How does customer's product expertise moderate the usefulness of information recommendation agents in online stores?

Abstract

Introduction. Recommendation agents are software programs used by Internet stores to help customers find relevant information and make better purchasing decisions. This study investigates the moderating effect of customers' product expertise on the relationship between user evaluation of recommendation agents and its antecedents. Method. An experimental shopping mall of digital cameras was implemented for empirical examination of the hypotheses. Participants were asked to conduct virtual shopping in the shopping mall using the information recommendation agents. Analysis. The hypotheses were tested with the partial least squares method using the collected data. The samples were divided into high and low product expertise groups and the results of the analysis were compared between the two groups to see the moderating effect of product expertise. Results. Product expertise does moderate some of the relationships, showing difference between high and low product expertise groups. Analysis of the results shows that familiarity with recommendation agents and frequency of online shopping affect only the high expertise group, while specificity of shopping intention affects only the low expertise group. Conclusions. The difference in customers' product expertise needs to be taken into account when developing and providing information recommendation agents to customers to improve their shopping experience.