• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.177-198
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• 2018

Recently, as economic property it has become necessary to acquire and utilize the framework for water resource measurement and performance management as the property of water resources changes to hold "public property". To date, the evaluation of water technology has been carried out by feasibility study analysis or technology assessment based on net present value (NPV) or benefit-to-cost (B/C) effect, however it is not yet systemized in terms of valuation models to objectively assess an economic value of technology-based business to receive diffusion and feedback of research outcomes. Therefore, K-water (known as a government-supported public company in Korea) company feels the necessity to establish a technology valuation framework suitable for technical characteristics of water resources fields in charge and verify an exemplified case applied to the technology. The K-water evaluation technology applied to this study, as a public interest goods, can be used as a tool to measure the value and achievement contributed to society and to manage them. Therefore, by calculating the value in which the subject technology contributed to the entire society as a public resource, we make use of it as a basis information for the advertising medium of performance on the influence effect of the benefits or the necessity of cost input, and then secure the legitimacy for large-scale R&D cost input in terms of the characteristics of public technology. Hence, K-water company, one of the public corporation in Korea which deals with public goods of 'water resources', will be able to establish a commercialization strategy for business operation and prepare for a basis for the performance calculation of input R&D cost. In this study, K-water has developed a web-based technology valuation model for public interest type water resources based on the technology evaluation system that is suitable for the characteristics of a technology in water resources fields. In particular, by utilizing the evaluation methodology of the Institute of Advanced Industrial Science and Technology (AIST) in Japan to match the expense items to the expense accounts based on the related benefit items, we proposed the so-called 'K-water's proprietary model' which involves the 'cost-benefit' approach and the FCF (Free Cash Flow), and ultimately led to build a pipeline on the K-water research performance management system and then verify the practical case of a technology related to "desalination". We analyze the embedded design logic and evaluation process of web-based valuation system that reflects characteristics of water resources technology, reference information and database(D/B)-associated logic for each model to calculate public interest-based and profit-based technology values in technology integrated management system. We review the hybrid evaluation module that reflects the quantitative index of the qualitative evaluation indices reflecting the unique characteristics of water resources and the visualized user-interface (UI) of the actual web-based evaluation, which both are appended for calculating the business value based on financial data to the existing web-based technology valuation systems in other fields. K-water's technology valuation model is evaluated by distinguishing between public-interest type and profitable-type water technology. First, evaluation modules in profit-type technology valuation model are designed based on 'profitability of technology'. For example, the technology inventory K-water holds has a number of profit-oriented technologies such as water treatment membranes. On the other hand, the public interest-type technology valuation is designed to evaluate the public-interest oriented technology such as the dam, which reflects the characteristics of public benefits and costs. In order to examine the appropriateness of the cost-benefit based public utility valuation model (i.e. K-water specific technology valuation model) presented in this study, we applied to practical cases from calculation of benefit-to-cost analysis on water resource technology with 20 years of lifetime. In future we will additionally conduct verifying the K-water public utility-based valuation model by each business model which reflects various business environmental characteristics.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.53-77
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• 2012

This study analyses the difference of contents and tones of arguments among three Korean major newspapers, the Kyunghyang Shinmoon, the HanKyoreh, and the Dong-A Ilbo. It is commonly accepted that newspapers in Korea explicitly deliver their own tone of arguments when they talk about some sensitive issues and topics. It could be controversial if readers of newspapers read the news without being aware of the type of tones of arguments because the contents and the tones of arguments can affect readers easily. Thus it is very desirable to have a new tool that can inform the readers of what tone of argument a newspaper has. This study presents the results of clustering and classification techniques as part of text mining analysis. We focus on six main subjects such as Culture, Politics, International, Editorial-opinion, Eco-business and National issues in newspapers, and attempt to identify differences and similarities among the newspapers. The basic unit of text mining analysis is a paragraph of news articles. This study uses a keyword-network analysis tool and visualizes relationships among keywords to make it easier to see the differences. Newspaper articles were gathered from KINDS, the Korean integrated news database system. KINDS preserves news articles of the Kyunghyang Shinmun, the HanKyoreh and the Dong-A Ilbo and these are open to the public. This study used these three Korean major newspapers from KINDS. About 3,030 articles from 2008 to 2012 were used. International, national issues and politics sections were gathered with some specific issues. The International section was collected with the keyword of 'Nuclear weapon of North Korea.' The National issues section was collected with the keyword of '4-major-river.' The Politics section was collected with the keyword of 'Tonghap-Jinbo Dang.' All of the articles from April 2012 to May 2012 of Eco-business, Culture and Editorial-opinion sections were also collected. All of the collected data were handled and edited into paragraphs. We got rid of stop-words using the Lucene Korean Module. We calculated keyword co-occurrence counts from the paired co-occurrence list of keywords in a paragraph. We made a co-occurrence matrix from the list. Once the co-occurrence matrix was built, we used the Cosine coefficient matrix as input for PFNet(Pathfinder Network). In order to analyze these three newspapers and find out the significant keywords in each paper, we analyzed the list of 10 highest frequency keywords and keyword-networks of 20 highest ranking frequency keywords to closely examine the relationships and show the detailed network map among keywords. We used NodeXL software to visualize the PFNet. After drawing all the networks, we compared the results with the classification results. Classification was firstly handled to identify how the tone of argument of a newspaper is different from others. Then, to