The differences in hotel selection among various types of travellers: A comparative analysis with a useful bounded rationality behavioural decision support model

Wang, Le; Wang, Xiaokang; Peng, Juanjuan; Wang, Jianqiang

doi:10.1016/j.tourman.2019.103961

Cited by 161 publications

(97 citation statements)

References 56 publications

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“…Moreover, it is easy to integrate with other MCDM approaches (such as AHP/BWM) and provides reliable evaluation results, which has led to this technique being used in many site selection problems [28]. Since TOPSIS is a technique that relies heavily on the value of information, the reliability of information will directly affect the quality of ranking results [29]. This approach is further extended to Z-numbers in our study.…”

Section: Methods For Npp Site Selectionmentioning

confidence: 98%

A Multi-Criteria Decision Support Framework for Inland Nuclear Power Plant Site Selection under Z-Information: A Case Study in Hunan Province of China

Peng

Wang

et al. 2020

Mathematics

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To promote the development of nuclear power project in inland China, a specialized multi-criteria decision support framework is constructed for the site selection of inland nuclear power plants in this work. The best worst method (BWM), decision-making trial and evaluation laboratory (DEMATEL), and technique for order performance by similarity to ideal solution (TOPSIS) are integrated with Z-numbers, namely Z-BWM, Z-DEMATEL, and Z-TOPSIS. Z-BWM and Z-DEMATEL are combined to produce the weights of criteria, and an extended Z-TOPSIS is utilized to determine the ranking of all alternatives. Finally, a case study is performed in Hunan province to demonstrate the practicability of the proposed decision support framework. The robustness and feasibility of the proposed method are shown by an in-depth analysis of the decision results.that are not prone to tsunamis or typhoons. China has a total of 48 nuclear power units in operation, but they are all in coastal areas. The specific research on the site selection of China's inland NPPs is still insufficient. In this work, a multi-criteria decision support framework is provided to identify the best site for inland NPPs in China, and the contributions are summarized as follows:(1) The existing researches on multi-criteria decision-making (MCDM) problems inevitably involve the uncertainly and unreliability of human preferences. Therefore, Z-number is introduced into the proposed MCDM framework in this work, and all evaluation information is given using Z-number linguistic variables.(2) Best worst method (BWM) and decision-making trial and evaluation laboratory (DEMATEL) are extended to Z-numbers, i.e., Z-BWM and Z-DEMATEL. The hybrid model not only considers the impact of the criterion relations on the criterion weights, but also provides a long-term improvement for inland NPP site selection.(3) The technique for order performance by similarity to ideal solution (TOPSIS) is combined with Z-numbers, namely Z-TOPSIS. It can effectively reduce the influence of outliers, and provide more reliable ranking results than the classic TOPSIS.(4) Currently, few researches focus on the site selection of China's inland NPPs. Based on the reactor siting criteria developed by IAEA, a specialized evaluation system considering the eco-environment, geographic features, and socio-economic factors in China's interior is constructed.The structure of the paper is organized as follows. Section 2 reviews some studies related to NPP site selection. Section 3 introduces some basic concepts of Z-numbers. Section 4 presents the proposed framework for inland NPP site selection. Section 5 provides a case study in Hunan province of China. Section 6 conducts an in-depth analysis concerning selection results. Finally, Section 7 draws conclusions.

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Section: Methods For Npp Site Selectionmentioning

confidence: 98%

A Multi-Criteria Decision Support Framework for Inland Nuclear Power Plant Site Selection under Z-Information: A Case Study in Hunan Province of China

Peng

Wang

et al. 2020

Mathematics

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“…37,38 The fuzzy comprehensive evaluation method, which consolidates the comprehensive evaluation methodology (commonly regarded as a multicriteria decision issue) and fuzzy theory (managing vagueness or information full of uncertainties), 25 is widely applied for decision support, prediction analysis, and risk assessment in many fields. 37,38 The fuzzy comprehensive evaluation method, which consolidates the comprehensive evaluation methodology (commonly regarded as a multicriteria decision issue) and fuzzy theory (managing vagueness or information full of uncertainties), 25 is widely applied for decision support, prediction analysis, and risk assessment in many fields.…”

