Low-carbon tourism destination selection by a thermodynamic feature-based method

Cheng Zhang, Huchang Liao, Li Luo and Zeshui Xu

Journal of the Operational Research Society, 2022, vol. 73, issue 8, 1692-1707

Abstract: Developing low-carbon tourism can not only improve the ecological environment, but also promote the development of economy in China. To select a desirable low-carbon tourism destination, we need to consider multiple conflicting and incommensurate criteria, simultaneously. However, traditional decision-making methods such as analytical hierarchy process and Delphi fail to model the complex cognition of decision makers. In this regard, this article proposes a novel multi-criteria decision making method called the thermodynamic feature-based method to aid decision makers to select the optional low-carbon tourism destination. The q-rung orthopair fuzzy set (q-ROFS), as a recently proposed information representation model, is used to express the imprecise information of decision makers. We first introduce new distance measures of q-ROFSs and investigate their desirable properties in detail. Afterwards, a thermodynamic feature-based method is developed from the aspects of energy, exergy and entropy of alternatives integrating both quantitative and qualitative decision information. Finally, a case study concerning the selection of low-carbon tourism destination is given to illustrate the applicability and superiority of the proposed method.

Date: 2022
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DOI: 10.1080/01605682.2021.1908862

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