Constructing Taiwan's Low-Carbon Tourism Development Suitability Evaluation Indicators

2018

Energy-saving and low-carbon technologies play important roles in reducing environmental risk and developing green tourism. An energy-saving and low-carbon technology scheme selection may often involve multiple criteria and sub-criteria as well as multiple stakeholders or decision makers, and thus can be structured as a hierarchical multi-criteria group decision making problem. This paper proposes a framework to solve group consensus decision making problems, where decision makers’ preferences between the alternatives considered with respective to each criterion are elicited by the paired comparison method, and expressed as triangular fuzzy preference relations (TFPRs). The paper first simplifies the existing computation formulas used to determine triangular fuzzy weights of TFPRs. A consistency index is then devised to measure the inconsistency degree of a TFPR and is used to check acceptable consistency of TFPRs. By introducing a possibility degree formula of comparing any two triangular fuzzy weights, an index is defined to measure the consensus level between an individual ranking order and the group ranking order for all alternatives. A consensus model is developed in detail for solving group decision making problems with TFPRs. A case study of selecting energy-saving and low-carbon technology schemes in star hotels is provided to illustrate how to apply the proposed group decision making consensus model in practice.

Section: Theoretical Backgroundmentioning

confidence: 99%

Fuzzy Group Consensus Decision Making and Its Use in Selecting Energy-Saving and Low-Carbon Technology Schemes in Star Hotels

Lü

Yang

2018

“…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. Cho et al [ 18 ] constructed a framework of Taiwan’s low-carbon tourism evaluation indicators concerning with travel agencies, transportation, hotels and accommodation, food service, tourism scenic spots, and local communities, and used the fuzzy AHP to derive real-valued weights of criteria and sub-criteria. Zhang [ 19 ] developed a triangular fuzzy Delphi-analytic network process model to evaluate regional low-carbon tourism strategies, and applied it to determine priority weights of low-carbon tourism strategies in China’s Chengguan District of Lhasa.…”

Section: Introductionmentioning

confidence: 99%

Intuitionistic Fuzzy Hierarchical Multi-Criteria Decision Making for Evaluating Performances of Low-Carbon Tourism Scenic Spots

Yang

2020

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.

“…A low-carbon economy has been considered to be an effective development framework for carbon reduction and environmental protection without affecting economic enhancement [ 1 , 2 ]. As a significant part of economic development, the tourism industry is encouraging low-carbon tourism and developing low-carbon tourism destinations (LCTDs) [ 3 , 4 ]. Meanwhile, more and more tourists are paying attention to carbon reduction and environmental protection, and thus select low-carbon tourism destinations to relieve the mental pressure caused by their work.…”

Section: Introductionmentioning

confidence: 99%

“…Tong and Wang [ 20 ] proposed a group decision-making framework with intuitionistic fuzzy preference relations and applied it to low-carbon supplier selection. Cho et al [ 3 ] adopted the fuzzy analytic hierarchy process to construct evaluation indicators of Taiwan’s low-carbon tourism development. Cheng [ 3 ] used the Delphi method and the analytic hierarchy process to establish evaluation indicators of low-carbon tourist attractions.…”

Section: Introductionmentioning

confidence: 99%

“…Cho et al [ 3 ] adopted the fuzzy analytic hierarchy process to construct evaluation indicators of Taiwan’s low-carbon tourism development. Cheng [ 3 ] used the Delphi method and the analytic hierarchy process to establish evaluation indicators of low-carbon tourist attractions. Zhang [ 21 ] employed the analytic network process to evaluate regional low-carbon tourism strategies.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Linguistic Multi-Attribute Group Decision Making with Risk Preferences and Its Use in Low-Carbon Tourism Destination Selection

Lin

2017

Low-carbon tourism plays an important role in carbon emission reduction and environmental protection. Low-carbon tourism destination selection often involves multiple conflicting and incommensurate attributes or criteria and can be modelled as a multi-attribute decision-making problem. This paper develops a framework to solve multi-attribute group decision-making problems, where attribute evaluation values are provided as linguistic terms and the attribute weight information is incomplete. In order to obtain a group risk preference captured by a linguistic term set with triangular fuzzy semantic information, a nonlinear programming model is established on the basis of individual risk preferences. We first convert individual linguistic-term-based decision matrices to their respective triangular fuzzy decision matrices, which are then aggregated into a group triangular fuzzy decision matrix. Based on this group decision matrix and the incomplete attribute weight information, a linear program is developed to find an optimal attribute weight vector. A detailed procedure is devised for tackling linguistic multi-attribute group decision making problems. A low-carbon tourism destination selection case study is offered to illustrate how to use the developed group decision-making model in practice.