Abstract
the purpose of this paper is to explore the relationship between recommender systems with customer satisfaction in B2C e-commerce. And this research fills a research gap by focusing on application of recommendation systems from the view of customer satisfaction, which has received almost no attention. The studies proposed a model that inter-relates different patterns of recommendation system and customer satisfaction. Analysis of survey data from 910 customers reveals those hypotheses are supported. We focus on recommendation applications which have different effects on customer satisfaction. The results provide strong support for the research model and suggest that recommendation system can improve customer satisfaction by enhancing customers' perceived information quality and usability, and deep personalization can directly improve customer satisfaction.
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