• Proceedings of the Korea Society for Industrial Systems Conference
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• 2008.10b
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• pp.301-306
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• 2008

The World Wide Web (WWW) has continued to grow at very rapid speed in both the sheer volume of traffic and size and the complexity of Web sites. Web Analytics Industry also has been growing rapidly. Web Analytics is to analyze web log files to discover accessing patterns of web pages. In this paper, we identify factors which can affect the continuous usage intention of a firm using services in web analytics services and empirically validate the relationships between the identified factors. For this purpose, we analyze 174 Korea firms. The analysis results show that the satisfaction is significantly associated with service quality and switching cost and the service usage period is not significantly associated with continuous service usage intention. We measure the service quality using SERVQUAL. It turn out that two dimensions of SERVQUAL, reliability and empathy are significantly associated with satisfaction, but another dimension of SERVQUAL, responsibility, is not. Finally, satisfaction is significantly associated with continuous service usage intention.

• 한국경영정보학회:학술대회논문집
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• 2008.06a
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• pp.305-311
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• 2008

급속히 성장하고 있는 Web Analytics 서비스는 기본적으로 인터넷 상에서 기업간의 거래를 전제로 하며 서비스를 이용하는 고객사의 입장에서는 웹분석 분야 정보시스템 아웃소싱의 한 형태이다. 본 연구는 이러한 거래적 특징들을 바탕으로 경쟁이 치열해지고 있는 Web analytics 서비스 산업에서 고객사의 지속적 이용의도와 이에 영향을 주는 요인들 간의 관계를 실증연구를 통하여 살펴보았다. 연구결과 첫째, 서비스를 이용하는 고객회사들의 지속적 이용의 도는 동기적 요인인 만족도와 이탈억제 요인인 의존도가 동시에 고려됨을 알 수 있었다. 둘째, Web Analytics 서비스 산업에서 고객사의 만족도에 영향을 주는 품질 요인으로는 정보품질만이 통계적으로 유의하였다. 셋째, 거래상대방과의 관계에서 이탈이 고려될 때 이탈을 억제하는 역할을 수행하는 의존도 에 영향을 주는 요인으로는 관계가치, 전환비용, 서비스 이용기간이 의미 있는 것으로 나타났다. 넷째, 동기적 측면에서는 전환경험의 유무에 따라 시스템 품질과 공감성이 만족도에 미치는 영향관계가 다르게 나타났고, 이탈억제 측면에서는 전환경험의 유무에 따라 전환비용이 의존도에 미치는 영향관계에서 차이가 있었다.

• The Korean Journal of Archival Studies
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• no.45
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• pp.83-120
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• 2015

Record Information Services is an aggressive action of connecting documentaries focusing on the information needs of user. However, recent studies on the parliament's written information service recognize the necessity that it should segment the user's information requests, and provide personalized service, but have not discussed for specific cases or measures. While the importance of Web services written with the proliferation of information and popularization of the Web is emerging right to know but, it is not being performed properly by lack of sufficient manpower and budget along with lack of recognition in hands-on sites upon the user analysis. So, while increasing the efficiency of the hands-on workers of Record Information Services, the introduction of analytical tools that can be utilized in low budget agencies is needed. Web analytics is to analyze the behavior by analyzing Web logs which web users have left you visit the site. To estimate the behavior they want to request information of the analyzed Web user aims to provide a Web service, the Web service further continued improvement. There are several types that include among them Google Analytics offering a variety of analysis items for free and all over the world, many people are already using. This study introduces a Google Analytics web analytics focused and proposes a service improvement plan with specific web user segmentation analyzes the cases of Korea Democracy Foundation of Open Archives introduces them to the actual institutions.

• The Journal of Information Systems
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• v.30 no.1
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• pp.21-44
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• 2021

Purpose The opportunities and approaches to big data have grown in various ways in the digital era. Business analytics is nowadays an inevitable strategy for organizations to earn a competitive advantage in order to survive in the challenged environments. The purpose of this study is to analyze the intellectual structure of business analytics literature to have a better insight for the organizations to the field. Design/methodology/approach This research analyzed with the data extracted from the database Web of Science. Total of 427 documents and 23,760 references are inserted into the analysis program CiteSpace. Author co-citation analysis is used to analyze the intellectual structure of the business analytics. We performed clustering analysis, burst detection and timeline analysis with the data. Findings We identified seven sub- areas of business analytics field. The top four sub-areas are "Big Data Analytics Infrastructure", "Performance Management System", "Interactive Exploration", and "Supply Chain Management". We also identified the top 5 references with the strongest citation bursts including Trkman et al.(2010) and Davenport(2006). Through timeline analysis we interpret the clusters that are expected to be the trend subjects in the future. Lastly, limitation and further research suggestion are discussed as concluding remarks.

