• Journal of Preventive Medicine and Public Health
• /
• v.30 no.2 s.57
• /
• pp.437-461
• /
• 1997

Because of a significant improvement in the economic situation and development of scientific techniques in Korea during the last 30 years, the life expectancy of the Korean people has lengthened considerably and as a result, the number of the elderly has markedly increased. Such an increase of the number of aged population brought about many social, economic, and medical problems which were never seriously considered before. This study was conducted to assess the trend of medical care utilization and medical expenditure of the elderly. The data of each patient in the study were taken from computer database maintained for administrative purpose by the Korea Medical Insurance Corporation. The study population was 132,670 who were 60 years old or more and registered in Korean Medical Insurance Corporation from 1989 to 1993. The study subjects were predominantly female(56.3%) and 10,000-20,000 Won premium group(50.6%). The following are summaries of findings : The total increase of the number of inpatient cases was 40.5% from 1989 through 1993. The average annual increase was 3.7% in inpatient medical expenditures per case, 4.4% in inpatient medical expenditures per day and 0.08% in length of stay per case from 1989 through 1993. Cataract was the most prevalent disease of 10 leading frequent diseases in all ages from 1989 through 1993. The case mix in 1993 compared to 1989 revealed that cataract and ischemic cerebral disease were increased whereas essential hypertension and pulmonary tuberculosis were decreased . The average annual increase of medical expenditures was 3.8% in general hospitals, 6.3% in hospitals and 2.4% in clinics. From 1989 through 1993, medical expenditures used by high-cost patients accounted for about 14% to 20% of all expenditures for inpatient care, while they represented less than 2.5% of the elderly population. Time series analysis revealed that total medical expenditures and doctor's fee for inpatient will be progressively increased whereas drug expenditures for inpatient will be decreased. And there will be no change in length of stay. Based on the above results, the factors increasing medical cost and utilization should be identified and the method of cost containment for the elderly health care should be developed systematically.

• Journal of Intelligence and Information Systems
• /
• v.26 no.3
• /
• pp.51-69
• /
• 2020

Now, it is a stylized fact that a small number of technology firms such as Apple, Alphabet, Microsoft, Amazon, Facebook and a few others have become larger and dominant players in an industry. Coupled with the rise of these leading firms, we have also observed that a large number of young firms have become an acquisition target in their early IPO stages. This indeed results in a sharp decline in the number of new entries in public exchanges although a series of policy reforms have been promulgated to foster competition through an increase in new entries. Given the observed industry trend in recent decades, a number of studies have reported increased concentration in most developed countries. However, it is less understood as to what caused an increase in industry concentration. In this paper, we uncover the mechanisms by which industries have become concentrated over the last decades by tracing the changes in industry concentration associated with a firm's status change in its early IPO stages. To this end, we put emphasis on the case in which firms are acquired shortly after they went public. Especially, with the transition to digital-based economies, it is imperative for incumbent firms to adapt and keep pace with new ICT and related intelligent systems. For instance, after the acquisition of a young firm equipped with AI-based solutions, an incumbent firm may better respond to a change in customer taste and preference by integrating acquired AI solutions and analytics skills into multiple business processes. Accordingly, it is not unusual for young ICT firms become an attractive acquisition target. To examine the role of M&As involved with young firms in reshaping the level of industry concentration, we identify a firm's status in early post-IPO stages over the sample periods spanning from 1990 to 2016 as follows: i) being delisted, ii) being standalone firms and iii) being acquired. According to our analysis, firms that have conducted IPO since 2000s have been acquired by incumbent firms at a relatively quicker time than those that did IPO in previous generations. We also show a greater acquisition rate for IPO firms in the ICT sector compared with their counterparts in other sectors. Our results based on multinomial logit models suggest that a large number of IPO firms have been acquired in their early post-IPO lives despite their financial soundness. Specifically, we show that IPO firms are likely to be acquired rather than be delisted due to financial distress in early IPO stages when they are more profitable, more mature or less leveraged. For those IPO firms with venture capital backup have also become an acquisition target more frequently. As a larger number of firms are acquired shortly after their IPO, our results show increased concentration. While providing limited evidence on the impact of large incumbent firms in explaining the change in industry concentration, our results show that the large firms' effect on industry concentration are pronounced in the ICT sector. This result possibly captures the current trend that a few tech giants such as Alphabet, Apple and Facebook continue to increase their market share. In addition, compared with the acquisitions of non-ICT firms, the concentration impact of IPO firms in early stages becomes larger when ICT firms are acquired as a target. Our study makes new contributions. To our best knowledge, this is one of a few studies that link a firm's post-IPO status to associated changes in industry concentration. Although some studies have addressed concentration issues, their primary focus was on market power or proprietary software. Contrast to earlier studies, we are able to uncover the mechanism by which industries have become concentrated by placing emphasis on M&As involving young IPO firms. Interestingly, the concentration impact of IPO firm acquisitions are magnified when a large incumbent firms are involved as an acquirer. This leads us to infer the underlying reasons as to why industries have become more concentrated with a favor of large firms in recent decades. Overall, our study sheds new light on the literature by providing a plausible explanation as to why industries have become concentrated.

• Journal of Intelligence and Information Systems
• /
• v.26 no.1
• /
• pp.47-73
• /
• 2020

KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.