analyze tones of arguments, all the paragraphs were divided into two types of tones, Positive tone and Negative tone. To identify and classify all of the tones of paragraphs and articles we had collected, supervised learning technique was used. The Na$\ddot{i}$ve Bayesian classifier algorithm provided in the MALLET package was used to classify all the paragraphs in articles. After classification, Precision, Recall and F-value were used to evaluate the results of classification. Based on the results of this study, three subjects such as Culture, Eco-business and Politics showed some differences in contents and tones of arguments among these three newspapers. In addition, for the National issues, tones of arguments on 4-major-rivers project were different from each other. It seems three newspapers have their own specific tone of argument in those sections. And keyword-networks showed different shapes with each other in the same period in the same section. It means that frequently appeared keywords in articles are different and their contents are comprised with different keywords. And the Positive-Negative classification showed the possibility of classifying newspapers' tones of arguments compared to others. These results indicate that the approach in this study is promising to be extended as a new tool to identify the different tones of arguments of newspapers.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.1-17
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• 2015

In this paper, we report what we have observed with regards to a prediction model for the military based on enlisted men's internal(cumulative records) and external data(SNS data). This work is significant in the military's efforts to supervise them. In spite of their effort, many commanders have failed to prevent accidents by their subordinates. One of the important duties of officers' work is to take care of their subordinates in prevention unexpected accidents. However, it is hard to prevent accidents so we must attempt to determine a proper method. Our motivation for presenting this paper is to mate it possible to predict accidents using enlisted men's internal and external data. The biggest issue facing the military is the occurrence of accidents by enlisted men related to maladjustment and the relaxation of military discipline. The core method of preventing accidents by soldiers is to identify problems and manage them quickly. Commanders predict accidents by interviewing their soldiers and observing their surroundings. It requires considerable time and effort and results in a significant difference depending on the capabilities of the commanders. In this paper, we seek to predict accidents with objective data which can easily be obtained. Recently, records of enlisted men as well as SNS communication between commanders and soldiers, make it possible to predict and prevent accidents. This paper concerns the application of data mining to identify their interests, predict accidents and make use of internal and external data (SNS). We propose both a topic analysis and decision tree method. The study is conducted in two steps. First, topic analysis is conducted through the SNS of enlisted men. Second, the decision tree method is used to analyze the internal data with the results of the first analysis. The dependent variable for these analysis is the presence of any accidents. In order to analyze their SNS, we require tools such as text mining and topic analysis. We used SAS Enterprise Miner 12.1, which provides a text miner module. Our approach for finding their interests is composed of three main phases; collecting, topic analysis, and converting topic analysis results into points for using independent variables. In the first phase, we collect enlisted men's SNS data by commender's ID. After gathering unstructured SNS data, the topic analysis phase extracts issues from them. For simplicity, 5 topics(vacation, friends, stress, training, and sports) are extracted from 20,000 articles. In the third phase, using these 5 topics, we quantify them as personal points. After quantifying their topic, we include these results in independent variables which are composed of 15 internal data sets. Then, we make two decision trees. The first tree is composed of their internal data only. The second tree is composed of their external data(SNS) as well as their internal data. After that, we compare the results of misclassification from SAS E-miner. The first model's misclassification is 12.1%. On the other hand, second model's misclassification is 7.8%. This method predicts accidents with an accuracy of approximately 92%. The gap of the two models is 4.3%. Finally, we test if the difference between them is meaningful or not, using the McNemar test. The result of test is considered relevant.(p-value : 0.0003) This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of enlisted men's data. Additionally, various independent variables used in the decision tree model are used as categorical variables instead of continuous variables. So it suffers a loss of information. In spite of extensive efforts to provide prediction models for the military, commanders' predictions are accurate only when they have sufficient data about their subordinates. Our proposed methodology can provide support to decision-making in the military. This study is expected to contribute to the prevention of accidents in the military based on scientific analysis of enlisted men and proper management of them.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.101-123
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• 2013

Recently due to the advancements of science and information technology, the socio-economic business areas are changing from the industrial economy to a knowledge economy. Furthermore, companies need to do creation of new value through continuous innovation, development of core competencies and technologies, and technological convergence. Therefore, the identification of major trends in technology research and the interdisciplinary knowledge-based prediction of integrated technologies and promising techniques are required for firms to gain and sustain competitive advantage and future growth engines. The aim of this paper is to understand the recent research trend in management of technology (MOT) and to foresee promising technologies with deep knowledge for both technology and business. Furthermore, this study intends to give a clear way to find new technical value for constant innovation and to capture core technology and technology convergence. Bibliometrics is a metrical analysis to understand literature's characteristics. Traditional bibliometrics has its limitation not to understand relationship between trend in technology management and technology itself, since it focuses on quantitative indices such as quotation frequency. To overcome this issue, the network focused bibliometrics has been used instead of traditional one. The network focused bibliometrics mainly uses "Co-citation" and "Co-word" analysis. In this study, a keywords network analysis, one of social network analysis, is performed to analyze recent research trend in MOT. For the analysis, we collected keywords from research papers published in international journals related MOT between 2002 and 2011, constructed a keyword network, and then conducted the keywords network analysis. Over the past 40 years, the studies