The Effect of Recommender Systems on Users' Situation Awareness and Actions

Many organizations are implementing recommender systems with the expectation to influence users’ actions. However, research has shown that poorly designed recommender systems may be counterproductive. For instance, if a recommender system provides too many recommendations, users cannot focus on relevant recommendations anymore. Therefore, recommender systems need to be balanced and adjusted to the processes in which they shall support users. Only designed correctly, recommender systems may influence users’ situation awareness and, ultimately, enable them to perform informed actions. Research has shown that users’ situation awareness depends on users’ elaboration. Therefore, we draw on the Elaboration Likelihood Model to conceptualize recommendation velocity and recommendation faithfulness as two variables that influence users’ situation awareness. Furthermore, since research identified process automation as a major antecedent of situation awareness, we conceptualize process automation as a third influencing variable. Finally, we develop a conceptual research model and outline our intended validation and expected contributions.