• Journal of Intelligence and Information Systems
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• 제24권2호
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• pp.221-241
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• 2018

Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.

• Asia pacific journal of information systems
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• 제24권4호
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• pp.443-472
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• 2014

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.

• The Journal of Small Business Innovation
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• 제19권2호
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• pp.53-68
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• 2016

Motivation and activities for technological learning, entrepreneurship, innovation, and creativity are driving forces of economic development in Asian countries. In the early stages of technological development, technological learning and entrepreneurship are efficient ways in which to catch up with advanced countries because firms can accumulate skills and knowledge quickly at relatively low risk. In the later stages of technological development, however, innovation and creativity become more important. This study aims to identify a) the factors (learning capabilities) that influence technological learning performance and b) barriers to enhancing innovation capabilities for the creative economy and organizations. The major part of this study is related to learning capabilities in the post-catch-up era. Based on a literature review and observations from Korean experiences, this study proposes a technological learning model composed of various influencing factors on technological learning. Three hypotheses are derived, and data are collected from Korean machine tool manufacturers. Intense interviews with CEOs and R&D directors are conducted using structured questionnaires. Statistical analysis, such as correlation and ANOVA are then carried out. Furthermore, this study addresses how to enhance innovation capabilities to move forward. Innovation enablers and barriers are identified by case studies and policy analysis. The results of the empirical study identify several levels of firms' learning capabilities and activities such as a) stock of technology, b) potential of technical labor, c) explicit technological efforts, d) readiness to learn, e) top management support, f) a formal technological learning system, g) high learning motivation, h) appropriate technology choice, and i) specific goal setting. These learning capabilities determine firms' learning performance, especially in the early stages of development. Furthermore, it is found that the critical factors for successful technological learning vary along the stages of technology development. Throughout the statistical and policy analyses, this study confirms that technological learning can be understood as an intrinsic principle of the technology development process. Firms perform proactive and creative learning in the late stages, while reactive and imitative learning prevails in the early stages. In addition, this study identifies the driving forces or facilitating factors enhancing innovation performance in the post catch-up era. The results of the preliminary case studies and policy analysis show some facilitating factors such as a) the strategic intent of the CEO and corporate culture, b) leadership and change agents, c) design principles and routines, d) ecosystem and collaboration with partners, and e) intensive R&D investment.

• Korean Security Journal
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• 제24호
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• pp.147-170
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• 2010

This study is to present a improvement directions for the protection of industrial key technology. For the purpose of the study, the survey was carried out on the administrative security activity of 68 enterprises including Large companies, small-midium companies and public corporations. survey result on the 10 items of security policy, 10 items of personal management and 7 items of the assets management are as follows; First, stable foundation for the efficient implement of security policy is needed. Carrying a security policy into practice and continuous upgrade should be fulfilled with drawing-up of the policy. Also for the vitalization of security activity, arrangement of security organization and security manager are needed with mutual assistance in the company. Periodic security inspection should be practiced for the improvement of security level and security understanding. Second, the increase of investment for security job is needed for security invigoration. Securing cooperation channel with professional security facility such as National Intelligence Service, Korea internet & security agency, Information security consulting company, security research institute is needed, also security outsourcing could be considered as the method of above investment. Especially small-midium company is very vulnerable compared with Large company and public corporation in security management, so increase of government's budget for security support system is necessary. Third, human resource management is important, because the main cause of leak of confidential information is person. Regular education rate for new employee and staff members is relatively high, but the vitalization of security oath for staff members and the third party who access to key technology is necessary. Also access right to key information should be changed whenever access right changes. Reinforcement of management of resigned person such as security oath, the elimination of access right to key information and the deletion of account. is needed. Forth, the control and management of important asset including patent and design should be tightened. Classification of importance of asset and periodic inspection are necessary with the effects evaluation of leak of asset.