in social network have attempted to understand the social interactions through the network structure represented by connection patterns. In other words, social network analysis has been used to explain the structures and behaviors of various social formations such as teams, organizations, and industries. In general, the social network analysis uses data as a form of matrix. In our context, the matrix depicts the relations between rows as papers and columns as keywords, where the relations are represented as binary. Even though there are no direct relations between papers who have been published, the relations between papers can be derived artificially as in the paper-keyword matrix, in which each cell has 1 for including or 0 for not including. For example, a keywords network can be configured in a way to connect the papers which have included one or more same keywords. After constructing a keywords network, we analyzed frequency of keywords, structural characteristics of keywords network, preferential attachment and growth of new keywords, component, and centrality. The results of this study are as follows. First, a paper has 4.574 keywords on the average. 90% of keywords were used three or less times for past 10 years and about 75% of keywords appeared only one time. Second, the keyword network in MOT is a small world network and a scale free network in which a small number of keywords have a tendency to become a monopoly. Third, the gap between the rich (with more edges) and the poor (with fewer edges) in the network is getting bigger as time goes on. Fourth, most of newly entering keywords become poor nodes within about 2~3 years. Finally, keywords with high degree centrality, betweenness centrality, and closeness centrality are "Innovation," "R&D," "Patent," "Forecast," "Technology transfer," "Technology," and "SME". The results of analysis will help researchers identify major trends in MOT research and then seek a new research topic. We hope that the result of the analysis will help researchers of MOT identify major trends in technology research, and utilize as useful reference information when they seek consilience with other fields of study and select a new research topic.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.1-32
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• 2018

In addition to stakeholders including managers, employees, creditors, and investors of bankrupt companies, corporate defaults have a ripple effect on the local and national economy. Before the Asian financial crisis, the Korean government only analyzed SMEs and tried to improve the forecasting power of a default prediction model, rather than developing various corporate default models. As a result, even large corporations called 'chaebol enterprises' become bankrupt. Even after that, the analysis of past corporate defaults has been focused on specific variables, and when the government restructured immediately after the global financial crisis, they only focused on certain main variables such as 'debt ratio'. A multifaceted study of corporate default prediction models is essential to ensure diverse interests, to avoid situations like the 'Lehman Brothers Case' of the global financial crisis, to avoid total collapse in a single moment. The key variables used in corporate defaults vary over time. This is confirmed by Beaver (1967, 1968) and Altman's (1968) analysis that Deakins'(1972) study shows that the major factors affecting corporate failure have changed. In Grice's (2001) study, the importance of predictive variables was also found through Zmijewski's (1984) and Ohlson's (1980) models. However, the studies that have been carried out in the past use static models. Most of them do not consider the changes that occur in the course of time. Therefore, in order to construct consistent prediction models, it is necessary to compensate the time-dependent bias by means of a time series analysis algorithm reflecting dynamic change. Based on the global financial crisis, which has had a significant impact on Korea, this study is conducted using 10 years of annual corporate data from 2000 to 2009. Data are divided into training data, validation data, and test data respectively, and are divided into 7, 2, and 1 years respectively. In order to construct a consistent bankruptcy model in the flow of time change, we first train a time series deep learning algorithm model using the data before the financial crisis (2000~2006). The parameter tuning of the existing model and the deep learning time series algorithm is conducted with validation data including the financial crisis period (2007~2008). As a result, we construct a model that shows similar pattern to the results of the learning data and shows excellent prediction power. After that, each bankruptcy prediction model is restructured by integrating the learning data and validation data again (2000 ~ 2008), applying the optimal parameters as in the previous validation. Finally, each corporate default prediction model is evaluated and compared using test data (2009) based on the trained models over nine years. Then, the usefulness of the corporate default prediction model based on the deep learning time series algorithm is proved. In addition, by adding the Lasso regression analysis to the existing methods (multiple discriminant analysis, logit model) which select the variables, it is proved that the deep learning time series algorithm model based on the three bundles of variables is useful for robust corporate default prediction. The definition of bankruptcy used is the same as that of Lee (2015). Independent variables include financial information such as financial ratios used in previous studies. Multivariate discriminant analysis, logit model, and Lasso regression model are used to select the optimal variable group. The influence of the Multivariate discriminant analysis model proposed by Altman (1968), the Logit model proposed by Ohlson (1980), the non-time series machine learning algorithms, and the deep learning time series algorithms are compared. In the case of corporate data, there are limitations of 'nonlinear variables', 'multi-collinearity' of variables, and 'lack of data'. While the logit model is nonlinear, the Lasso regression model solves the multi-collinearity problem, and the deep learning time series algorithm using the variable data generation method complements the lack of data. Big Data Technology, a leading technology in the future, is moving from simple human analysis, to automated AI analysis, and finally towards future intertwined AI applications. Although the study of the corporate default prediction model using the time series algorithm is still in its early stages, deep learning algorithm is much faster than regression analysis at corporate default prediction modeling. Also, it is more effective on prediction power. Through the Fourth Industrial Revolution, the current government and other overseas governments are working hard to integrate the system in everyday life of their nation and society. Yet the field of deep learning time series research for the financial industry is still insufficient. This is an initial study on deep learning time series algorithm analysis of corporate defaults. Therefore it is hoped that it will be used as a comparative analysis data for non-specialists who start a study combining financial data and deep learning time series algorithm.

