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Customer satisfaction using fuzzy set qualitative comparative analysis and Kano's model: the case of super markets

Sovatzidi Paraskevi-Panagiota

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Summary

The aim of this thesis is to find the necessary and satisfactory conditions regarding the satisfaction of customers by Supermarkets utilizing Qualitative Comparative analysis using fuzzy sets, known as fsQCA and afterwards the attribute categorization into Kano’s quality levels. The fsQCA method uses the theory of fuzzy sets and Boolean algebra to analyze to what extent some factors or combinations of factors are present or absent when the phenomenon in question happens or not. The causal conditions (combinations of satisfaction dimensions) that are capable of causing a high or low level of consumer satisfaction are identified, as long as any necessary conditions for the presence of the result (Total Satisfaction). In particular, fsQCA will be performed in order to examine the relationship between nine dimensions of satisfaction and Total Satisfaction of a sample of 2101 customers of various supermarkets, utilizing the data of a previous survey aimed at creating rules for understanding consumer behavior. Analysis will then be performed, using the MUSA software. MUSA is a multi‐criteria model that calculates the estimated significance proposed by Grigoroudis & Siskos (2002) and is a methodology for assessing the satisfaction of a sample of clients and the importance of satisfaction criteria. The estimation is based on the preferences of all customers, which are considered to be unified. Then the sample will be separated, distinguishing the latter in satisfied and dissatisfied customers. These two groups will then be analyzed using the MUSA software. This will redefine the quality characteristics and lead to more accurate conclusions regarding the relationship between the features in question and customer satisfaction. Then the attributes will be categorized according to the Kano model. Concerning the Kano model, the classification of attributes is based on the Attractive Quality Theory, according to which the characteristics are grouped into three distinct levels: expected quality, desirable quality and attractive quality. The consumer's decision to choose a particular store for his purchases and hence his satisfaction is influenced by a variety of factors that are present to a different extent and even if those factors were absent, they will never be expressed by any customer. This is why the examination of this problem using multiple methods seemed appropriate. Performing the MUSA analysis, both with the generalized model and with alternative stability analysis approaches, such as MUSA I, II and III, we were able to define the type of consumers tested, the overall satisfaction and ultimately map out a possible strategy that can be followed by the business. In detail, we concluded that a sample of neutral and non‐demanding customers is being examined and for the most part there are extremely high satisfaction indices, both for total satisfaction and for each attribute itself. Regarding the action maps, it is noted that Variety is the most important feature and that the first priority of the business should be the criteria: Easy Access, Variety, Sales, Atmosphere, Services and Quality. Finally, regarding the improvement maps it is proposed to improve the dimensions of high satisfaction combined with low demanding indices, such as Quality, Reputation, Services, Easy Access and Ambience. At this point, fsQCA results proved to be particularly interesting, since it was possible to examine the participation of the dimensions of satisfaction considered, revealing causal recipes that could discourage consumers and reduce their satisfaction. High levels of consumer dissatisfaction may occur in case of absence of product quality OR absence of product variety combined with absence of sales OR reputation OR ambience OR services OR arrangement. Finally, Kano model categorization of the attributes in which the majority of the sample was satisfied but without expressing in detail why, drew a clear picture regarding consumer preferences. In more detail, according to our results regarding the 3 versions of MUSA software we concluded that Quality consists a constant and is characterized as a must‐be attribute, while Variety and Price vary from one‐dimensional to attractive attributes and Reputation varies from one dimensional to a must‐be attribute.

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