Fuzzy Decision-Making Model for Grocery Store Selection with Strength and Weakness Analysis

Abstract

Decision-making is a complex process which involves assessment over multiple criteria in obtaining the best option. Usually, decision-making process is fashioned by uncertainty and vagueness due to lack of information and complexity of alternatives. This issue can be
overcome by reducing the number of evaluations over pairwise comparisons using consistent fuzzy preference relation (CFPR). This research integrates the CFPR with weighted aggregated sum product assessment (WASPAS) approach to rank the best grocery stores by evaluating several criteria: price, convenience, freshness, service and parking area. Among these criteria, respondents tend to prioritize freshness or quality of products in selecting the best grocery store. The CFPR promises consistent decision preferences in evaluating the criteria weights, while the WASPAS combines the aggregated sum and aggregated product of decision preferences in ranking the alternatives. The stability of the obtained results is tested using different utility values in combining the weighted sum and weighted product of alternatives selection in WASPAS. Further, the strength and weakness of each grocery store are analysed over all criteria. The findings of the research can be shared with the grocery stores to improve their offered service to stay relevant in the industry.