• Korean Journal of Community Nutrition
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• v.26 no.3
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• pp.188-199
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• 2021

Objectives: The purpose was to identify the ingredients that are usually surveyed for assessing real prices and to present the demand for such surveys by nutrition teachers and dietitians for ingredients used by school foodservice. Methods: A survey was conducted online from December 2019 to January 2020. The survey questionnaire was distributed to 1,158 nutrition teachers and dietitians from elementary, middle, and high schools nationwide, and 439 (37.9% return rate) of the 1,158 were collected and used for data analysis. Results: The ingredients which were investigated for price realities directly by schools were industrial products in 228 schools (51.8%), fruits in 169 schools (38.4%), and specialty crops in 166 schools (37.7%). Moreover, nutrition teachers and dietitians in elementary, middle, and high schools searched in different ways for the real prices of ingredients. In elementary schools, there was a high demand for price information about grains, vegetables or root and tuber crops, special crops, fruits, eggs, fishes, and organic and locally grown ingredients by the School Foodservice Support Centers. Real price information about meats, industrial products, and pickled processed products were sought from the external specialized institutions. In addition, nutrition teachers and dietitians in middle and high schools wanted to obtain prices of all of the ingredients from the Offices of Education or the District Office of Education. Conclusions: Schools want to efficiently use the time or money spent on research for the real prices of ingredients through reputable organizations or to co-work with other nutrition teachers and dietitians. The results of this study will be useful in understanding the current status of the surveys carried out to determine the real price information for ingredients used by the school foodservice.

• The Korean Nurse
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• v.20 no.4 s.112
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• pp.27-38
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• 1981

