• Journal of Family Resource Management and Policy Review
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• v.19 no.2
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• pp.1-26
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• 2015

The purpose of this study was to analyze the quality of life (QoL) of elderly women and the effect of social support on their QoL. The data were used 'urvey on the Elderly in 2011', which was held from 'Ministry of Health & Welfare' and 'Korea Institute for Health and Social Affairs'. Among the total 15,146 respondents, 3,880 of elderly women whose age was over 65, and who did not live together with their married children were included in the analysis. Multiple regression analysis and path analysis were used to analyze the research model. The findings were as follows. First, from the fact that the elderly women showed the highest mean in 'contact frequency with friends' among social support, it seemed that the elderly women contacted their friends more than their children in their old age. Among the support types from their children, elderly women received emotional support, physical support, instrumental support in order and irregular cash as a way of economic support. Second, from the regression results, the most critical factor that affected the QoL of elderly women was 'subjective physical condition level' and 'subjective standard of living' comes next. Third, the most important factor was 'subjective standard of living' from path analysis results, and 'subjective physical condition level' and 'total amount of annual income' in order. Also, social supports such as 'phone call contact frequency with children', 'emotional support from children', phone call contact frequency with relatives', 'phone call contact frequency with friends' positively affected the QoL of elderly women. Therefore, raising social supports from children, relatives, and friends positively contributes to improve the QoL of elderly women directly and indirectly. The results show that social supporters, which is a part of the structural aspects of social support, and types of social support, which lies in functional aspects, directly affect QoL of the elderly women and turn out to be factors that improve the QoL as mediating variables. It is concluded that the social supports can be the most important resources that make up declining personal and social resources in old age and maintain the QoL of elderly women.

• Environmental and Resource Economics Review
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• v.13 no.2
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• pp.219-243
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• 2004

Generally, electricity market has monopoly market structure because of need of enormous investment for infrastructure. However, the introduction of competition in network industry as electricity is a tendency of the world with decreasing the effects of economy of scale due to the advancement of technology. Now, electricity industry restructuring is in progress but the competition in electricity retail market is not in force yet in Korea. Whether a effective competition exist or not is very important to policy decision maker who drive restructuring, but there are small numbers of quantitative researches on that. In this study, we estimated the effectiveness of competition in the electricity retail market through switching costs. If switching costs are high, consumers actually can be locked in incumbent firm in spite of introduction of competition. Therefore switching is a critical factor to determine effectiveness of competition and to estimate the size of switching costs quantitatively can proffer the information about whether the competition in the electricity retail market is effective or not in the future. We estimated switching costs using consumer' stated-preference data by conjoint analysis. In according to estimation results, the cost of switching process is not so high, but the relative brand loyalty of an incumbent company is significantly high. And the price is considered as the most important factor choosing an electric service commodity. Based on the empirical results, it is possible to analyze the relationship between suppliers' competitiveness resulted from management efficiency and customers' switching possibilities. The paper therefore provides guidance for suppliers in deciding to enter into retail competition and for policy makers in introducing retail competition. And it has a significance of estimating the switching costs directly.

• Journal of Korea Water Resources Association
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• v.52 no.7
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• pp.475-482
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• 2019

Subseasonal-to-Seasonal (S2S) prediction information which have 2 weeks to 2 months lead time are expected to be used through many parts of industry fields, but utilizability is not reached to expectation because of lower predictability than weather forecast and mid- /long-term forecast. In this study, we used multi-layer perceptron (MLP) which is one of machine learning technique that was built for regression training in order to improve predictability of S2S precipitation data at South Korea through post-processing. Hindcast information of ECMWF was used for MLP training and the original data were compared with trained outputs based on dichotomous forecast technique. As a result, Bias score, accuracy, and Critical Success Index (CSI) of trained output were improved on average by 59.7%, 124.3% and 88.5%, respectively. Probability of detection (POD) score was decreased on average by 9.5% and the reason was analyzed that ECMWF's model excessively predicted precipitation days. In this study, we confirmed that predictability of ECMWF's S2S information can be improved by post-processing using MLP even the predictability of original data was low. The results of this study can be used to increase the capability of S2S information in water resource and agricultural fields.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.31-59
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• 2007

