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Paper Number
1768
Paper Type
Short
Description
Recommender systems are a common approach in retail e-commerce to support consumers in finding relevant products. Not surprisingly, user acceptance of personalized product recommendations tends to be higher, leading to higher click rates. Since contextual information also influences user search behavior, we analyze the importance of similarity between recommendations and the underlying context a currently inspected product provides. Using data from a midsize European retail company, we conduct a field experiment and investigate the role of similarities between focal product information and recommendations from a collaborative filtering algorithm. We find that contextual similarity, primarily visual similarity contributes much explanation to consumer click behavior, underlining the importance of contextual and content information in the recommender system's environment.
Recommended Citation
Lill, Markus and Spann, Martin, "Influence of Assimilation Effects on Recommender Systems" (2022). ICIS 2022 Proceedings. 3.
https://aisel.aisnet.org/icis2022/online_reviews/online_reviews/3
Influence of Assimilation Effects on Recommender Systems
Recommender systems are a common approach in retail e-commerce to support consumers in finding relevant products. Not surprisingly, user acceptance of personalized product recommendations tends to be higher, leading to higher click rates. Since contextual information also influences user search behavior, we analyze the importance of similarity between recommendations and the underlying context a currently inspected product provides. Using data from a midsize European retail company, we conduct a field experiment and investigate the role of similarities between focal product information and recommendations from a collaborative filtering algorithm. We find that contextual similarity, primarily visual similarity contributes much explanation to consumer click behavior, underlining the importance of contextual and content information in the recommender system's environment.
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