오늘 저희에게 주어진 주제, 내일에 타당한 간호사업 및 간호교육의 향방을 어떻게 정하여야 하는가의 논의는 오늘날 간호계 주변에 일어나고 있는 변화의 실상을 이해하는 데서 비롯되어져야 한다고 생각하는 입장에서 먼저 세계적으로 건강관리사업이 당면한 딜레마가 어떠한 것이며 이러한 문제해결을 위해 어떠한 새로운 제안들이 나오고 있는가를 개관 하므로서 그 교육적 의미를 정의해 보고 장래 간호교육이 지향해야할 바를 생각해 보려 합니다. 오늘의 사회의 하나의 특징은 세계 모든 나라들이 각기 어떻게 전체 국민에게 고루 미칠 수 있는 건강관리체계를 이룩할 수 있느냐에 관심을 모으고 있는 사실이라고 봅니다. 부강한 나라에 있어서나 가장 빈궁한 나라에 있어서나 그 관심은 마찬가지로 나타나고 있읍니다. 보건진료 문제의 제기는 발달된 현대의학의 지식과 기술이 지닌 건강관리의 방대한 가능성과 건강 관리의 요구를 지닌 사람들에게 미치는 실질적인 혜택간에 점점 더 크게 벌어지는 격차에서 발생한다고 봅니다. David Rogers는 1960년대 초반까지 갖고 있던 의료지식의 축적과 민간인의 구매력 향상이 자동적으로 국민 건강의 향상을 초래할 것이라고 믿었던 순진한 꿈은 이루어지지 않았고 오히려 의료사업의 위기는 의료지식과 의료봉사간에 벌어지는 격차와 의료에 대한 막대한 투자와 그에서 얻는 건강의 혜택간의 격차에서 온다고 말하고 있읍니다. 균등 분배의 견지에서 보면 의료지식과 기술의 향상은 그 단위 투자에 대한 생산성을 낮춤으로서 오히려 장애적 요인으로 작용해온 것도 사실이고 의료의 발달에 따른 일반인의 기대 상승과 더불어 의료를 태성의 권리로 규명하는 의료보호사업의 확대로 야기되는 의료수요의 급증은 모두 기존 시설 자원에 압박을 초래하여 전래적 의료공급체제에 도전을 가해 왔으며 의료의 발달에 건 기대와는 달리 인류의 건강 문제 해결은 더욱 요원한 과제로 남게 되었읍니다. 현시점에서 세계인구의 건강문제는 기아, 영양실조, 안전한 식수 공급 및 위생적 생활환경조성의 문제에서부터 가장 정밀한 의료기술발달에 수반되는 의료사회문제에 이르는 다양한 문제를 지니고 있으며 주로 각개 국가의 경제 사회적 여건이 이 문제의 성격을 결정짓고 있다고 볼수 있읍니다. 그러나 건강 관리에 대한 요구는 영구히, 완전히 충족될 수 없는 요구에 속한다는 의미에서 경제 사회적 발달 수준에 상관없이 모든 국가가 공히 요구에 미치지 못하는 제한된 자원문제로 고심하고 있는 실정입니다. 또 하나의 공통된 관점은 각기 문제의 상황은 달라도 오늘날의 건강 문제는 주로 의료권 밖의 유전적 소인, 사회경제적, 정치문화적인 환경여건과 각기 선택하는 삶의 스타일에 깊이 관련되어 있다는 사실입니다. 따라서 오늘과 내일의 건강관리 문제는 의학적 견지에서 뿐 아니라 널리 경제, 사회, 정치, 문화적 관점에서 포괄적인 접근이 시도되어야 한다는 점과 의료의 고급화, 전문화, 일변도의 과정에서 소외되었던 기본건강관리체계 강화에 역점을 둔 다양하고 탄력성 있는 사업전개가 요구되고 있다는 점입니다. 다양한 건강관리요구에 적절히 대처할 수 있기 위한 그간 세계 각처에서 시도된 새로운 건강관리 접근과 그 제안을 살펴보면 대체로 4가지의 뚜렷한 성격들로 집약할 수 있을 것 같습니다. 그 첫째는 건강관리사업계획 및 그 수행에 있어 지역 사회의 적극적 참여를 유도하는 일, 둘째는 지역단위의 일차보건의료에서 부터 도심지 신예 종합병원, 시설 의료에 이르기까지 건강관리사업을 합리적으로 체계화하는 일. 셋째로 의료인력이용의 효율화 및 비의료인의 훈련과 협조 유발을 포함하는 효과적인 인력관리에 대한 제안과 넷째로 의료보험 및 각양 집단 의료유형을 포함하는 대체 의료재정 운영관리에 관련된 제안들을 들 수 있읍니다. 건강관리사업에 있어 지역사회 참여의 의의는 첫째로 사회 경제적인 제약이 모든 사람에게 가능한 최대한의 의료를 모두 고루 공급하기 어렵게 하고 있다는 점에서 제한된 정부재정과 지역사회가용자원을 보다 효율적으로 이용할 수 있게 하는 자조적이고 자율적인 지역사회건강관리체제의 구현에 있다고 볼 수 있으며 둘때로는 개인과 가족 및 지역민의 건강에 영향하는 많은 요인들은 실질적으로 의료권 외적 요인들로서 위생적인 생활양식, 식사습관, 의료시설이용 등 깊이 지역사회특성과 관련되어 국민보건의 실질적 향상을 위하여는 지역 주민의 자발적인 참여가 필수여건이 된다는 점 입니다. 지역 단위별 체계적인 의료사업의 전개는 제한된 의료자원의 보다 합리적이고 효율적인 이용을 가능하게 하며 요구가 있을때 언제나 가까운 거리에서 경제 사회적 제약을 받지 않고 이용할 수 있는 일차건강관리망을 통하여 건강에 관련된 정보를 얻으며 질병예방, 건강증진 및 기초적인 진료의 도움을 얻을 수 있고 의뢰에 대한 제2차, 제3차 진료에의 길은 건강관리사업의 질과 폭을 동시에 높고 넓게 해 줄 수 있는 길이 된다는 것입니다. 인력 관리에 관련된 두가지 기본 방향으로서는 첫째로 기존보건의료인력의 적정배치 유도이고 둘째는 기존인력의 역할확대, 조정 및 비의료인의 교육훈련과 부분적 업무대체를 들수 있으며 이러한 인력관리의 기본 방향은 부족되는 의료인력의 생산성을 높이고 주민들의 자조적 능력을 강화시킨다는 데에 두고 있음니다. 대체적 의료재정운영안은 대체로 의료공급과 재정관리를 이원화하여 주민의 경제능력이 의료수혜의 장애요소로 작용함을 막고 의료인의 경제적 동기에 의한 과잉치료처치에 의한 낭비를 줄임으로써 의료재정의 투자의 효과를 증대하는 데(cost-effectiveness) 그 기본방향을 두고 있다고 봅니다. 