Does the Users' Tendency to Seek Information Affect Recommender Systems' Performance?

Umberto Panniello (Politecnico di Bari, Italy)

Lorenzo Ardito (Politecnico di Bari, Italy)

Antonio Messeni Petruzzelli (Politecnico di Bari, Italy)

Abstract: Much work has been done on developing recommender system (RS) algorithms, on comparing them using business metrics (such as customers' trust or perception of recommendations' novelty) and on exploring users' reactions to recommendations. It was demonstrated that different recommender systems perform differently on several performance metrics and that different users react differently to the same kind of recommendations. As a consequence, some scholars challenged to explore how users with different tendency to seek information during their purchasing process may react to different kind of recommendations. To the best of our knowledge, none of the prior works studied if users' tendency to seek information has an effect on recommender systems' performance. Different users may traditionally have different propensity to seek information and to receive suggestions and therefore they may react differently to the same recommendations. To this aim, we performed a live experiment with real customers coming from a European firm.

Keywords: accuracy, context-aware, experiment, novelty, recommender system, trust

Categories: H.3.3, H.3.5, L.3.2