A conceptual model for quality dimensions for b2c recommender systems

During the last ten years numerous research instruments emerged for evaluating the service quality of Web-based information systems. B2C recommender systems are information systems that support users in selecting information, products, or services improving their decision making process. Unfortunately, the majority of these instruments do not acknowledge the full range of recommendation functionalities like personalization, registration, security or satisfaction with the proposals given by recommender systems. Therefore, this study focused on the recently published E-S-QUAL scale developed by Parasuraman et al. (2005). A qualitative item generating procedure was used to extend the conceptualization appropriate for recommender systems. This instrument was tested among 15 different B2C recommenders. The empirical data were used to examine the conceptual stability of the extended measurement model about recommender service quality (rSQ). The following six dimensions were successfully identified: efficiency, information quality, personalization, reliability, security, and usability. Efficiency and personalization turned out to be the most dominant influencing factors on web recommender satisfaction.