What makes consumers loyal to fashion recommendation systems that combine artificial intelligence and human expertise?
(A2023-114218)

AUTHORS

Agardi Irma, Corvinus University of Budapest; Dalma Peller, Corvinus University of Budapest

ABSTRACT

This paper aims to study what factors influence the loyalty intentions of consumers toward fashion recommendation systems combining artificial intelligence and human expertise. Therefore, we conducted an online survey among consumers of an online fashion retailer in the U.S. that generates offers based on artificial intelligence algorithms for their subscribers. Our data collection resulted in a sample of 194 respondents that were analyzed by structural equation modeling. Our findings suggested that perceived usefulness was mostly influenced by the perceived quality, economic value, and enjoyment provided by the fashion recommendation systems using artificial intelligence and human expertise. The perceived ease of use was affected by the convenience of using these systems. Perceived usefulness contributed substantially to developing favorable attitudes toward the recommendation system leading to higher loyalty intentions of consumers. The results have theoretical and business implications.