Retail store performance measurement using a novel interval-valued Pythagorean fuzzy WASPAS method

Retail store selection is an important decision for both customers and retailers because it is directly linked to customer satisfaction and profitability of retailers. Because of the competitive market conditions, retailers severely try to find out what they should do to be preferred by potential customers, and consequently to grow their sales. In this context, the criteria influencing customers' store selection decision have to be analyzed. Although the relationship between customer preferences and retail store attributes has been widely studied through exploratory studies, a comprehensive framework using a multi-criteria decision making method under uncertainty to provide an overall assessment for retail stores has not yet been proposed. Pythagorean fuzzy sets are quite capable of representing uncertainty and vagueness in a decision making process by providing a larger domain to experts in expressing their opinions. Therefore, in this study, a novel interval-valued Pythagorean fuzzy WASPAS method is developed to evaluate the performance of retail stores. The obtained results are compared with crisp WASPAS and interval-valued intuitionistic WASPAS methods and it is revealed that the proposed method provides reliable and informative outputs.