The dual role of perceived effort in personalized recommendations

Effort has been central in decision-making and effort saving is one of the main benefits of the use of recommendation agents (RAs). Since human-computer interactions tend to mimic human social encounters, we focus on two distinct types of perceived effort, namely user and RA effort. In two experimental studies in diverse empirical contexts, we provide generalizable insights on how these types can influence perceived RA quality. More...