• Journal of the Korean Society for information Management
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• v.40 no.4
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• pp.403-428
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• 2023

This study investigates the development path and intellectual structure of data literacy research, aiming to identify emerging topics in the field. A comprehensive search for data literacy-related articles on the Web of Science reveals that the field is primarily concentrated in Education & Educational Research and Information Science & Library Science, accounting for nearly 60% of the total. Citation network analysis, employing the PageRank algorithm, identifies key papers with high citation impact across various topics. To accurately trace the development path of data literacy research, an enhanced PageRank main path algorithm is developed, which overcomes the limitations of existing methods confined to the Education & Educational Research field. Keyword bibliographic coupling analysis is employed to unravel the intellectual structure of data literacy research. Utilizing the PNNC algorithm, the detailed structure and clusters of the derived keyword bibliographic coupling network are revealed, including two large clusters, one with two smaller clusters and the other with five smaller clusters. The growth index and mean publishing year of each keyword and cluster are measured to pinpoint emerging topics. The analysis highlights the emergence of critical data literacy for social justice in higher education amidst the ongoing pandemic and the rise of AI chatbots. The enhanced PageRank main path algorithm, developed in this study, demonstrates its effectiveness in identifying parallel research streams developing across different fields.

• International Commerce and Information Review
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• v.14 no.3
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• pp.539-558
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• 2012

The purpose of this study is examining the differences of mobile SNS's service quality, which consists data quality and system quality, among the groups that are classified by commitment and customer loyalty. For the experimental analysis, the frequency analysis was performed for general characteristics of sample. The variables were selected by factor analysis that also prove the validity of variables. The value of Cronbach's alpha was calculated to check the reliability of variables. In addition, the group was determined by the both hierarchical and hierarchical cluster analysis, then ANOVA was performed to test the hypotheses that there are differences of mobile SNS's service quality, among the groups that are classified by commitment and customer loyalty. The results of this study support that there are differences among the groups toward mobile SNS's service quality and also shows the more commitment and loyalty group is the higher recognition of mobile SNS's service quality. Thus, the companies have to realize that mobile SNS is very important key factor to success in rapidly changing business environment. In conclusion, the companies implement different customized strategy for the different group and develop the contents and the applications to maximize the commitment and loyalty of for the mobile SNS users.

• Journal of Distribution Science
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• v.13 no.1
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• pp.27-33
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• 2015

Purpose - The ICT market in the EU is lagging behind that of the US; however, algorithm and software development within the EU have grown steadily, and they involve focusing on the creative cultural convergence conceptualized as part of Horizon 2020 and connecting neighboring markets in the EE and the Mediterranean region. It is essential to study the requirements to market the EU's creative ICT development in emerging industrial countries after examining its applicability in these countries. Research design, data, and methodology - This study deals with data pertaining to the EU's creative industry and competitive edge. The global cultural expansion of the EU facilitates a new concept involving not only low-cost IT products to enhance local cultural artifacts through R&D and the construction of efficient infrastructure services, but also information exchange with a realistic commercialization of the technology that can be applied for creative cultural localization. In the European industry, research on algorithms has been applied for the benefit of consumers. We investigated how the process is conducted in the EU. Results - Europe needs to adjust its economic structure to the local culture as part of IT distribution convergence. The convergence has been converted into a production algorithm with IT in the form of low-cost production. This is because there is an attempt to improve the quality of transport infrastructure, workforce availability, and the distribution of the distance to the local industries and consumers, using IT algorithms. Integrated into the manufacturing industry, based on the ICT infrastructure and solutions, smart localized regional clusters are formed with the help of grafting. Europe has own strategy to increase the number of hub-and-spoke cities. Europe is now becoming integrated, with an EPC system for regional cooperation rather than national competition in ICT technology. Europe has also been recognized in this study as changing the step-by-step paradigm for global competitiveness through new creative culture industries. Conclusions - As a result, there are several ways of converging with others through EU R&D intensity; therefore, the EU can be seen as successfully increasing marginal value, which is useful in developing a special industrial cluster or local cultural cities that create converged development by connecting people and objects with IT. In fact, when compared to the US, Europe has a strong culture and the car industries have a tendency to overshadow the IT industries with integration of services in IT distribution. Considering the rapid environmental changes, the convergence of IT services is likely to take place in Europe, similar to the pharmaceutical industry and the automotive industry. This requires a focus on human resources and automated systems management. The trend is to move away from low-wage industries, switched to key personnel centers of the local university-industry. EU emphasizes the creation of IT market demand in Europe involving local cultural convergence for marketing as the second step to strengthen the economic hub-and-spoke areas.