이러한 주변의료 사회적인 동향이 간호교육의 미래상에 끼치는 영향은 지대한 것이라 봅니다. 첫째로 장래 세계인구의 건강문제는 정치, 사회, 경제, 환경적인 의료권 밖의 요인들에 의해 더욱 크게 영향 받는다고 전제한다면 건강문제해결에 있어서도 전통적인 의료사업의 접근에서 더나아가 문제발생의 근원이 되는 생활개선이라는 차원에서 포괄적 접근을 생각하여야 하고 이를 위해선 정치, 경제, 사회전반에 걸친 깊이있는 이해과 주민의 생활환경에 직접 영향하는 교통수단, 통신망 mass media, 전력문제, 농업경영방법 및 조직적 사회활동 등 폭넓은 이해가 요구된다고 봅니다. 둘째로, 지역사회참여의 의의를 인정한다면 지역민의 자발적 참여를 효과적으로 유발시킬수 있고 의료집단과 각종 주민조직과 일반주민들 사이에서 협조적으로 일할수 있는 역량을 기르기위한 교육적 준비가 요구된다고 봅니다. 셋째로, 지역주민의 건강관리 자조능력 강화를 하나의 목표로 삼는다면 치료자에서 교육자로, 지도자에서 촉진자로, 제공자에서 지원자료의 역할의 변화 내지 다양화를 요구하게 될 것이므로 그에 대처할 수 있는 준비가 필요하다고 봅니다. 넷째로, 생각되어야 할 점은 지역중심건강관리사업을 지향하는 보건의료의 이념적 방향과 그에 상응하는 구체적 접근방법을 효율적으로 적용하기 위해서는 종횡으로 연결되는 의사소통체계의 정립과 민활한 정보교환이 이루어질 수 있어야 한다는 점에서 의사소통의 구심체로서 역할할 수 있는 역량을 함양해야 할 교육적 과제가 있다고 봅니다. 마지막으로 생각되어야 할 점은 지역중심으로 전개될 건강관리사업은 건강증진 및 질병예방적 측면과 질병진료 및 회복과 재활에 이르는 종합적이고 포괄적인 사업이어야 한다는 점에서 종래 공공 의료부문과 사설의료기관 사이에 나누어져 있던 예방의학과 치료의학의 통합 뿐 아니라 정부주축으로 이루어 지고 있는 지역사회개발사업 및 농촌지도사업과 종교 및 각종 민간인 집단이 벌이고있는 사업들과의 전체적인 통합적 접근이 이루어져야 한다고 생각하는 입장에서 종래 간호교육이 강조하지 않던 진료의 의무와 대외적 조직활동에 대한 보완적인 교육조치가 요구된다고 봅니다. 간호의 학문체계로서의 입장은 오랜 역사를 두고 논의의 대상이 되어왔으나 아직까지 뚜렷이 어떤 것이 간호 특유의 지식체계이며 건강문제에 관련하여 무엇이 간호특유의 결정영역이며 이 결정과 그 결과를 어떠한 방법으로 치료적 행위로 옮길 수 있는가에 대한 확실한 답을 얻지 못하고 있는 실정이라고 봅니다. 다만 근래에 제시된 여러 간호이론들 속에서 공통적으로 이야기되어지고 있는 개념들로선 우선 간호학문을 건강과 질병에 관련된 인간의 전인적이고 전체적인 상황을 다루는 학제적 과학으로서보는 입장이 있고 따라서 생물신체적인 면 외에 정신심리적, 사회경제적, 정치문화적 환경과의 상호작용 속에서 인간의 건강과 질병문제를 생각한다는 지향을 갖고 있다고 말할 수 있겠읍니다. 간호교육은 간호계 내적인 학문적, 이론적 체계화의 요구에 못지않게 대민봉사하는 전문직으로서의 사회적 책임을 감당해야하는 중요과제를 안고있어 변화하는 사회요구에 효과적으로 대처해 나가야 할 당면문제를 안고 있읍니다. 간효역할 확대, 보건진료원훈련 등 이러한 사회적 요구에 대응하려는 조치가 되겠읍니다. 이러한 시점에서 간호계가 분명히 짚고 넘어가야 할 사실은 이러한 움직임들이 종래의 의사들의 외업무공급을 연장 확대하는 입장에 서서 간호의 특수전문직 명목을 흐리게 할수있는 위험을 감수할 것인지 아니면 가능한 대체방안을 갖고 간호전문직의 독자적인 진로를 개척하면서 다각적인 도전을 받아들일 준비를 갖추든지 그 방향을 뚜렷이 해야할 일이라 생각합니다. 저로서는 이미 잘 훈련된 간호원들과 조산원들의 교육적, 경험적 배경을 기반으로 지역사회 최일선 건강관리요원으로 사회적 효능을 다 할수 있는 일차건강관리간호조직의 구현을 대체방안으로 제시하고 싶습니다. 간호원과 조산원들의 훈련된 역량과 건강관리체제의 구조적 변화를 효과적으로 조화시킨다면 대부분의 세계인구의 건강문제는 해결가능하다고 보는 입장입니다. 물론 정책과 의료와 행정적지원이 활성화되어지는 환경속에서만 그 기대하는 결과가 확대되리라는 점 부언하는 바입니다. 마지막으로 언급하고 싶은 점은 바로 오늘의 주제 ''교육의 동역자-선생과 학생''이라는 개념입니다. 특히 상회정의적 입장에서 보는 의료사업전개에 지역민 내지 의료소비자의 참여를 강조하는 현시점에 있어 교육자와 학생이 교육의 현장에서 서로 동역자로서 학습의 책임을 나누는 경험은 아주 시기적으로 적합하여 교육적으로 지대한 의미를 갖는 것이라고 생각합니다. 이에 수반되어져야 할 역할의 변화에 수용적인 자세를 갖고 적극 실제적용하려 노력하는 선생앞에서 자주적 결정을 행사해본 학생이야말로 건강관리대상자로 하여금 같은 결정권을 행사할수 있도록 촉구하여 주민의 자조적 역량을 기르고 의료사업의 민주화, 인간화를 이룩할 수 있는 길잡이가 될 수 있으리라 믿는 바입니다.