• 대한공업교육학회지
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• 제38권1호
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• pp.1-27
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• 2013

The purpose of this study was to find out the areas and their constitute elements of new apprenticeship through the expert of vocational education to improve the growth potential in the field of industry. Through the three times Delphi research process final composing areas and elements(total 6 areas and 41 sub-elements) of new apprenticeship were extracted. Followings are specific study results of 41 sub-elements for the 6 areas. In area A(Technology Skill aspect) total nine sub-elements were deducted as follows. Technology skill's field appling ability, new technology skill's acquisition, quality assurance ability, research development ability, material management using ability, problem solving ability, core technology skill understanding ability, idea's imagery expressing ability, creative design ability. In area B(Institutional aspect) total five sub-elements were deducted as follows. Flexible human material support, precise division of works, objective result assessment, institutionalization of responsibilities and liabilities between teacher and student, institutionalization of duty invention reward. In area C(Affective aspect) total eight sub-elements were deducted as follows. Manners and cooperation between teacher & student and peer, values for job, basic attitude for technology, job ethic sense, respect of other organization, active action to organization change, attitude of technology successor, service mind. In area D(Self-improvement aspect) total nine sub-elements were deducted as follows. Self evaluation and reflection, cultivate of organization understanding, career planning and developing ability, sound philosophy of life, communication ability, decision making ability, prepare of individual competence enhance system, self-control ability improvement, reaction of unexpected situation. In area E(Knowledge aspect) total four sub-elements were deducted as follows. Basic knowledge of relevant area, knowledge of new technology & preceding technology, fusion and relocation of knowledge, practical knowledge. In area F(Environmental aspect) total six sub-elements were deducted as follows. Awareness of business environment, understanding of education and practice environment, understanding of apprenticeship's business demand, connectivity of region community, adapt ability of labor market's change, awareness of society environment change.

• Journal of Intelligence and Information Systems
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• 제18권4호
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• pp.1-17
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• 2012

Personalized smart devices such as smartphones and smart pads are widely used. Unlike traditional feature phones, theses smart devices allow users to choose a variety of functions, which support not only daily experiences but also business operations. Actually, there exist a huge number of applications accessible by smart device users in online and mobile application markets. Users can choose apps that fit their own tastes and needs, which is impossible for conventional phone users. With the increase in app demand, the tastes and needs of app users are becoming more diverse. To meet these requirements, numerous apps with diverse functions are being released on the market, which leads to fierce competition. Unlike offline markets, online markets have a limitation in that purchasing decisions should be made without experiencing the items. Therefore, online customers rely more on item-related information that can be seen on the item page in which online markets commonly provide details about each item. Customers can feel confident about the quality of an item through the online information and decide whether to purchase it. The same is true of online app markets. To win the sales competition against other apps that perform similar functions, app developers need to focus on writing app descriptions to attract the attention of customers. If we can measure the effect of app descriptions on sales without regard to the app's price and quality, app descriptions that facilitate the sale of apps can be identified. This study intends to provide such a quantitative result for app developers who want to promote the sales of their apps. For this purpose, we collected app details including the descriptions written in Korean from one of the largest app markets in Korea, and then extracted keywords from the descriptions. Next, the impact of the keywords on sales performance was measured through our econometric model. Through this analysis, we were able to analyze the impact of each keyword itself, apart from that of the design or quality. The keywords, comprised of the attribute and evaluation of each app, are extracted by a morpheme analyzer. Our model with the keywords as its input variables was established to analyze their impact on sales performance. A regression analysis was conducted for each category in which apps are included. This analysis was required because we found the keywords, which are emphasized in app descriptions, different category-by-category. The analysis conducted not only for free apps but also for paid apps showed which keywords have more impact on sales performance for each type of app. In the analysis of paid apps in the education category, keywords such as 'search+easy' and 'words+abundant' showed higher effectiveness. In the same category, free apps whose keywords emphasize the quality of apps showed higher sales performance. One interesting fact is that keywords describing not only the app but also the need for the app have asignificant impact. Language learning apps, regardless of whether they are sold free or paid, showed higher sales performance by including the keywords 'foreign language study+important'. This result shows that motivation for the purchase affected sales. While item reviews are widely researched in online markets, item descriptions are not very actively studied. In the case of the mobile app markets, newly introduced apps may not have many item reviews because of the low quantity sold. In such cases, item descriptions can be regarded more important when customers make a decision about purchasing items. This study is the first trial to quantitatively analyze the relationship between an item description and its impact on sales performance. The results show that our research framework successfully provides a list of the most effective sales key terms with the estimates of their effectiveness. Although this study is performed for a specified type of item (i.e., mobile apps), our model can be applied to almost all of the items traded in online markets.

