Abstract
Low-carbon tourism is an effective solution to cope with the goal conflict between developing tourist economy and responding to carbon emission reduction and ecological environment protection. Tourism scenic spots are important carriers of tourist activities and play a crucial role in low-carbon tourism. There are multiple factors affecting the low-carbon performance of a tourism scenic spot, and thus the performance evaluation and ranking of low-carbon tourism scenic spots can be framed as a hierarchical multi-criteria decision making (MCDM) problem. This paper develops a novel method to tackle hierarchical MCDM problems, in which the importance preferences of criteria over the decision goal and sub-criteria with respect to the upper-level criterion are provided by linguistic-term-based pairwise comparisons and the assessments of alternatives over each of sub-criteria at the lowest level are furnished by positive interval values. The linguistic-term-based pairwise comparison matrices are converted into intuitionistic fuzzy preference relations and an approach is developed to obtain the global importance weights of the lowest level sub-criteria. A multiplicatively normalized intuitionistic fuzzy decision matrix is established from the interval-value-based assessments of alternatives and a method is proposed to determine the intuitionistic fuzzy value based comprehensive scores of alternatives. A case study is offered to illustrate how to build a performance evaluation index system of low-carbon tourism scenic spots located at Zhejiang Province of China and show the use of the proposed intuitionistic fuzzy hierarchical MCDM method.
Highlights
With the increasing challenge on climate change, low-carbon economy has become a consensual solution for coping with global warming and preserving ecological environment [1]
They utilized the commonly used multi-criteria decision making (MCDM) method called analytic hierarchy process (AHP) to obtain real-valued importance weights of criteria and sub-criteria, and gave a case study of the low-carbon performance evaluation for the Xixi National Wetland located at Hangzhou of China
We proposed a method to tackle hierarchical MCDM problems, where the importance weights of criteria and sub-criteria are without past data and the assessments of alternatives with respect to the lowest level sub-criteria are characterized by different dimension interval values derived from statistical tables and questionnaires
Summary
With the increasing challenge on climate change, low-carbon economy has become a consensual solution for coping with global warming and preserving ecological environment [1]. Cheng et al [17] established a 4-level index system consisting of 27 lowest-level sub-criteria concerned with eco-environment, tourist facilities, management and participant attitudes to evaluate the low-carbon performance of tourism attractions They utilized the commonly used multi-criteria decision making (MCDM) method called analytic hierarchy process (AHP) to obtain real-valued importance weights of criteria and sub-criteria, and gave a case study of the low-carbon performance evaluation for the Xixi National Wetland located at Hangzhou of China. This paper devises a scale conversion between linguistic terms and intuitionistic fuzzy values (IFVs) and develops a novel approach to aggregate local importance weights of criteria and sub-criteria into the global importance weights of the lowest level sub-criteria in an evaluation index system Another important stage in evaluating performances of low-carbon tourism scenic spots is to obtain the comprehensive scores of alternatives [17,19,22,23,24].
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