Psychological factors explaining consumer adoption of an e-vendor’s recommender

e-Commerce recommenders have positive benefits both for consumers and the online stores using them. The focus of research in this topic has mostly been technical (e.g. design, type of recommenders, inputs, or outputs). However, a prior key question is what leads a consumer to use an e-vendor’s recommender. The consumer process of adoption and use of such recommenders involves subjective factors which need a psychological approach. This perspective has been neglected so far. The purpose of this paper is to discuss and validate an integrative model which adapts various theories and models – i.e. the original formulation of the technology acceptance model (TAM), the integrated trust-TAM model, and the theory of planned behavior (TPB) – in order to explain such a process.

The field study consisted of a simulated online shopping process undertaken by a valid sample of 300 internet users with a recommender at a real online store (Amazon). Many of the constructs’ measurement scales have been adapted from previously validated scales never before applied to this study’s context, and the authors have consequently rigorously validated them here too; this also constitutes one of the research’s valuable contributions. Detailed exploratory and confirmatory factor analyses are applied to assess the empirical validity of the model.

The model’s core structure and its relationships are proved to be valid for explaining a consumer’s intention to use an e-vendor’s recommender In particular, trust and perceived usefulness of the recommender stand out as the determining factors of its use, though the consumer’s attitude toward the recommender and others’ opinion of its use also have significant influence too.

The consumer’s psychological angle has been overlooked by previous studies on the adoption and use of online stores’ recommendation systems. To the best of the knowledge, this is the first attempt to validate a model aimed at comprehensively approaching the consumer’s adoption of an e-vendor’s recommender. The findings provide several theoretical contributions and implications for practitioners.