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.

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Dec 12th, 12:00 AM

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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