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Issue title: Special Section: Similarity, correlation and association measures - dedicated to the memory of Lotfi Zadeh
Guest editors: Ildar Batyrshin, Valerie Cross, Vladik Kreinovich and Maria Rifqi
Article type: Research Article
Authors: Kumar, Mohit; *
Affiliations: Department of Mathematics, Institute of Infrastructure Technology Research and Management, Ahmedabad, India
Correspondence: [*] Corresponding author. Mohit Kumar, Department of Mathematics, Institute of Infrastructure Technology Research and Management, Ahmedabad, India. E-mail: [email protected].
Abstract: The correlation between the performance of attributes and the overall satisfaction perceived by the customers is a successful indirect approach to evaluate the importance of the attributes in services. Recently, the fuzzy importance of attributes was discussed as the fuzzy correlation between the performance of attributes and the overall satisfaction. In this paper, the concept of fuzzy set is extended to the idea of intuitionistic fuzzy set and a novel simple approach is presented to evaluate the importance of attributes as the intuitionistic fuzzy correlation between the performance of attributes and the overall satisfaction. The qualitative input data such as customer’s opinions are available and expressed as linguistic terms. Each of these linguistic terms is mathematically represented by membership and non-membership functions of intuitionistic fuzzy number instead of a fuzzy number or a crisp number. The calculation is based on the weakest triangular norm (t-norm) arithmetic operations on triangular intuitionistic fuzzy numbers. The proposed approach has been applied to a survey with respect to the quality of hotel services in Oradea (Romania) and then compared with other existing approaches to calculating the importance of hotel quality attribute.
Keywords: Correlation coefficient, intuitionistic fuzzy number, weakest t-norm arithmetic, triangular intuitionistic fuzzy number, intuitionistic fuzzy importance
DOI: 10.3233/JIFS-18485
Journal: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 4, pp. 3211-3223, 2019
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