Recommender systems are an integral part of the online retail environment. Prior research has focused largely on computational approaches to improving recommendation accuracy, and only recently researchers have started to study their behavioral implications and potential side effects. We used...

Recommender systems are becoming a salient part of many e-commerce websites. Much research has focused on advancing recommendation technologies to improve accuracy of predictions, while behavioral aspects of using recommender systems are often overlooked. In our studies, we explore how consumer...

Online labor markets and the humans that power them serve a critical role in the advancement of artificial intelligence and supervised machine learning via the creation of high-quality training datasets. The use of human effort in online labor markets is not enough, however, as a key factor is...

Innovation contest platforms are often organized around specific fields of interest and involve contests that span a variety of interdependent problem domains. While specialization in contests within a problem domain can improve a contestant's performance in a future contest in the same domain,...