Abstract
Recommender systems aim to support users 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 them. On the other hand, providing unconventional items may increase 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 disadvantageous. Instead, recommenders should provide more serendipitous recommendations as this leads to higher perceived preference fit and enjoyment. In addition, market and recommender technology characteristics must be taken into account, since 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 support online retailers in developing better recommenders.
Dokumententyp: | Konferenzbeitrag (Paper) |
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Fakultät: | Betriebswirtschaft > Institut für Digitales Management und Neue Medien |
Themengebiete: | 300 Sozialwissenschaften > 330 Wirtschaft |
Sprache: | Englisch |
Dokumenten ID: | 104782 |
Datum der Veröffentlichung auf Open Access LMU: | 17. Jul. 2023, 11:02 |
Letzte Änderungen: | 15. Nov. 2023, 13:22 |