Decision-making methodology by using multi-expert knowledge for uncertain environments: green metric assessment of universities

• Published in: Environment, development and sustainability Vol. 25; no. 8; pp. 7393 - 7422
• Main Authors: Karasan, Ali, Kutlu Gündoǧdu, Fatma, Aydın, Serhat
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.08.2023; Springer Nature B.V
• Subjects: Climate change; Cognitive ability; Cognitive mapping; Cognitive maps; College campuses; Colleges & universities; Criteria; Decision analysis; Decision makers; Decision making; Decision making models; Earth and Environmental Science; Ecology; Economic Geology; Economic Growth; Environment; Environmental Economics; Environmental Management; Fuzzy systems; Mathematical models; Methodology; Ranking; Ratings & rankings; Research methodology; Sensitivity analysis; Sustainability; Sustainable Development; Cognitive maps; Intuitionistic fuzzy sets; DEMATEL; VIKOR; Sustainability; Fuzzy inference systems
• ISSN: 1387-585X; 1573-2975
• DOI: 10.1007/s10668-022-02321-7

Campus sustainability and climate change reduction have become a significant global concern for university administrators in recent days. Several evaluation systems of universities exist, and UI GreenMetric World University is one of the most used ranking one among them. The goal is to provide an image of current conditions relating to the green campus and sustainability of universities worldwide. The ranking system uses six main criteria and 39 sub-criteria and a numeric scoring system to evaluate universities. Unfortunately, collecting a numeric datum is not always easy for decision-makers. Decision-makers need a system using human judgments. For this aim, we proposed a new fuzzy ranking system based on a multi-stage decision-making model including DEMATEL, Cognitive maps, VIKOR, and Fuzzy inference systems. The proposed model uses 18 different criteria collected from UI GreenMetric World University ranking methodology. It captures the qualitative factors of the ranking system. To show the applicability of the method, we applied the proposed method to determine the universities’ green index. The sensitivity analysis is also performed by changing decision-makers’ weights. The results demonstrate that the proposed methodology is a useful and sensitive tool to calculate the green index of the universities with fuzzy linguistic expressions.