• Journal of Digital Contents Society
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• v.13 no.2
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• pp.205-211
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• 2012

This paper presents research result of digital marketing model for improving enterprise marketing campaign performance. Recently, the enterprises which had completed projects such as ERP, CRM, and SCM for business value chain process transformation are working to improve enterprise marketing process. It is the trend for enterprises to use digital marketing tactics to overcome the limit of existing traditional marketing tactics. Especially, enterprises try to adopt digital marketing for marketing campaign performance. In this paper, digital marketing research model and hypothesis were established and statistically analyzed by marketing expert survey research. The research finding is that Web Analytics, Social Analytics, Personalized CRM, Campaign execution automation, Real-Time campaign management can be core influencers for marketing campaign performance improvement.

• Journal of Information Technology Services
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• v.16 no.1
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• pp.1-26
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• 2017

Keeping good, talented people is one of the most significant factors in a company's success. HR analytics is an important area for applying big data analysis techniques to human resources. It provides organizational insight that enables effective management of employees, allowing management to reach their business goals quickly and efficiently. Job satisfaction and employee turnover analysis are the keys to HR analytics. Job review web services have been becoming popular. Because people exchange information about job satisfaction and turnover through these web services, useful information about HR Analytics is accumulated on the job review web sites. In this paper, we identified factors of employee retention by analyzing a Job Satisfaction/Retention group, and the factors of employee turnover by analyzing a Job Unsatisfaction/Turnover group. In order to do this, we first classified employees according to whether their self-reported job satisfaction or turnover was true. We collected and analyzed data from Jobplanet, a popular job review site. Through dominance analysis and LDA topic modeling, we found major factors, topics, and keywords of the classified groups by IT, service, and manufacturing domains. Our approach is a novel model to apply the analysis of reviews and text mining to the HR domain, and it will be practically helpful for setting new strategies that improve job satisfaction.

• Journal of Information Science Theory and Practice
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• v.8 no.1
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• pp.45-55
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• 2020

The purpose of this work was to study library website users' actions by tracking their behavior, determining popular content, and identifying browsing patterns and subsequent improvement of access to popular content. The study of behavior models and the use of web analytics has led to the emergence of solutions that improve the usability and functionality of the State Public Scientific-Technological Library of the Siberian Branch of the Russian Academy of Sciences (SPSTL SB RAS) website. These are: identifying user tasks as they are developed, conducting user testing to better understand the event. tracking data and collecting additional data to verify the effectiveness of the changes made. Examining data on the duration of the session and the number of visits will help determine the goals of user visits and develop new recommendations. Usability analysis and testing will make it possible to compare the data obtained using web analytics and the perception of the library site by the users themselves. Recommendations are offered to libraries on the use of data on the real behavior of the target audience of the library website to improve access to library resources and services, increase their relevance and improve information services.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_1
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• pp.927-939
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• 2022

This study was conducted to develop a Web-GIS based monitoring module of smart city that can effectively respond, manage and improve situation in all stages of illegal dumping management on a city scale. First, five technologies were set for the core technical elements of the module configuration. Five core technical elements are as follows; video screening technology based on motion vector analysis, human behavior detection based on intelligent video analytics technology, mobile app for receiving civil complaints about illegal dumping, illegal dumping risk model and street cleanliness map, Web-GIS based situation monitoring technology. The development contents and results for each set of core technical elements were evaluated. Finally, a Web-GIS based 'illegal dumping monitoring module' was proposed. It is possible to collect and analyze city data at the local government level through operating the proposed module. Based on this, it is able to effectively detect illegal dumpers at relatively low cost and identify the tendency of illegal dumping by systematically managing habitual occurrence areas. In the future, it is expected to be developed in the form of an add-on module of the smart city integration platform operated by local governments to ensure interoperability and scalability.

• Convergence Security Journal
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• v.15 no.2
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• pp.19-24
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• 2015

As the Internet usage such as Web3.0, future internet, and internet of things increases, the big data through information exchange between the users and web servers increases. Analyzing those web data, the commercial web sites use the analytic results for marketing and campaign, and non-commercial web sites also use the results to improve the user's services satisfaction. In this paper, the quantitative index is presented to analyze the web sites, and optimized web site design method is also presented through the correlation analysis of index and significance test. From the results for 138 web sites, it is observed that strong plus(+) correlation for visits-unique visitors and page views-average visit duration exists. We also observe the minus(-) correlation between bounce rate and page views per user(or ratio of new visits). In specific, to reduce the bounce rate for users, the strategy to increase the page views and ratio of new visits rather than visits and unique visitors is needed.

• KIISE Transactions on Computing Practices
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• v.21 no.10
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• pp.651-657
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• 2015

The amount of web traffic has increased as a result of the rapid growth of the use of web-based applications. In order to obtain valuable information from web logs, we need to develop systems that can support interactive, flexible, and efficient ways to analyze and handle large amounts of data. In this paper, we present CERES, a log-based, interactive web analytics system for backbone networks. Since CERES focuses on analyzing web log records generated from backbone networks, it is possible to perform a web analysis from the perspective of a network. CERES is designed for deployment in a server cluster using the Hadoop Distributed File System (HDFS) as the underlying storage. We transform and store web log records from backbone networks into relations and then allow users to use a SQL-like language to analyze web log records in a flexible and interactive manner. In particular, we use the data cube technique to enable the efficient statistical analysis of web log. The system provides users a web-based, multi-modal user interface.