(A) study on web shopping mall user behavior using log files : W. cosmetic mall case = 로그 파일을 이용한 인터넷 쇼핑몰 사용자의 구매행동 연구 : W. cosmetic mall 사례 W. cosmetic mall case

As millions of people place their orders online, retailers have been eager to know what spur customers in online purchasing. Data about online customers purchasing behavior are needed to help retailers define their online retail strategies for Web site design, online advertising, market segmentation, product variety, inventory holding and distribution. People began shedding light on log data of a Web shopping mall to get objective information of customers`` behavior in a site using data mining techniques. Web sites such as Alexa.com also use customer log data to rank Web sites on the base of page view of each site. However, few studies have been performed to evaluate validity of page view forecasting site``s sales performance. To do this, we first suggest three factors that can be found in log data as a trigger of purchase in a Web shopping mall and evaluate effectiveness of them using statistical methods. Second, we evaluate whether the characteristics of a product affect these factors using real log data of a Korean cosmetic site. According to our research, not only page view of a site but also session time of a customer and customer involvement such as participation in typical event should be considered as important indices of sales performance of a Web shopping mall for Korean Internet users. Finally, on the basis of the findings of studies, we draw managerial implications, discuss limitations pertaining to the generalizability of the results and offer guidelines for further research.
Kim, Soung-Hieresearcher김성희researcher
Issue Date
173789/325007 / 020003486

학위논문(석사) - 한국과학기술원 : 경영공학전공, 2002.2, [ [iv], 46 p. ]


User Behavior; Web Shopping Mall; Log Files; 사용자 구매행동; 인터넷 쇼핑몰; 로그파일

Appears in Collection
Files in This Item
There are no files associated with this item.
  • Hit : 143
  • Download : 0
  • Cited 0 times in thomson ci


  • mendeley


rss_1.0 rss_2.0 atom_1.0