• Journal of Distribution Research
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• v.17 no.1
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• pp.87-115
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• 2012

Introduction: In these days, a loyalty program is one of the most common marketing mechanisms (Lacey & Sneath, 2006; Nues & Dreze, 2006; Uncles et al., 20003). In recent years, Coalition Loyalty Program is more noticeable as one of progressed forms. In the past, loyalty program was operating independently by single product brand or single retail channel brand. Now, companies using Coalition Loyalty Program share their programs as one single service and companies to participate to this program continue to have benefits from their existing program as well as positive spillover effect from the other participating network companies. Instead of consumers to earn or spend points from single retail channel or brand, consumers will have more opportunities to utilize their points and be able to purchase other participating companies products. Issues that are related to form of loyalty programs are essentially connected with consumers' perceived view on convenience of using its program. This can be a problem for distribution companies' strategic marketing plan. Although Coalition Loyalty Program is popular corporate marketing strategy to most companies, only few researches have been published. However, compared to independent loyalty program, coalition loyalty program operated by third parties of partnership has following conditions: Companies cannot autonomously modify structures of program for individual companies' benefits, and there is no guarantee to operate and to participate its program continuously by signing a contract. Thus, it is important to conduct the study on how coalition loyalty program affects companies' success and its process as much as conducting the study on effects of independent program. This study will complement the lack of coalition loyalty program study. The purpose of this study is to find out how consumer loyalty affects affiliated brands, its cause and mechanism. The past study about loyalty program only provided the variation of performance analysis, but this study will specifically focus on causes of results. In order to do these, this study is designed and to verify three primary objects as following; First, based on opinions of Switching Barriers (Fornell, 1992; Ping, 1993; Jones, et at., 2000) about causes of loyalty of coalition brand, 'brand attractiveness' and 'brand switching cost' are antecedents and causes of change in 'brand loyalty' will be investigated. Second, influence of consumers' perception and attitude prior to joining coalition loyalty program, influence of program in retail brands, brand attractiveness and spillover effect of switching cost after joining coalition program will be verified. Finally, the study will apply 'prior brand preference' as a variable and will provide a relationship between effects of coalition loyalty program and prior preference level. Hypothesis Hypothesis 1. After joining coalition loyalty program, more preferred brand (compared to less preferred brand) will increase influence on brand attractiveness to brand loyalty. Hypothesis 2. After joining coalition loyalty program, less preferred brand (compared to more preferred brand) will increase influence on brand switching cost to brand loyalty. Hypothesis 3. (1)Brand attractiveness and (2)brand switching cost of more preferred brand (before joining the coalition loyalty program) will influence more positive effects from (1)program attractiveness and (2)program switching cost of coalition loyalty program (after joining) than less preferred brand. Hypothesis 4. After joining coalition loyalty program, (1)brand attractiveness and (2)brand switching cost of more preferred brand will receive more positive impacts from (1)program attractiveness and (2)program switching cost of coalition loyalty program than less preferred brand. Hypothesis 5. After joining coalition loyalty program, (1)brand attractiveness and (2)brand switching cost of more preferred brand will receive less impacts from (1)brand attractiveness and (2)brand switching cost of different brands (having different preference level), which joined simultaneously, than less preferred brand. Method : In order to validate hypotheses, this study will apply experimental method throughout virtual scenario of coalition loyalty program if consumers have used or available for the actual brands. The experiment is conducted twice to participants. In a first experiment, the study will provide six coalition brands which are already selected based on prior research. The survey asked each brand attractiveness, switching cost, and loyalty after they choose high preference brand and low preference brand. One hour break was provided prior to the second experiment. In a second experiment, virtual coalition loyalty program "SaveBag" was introduced to participants. Participants were informed that "SaveBag" will be new alliance with six coalition brands from the first experiment. Brand attractiveness and switching cost about coalition program were measured and brand attractiveness and switching cost of high preference brand and low preference brand were measured as same method of first experiment. Limitation and future research This study shows limitations of effects of coalition loyalty program by using virtual scenario instead of actual research. Thus, future study should compare and analyze CLP panel data to provide more in-depth information. In addition, this study only proved the effectiveness of coalition loyalty program. However, there are two types of loyalty program, which are Single and Coalition, and success of coalition loyalty program will be dependent on market brand power and prior customer attitude. Therefore, it will be interesting to compare effects of two programs in the future.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.79-94