• Cartoon and Animation Studies
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• 통권47호
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• pp.31-52
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• 2017

NCS education was created to realize a society in which skills and abilities are respected, such as transcending specifications, establishing recruitment systems, and developing and disseminating national incompetence standards. At the university level, special lectures and job training are being strengthened to raise industrial experts. Especially, in the field of animation, new technologies are rapidly emerging and demanding convergent talents with various fields. In order to meet these social demands, there is a limit to the existing one-class teaching method. In order to solve this problem, it is necessary to participate in a variety of specialized teachers. In other words, rather than solving problems of students' job training and job creation, It is aimed to solve jointly, Team teaching was suggested as a method for this. The expected effects that can be obtained through this are as follows. First, the field of animation is becoming more diverse and complex. The ability to use NCS job-related skills pools can be matched with professors from other departments to enable a wider range of professional instruction. Second, it is possible to use partial professorships in other departments by actively utilizing professors in the university. This leads to the strengthening of the capacity of teachers in universities. Third, it is possible to build a broader and more integrated educational system through cooperative teaching of professors in other departments. Finally, the advantages of special lectures and mentor support of college professors' pools are broader than those of field specialists. A variety of guidance for students can be made with responsible professors. In other words, time and space constraints can be avoided because the mentor is easily met and guided by the university.

• Journal of Korea Port Economic Association
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• 제36권2호
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• pp.63-86
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• 2020

The tax lease scheme for ships is an advanced ship financing tool that generates tax benefits through accelerated depreciation of capital allowances and transferring them to the ship operator (leasee) via reductions in rental payments. The scheme was introduced by Japan in 1978 and by France in 1998 to support their shipping and shipbuilding industries. The size of tax benefits varies by country depending on the depreciation rate for ships, corporate tax rate, and the tax system on profits from the sale of ship. This study uses a virtual model of the Korean tax lease scheme for ships based on the French tax lease scheme. The size of tax benefits is calculated and compared to those in the French and Japanese tax lease schemes. According to the analysis, the size of the tax benefit was approximately 19% for France, 14% for Japan, and 12% for Korea. This is differentiated by the country's depreciation rate and corporate tax rate, which have the greatest impact on the size of tax benefits. For the Korean virtual model, if the tax benefits are distributed by the operator and the investor at the rate of 75:25, the operator is expected to enjoy tax benefits equivalent to about 9% of the ship price and the investor to enjoy 3%. Despite limited information and data regarding the tax lease scheme for ships, this study was the first attempt in Korea to design a virtual model of the Korean tax lease scheme based on some predictable assumptions. Therefore, a group of shipping, financing, and legal experts will follow up on more professional and practical reviews of the model in the near future. Hence, this study will serve as a small contribution to the early introduction of the Korean tax lease scheme for ships.

• Journal of Korean Academy of Nursing
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• 제23권3호
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• pp.417-430
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• 1993

