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Recommender systems aim to support consumers in identifying the most relevant items. However, there are concerns that recommenders may imprison users in a “filter bubble” by recommending items predominantly known to users. On the other hand, providing unconventional items increases risks of not meeting users’ taste. Given this trade-off, we analyze the effects of consumers’ perceived levels of recommendation novelty and serendipity on perceived preference fit and enjoyment. We find that merely increasing the level of novel recommendations is insufficient. Instead, recommenders should provide more serendipitous recommendations as this leads to higher perceived preference fit and enjoyment. In addition, market and recommender technology characteristics need to be taken into account as they partially determine the level of novel and serendipitous recommendations. Our findings have significant implications for research as they add additional insights on users’ evaluations of recommender systems. For practice, our results enable online retailers to develop better recommenders.

Escaping from the Filter Bubble? The Effects of Novelty and Serendipity on Users' Evaluations of Online Recommendations