spherical fuzzy sets and grey numbers are used to express the ambiguous linguistic evaluation statements of experts. In the first stage, the evaluation criteria system is identified through a literature review and experts’ opinions. The SF-AHP is then used to determine the criteria weights. Finally, the G-COPRAS method is utilized to select sustainable suppliers. A case study in the automotive industry in Vietnam is presented to demonstrate the proposed approach’s effectiveness. From the SF-AHP findings, “quality”, “use of personal protective equipment”, “cost/price”, “safety and health practices and wellbeing of suppliers”, and “economic recovery programs” have been ranked as the five most important criteria. From G-COPRAS analysis, THACO Parts (Supplier 02) is the best supplier. A sensitivity study was also conducted to verify the robustness of the proposed model, in which the priority rankings of the best suppliers are very similar. For long-term development and increased competitiveness, industrial businesses must stress the integration of response mechanisms during SSS implementation in the COVID-19 epidemic, according to the findings. This will result in significant cost and resource savings, as well as reduced environmental consequences and a long-term supply chain, independent of the crisis.

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Section: Literature Review On Proposed Methodologymentioning

confidence: 99%

A Two-Stage Multi-Criteria Supplier Selection Model for Sustainable Automotive Supply Chain under Uncertainty

Dang

Nguyen

et al. 2022

Axioms

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“…Guner et al [71] utilized the spherical fuzzy set to put forward a model with the Hamacher function, AHP, and CO-PRAS methods for group decision making. Masoomi et al [72] selected renewable energy suppliers for effective sustainability strategically, by combining the BWM, WASPAS, and COPRAS methods under the fuzzy context. Mishra et al [73] performed a selection of a desalination technology to support demand by extending the COPRAS method to an interval-valued, hesitant, Fermetean fuzzy environment.…”

Section: Copras Methodsmentioning

confidence: 99%

A New Approach to the Viable Ranking of Zero-Carbon Construction Materials with Generalized Fuzzy Information

Krishankumar

Mishra²,

Cavallaro³

et al. 2022

Sustainability

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This paper aims to put forward an integrated decision approach, with generalized fuzzy information for the viable selection of zero- and low-carbon materials for construction. In countries such as India, the construction sector accounts for high pollution levels and high carbon emissions. To restore sustainability and eco-friendliness, the adoption of low-carbon materials for construction is essential and, owing to the multiple attributes associated with the selection, the problem is viewed as a multi-criteria decision-making problem. Earlier studies on material selection have faced certain issues, such as the following: (i) the modeling of uncertainty is an ordeal task; (ii) the flexibility given to experts during preference elicitation is lacking; (iii) the interactions among the criteria are not well captured; and (iv) a consideration of the criteria type is crucial for ranking. To alleviate these issues, the primary objective of this paper was to develop an integrated framework, with decision approaches for material selection in the construction sector that promote sustainability. To this end, generalized fuzzy information (GFI) was adopted as the preference style as it is both flexible and has the ability to model uncertainty from the following three dimensions: membership, non-membership, and hesitancy grades. Furthermore, the CRITIC approach was extended to the GFI context for calculating criteria weights objectively, by effectively capturing criteria interactions. Furthermore, the COPRAS technique was put forward with the GFI rating for ranking zero- and low-carbon construction materials, based on diverse attributes. The usefulness of the framework was demonstrated via a case example from India and the results showed that the design cost, the financial risk, safety, water pollution, and land contamination were the top five criteria, with blended cement, mud bricks, and bamboo as the top three material alternatives for zero- and low-carbon construction. Finally, a sensitivity analysis and a comparison with other methods revealed the theoretical positives of this framework’s robustness and consistency–but it also revealed some limitations of the proposed framework.

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“…Foody firması ise bu kriterlere göre en iyi performansı gösteren firma olmuştur. Masoomi vd., [50] dokuz kritere göre stratejik yeşil tedarikçi seçimi yapmışlardır. Uygulama kısmında WASPAS, COPRAS ve F-BWM yöntemleri entegre bir şekilde kullanılmıştır.…”

Section: Literatür Taraması (Literature Review)unclassified

Kaos durumu altında hava kargo şirketi seçimi: Bütünleşik Bayesian BWM ve WASPAS çerçevesi

Boz

Çizmecioğlu

Çalık

2023

Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi

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Karar problemlerinin sonuçları ve problemin sonuçlarını etkileyen faktörler, herhangi bir kaos durumunun bulunup bulunmamasına göre değişiklik gösterebilmektedir. Kaos durumları altında, karar alıcıların tercihleri için farklı kriterler eklenebilmekle ve kriterlerin önem düzeyleri değişebilmektedir. COVID-19 pandemisi her alanda olduğu gibi havacılık sektörünü de etkilemiş olmasına rağmen hava kargo taşımacılığı bu dönemde güçlü bir performans göstermektedir. Bu noktadan hareketle, bu çalışmada kaos durumlarının hava kargo şirketi seçimine yansıması incelenmektedir. Karar vericilerin, karar problemlerini sonuçlandırmasında etkili bir çözüm yöntemi olan Çok Kriterli Karar Verme (ÇKKV) yöntemleri ile yeni bir karar verme çerçevesi önerilmektedir. Yeni önerilen yöntemlerin daha hassas yanıt vermesinden dolayı, kriter ağırlıklarının belirlenmesinde yeni yöntemlerden olan Bayesian BWM (En İyi-En Kötü) yöntemi kullanılırken, hava kargo şirketlerinin sıralanmasında ise WASPAS yöntemi kullanılmaktadır. Böylece bu iki yöntem bütünleştirilmekte ve aynı zamanda sıralama sonuçları TOPSIS ve COPRAS yöntemi ile kıyaslanarak sonuçlar analiz edilmektedir. Buna göre, kaos ortamında hava kargo şirketi seçimi için en önemli kriter ekonomik kriterler olarak görünmektedir.

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Strategic supplier selection for renewable energy supply chain under green capabilities (fuzzy BWM-WASPAS-COPRAS approach)

Cited by 100 publications

References 82 publications

A Two-Stage Multi-Criteria Supplier Selection Model for Sustainable Automotive Supply Chain under Uncertainty

A Two-Stage Multi-Criteria Supplier Selection Model for Sustainable Automotive Supply Chain under Uncertainty

A New Approach to the Viable Ranking of Zero-Carbon Construction Materials with Generalized Fuzzy Information

Kaos durumu altında hava kargo şirketi seçimi: Bütünleşik Bayesian BWM ve WASPAS çerçevesi

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