We frequently use search engines to find relevant information in the Web but still end up with too much information. In order to solve this problem of information overload, ranking algorithms have been applied to various domains. As more information will be available in the future, effectively and efficiently ranking search results will become more critical. In this paper, we propose a ranking algorithm for the Semantic Web resources, specifically RDF resources. Traditionally, the importance of a particular Web page is estimated based on the number of key words found in the page, which is subject to manipulation. In contrast, link analysis methods such as Google's PageRank capitalize on the information which is inherent in the link structure of the Web graph. PageRank considers a certain page highly important if it is referred to by many other pages. The degree of the importance also increases if the importance of the referring pages is high. Kleinberg's algorithm is another link-structure based ranking algorithm for Web pages. Unlike PageRank, Kleinberg's algorithm utilizes two kinds of scores: the authority score and the hub score. If a page has a high authority score, it is an authority on a given topic and many pages refer to it. A page with a high hub score links to many authoritative pages. As mentioned above, the link-structure based ranking method has been playing an essential role in World Wide Web(WWW), and nowadays, many people recognize the effectiveness and efficiency of it. On the other hand, as Resource Description Framework(RDF) data model forms the foundation of the Semantic Web, any information in the Semantic Web can be expressed with RDF graph, making the ranking algorithm for RDF knowledge bases greatly important. The RDF graph consists of nodes and directional links similar to the Web graph. As a result, the link-structure based ranking method seems to be highly applicable to ranking the Semantic Web resources. However, the information space of the Semantic Web is more complex than that of WWW. For instance, WWW can be considered as one huge class, i.e., a collection of Web pages, which has only a recursive property, i.e., a 'refers to' property corresponding to the hyperlinks. However, the Semantic Web encompasses various kinds of classes and properties, and consequently, ranking methods used in WWW should be modified to reflect the complexity of the information space in the Semantic Web. Previous research addressed the ranking problem of query results retrieved from RDF knowledge bases. Mukherjea and Bamba modified Kleinberg's algorithm in order to apply their algorithm to rank the Semantic Web resources. They defined the objectivity score and the subjectivity score of a resource, which correspond to the authority score and the hub score of Kleinberg's, respectively. They concentrated on the diversity of properties and introduced property weights to control the influence of a resource on another resource depending on the characteristic of the property linking the two resources. A node with a high objectivity score becomes the object of many RDF triples, and a node with a high subjectivity score becomes the subject of many RDF triples. They developed several kinds of Semantic Web systems in order to validate their technique and showed some experimental results verifying the applicability of their method to the Semantic Web. Despite their efforts, however, there remained some limitations which they reported in their paper. First, their algorithm is useful only when a Semantic Web system represents most of the knowledge pertaining to a certain domain. In other words, the ratio of links to nodes should be high, or overall resources should be described in detail, to a certain degree for their algorithm to properly work. Second, a Tightly-Knit Community(TKC) effect, the phenomenon that pages which are less important but yet densely connected have higher scores than the ones that are more important but sparsely connected, remains as problematic. Third, a resource may have a high score, not because it is actually important, but simply because it is very common and as a consequence it has many links pointing to it. In this paper, we examine such ranking problems from a novel perspective and propose a new algorithm which can solve the problems under the previous studies. Our proposed method is based on a class-oriented approach. In contrast to the predicate-oriented approach entertained by the previous research, a user, under our approach, determines the weights of a property by comparing its relative significance to the other properties when evaluating the importance of resources in a specific class. This approach stems from the idea that most queries are supposed to find resources belonging to the same class in the Semantic Web, which consists of many heterogeneous classes in RDF Schema. This approach closely reflects the way that people, in the real world, evaluate something, and will turn out to be superior to the predicate-oriented approach for the Semantic Web. Our proposed algorithm can resolve the TKC(Tightly Knit Community) effect, and further can shed lights on other limitations posed by the previous research. In addition, we propose two ways to incorporate data-type properties which have not been employed even in the case when they have some significance on the resource importance. We designed an experiment to show the effectiveness of our proposed algorithm and the validity of ranking results, which was not tried ever in previous research. We also conducted a comprehensive mathematical analysis, which was overlooked in previous research. The mathematical analysis enabled us to simplify the calculation procedure. Finally, we summarize our experimental results and discuss further research issues.

