The performance of recommender systems in online shopping: a usercentric study

This research investigates the effects of preference relaxation on decisionmaking performance of users in online preference-based product search contexts. We compare four recommender systems based on different preference relaxation methods in extensive user experiments with 111 subjects that use two real-world datasets: 1818 digital cameras and 45278 used car advertisements gathered from popular e-commerce websites. Our results provide new insights into the positive impact of the soft-boundary preference relaxation methods on decision-making quality and effort. The paper extends previous studies on this topic and demonstrates that decision aids based on preference relaxation techniques can effectively enhance preference-based product search in online product catalogues and help alleviate common disadvantages of form-based filtering mechanisms.