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Kim, Jinhwa
- A Web Usage Mining for Modeling Buying Behavior at a Web Store using Network Analysis
Abstract Views :165 |
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Authors
Affiliations
1 School of Business, Sogang University, KR
2 Department of Public Management Information Systems, Korea National University of Transportation, KR
1 School of Business, Sogang University, KR
2 Department of Public Management Information Systems, Korea National University of Transportation, KR
Source
Indian Journal of Science and Technology, Vol 8, No 25 (2015), Pagination:Abstract
Understanding visitors’ invisible behaviors and responding with appropriate answers are important issues in continually increasing online market. To promote online transactions, customers’ behavior should be predicted correctly to keep low purchase conversion rate. In this study, we suggest an approach based on the idea that customers’ sessions in a web store can be transformed into the structure of a graph, which are represented as density of a session based on a graph theory. Online users visit lots of sites and their activities include information acquisition and browsing. The history of these activities can be used to construct a relationship network among web sites. This study analyzes this visit history made by website visitors with graph theory. The density of a network refers to the differentiated degrees of relationship among objects. In this study, we dichotomize into “purchase” and “no purchase group” since predicting whether a customer will buy or not buy our products is an important issue in web stores. We collect data on sessions which are a sequence of page views or a period of sustained web browsing. We model the sessions on the basis of density of a graph, which resulted in DOS (Density of a Session). The performance of other predictors including DOS is compared to that of suggested method in this study. Predictors are TVT (Total Visit Time during a period of a visit), AVT (The Average Time per Page Viewed), TNC (Total Number of Clicks), TPP (Total Number of Product-Related Pages Viewed), and DOS (Density of a Session Based on Graph Analysis). The study found that all predictors except total visit time are useful to differentiate between “purchase” and “no purchase” group. And we conducted Logit Analysis to examine the performance of each purchase prediction method. The results from Logit Analysis show that DOS predicts purchase behavior better in comparison with other predictors. It means understanding customers’ sessions with respect to a graph structure is useful to predict whether a customer will buy or not buy products in a web store.Keywords
Click Stream Data, Predicting Customer Behavior, Web Usage Mining- A Solution to Privacy Violation Problem in Korean Ubiquitous Government Service
Abstract Views :165 |
PDF Views:0
Authors
Affiliations
1 School of Business, Sogang University, KR
1 School of Business, Sogang University, KR
Source
Indian Journal of Science and Technology, Vol 8, No 25 (2015), Pagination:Abstract
The u-government services become more personalized and intelligent. For the successful implementation of personalization, individual’s privacy must be respected and taken care of. Based on an empirical survey, this research investigates the reluctance to the government’s use of private information in six categories. We measure people’s psychological distance toward e-government using four intimacy levels suggested by the Proxemics. Since a positive correlation is identified between people’s psychological intimacy toward e-government and their tolerance to the use of private information, the amount and types of private information should be sequentially used in designing a personalization system. Beginning with the least intolerable private information such as information on one’s occupation, personalized systems should additionally use next tolerable private information such as health information or service request/interest information, as people’s psychological distance toward government services becomes shorter.Keywords
Intimacy, Keywords4, Personalization of Service, Privacy, Ubiquitous Government- Promoting Usage of Location-based Services, an Approach Based on Intimacy Theory and Data Mining Techniques
Abstract Views :135 |
PDF Views:0
Authors
Affiliations
1 Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Guseong-dong,Yuseong-gu, Daejeon, South Korea
2 Graduate School of Business, Sogang University, 35 Baekbeom-ro, Daeheung-dong, Mapo-gu, Seoul, South Korea
1 Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Guseong-dong,Yuseong-gu, Daejeon, South Korea
2 Graduate School of Business, Sogang University, 35 Baekbeom-ro, Daeheung-dong, Mapo-gu, Seoul, South Korea