• Information Systems Review
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• v.11 no.2
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• pp.45-66
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• 2009

A number of companies are considering for merger and acquisition (M&A) as one of business strategies for their growth and survival. However, many of them do not create the synergy they had sought, and failed M&A, often result in negative outcomes in terms of productivity, market share, profitability and turnover of qualified employees. There have been numerous research studies conducted to analyze the factors that determine the success and failure of M&A, and it has been found that with the increasing dependence of many companies on information systems, post-M&A IS (information systems) integration success has a critical effect on the success of M&A. However, there have been very few studies on post-M&A IS integration success, and most have been restricted to integration of IS organizations or physical information systems. In order to conduct a comprehensive research on the factors that affect the success of post-M&A IS integration, this study surveyed preceding researches on not only information systems but also strategic management, economics, finance, HRM (human resource management) and organization management. Based on the findings, a comprehensive and integrated model of the influential factors on post-M&A IS integration has been proposed. The proposed model categorizes the factors into perspectives of M&A, strategy, organization, HRM and IS, and provides an empirical evaluation of each factor on the success of IS integration based on comparative case studies.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.28 no.4
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• pp.321-340
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• 2017

The purpose of this study is to design a teaching model applying a problem-based learning model and to analyze the educational benefits that students felt. This study initiated a problem-based learning model from an analysis of existing studies. Through the consultation of experts, the scenario was modified. The problem was designed according to the design stage activity (problem analysis, PBL class suitability judgment, contents analysis, learner analysis, environment analysis, PBL operating environment decision, PBL class) and Strategic Design (problem situation design, learning resource design, Facilitation design, operational strategy design, evaluation design, PBL operating environment design). Based on the initial scenarios, the researcher analyzed the results of the problem - based learning through learners' reflective diaries. The researcher was able to confirm that the critical thinking and creativity were improved in the first PBL problem situation, and the method for smooth communication and cooperation was utilized. The results on analyzing the effects of education about the first problem-based learning and students' opinions about modification will be used for the second revision and supplement of the course design. This study introduces a case of PBL course development and expects further application and research.

• Journal of The Korean Association For Science Education
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• v.40 no.6
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• pp.657-670
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• 2020

The knowledge-information-processing competency is the most essential competency in a knowledge-information-based society and is the most fundamental competency in the new problem-solving ability. Data-driven science inquiry, which emphasizes how to find and solve problems using vast amounts of data and information, is a way to cultivate the problem-solving ability in a knowledge-information-based society. Therefore, this study aims to develop a teaching-learning model and strategy for data-driven science inquiry and to verify the validity of the model in terms of knowledge information processing competency. This study is developmental research. Based on literature, the initial model and strategy were developed, and the final model and teaching strategy were completed by securing external validity through on-site application and internal validity through expert advice. The development principle of the inquiry model is the literature study on science inquiry, data science, and a statistical problem-solving model based on resource-based learning theory, which is known to be effective for the knowledge-information-processing competency and critical thinking. This model is titled "Exploratory Scientific Data Analysis" The model consisted of selecting tools, collecting and analyzing data, finding problems and exploring problems. The teaching strategy is composed of seven principles necessary for each stage of the model, and is divided into instructional strategies and guidelines for environment composition. The development of the ESDA inquiry model and teaching strategy is not easy to generalize to the whole school level because the sample was not large, and research was qualitative. While this study has a limitation that a quantitative study over large number of students could not be carried out, it has significance that practical model and strategy was developed by approaching the knowledge-information-processing competency with respect of science inquiry.

