4.7 Article

Interval type 2 trapezoidal-fuzzy weighted with zero inconsistency combined with VIKOR for evaluating smart e-tourism applications

期刊

INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
卷 36, 期 9, 页码 4723-4774

出版社

WILEY-HINDAWI
DOI: 10.1002/int.22489

关键词

data management; evaluation and benchmarking; IT2TR-FWZIC; multicriteria decision-making; smart e-tourism; VIKOR

资金

  1. National Natural Science Foundation of China [71910107002]
  2. State key R&D Program of China [2020YFC0832702]
  3. Major project of the National Social Science Foundation of China [19ZDA092]

向作者/读者索取更多资源

The study effectively addresses the issue of multicriteria decision-making by constructing a decision matrix, computing weights of key concepts, and evaluating and benchmarking smart e-tourism data management applications.
The benchmarking of smart e-tourism data management applications falls under the problem of multicriteria decision-making (MCDM). This claim is supported by three issues: 12 smart key concepts need to be considered in the evaluation, criteria importance, and data variation among these criteria. Thus, an MCDM solution is essential to overcome problem complexity. To end this, this study presents a decision-making framework on the basis of the extension of interval type 2 trapezoidal-fuzzy weighted with zero inconsistency (IT2TR-FWZIC) integrated with the Vlsekriterijumska Optimizcija I Kaompromisno Resenje (VIKOR) method for evaluating and benchmarking the smart e-tourism data management applications. Our methodology comprises two consecutive phases. In the first phase, a decision matrix is constructed using the intersection between the 12 key concepts and smart e-tourism data management applications of each category and subcategory in smart e-tourism. In the second phase, the integration of the IT2TR-FWZIC formulation and VIKOR is presented to compute the weights for the 12 key concepts and benchmark the smart e-tourism data management applications for each category. The results are as follows: (1) A clear difference is found among the criteria weights (12 smart key concepts). Specifically, the real-time criterion achieves the highest importance weight (0.098), whereas augmented reality obtains the lowest weight (0.068). The context-awareness and recommender systems have the same weight value (0.087), and the other eight criteria are distributed in between. (2) The smart e-tourism data management applications are evaluated and benchmarked effectively per category and subcategories. (3) Benchmarked applications in each category are subjected to a systematic ranking in the evaluation process. The sensitivity analysis has shown high correlation outcomes to the systematic ranking results over the 31 scenarios of criteria weight changing. Moreover, a comparative analysis of the proposed work with other existing studies is also discussed.

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