이 연구는 환경적 요소(간호사의 자율성, 조직의 표준화)와 개인의 특성(통제위, 나이, 경험. 간호역할개념, 도덕성), 직무 스트레스, 윤리적 의사결정 사이의 관계를 이론적 틀을 구성하여 테스트함으로써 그 인과관계를 탐구하였다. 본 연구를 위해 개발된 모형은 1) Katz와 Kahn의 조직에 대한 개방체계 이론(open systems theory of organization) ; 2) Kahn. Wolfe, Quinn, Snoek의 스트레스 이론 (theory of stress) : 3) Kohlberg의 도덕발달 이론(theory of moral develop-ment): 그리고 4) 여러 문헌고찰을 기초로 하였다. 본 연구의 모형은 2가지의 주요 종속변수(직무 스트레스, 윤리적 간호행위), 2가지 매개변수(간호 역할개념, 도덕성 발달정도) 그리고 여러 독립변수들(조직의 표준화, 자율성, 통제위, 교육, 나이, 경험 등)로 구성되었다. 간단히 말해, 간호사의 스트레스와 윤리적 간호행위 를 개인 자신과 환경이라는 두 요소의 결과로 간주한 것이다. 미국(2개주)의 여러 건강관리기관에 근무하는 224명의 정규 간호사를 대상으로 하였고. 가설 검증을 위하여 1) 변수간의 인과관계를 조사하기 위한 Linear Structural Relationships(LISREL)기법과 2) 나이, 경험, 교육이 변수간의 관계에 미치는 중간역할을 알아보기 위해 상관분석을 이용하였다. LISREL결과를 보면 제시된 모델이 각 내재 변수에 상당한 설명력을 가지면서 자료에 잘 맞는 것으로 나타났다. 이 연구에서 가장 뚜렷한 점으로 나타난 것은 개인의 특성보다 환경적 요소로서의 자율성이 직무스트레스와 윤리적 의사결정을 예견하는데 훨씬 중요한 변수로 부각되었다는 점이다. 또한 간호사의 전문적 역할개념과 봉사적 역할개념이 간호사의 윤리적 의사결정을 예견하는 가장 중요한 요소로 나타났다. 중간영향(moderation effect)을 보면, 젊고 경험이 적은 간호사일수록 나이가 많고 경험있는 간호사보다 환경적 요소(자율성)에 더 큰 영향을 받는다는 것을 암시하고 있다. 또한 4년제 대학 이상을 졸업한 간호사의 윤리 적 간호행 위 는 2, 3년제 를 졸업 한 간호사 보다 환경적 요소에 의해 덜 영향을 받는 것으로 나타났다. 한편 자율성의 부족은 2, 3년제 졸업 간호사보다 4년제 졸업 간호사에게 더 심한 스트레스가 되고 있음을 시사하였다. 이 연구의 결과로부터 적어도 다음과 같은 두 가지 실제적인 제언을 도출할 수 있다. 첫째, 이 연구는 환경적요소로서의 자율성이 다른 어떤 개인적인 요소보다 직무 스트레스를 예견하는 데 중요한 요소라는 것을 제시하였다. 이것은 간호행정가들에게, 간호사의 직무 스트레스를 감소시키기 위해선 “자율성”이 아주 중요히 다루어져야 한다는 것을 의미한다. 만일 간호사들의 직무스트레스가 그 개인의 복지에 큰 해가 되고 환자를 간호하는 데 직접적으로 관계된다면, 간호행정가는 그 조직의 직무체계를 다시 평가해서 일에 대한 새로운 설계가 필요한지를 파악해야 한다. 또한 이 연구는 직무를 다시 설계할 경우, 누구에게 먼저 촛점을 두고 시작해야 하는지를 밝혀주고 있다. 즉, 젊고 경험이 미숙한 간호사들에게 촛점을 두고 시작해야 하며, 작업환경의 가장 중요한 차원중의 하나인 사회적 지원(social support)을 조심스럽게 고려해 보아야 한다. 둘째, 간호사의 윤리적 간호행위를 높히기 위해 전문적 역할개념과 봉사적 역할개념이 재강조될 필요가 있다. 이 두 역할개념 들을 교육을 통하여 효과적으로 가르칠 필요가 있다고 본다. 이 두 개념들이 간호사의 바람직한 간호행 위에 영향을 미치는 가장 중요한 요소로 나타났기 때문이다. 또한, 본 연구결과에 따르면, 경험이 많을수록 일에 싫증을 느껴 바람직한 윤리적 간호행위가 감소되는 경향이 있었다. 따라서, 건강관리체제 (health care system) 안에서의 간호사의 역할이-전문직으로서의, 그리고 환자를 위한 옹호자로서의-학교와 임상에서 효과적으로 교육되어져야 한다고 본다. 간호사들의 역할에 대한 계속적인 교육이 학생은 물론 임상 간호사들에게도 실시되어져야 할 것이다. 미래연구의 방향을 제시해 보면 첫째로 연구의 일반화를 높히기 위해 더 많은 대상자를 포함시켜야 한다. 이는 여러 종류의 표본을 반드시 한번에 전부 포함시켜야 한다는 것을 의미하는 것이 아니고, 특정한 여러 표본들을 연속적으로 연구함으로서 이 목표를 성취할 수 있다고 생각한다. 둘째는 여러 construct들(윤리적 간호행위, 직무 스트레스, 간호 역할개념 등)에 대한 적절한 측정도구를 개발해야 한다. 측정도구를 개발하기 위해서는 풍부하고 세세한 통찰력을 제공하는 질적인 정보를 얻는 것이 선행되어야 한다. 셋째, 윤리적 간호행위와 직무 스트레스에 관한 연구를 증진시키기 위해 실험설계 및 종단적 연구(expel-imental, longitudinal design)가 시도될 필요가 있다. 마지막으로, 윤리적 간호행위와 직무 스트레스를 예견할 수 있는 이론적 탐구(theoretical exploration), 즉 이론정립을 위하여, 환경적 요소와 개인의 특성에 대한 자세한 정보를 제공해 줄 수 있는 질적 연구들이 요구된다.

