• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.143-146
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• 2004

With the rapid growth of e-commerce, marketers are able to observe not only purchasing behavior on what and when customers purchased, but also the individual Web usage behavior that affect purchasing. The richness of this information has the potential to provide marketers with an in-depth understanding of customer. Using commonly available Web log data, this paper examines Web usage behaviors at the individual level. By decomposing the buying process into a pattern of visits and purchase conversion at each visit, we can better understand the relationship between Web usage behavior and purchase decision. This allows us to more accurately forecast a shopper's future purchase decision at the site and hence determine the value of individual customers to the siteAccording to our research, not only information seeking behavior but also visiting duration of a customer and participative behavior such as participation in event should be considered as important predicators of purchase decision of customer in a cosmetic internet shopping mall.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.27-38
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• 2008

Since the current mobile web market is already in its maturity, a research concerning the continued behavior of mobile Internet users should be carried out. The purpose of this research is to understand user's continued behaviors by theoretically constructing and empirically testing a continued model using real usage data. The model consists of four post-expectation factors (usefulness, ease of use, enjoyment, and perceived value) as well as user satisfaction, continuance intention, and the actual usage amount. To test the model, an on-line survey had been conducted, and we collected the actual usage data of survey respondents via the support of telecommunication companies. The study results indicate that post expectation variables were found to influence satisfaction, continuance intention, and actual usage amount of mobile web users. This paper ends with study limitations and implications on mobile web industry.

• Korean Management Science Review
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• v.23 no.3
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• pp.63-75
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• 2006

There are many kinds of research on web graph, most of them are focus on the hyperlinked structure of the web graph. Well known results on the web graph are rich-get-richer phenomenon, small-world phenomenon, scale-free network, etc. In this paper, we define 3 new directed web graph, so called the Web Usage Pattern Graph (WUPG), that nodes represent web sites arid arcs between nodes represent a movement between two sites by users' browsing behavior. The data to constructing the WUPG, approximately 56,000 records, are gathered from some users' PCs. The results analysing the data summarized as follows : (i) extremely rich-get-richer phenomenon (ii) average path length between sites is significantly less than the previous one (iii) less external hyperlinks, more internal hyperlinks.

• The Journal of Bigdata
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• v.2 no.2
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• pp.105-114
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• 2017

Today, many services are supported on the web sites. Analysis of usage patterns of web site visitors is very important to optimize the use and efficiency of the web sites. In this study, analysis of usage patterns and comparative analysis of user groups were conducted by analyzing web access log provided by BPI Challenge 2016. This data provides access logs to the web site in the IT system of a Dutch Employee Insurance Agency (UWV). The customer information, and the click data describing the customers' behavior when using the agency's web site. In this study, we use process mining techniques to analyze the usage patterns of customers and the characteristics of customer groups, and ultimately improve the service quality of customers using web services.

• Knowledge Management Research
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• v.10 no.2
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• pp.85-103
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• 2009

Web 2.0, characterized as openness, sharing, and participation, has enabled Internet users to easily generate a variety of contents, and to share them through Web 2.0 services. Knowledge search service (KSS) is positioning itself as one of typical Web 2.0 services. Yet, few studies have sharpened our understanding of users' knowledge sharing behavior in the KSS environment. In order to address this knowledge void, this paper attempts to explore antecedents of their usage behavior in the KSS environment. Typically, they utilize stored knowledge and share their knowledge simultaneously. Considering this characteristic, our study regards service usage intention and knowledge sharing intention as final dependent variables. This study advances a research model based on Bhattacherjee's expectation-confirmation model, which is expanded by incorporating trust belief. Because of the openness of KSS, trust belief is believed to play a critical role in forming users' service usage intention and knowledge sharing intention. Furthermore, this study examines the difference of the antecedents' effects in terms of users' gender. We collected data from 275 respondents who have experience in using KSS. PLS (partial least squares) was employed for the analysis of the data. Analysis results confirm the important role of user satisfaction and trust belief in the formation of users' service usage intention and knowledge sharing intention. More importantly, trust belief has a more salient effect on knowledge service usage intention than user satisfaction. This study also shows the moderating role of users' gender. Finally, this paper provides managerial guidance on strategic planning aimed at improving users' service usage intention and knowledge sharing intention in the KSS environment.

