Product recommendation using online reviews with emotional preferences

Abstract

PurposeThe purpose of this paper is to develop a novel recommendation method using online reviews with emotional preferences for facilitating online purchase decisions. This leads to better use of information-rich online reviews for providing users with personalized recommendations.Design/methodology/approachA novel method is developed for producing personalized recommendations in online purchase decision-making. Such a method fuses the belief structure and the Shapley function together to effectively deal with the emotional preferences in online reviews and adequately tackle the interaction existent between product criteria with the use of a modified combination rule for making better online recommendations for making online purchase decisions.FindingsAn example is presented for demonstrating the applicability of the method for facilitating online purchase. The results show that the recommendation using the proposed method can effectively improve customer satisfaction with better purchase decisions.Research limitations/implicationsThe proposed method can better utilize online reviews for satisfying personalized needs of consumers. The use of such a method can optimize interface design, refine customer needs, reduce recommendation errors and provide personalized recommendations.Originality/valueThe proposed method adequately considers the characteristics of online reviews and the personalized needs of customers for providing customers with appropriate recommendations. It can help businesses better manage online reviews for improving customer satisfaction and create greater value for both businesses and customers.

The effects of appearance personification of service robots on customer decision-making in the product recommendation context

“…, 2020; Lin and Mattila, 2021; Seyitoglu et al. , 2021; Hu et al. , 2021), this study examines the effects of service robots on in-store product recommendation.…”

“…In contrast with previous studies, which focused on hotel, restaurant and airport contexts (e.g. Chi et al, 2020;Lin and Mattila, 2021;Seyitoglu et al, 2021;Hu et al, 2021), this study examines the effects of service robots on in-store product recommendation. Thus, the study enriches the literature on application scenarios of service robots, will stimulate further research in the sales and retail field, and will guide the investments of companies in service robot applications.…”