With transaction-driven personalization engines online merchants can use knowledge gained from an individual customer’s past transactions to match web content to the customer’s individual interests and preferences. Prior research in this area has focused on how to maximize knowledge mined from transaction logs to generate recommendations which are highly similar to the individual’s past preferences. However, it remains an empirical question as to whether a recommendation closely matched with previous transactions is most likely to influence choice behavior? In this study, we postulate that a recommendation closely matched with previous transactions may not be the most efficient in biasing an individual. In the consideration and choice process, an individual’s personality traits play a pivotal role in moderating the effect of personalized content. Drawing on prior work in marketing, we examine two key personality traits, need for cognition and variety seeking, and explore their effects on choice behavior in the context of transaction-driven personalization. Research hypotheses are tested using 2,294 pre-selected subjects in an online field experiment based on a ring tone download website. Our findings establish that personality traits of an individual moderate content consideration and choice. Theoretical and practical implications of the findings are discussed.
Ho, Shuk Ying; Tam, Kar Yan; and Davern, Michael J., "Transaction-Driven Personalization: The Moderating Effects of Personality Traits" (2007). PACIS 2007 Proceedings. 9.