Abstract
Choquet integral is a type of aggregation operator that is commonly used to aggregate the interrelated information. Nowadays, this operator has been successfully embedded with fuzzy measures in solving various evaluation problems. Inspired from this new development, this paper aims to introduce a combined Choquet integral-fuzzy measures (CI-FM) operator that uses the Shapley value standard and interaction index to deal with the interactions between elements of information. The proposed operator takes into account not only the importance of elements or their ordered positions but also the interaction among criteria during the evaluation process. A case of customers’ satisfaction over two fast restaurants in Malaysia is presented to illustrate the application of the proposed aggregation operator. Based on three customers’ satisfaction criteria, restaurant 1 and restaurant 2 received CI-FM scores of 0.711011 and 0.704945, respectively. Interestingly, the criterion “services” constantly received the highest rating across both restaurants. In addition, the proposed aggregation operator successfully identified which restaurant is superior in the eyes of customers. Finally, this study offers some research ideas for the future.
Highlights
Current developments in information processing have increased the need for an efficient information aggregation operator. e interaction between criteria exists in a real multicriteria decision-making analysis
We presented the application of the Choquet integral-fuzzy measures (CI-FM) model to suggest the better fast-food restaurant from the perception of consumers’ satisfaction
Evaluation with the linguistic “satisfaction” of two fast-food restaurants in Terengganu Malaysia and three criteria was conducted by a group of customers. e results of Choquet values were obtained after executing series of computational procedures
Summary
Current developments in information processing have increased the need for an efficient information aggregation operator. e interaction between criteria exists in a real multicriteria decision-making analysis. On a subset of Kansei characteristics, this entropy-based technique was used to estimate the fuzzy measure In another customers’ satisfaction research, Pelaez, et al [20] proposed a new purchase decision prediction model in investigating the rank of consumer purchasing factors in digital ecosystem. Is computation allows to comprehensively reflect the interaction between all possible combination of criteria in consumers’ satisfaction decision problem where information about multiple products and their multiple interdependent criteria are aggregated. Motivated by this advantage, this paper extends the application of CI-FM to another real case study of consumers’ satisfaction decision problem. To the best of authors knowledge, this is the first identifiable work of CIFM application to customers’ satisfaction. e basic concepts of the fuzzy measures, Choquet integral, and Shapley value standard are recalled
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