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Article type: Research Article
Authors: Wen, Haolan | Chen, Yu | Wang, Weizhong; * | Ding, Ling
Affiliations: School of Economics and Management, Anhui Normal University, Wuhu, Anhui, China
Correspondence: [*] Corresponding author. Weizhong Wang, School of Economics and Management, Anhui Normal University, Wuhu, 241002, Anhui, China. E-mail: wangweizhongky@163.com.
Abstract: Sustainable food consumption and production (SFCP) has become increasingly significant for creating new value, reducing costs, and reducing greenhouse gas emissions. However, there are some challenges and barriers to implementing SFCP in practice. Moreover, current methods for prioritizing barriers to SFCP seldom consider the behavioral preference of experts and interactions among factors, especially with q-Rung orthopair fuzzy set (q-ROFS)-based information. Thus, this study aims to construct a hybrid q-ROFS-based framework for ranking these barriers. First, the q-ROFS is introduced to express the experts’ uncertain information. Then, the q-ROF- CRITIC (CRiteria importance through intercriteria correlation) method is utilized to determine criteria weights considering the interrelations among barriers. Next, the q-ROF generalized TODIM method is built to rank the barriers to SFCP by considering the impact of experts’ behavioral preferences. Finally, a numerical case of barriers analysis for SFCP is organized to display the application procedures of the constructed ranking method. The result indicates that the top-priority set is education and culture (a4), with the most significant overall dominance value (0.839). Further, a comparison exploration is given to demonstrate the preponderances of the present barriers ranking method. The outcomes demonstrate that the proposed ranking method can provide a synthetic and reliable framework to handle the prioritizing issue for the barriers to SFCP within a complex and uncertain context.
Keywords: Sustainable food consumption and production, q-Rung orthopair fuzzy set, generalized TODIM method, CRITIC approach
DOI: 10.3233/JIFS-230526
Journal: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 3, pp. 5063-5074, 2023
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