• Korean Journal of Social Welfare Studies
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• v.49 no.2
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• pp.5-38
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• 2018

The purpose of this study is to examine work-life balance by analyzing time schedules of married couple. The 2014 Korea Time Use Survey dataset was used for the analysis. Finally, 6,262 time diaries of 3,131 households were included in the analysis. The study used sequence analysis in particular, by applying the Lesnard(2014)'s dynamic hamming matching (DHM) method, which is useful for the time diary analysis where timing is a key factor. This study explored daily schedules of each man and woman according to 9 types of couple-combined work-schedules, which had been already derived by cluster analysis. The daily schedules were identified according to the activities divided as labor, housework, sleep, self-management, active leisure, passive leisure, and others. Here, time allocation was analyzed through various graphs showing average time amount and modal states by time period. Based on the analysis, it summarized that "long working hours as a main factor of work-life imbalance", "gender inequality of time use", "non-standard hours work impairing quality of life and "poverty of leisure time"as characteristics of work-life imbalance. Finally this study discussed the social policy implications to support work-life balance.

• International Area Studies Review
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• v.14 no.1
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• pp.257-277
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• 2010

Rural tourism is considered one of the main components of travel today. This may explain the emerging interest in tourist behavior at rural sites. Nevertheless, it can be argued that research on tourists' motivation as well as segmentation for visiting rural sites is still in its infancy. The purpose of this study has three main objectives: (1)to adjust the motivations of rural tourism to the general motivations for all travelers and find the core factors for rural tourists. (2)to show the segmentation of korean rural tourists, and (3)to suggest the characteristics of rural tourists' typology. This paper was conducted through two studies: a literature review and a survey for empirical exploration of the ideas. The empirical data are extracted through convenience, and the valid questionnaires totaled to 828. The Frequency, Descriptive, Factor, Cluster, Discriminant, Cross-tabulation analysis were used for the data analysis. The results of analysis indicate that the rural tourists' motivation is consisted of 14 factors. the key elements play a major role in rural tourism. and the rural tourists' market was divided into 5 different groups. The results of this study will not only contributes to a better understanding of rural tourism due to clarification of tourist motivations but also have implication for the development and management of rural sites.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.543-553
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• 2021

As a key policy for achieving the goal of reducing GHG in the building sector, Korea has enforced the mandatory certification of zero-energy buildings for new buildings in the public sector from 2020. This study evaluated a policy to achieve Net Zero by identifying the trend of changes in building energy performance according to policy and presenting a methodology to analyze the current performance state of energy technology applied to buildings. The final goal was to help stakeholders apply appropriate energy technologies for new buildings. For this study, data collected on building energy efficiency certification over the last four years have shown a gradual increase in energy performance. In addition, K-means cluster analysis was used to analyze the performance status of energy technologies applied to buildings. The high and low clusters of education and office facilities were used to analyze the comparative group (2016-2020, 2020). As a result, the solar module area in both high and low clusters of education facilities increased by 261.1% and 283.5%. In contrast, the solar module area decreased by both high and low clusters of office facilities. The most passive and active technologies showed an increase in energy performance.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.85-107
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• 2019

Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.137-152
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• 2012

