Evidence map›Paper›PMID 34493927›Full record

ArticleEnvironment, development and sustainability2022

Low-carbon tourism strategy evaluation and selection using interval-valued intuitionistic fuzzy additive ratio assessment approach based on similarity measures.

Arunodaya Raj Mishra, Ayushi Chandel, Parvaneh Saeidi

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Article in Environment, development and sustainability, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Arunodaya Raj MishraDepartment of Mathematics, Government College Jaitwara, Satna, Madhya Pradesh 485221 India.ORCID 0000-0001-9949-5813
Ayushi ChandelDepartment of Computer Science & Engineering, ITM University, Gwalior, Madhya Pradesh 474001 India.
Parvaneh SaeidiFacultad de Ciencias Adminsitrativas y Económicas, Universidad Tecnológica Indoamérica, Quito, Ecuador.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, the assessment and selection of most suitable low-carbon tourism strategy has gained an extensive consideration from sustainable perspectives. Owing to participation of multiple qualitative and quantitative attributes, the low-carbon tourism strategy (LCTS) selection process can be considered as multi-criteria decision-making (MCDM) problem. As uncertainty is usually occurred in LCTSs evaluation, the theory of interval-valued intuitionistic fuzzy sets (IVIFSs) has been established as more flexible and efficient tool to model the uncertain decision-making problems. The idea of the present study is to develop an extended method using additive ratio assessment (ARAS) framework and similarity measures in a way to find an effective solution to the decision-making problems using IVIFSs. The bases of the proposed method are the IVIFSs operators, some modifications in the traditional ARAS framework and a calculation procedure of the weights of the criteria. To calculate criterion weight, new similarity measures for IVIFSs are developed aiming at the achievement of more realistic weights. Also, a comparison is demonstrated to the currently used similarity measures in order to show the efficiency of the developed approach. To confirm that the developed IVIF-ARAS approach can be successfully employed to practical decision-making problems, a case study of LCTS selection problem is considered. The final results from the developed approach and the extant models are compared for the validation of the proposed approach in this study.

Indexed as

ARASInterval-valued intuitionistic fuzzy setsLow-carbon tourismMCDMSimilarity measure

Identifiers

PMID34493927
PMCPMC8413083

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