Section: Fuzzy Comprehensive Evaluation Methodsmentioning

confidence: 99%

“…Fuzzy theory is applied extensively to the fuzzy system to support the multicriteria group decision-making and tends to generally combine with other theories to encourage a broader range of applications. 37,38 The fuzzy comprehensive evaluation method, which consolidates the comprehensive evaluation methodology (commonly regarded as a multicriteria decision issue) and fuzzy theory (managing vagueness or information full of uncertainties), 25 is widely applied for decision support, prediction analysis, and risk assessment in many fields. The result of FCEM is expressed as the fuzzy judgment vector, S, which is obtained from fuzzy evaluation matrix R and weight vector W ( Equation 14).…”

Section: Fuzzy Comprehensive Evaluation Methodsmentioning

confidence: 99%

Approaches for the evaluation of favorable shale gas areas and applications: Implications for China's exploration strategy

Zhang

Tang

et al. 2019

Energy Science & Engineering

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To explore practical approaches for the evaluation of favorable shale gas areas, a structural decomposition analysis with respect to the index system, evaluation criteria, weight determination, and evaluation methods was carried out. Five types of indexes were determined from 25 subindexes that formed the index system, and improved whitenization weight functions are proposed to establish evaluation criteria. The index weights calculated using entropy weight and Euclidean distance methods are consistent, whereas the weights determined by gray relational analysis are significantly affected by the relative number of indexes and evaluation objects, selected mother factor, and resolution coefficient. The significant linear positive correlation between the relative approach degree values calculated using TOPSIS and the scores obtained using fuzzy comprehensive evaluation (FCE) is indicative of a consistent evaluation result, but it should be noted that extreme indicator values can have strong effects on the evaluation using the fuzzy similarity method. Finally, an exploration strategy for China's shale gas is suggested: Areas with weak reformation and relatively low maturity are expected to be favorable for marine shale production in South China, and continental and transitional shale‐bearing basins are promising for the prospecting multiple‐origin shale gas and coal measure gas, respectively.

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“…To be specific, in subjective weight estimation methods, the weights information is obtained based on humans' subjective judgments or experience [35,36]. In contrast with the subjective methods, the objective weights are derived merely by the data given in the decision matrices [37,38]. Therefore, it may cause the intense subjectivity or the absence of subjective preference if only the subjective method or objective method is used in weights determination.…”

Section: Literature Reviewmentioning

confidence: 99%

New Framework for Quality Function Deployment Using Linguistic Z-Numbers

Song

Wang

2020

Mathematics

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Quality function deployment (QFD) is a useful design quality control tool in service enterprises and manufacturing enterprises. However, there are several issues in extant QFD frameworks, that is, in three aspects: description of evaluation information, weight determination of expert team members (TMs), and weight identification of customer requirements (CRs). In order to address these issues, a novel QFD framework is first proposed utilizing linguistic Z-numbers (LZNs) with integrated subjective and objective weights of TMs and CRs. The LZNs can represent uncertain information and the reliability of information in a specific way while the fuzzy numbers cannot. Moreover, the order relation analysis (G1) method and improved maximum consensus (MC) method are developed to get the subjective and objective weights of TMs, respectively. Further, the step-wise weight assessment ratio analysis (SWARA) method and statistical distance (SD) method are studied to acquire combined weights of CRs. Next, the proposed QFD framework is applied to a case of logistics service provider, which illustrates the availability and utility of the framework. Then, a sensitivity analysis is conducted to prove the reliability of the framework. Finally, two comparative analyses are performed to declare the advantages of the framework. Results indicate the proposed QFD framework is better than existing models.

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The differences in hotel selection among various types of travellers: A comparative analysis with a useful bounded rationality behavioural decision support model

Cited by 161 publications

References 56 publications

A Multi-Criteria Decision Support Framework for Inland Nuclear Power Plant Site Selection under Z-Information: A Case Study in Hunan Province of China

A Multi-Criteria Decision Support Framework for Inland Nuclear Power Plant Site Selection under Z-Information: A Case Study in Hunan Province of China

Approaches for the evaluation of favorable shale gas areas and applications: Implications for China's exploration strategy

New Framework for Quality Function Deployment Using Linguistic Z-Numbers

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