Recommender Agents (RAs) facilitate consumers’ online purchase decisions for complex, multi-attribute products. As not all combinations of attribute levels can be obtained, users are forced into trade-offs. The exposure of trade-offs in a RA has been found to affect consumers’ perceptions. However, little is known about how different preference elicitation methods in RAs affect consumers by varying degrees of trade-off exposure. We propose a research model that investigates how different levels of trade-off exposure cognitively and affectively influence consumers’ satisfaction with RAs. We operationalize these levels in three different RA types and test our hypotheses in a laboratoryexperiment with 116 participants. Our results indicate that with increasing trade-off exposure, perceived enjoyment and perceived control follow an inverted U-shaped relationship. Hence, RAs using preference elicitation methods with medium trade-off exposure yield highest consumer satisfaction. This contributesto the understanding of trade-offs in RAs and provides valuable implications to e-commerce practitioners.
|Titel||Proceedings of 14th International Conference on Wirtschaftsinformatik|
|Redakteure/-innen||Thomas Ludwig, Volkmar Pipek|
|Seiten||1190 - 1204|
|Publikationsstatus||Veröffentlicht - 2019|
Österreichische Systematik der Wissenschaftszweige (ÖFOS)
- 502050 Wirtschaftsinformatik