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논문검색

클릭스트림 데이터를 활용한 전자상거래에서 상품추천이 고객 행동에 미치는 영향 분석

원문정보

초록

영어

Studies of recommender systems have focused on improving their performance in terms of error rates between the actual and predicted preference values. Also, many studies have been conducted to investigate the relationships between customer information processing and the
characteristics of recommender systems via surveys and web-based experiments. However, the actual impact of recommendation on product pages for customer browsing behavior and decision-making in the commercial environment has not, to the best of our knowledge, been
investigated with actual clickstream data. The principal objective of this research is to assess the effects of product recommendation on customer behavior in e-Commerce, using actual clickstream data. For this purpose, we utilized an online bookstore’s clickstream data prior to and after the web site renovation of the store. We compared the recommendation effects on customer behavior with the data.
From these comparisons, we determined that the relevant recommendations in product pages have positive relationships with the acquisition of customer attention and elaboration. Additionally, the placing of recommended items in shopping cart is positively related to suggesting the relevant recommendations. However, the frequencies at which the recommended items were purchased did not differ prior to and after the renovation of the site.

목차

Abstract
 Introduction
 Literature Review
 Research Hypotheses
 Results Analysis
 토의
 참고문헌

저자정보

  • 이홍주 가톨릭대학교 경영학부

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