• International Commerce and Information Review
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• v.18 no.3
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• pp.249-273
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• 2016

Recently companies consider the patent activity as one of the critical factor for success in global economy even though one of the enterprise's competitiveness factor was productivity in past industry economy. Since there are so many patent dispute globally in IT industry, it is very important for companies to register and manage patents strategically. Therefore, this research analyze relationship between Financial result and 3 patent activity factors like productivity, effectiveness, and high-quality by investigating patent and financial data of 217 Korean IT enterprises. This paper get the following results after building research model and hypothesis based on resource-based theory and analysing the data sets using multiple regression model. First, effectiveness and high-quality of patents showed positive(+) effect on growth of total assets of IT enterprises. Second, three factors of patent activities do not have significant results with average increase rate of sales. Third, only high-quality of patents have positive(+) effect on average increase rate of net income. The differentiation factor of this research is that this paper categorized patent activity factors as quantitative and qualitative factors, and practically suggested strategic direction of patent activities of IT companies which face serious patent distribute globally.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.2
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• pp.462-471
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• 2018

Even though software (SW) education has not been considered part of the current national kindergarten curriculum, in practice there is growing interest in adopting it. Teachers would be expected to play a key role in the successful introduction and implementation of new educational changes, such as SW education. In preparation for its adoption in ECE, it would be useful to determine ECE teachers' perception and attitudes toward early childhood software education. For this study, 219 ECE teachers' level of concern toward SW education was surveyed using the Stages of Concern Questionnaire. It was found that the teachers' level of concern was the highest at stage 0-Unconcerned and that they had high levels of stage management, personal and informational concern. Thus, a non-user pattern was mostly indicated. However, compared to the typical non-user pattern, the pattern aspect close to critical non-user ever appeared to some extent. In addition, a significant difference in the level of concern was shown at all stages depending on the awareness of the necessity for SW education. The teachers with SW training experience showed a higher intensity only at stage 0. There was a statistically significant difference in stages 0 and 6 depending on the future implementation decision. These results will be utilized as a resource in building an ECE teachers' support system according to their level of concern about SW education.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.1
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• pp.45-55
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• 2017

Climate change causes changes in rainfall patterns, temperature and drought frequency. Climate change impact influences on water management and crop production. It is critical issue in agricultural industry. Rice is a staple cereal crop in South Korea and Korea uses a ponding system for its paddy fields which requires a significant amount of water. In addition, water supply has inter-relationship with crop production which indicates water productivity. Therefore, it is important to assess overall impacts of climate change on water resource and crop production. A water footprint concept is an indicator which shows relationship between water use and crop yield. In addition, it generally composed of three components depending on water resources: green, blue, grey water. This study analyzed the change trend of water footprint of paddy rice under the climate change. The downscaled climate data from HadGEM3-RA based on RCP 8.5 scenario was applied as future periods (2020s, 2050s, 2080s), and historical climate data was set to base line (1990s). Depending on agro-climatic zones, Suwon and Jeonju were selected for study area. A yield of paddy rice was simulated by using FAO-AquaCrop 5.0, which is a water-driven crop model. Model was calibrated by adjusting parameters and was validated by Mann-Whitney U test statistically. The means of water footprint were projected increase by 55 % (2020s), 51 % (2050s) and 48 % (2080s), respectively, from the baseline value of $767m^2/ton$ in Suwon. In case of Jeonju, total water footprint was projected to increase by 46 % (2020s), 45 % (2050s), 12 % (2080s), respectively, from the baseline value of $765m^2/ton$. The results are expected to be useful for paddy water management and operation of water supply system and apply in establishing long-term policies for agricultural water resources.