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• 2013

Recently, the high value added business is steadily growing in the culture and art area. To generated high value from a performance, the satisfaction of audience is necessary. The flow in a critical factor for satisfaction, and it should be induced from audience and measures. To evaluate interest and emotion of audience on contents, producers or investors need a kind of index for the measurement of the flow. But it is neither easy to define the flow quantitatively, nor to collect audience's reaction immediately. The previous studies of the group flow were evaluated by the sum of the average value of each person's reaction. The flow or "good feeling" from each audience was extracted from his face, especially, the change of his (or her) expression and body movement. But it was not easy to handle the large amount of real-time data from each sensor signals. And also it was difficult to set experimental devices, in terms of economic and environmental problems. Because, all participants should have their own personal sensor to check their physical signal. Also each camera should be located in front of their head to catch their looks. Therefore we need more simple system to analyze group flow. This study provides the method for measurement of audiences flow with group synchronization at same time and place. To measure the synchronization, we made real-time processing system using the Differential Image and Group Emotion Analysis (GEA) system. Differential Image was obtained from camera and by the previous frame was subtracted from present frame. So the movement variation on audience's reaction was obtained. And then we developed a program, GEX(Group Emotion Analysis), for flow judgment model. After the measurement of the audience's reaction, the synchronization is divided as Dynamic State Synchronization and Static State Synchronization. The Dynamic State Synchronization accompanies audience's active reaction, while the Static State Synchronization means to movement of audience. The Dynamic State Synchronization can be caused by the audience's surprise action such as scary, creepy or reversal scene. And the Static State Synchronization was triggered by impressed or sad scene. Therefore we showed them several short movies containing various scenes mentioned previously. And these kind of scenes made them sad, clap, and creepy, etc. To check the movement of audience, we defined the critical point, ${\alpha}$and ${\beta}$. Dynamic State Synchronization was meaningful when the movement value was over critical point ${\beta}$, while Static State Synchronization was effective under critical point ${\alpha}$. ${\beta}$ is made by audience' clapping movement of 10 teams in stead of using average number of movement. After checking the reactive movement of audience, the percentage(%) ratio was calculated from the division of "people having reaction" by "total people". Total 37 teams were made in "2012 Seoul DMC Culture Open" and they involved the experiments. First, they followed induction to clap by staff. Second, basic scene for neutralize emotion of audience. Third, flow scene was displayed to audience. Forth, the reversal scene was introduced. And then 24 teams of them were provided with amuse and creepy scenes. And the other 10 teams were exposed with the sad scene. There were clapping and laughing action of audience on the amuse scene with shaking their head or hid with closing eyes. And also the sad or touching scene made them silent. If the results were over about 80%, the group could be judged as the synchronization and the flow were achieved. As a result, the audience showed similar reactions about similar stimulation at same time and place. Once we get an additional normalization and experiment, we can obtain find the flow factor through the synchronization on a much bigger group and this should be useful for planning contents.

• Journal of The Korean Association For Science Education
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• v.37 no.1
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• pp.87-101
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• 2017

The analysis was carried out with meta-analysis on master's and doctoral dissertations, and academic journals that analyzed the effects of STEAM education between 2012 and 2015. From the total number of 75 dissertations and articles analyzed, 183 different effect sizes were calculated. The analysis was done to find out the kinds of differences that would be created according to the effect size of creativity, problem-solving ability, and researcher, target area, student division research design type, and level of schools. The total effect size of creativity scored 0.776, and demonstrated satisfaction in symmetry of funnel plot, with no publication biases. The fail-safe N scored 780, and since the number is smaller than 8,945, the results of this research has credibility. Furthermore, problem-solving ability shows intermediate level of effect size with a score of 0.584. It also showed satisfaction in symmetry with funnel plot, with no publication bias. With the different research methods of the sub-factors of creativity, fluency scored the highest with 0.929, flexibility with 0.881, originality with 0.838, sophistication with 0.653, abstractness with title 0.705, and resistance to termination, 0.527. This study finds its significance in the demonstration of average effect size of STEAM education through meta-analysis. According to research results, the effects of inclusive education could be determined, yet the specific effect cause or learning principles were difficult to find. It was found that the effects of STEAM education do not rise or fall depending on school age, and demonstrated differences in creativity according to the research methods or the researchers.