• Journal of Home Health Care Nursing
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• 제8권1호
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• pp.5-24
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• 2001

The purpose of this study was to develop a parenting intervention program and determine the efficacy of the program with low-birth weight infants and their mothers. Nine dyads for the experimental group and twelve dyads for the control group discharged from the Neonatal Intensive Care Unit of a University Hospital in Seoul were recruited for the study. For the intervention group, programmed education and support which focused on the maternal sensitivity of the infant's behavior. rearing environment. motherinfant interaction and infant care were given to each subject. Individual counseling and home visits were provided at discharge, one week after discharge. and one and three months of corrected age in every infant. Structured questionaires were administered and feeding interactions were videotaped and coded by a blinded certified observer. A Quasi-experimental design was conducted for this study. Postpartum depression, maternal self esteem. infant care burden, HOME. mother-infant interaction, and infant development were measured. Results were in favor of the intervention versus the control group. On the Beck depression inventory, intervention mothers showed decreasing trends in depressive symptom vs control mothers although, there were statistically no significant differences between the two groups at each time. The mean score of experimental group was 11.55(mild depression state) at discharge and became 8,6(normal state) at 1 month of corrected age. On the other hand, the mean score of the control group was 13.92(mild depression state) at discharge and became 14.0. Maternal self esteem in both groups improved over time. Infant care burden in both groups was also shown to increase over time. There was a significant difference between the two groups in HOME(p=.0340) at 3 months of corrected age. HOME scores of the experimental group and the control's were 31.10 and 25.58, respectively. Mothers' emotional and language responses were significantly high in the intervention group compared with the control group(p=.0155). Intervention group (53.33) showed a significantly high quality of motherinfant interaction compared with the in control group (42.80)(p =.0340). Intervention group mothers appeared have a better quality of mother-infant interaction behaviors. On the other hand, there was no statistical difference in the infant part between groups. Intervention group infants had higher trends in a general developmental quotient: although, there was no statistical difference between groups. The general developmental quotient of intervention infants was 102.56 and control's was 91.28. However, the developmental quotient of the domain of 'individuality-sociality' was higher in the intervention group infants compared with the control's(p=.0155). The concerns identified by parents revealed two domains of an infants' health management -knowledge and skills in caregiving of lowbirthweight-infants, characteristics of lowbirthweight infants, identifying a developmental milestone, coping with emergency situations and relaxation strategies of mothers from the infant care burden. Interview data with the mothers of low-birth weight infants can be used to develop intervention program contents. Limited intervention time and frequency due to time and cost limitations of this study should be modified. The intervention should be continuously implemented when low-birth weight infants become three years old. An NNNS demonstration appeared to be a very effective intervention for the mothers to improve the quality of mother-infant interactions. Therefore intervening in the mothers of low-birth weight infants as early after delivery as possible is desirable. This study has shown that home visit interventions are worthwhile for mothers only beyond the approach as an essential factor in ability of facilitating a growth fostering environment. In conclusion. the intervention program of this study was very effective in enhancing the parenting for the mothers of low-birth weight infants, resulting in health promotion of low-birth weight infants. The home-visit outreach intervention program of this study will contribute to the health delivery system in this country where there is a lack of continuous follow-up programs for low-birth weight infants after discharge from NICU, if it is activated as part of the home visit programs in community health systems.