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A New Decision-Making Approach Based on Fermatean Fuzzy Sets and WASPAS for Green Construction Supplier Evaluation

Author

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  • Mehdi Keshavarz-Ghorabaee

    (Department of Management, Faculty of Humanities (Azadshahr Branch), Gonbad Kavous University, Gonbad Kavous 49717-99151, Iran)

  • Maghsoud Amiri

    (Department of Industrial Management, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran 14348-63111, Iran)

  • Mohammad Hashemi-Tabatabaei

    (Department of Industrial Management, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran 14348-63111, Iran)

  • Edmundas Kazimieras Zavadskas

    (Institute of Sustainable Construction, Vilnius Gediminas Technical University, Sauletekio al. 11, LT-10223 Vilnius, Lithuania)

  • Arturas Kaklauskas

    (Department of Construction Management and Real Estate, Vilnius Gediminas Technical University, Sauletekio al. 11, LT-10223 Vilnius, Lithuania)

Abstract

The construction industry is an important industry because of its effects on different aspects of human life experiences and circumstances. Environmental concerns have been considered in designing and planning processes of construction supply chains in the recent past. One of the most crucial problems in managing supply chains is the process of evaluation and selection of green suppliers. This process can be categorized as a multi-criteria decision-making (MCDM) problem. The aim of this study is to propose a novel and efficient methodology for evaluation of green construction suppliers with uncertain information. The framework of the proposed methodology is based on weighted aggregated sum product assessment (WASPAS) and the simple multi-attribute rating technique (SMART), and Fermatean fuzzy sets (FFSs) are used to deal with uncertainty of information. The methodology was applied to a green supplier evaluation and selection in the construction industry. Fifteen suppliers were chosen to be evaluated with respect to seven criteria including “estimated cost”, “delivery efficiency”, “product flexibility”, “reputation and management level”, “eco-design”, and “green image pollution”. Sensitivity and comparative analyses were also conducted to assess the efficiency and validity of the proposed methodology. The analyses showed that the results of the proposed methodology were stable and also congruent with those of some existing methods.

Suggested Citation

  • Mehdi Keshavarz-Ghorabaee & Maghsoud Amiri & Mohammad Hashemi-Tabatabaei & Edmundas Kazimieras Zavadskas & Arturas Kaklauskas, 2020. "A New Decision-Making Approach Based on Fermatean Fuzzy Sets and WASPAS for Green Construction Supplier Evaluation," Mathematics, MDPI, vol. 8(12), pages 1-24, December.
  • Handle: RePEc:gam:jmathe:v:8:y:2020:i:12:p:2202-:d:460035
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    References listed on IDEAS

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    Cited by:

    1. Saraji, Mahyar Kamali & Streimikiene, Dalia, 2022. "Evaluating the circular supply chain adoption in manufacturing sectors: A picture fuzzy approach," Technology in Society, Elsevier, vol. 70(C).
    2. Radojko LUKIC, 2023. "Analysis of the Trade Performance of the European Union and Serbia on the Base of FF-WASPAS and WASPAS Methods," REVISTA DE MANAGEMENT COMPARAT INTERNATIONAL/REVIEW OF INTERNATIONAL COMPARATIVE MANAGEMENT, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 24(2), pages 228-250, May.
    3. Çiğdem Sıcakyüz, 2023. "Analyzing Healthcare and Wellness Products’ Quality Embedded in Online Customer Reviews: Assessment with a Hybrid Fuzzy LMAW and Fermatean Fuzzy WASPAS Method," Sustainability, MDPI, vol. 15(4), pages 1-41, February.
    4. Vladimir Simic & Ali Ebadi Torkayesh & Abtin Ijadi Maghsoodi, 2023. "Locating a disinfection facility for hazardous healthcare waste in the COVID-19 era: a novel approach based on Fermatean fuzzy ITARA-MARCOS and random forest recursive feature elimination algorithm," Annals of Operations Research, Springer, vol. 328(1), pages 1105-1150, September.
    5. Mohammad Javad Bidel & Hossein Safari & Hannan Amoozad Mahdiraji & Edmundas Kazimieras Zavadskas & Jurgita Antucheviciene, 2022. "A Framework for Project Delivery Systems via Hybrid Fuzzy Risk Analysis: Application and Extension in ICT," Mathematics, MDPI, vol. 10(17), pages 1-22, September.

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