In the generation of Web 2.0, as many users start to make lots of web contents called user created contents by themselves, the World Wide Web is overflowing by countless information. Therefore, it becomes the key to find out meaningful information among lots of resources. Nowadays, the information retrieval is the most important thing throughout the whole field and several types of search services are developed and widely used in various fields to retrieve information that user really wants. Especially, the legal information search is one of the indispensable services in order to provide people with their convenience through searching the law necessary to their present situation as a channel getting knowledge about it. The Office of Legislation in Korea provides the Korean Law Information portal service to search the law information such as legislation, administrative rule, and judicial precedent from 2009, so people can conveniently find information related to the law. However, this service has limitation because the recent technology for search engine basically returns documents depending on whether the query is included in it or not as a search result. Therefore, it is really difficult to retrieve information related the law for general users who are not familiar with legal terms in the search engine using simple matching of keywords in spite of those kinds of efforts of the Office of Legislation in Korea, because there is a huge divergence between everyday words and legal terms which are especially from Chinese words. Generally, people try to access the law information using everyday words, so they have a difficulty to get the result that they exactly want. In this paper, we propose a term mapping methodology between everyday words and legal terms for general users who don't have sufficient background about legal terms, and we develop a search service that can provide the search results of law information from everyday words. This will be able to search the law information accurately without the knowledge of legal terminology. In other words, our research goal is to make a law information search system that general users are able to retrieval the law information with everyday words. First, this paper takes advantage of tags of internet blogs using the concept for collective intelligence to find out the term mapping relationship between everyday words and legal terms. In order to achieve our goal, we collect tags related to an everyday word from web blog posts. Generally, people add a non-hierarchical keyword or term like a synonym, especially called tag, in order to describe, classify, and manage their posts when they make any post in the internet blog. Second, the collected tags are clustered through the cluster analysis method, K-means. Then, we find a mapping relationship between an everyday word and a legal term using our estimation measure to select the fittest one that can match with an everyday word. Selected legal terms are given the definite relationship, and the relations between everyday words and legal terms are described using SKOS that is an ontology to describe the knowledge related to thesauri, classification schemes, taxonomies, and subject-heading. Thus, based on proposed mapping and searching methodologies, our legal information search system finds out a legal term mapped with user query and retrieves law information using a matched legal term, if users try to retrieve law information using an everyday word. Therefore, from our research, users can get exact results even if they do not have the knowledge related to legal terms. As a result of our research, we expect that general users who don't have professional legal background can conveniently and efficiently retrieve the legal information using everyday words.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.45-68
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• 2022

The central and local governments of the Republic of Korea provided information necessary for disaster response through wireless emergency alerts (WEAs) in order to overcome the pandemic situation in which COVID-19 rapidly spreads. Among all channels for delivering disaster information, wireless emergency alert is the most efficient, and since it adopts the CBS(Cell Broadcast Service) method that broadcasts directly to the mobile phone, it has the advantage of being able to easily access disaster information through the mobile phone without the effort of searching. In this study, the characteristics of wireless emergency alerts sent to Seoul during the past year and one month (January 2020 to January 2021) were derived through various text mining methodologies, and various types of information contained in wireless emergency alerts were analyzed. In addition, it was confirmed through the population mobility by age in the districts of Seoul that what kind of influence it had on the movement behavior of people. After going through the process of classifying key words and information included in each character, text analysis was performed so that individual sent characters can be used as an analysis unit by applying a document cluster analysis technique based on the included words. The number of WEAs sent to the Seoul has grown dramatically since the spread of Covid-19. In January 2020, only 10 WEAs were sent to the Seoul, but the number of the WEAs increased 5 times in March, and 7.7 times over the previous months. Since the basic, regional local government were authorized to send wireless emergency alerts independently, the sending behavior of related to wireless emergency alerts are different for each local government. Although most of the basic local governments increased the transmission of WEAs as the number of confirmed cases of Covid-19 increases, the trend of the increase in WEAs according to the increase in the number of confirmed cases of Covid-19 was different by region. By using structured econometric model, the effect of disaster information included in wireless emergency alerts on population mobility was measured by dividing it into baseline effect and accumulating effect. Six types of disaster information, including date, order, online URL, symptom, location, normative guidance, were identified in WEAs and analyzed through econometric modelling. It was confirmed that the types of information that significantly change population mobility by age are different. Population mobility of people in their 60s and 70s decreased when wireless emergency alerts included information related to date and order. As date and order information is appeared in WEAs when they intend to give information about Covid-19 confirmed cases, these results show that the population mobility of higher ages decreased as they reacted to the messages reporting of confirmed cases of Covid-19. Online information (URL) decreased the population mobility of in their 20s, and information related to symptoms reduced the population mobility of people in their 30s. On the other hand, it was confirmed that normative words that including the meaning of encouraging compliance with quarantine policies did not cause significant changes in the population mobility of all ages. This means that only meaningful information which is useful for disaster response should be included in the wireless emergency alerts. Repeated sending of wireless emergency alerts reduces the magnitude of the impact of disaster information on population mobility. It proves indirectly that under the prolonged pandemic, people started to feel tired of getting repetitive WEAs with similar content and started to react less. In order to effectively use WEAs for quarantine and overcoming disaster situations, it is necessary to reduce the fatigue of the people who receive WEA by sending them only in necessary situations, and to raise awareness of WEAs.