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.

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Due mainly to COVID-19 and the demanding work schedules of many individuals, online purchasing sites have become indispensable. However, the dynamic online environment and everchanging customer demands make sustainable competitiveness challenging for e-commerce platforms. Humans primarily influence the preference for online purchase platforms. This study aimed to discover Türkiye’s top popular online shopping sites by adopting an extended intuitionistic fuzzy ORESTE (Organisation, Rangement Et Synthèse De Données Relationnelles) approach. Our study targeted this by surveying female users of four online shopping platforms using IF-ORESTE. The criteria were determined according to customer preferences. These were as follows: easy accessibility to the platform, providing regular discounts and campaigns, advanced filtering settings, the contractual merchants’ reliability, quick delivery, being more affordable than competing platforms, positive feedback in user comments, having a large brand volume, having an installment option, and having partnered cargo companies. The least important factor was the large volume of brands on the online websites. Quick delivery of orders and positive feedback in reviews were equally important. Similarly, the decision-makers considered regular discounts and promotions and the comprehensive filtering settings as equally critical. However, these criteria were less significant than quick delivery and positive customer feedback. This work’s novelty lies in implementing the IF to the ORESTE in the Turkish e-commerce industry. The implications and future directions are discussed.