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Article type: Research Article
Authors: Krishankumar, Raghunathana | Pamucar, Draganb; c; *
Affiliations: [a] Information Technology Systems and Analytics Area, Indian Institute of Management Bodh Gaya, Bodh Gaya, Bihar, India | [b] Faculty of Organizational Sciences, University of Belgrade, Belgrade, Serbia | [c] MEU Research Unit, Middle East University, Amman, Jordan
Correspondence: [*] Corresponding author: Dragan Pamucar, Faculty of Organizational Sciences, University of Belgrade, Serbia. E-mail: dpamucar@gmail.com.
Abstract: With a growing focus from the United Nations to eradicate the ill effects of climate change, countries around the world are transforming to green and sustainable habits/practices. Adoption of clean energy for demand satisfaction is a prime focus of many countries as it reduces carbon trace and promotes global development. In developing countries like India, there is an urge for sustainable global development. Literature shows that direct and complete adoption of clean energy incurs some barriers, which impede the sustainable development of the nation. Grading such barriers supports policymakers to effectively plan strategies, which motivates authors to put forward a novel decision model with integrated approaches. First, qualitative rating data on barriers and circular economy (CE) factors are collected from experts via questionnaires, which are transformed into q-rung orthopair fuzzy information (qRFI). Second, the weights of experts and CE factors are determined by the proposed variance measure and CRITIC. Third, barriers are graded by the proposed ranking algorithm that considers modified WAPAS formulation. Finally, these approaches are integrated into a model that is testified for practicality by using a case example from India. Sensitivity and comparative analyses are performed to realize the merits and limitations of the model for extant works.
Keywords: Clean energy, sustainability barriers, evidence measure, CoCoSo method, q-Rung orthopair fuzzy, circular economy
DOI: 10.3233/KES-230048
Journal: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. 27, no. 1, pp. 55-72, 2023
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