Analyzing Healthcare and Wellness Products' Quality Embedded in Online Customer Reviews: Assessment with a Hybrid Fuzzy LMAW and Fermatean Fuzzy WASPAS Method

With the high impetus in global digitization, online shopping (OS) is anticipated to increase further in the near future. Contrary to this anticipation, however, recent studies have emphasized a certain amount of drop in a considerable number of online purchasing transactions in 2022. One of the reasons might be customer dissatisfaction. To analyze online customer reviews, manual sentiment analysis was conducted to detect which quality criteria cause the dissatisfaction of online shoppers. The quality parameters are categorized into product, delivery service, and aftersales service quality (SQ). These main quality criteria are then divided into sub-factors. Eight health category products, including personal care products, wellness products, and household cleaners, were ranked to the importance of the sub-quality parameters using the multi-criteria decision-making (MCDM) method. In this study, a new hybrid MCDM method was also proposed, which combines the triangular fuzzy logarithm methodology of additive weights (F-LMAW) and the Fermatean fuzzy weighted aggregated sum product assessment method (FF-WASPAS). The study reveals that the most important criteria were products' performance, as well as their side effects, pay-back, and change possibility, while the products' reasonable price was the least important criterion. Aftersales service was more significant than delivery service. Furthermore, moisturizing creams and medical pillows were the most popular products bought in OS compared with hair conditioners and washing liquids. The study's multifold contributions and managerial implications were elaborately discussed.