A FIS-based fuzzy Kano’s model for consumer needs analysis

Nowadays, not only improving service levels is not sufficient for consumer satisfaction, but also, the consumers themselves determine product or service quality. In other words, we can interpret quality as "the degree of accordance with the consumer's need." Therefore, we should look for solutions to identify consumers' needs and requirements for applying them in the design and development of the product or service. One of these methods is the Kano model. This model shows the decision maker if any of the consumers' requirements are in the product/service or not and how much it will affect their satisfaction. This tool classifies consumers' needs for converting them to design requirements. But, human mentality and behavior always are accompanied by uncertainties. Linguistic variables or fuzzy numbers have been used in the literature to overcome this defect. Researchers developed the fuzzy Kano's model using this method and enhanced the model's efficiency compared to the deterministic one. The efficiency of this model has increased compared with the deterministic one. However, the decision-makers are unsure how to classify customers' needs using this strategy. This research uses a Fuzzy Inference System (FIS) to tackle this challenge. The essential contribution is developing a fuzzy Kano's model based on FIS for consumer requirements analysis. A case study from the restaurant industry in Yazd city of Iran was considered to validate the proposed model. The results show the superior performance of the proposed model compared with fuzzy Kano's model in recognizing consumers' needs.