• Knowledge Management Research
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• v.20 no.4
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• pp.169-183
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• 2019

The growth of mobile commerce (m-commerce) has been accelerated around the world. Why do e-retailers have to put a great deal of effort for the distribution of their mobile apps? The literature has paid little attention to the influence of the introduction of an e-commerce app on shopping behaviors of consumers. By analyzing the dataset of 2,342 users in Korea, this study aims to broaden our understanding of mobile shopping app usage across competing e-retailers and different channels. We found that a user's prior usage of a specific e-commerce mobile app increases her subsequent usage of its website through a mobile web browser. Thus, mobile apps do not cannibalize the mobile web channel, and there could be a complementary relationship. We also found that a user's usage of competitors' apps is positively associated with her subsequent usage of a specific e-commerce app. Because many consumers search products and compare prices across multiple e-retailers, having a mobile app helps an e-retailer be exposed to more potential consumers. This study is among the first to study the role of mobile apps in e-commerce by showing the dynamics of cross-channel and cross-vendor usage by a user.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.422-440
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• 2005

There are many kinds of research on web graph, most of them are focus on the hyperlinked structure of the web graph. Well known results on the web graph are rich-get-richer phenomenon, small-world phenomenon, scale-free network, etc. In this paper, we define a new directed web graph, so called the Web Usage Pattern Graph (WUPG), that nodes represent web sites and arcs between nodes represent a movement between two sites by users' browsing behavior. The data to constructing the WUPG, approximately 56,000 records, are gathered in the Kyungsung University. The results analysing the data summarized as follows: (i) extremely rich-get-richer phenomenon (ii) average path length between sites is significantly less than the previous one (iii) less external hyperlinks, more internal hyperlinks

• Industrial Engineering and Management Systems
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• v.11 no.1
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• pp.82-86
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• 2012

In For the past few years, query log data has been collected to find user's behavior in using the site. Many researches have studied on the usage of query logs to extract user's preference, recommend personalization, improve caching and pre-fetching of Web objects, build better adaptive user interfaces, and also to improve Web search for a search engine application. A query log contain data such as the client's IP address, time and date of request, the resources or page requested, status of request HTTP method used and the type of browser and operating system. A query log can offer valuable insight into web site usage. A proper compilation and interpretation of query log can provide a baseline of statistics that indicate the usage levels of website and can be used as tool to assist decision making in management activities. In this paper we want to discuss on the tasks performed of query logs in pre-processing of web usage mining. We will use query logs from an online newspaper company. The query logs will undergo pre-processing stage, in which the clickstream data is cleaned and partitioned into a set of user interactions which will represent the activities of each user during their visits to the site. The query logs will undergo essential task in pre-processing which are data cleaning and user identification.

• The Journal of Information Systems
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• v.17 no.2
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• pp.49-72
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• 2008

Today, the World Wide Web (WWW) impacts many facets of our lives, including communication, entertainment, social activities, shopping, etc. The web portal is the most accessed type of site and is advertising-supported the more users who visit the site, the more income it generates. User perception to a web site is very important much research has focused on the internet users' behavior. Some well-known theories, such as the technology acceptance model have been used to examine variables that motivate individuals to accept and use an IS. But Understanding continued use is the goal of this study. We focus on user beliefs (specifically, perceived usefulness) and attitude because pier studies of IT usage, predominantly based on the technology acceptance model (TAM) and similar models, have established these perceptions as the dey determinants of both initial IT usage (acceptance) and long-term usage (continuance) intention and behavior (Bhattacherjee 2001; Davis et al. 1989). Any change in beliefs or attitudes will likely have a corresponding impact on, and may even revers, users' continuance intention and behavior. Also, continuance use have some features which are prior use, habit, feature-centric view of technology. So this research reflected continuance use features. Examination of the paths in the model revealed several interesting results. First, Perceived usefulness was a stronger predictor of acceptance intention in TAM than attitude, But attitude was a stronger predictor of continuance intention in this study than perceive usefulness. Second, confirmation was not affect directly to attitude. Last, Habit was strongest predictor of continuance intention in this study.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.231-241
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• 2019

Web Usage Mining (WUM) is one part of Web mining and also the application of data mining technique. Web mining technology is used to identify and analyze user's access patterns by using web server log data generated by web users when users access web site. So first of all, it is important that the data should be acquired in a reasonable way before applying data mining techniques to discover user access patterns from web log. The main task of data acquisition is to efficiently obtain users' detailed click behavior in the process of users' visiting Web site. This paper mainly focuses on data acquisition stage before the first stage of web usage mining data process with activities like data acquisition strategy and field extraction algorithm. Field extraction algorithm performs the process of separating fields from the single line of the log files, and they are also well used in practical application for a large amount of user data.