Personalized product recommendations, generated by e-commerce recommender systems, can provide helpful information and decision support when users are overwhelmed by product alternatives. Although many successful Web-based recommender systems have been deployed, only a few have been designed for mobile users. Researchers at the Free University of Bozen-Bolzano created a critique-based recommendation methodology and applied it to the acquisition and revision of user preferences in a mobile recommender system. The approach has been implemented in a system that helps on-the-go travelers select their desired travel products. Results from user evaluations validated the system's functionality and usability. This article is part of a special issue on Recommender Systems.