• Journal of Intelligence and Information Systems
• /
• v.20 no.2
• /
• pp.109-122
• /
• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• Journal of Bio-Environment Control
• /
• v.27 no.1
• /
• pp.34-39
• /
• 2018

This research was conducted to estimate moisture content in cucurbitaceae seedlings, such as cucumber and watermelon, using hyperspectral imagery. Using a hyperspectral image acquisition system, the reflectance of leaf area of cucumber and watermelon seedlings was calculated after providing water stress. Then, moisture content in each seedling was measured by using a dry oven. Finally, using reflectance and moisture content, the moisture content estimation models were developed by PLSR analysis. After developing the estimation models, performance of the cucumber showed 0.73 of $R^2$, 1.45% of RMSE, and 1.58% of RE. Performance of the watermelon showed 0.66 of $R^2$, 1.06% of RMSE, and 1.14% of RE. The model performed slightly better after removing one sample from cucumber seedlings as outlier and unnecessary. Hence, the performance of new model for cucumber seedlings showed 0.79 of $R^2$, 1.10% of RMSE, and 1.20% of RE. The model performance combined with all samples showed 0.67 of $R^2$, 1.26% of RMSE, and 1.36% of RE. The model of cucumber showed better performance than the model of watermelon. This is because variables of cucumber are consisted of widely distributed variation, and it affected the performance. Further, accuracy and precision of the cucumber model were increased when an insignificant sample was eliminated from the dataset. Finally, it is considered that both models can be significantly used to estimate moisture content, as gradients of trend line are almost same and intersected. It is considered that the accuracy and precision of the estimating models possibly can be improved, if the models are constructed by using variables with widely distributed variation. The improved models will be utilized as the basis for developing low-priced sensors.

• Journal of Intelligence and Information Systems
• /
• v.27 no.1
• /
• pp.129-149
• /
• 2021

Recently, interest in social robots that can socially interact with humans is increasing. Thanks to the development of ICT technology, social robots have become easier to provide personalized services and emotional connection to individuals, and the role of social robots is drawing attention as a means to solve modern social problems and the resulting decline in the quality of individual lives. Along with the interest in social robots, the spread of social robots is also increasing significantly. Many companies are introducing robot products to the market to target various target markets, but so far there is no clear trend leading the market. Accordingly, there are more and more attempts to differentiate robots through the design of social robots. In particular, anthropomorphism has been studied importantly in social robot design, and many approaches have been attempted to anthropomorphize social robots to produce positive effects. However, there is a lack of research that systematically describes the mechanism by which anthropomorphism for social robots is formed. Most of the existing studies have focused on verifying the positive effects of the anthropomorphism of social robots on consumers. In addition, the formation of anthropomorphism of social robots may vary depending on the individual's motivation or temperament, but there are not many studies examining this. A vague understanding of anthropomorphism makes it difficult to derive design optimal points for shaping the anthropomorphism of social robots. The purpose of this study is to verify the mechanism by which the anthropomorphism of social robots is formed. This study confirmed the effect of the human-likeness of social robots(Within-subjects) and the construal level of consumers(Between-subjects) on the formation of anthropomorphism through an experimental study of 3×2 mixed design. Research hypotheses on the mechanism by which anthropomorphism is formed were presented, and the hypotheses were verified by analyzing data from a sample of 206 people. The first hypothesis in this study is that the higher the human-likeness of the robot, the higher the level of anthropomorphism for the robot. Hypothesis 1 was supported by a one-way repeated measures ANOVA and a post hoc test. The second hypothesis in this study is that depending on the construal level of consumers, the effect of human-likeness on the level of anthropomorphism will be different. First, this study predicts that the difference in the level of anthropomorphism as human-likeness increases will be greater under high construal condition than under low construal condition.Second, If the robot has no human-likeness, there will be no difference in the level of anthropomorphism according to the construal level. Thirdly,If the robot has low human-likeness, the low construal level condition will make the robot more anthropomorphic than the high construal level condition. Finally, If the robot has high human-likeness, the high construal levelcondition will make the robot more anthropomorphic than the low construal level condition. We performed two-way repeated measures ANOVA to test these hypotheses, and confirmed that the interaction effect of human-likeness and construal level was significant. Further analysis to specifically confirm interaction effect has also provided results in support of our hypotheses. The analysis shows that the human-likeness of the robot increases the level of anthropomorphism of social robots, and the effect of human-likeness on anthropomorphism varies depending on the construal level of consumers. This study has implications in that it explains the mechanism by which anthropomorphism is formed by considering the human-likeness, which is the design attribute of social robots, and the construal level of consumers, which is the way of thinking of individuals. We expect to use the findings of this study as the basis for design optimization for the formation of anthropomorphism in social robots.

• Journal of Korean Academy of Nursing
• /
• v.4 no.1
• /
• pp.162-178
• /
• 1974

The present study is purported to provide a basic information to be utilized by nurses to care and attend effectively for patients nearing the moment of death. Therefore, the primary purpose of the study has been placed upon grasping an understanding of the trends of death in general. For this purpose: 1. By utilizing the schneidman questionnaire, the trend of death has been categorized by 6 parts and analyzed. 2. A search has been conducted to find out dying patient's needs, nurse's attitudes viewed by the patient, and nurse attitudes to dying patient. The followings are itemized results of analysis: 1. Analysis by the schneidman questionnaire. (1) In general concepts of death. the first sighting of the occurrence of death was experienced upon strangers, grandfather and great grandfather. The death is openly discussed among people of all ages and sex. Ages in which the death is mostly feared were from 12 to well over 70 yews old that are evenly distributed regardless of difference in age. (2) As to the attitudes toward death the occurrence of death to most closely associated person influenced most upon the attitude of their own termination of lives. Among the reading materials, the maximum influence was effected by the Bible. In terms of religion, the thoughts of death were Influenced by religions education in case of the believers of the western religions (36%), and by their own health and physical conditions in case of the believers in the oriental religions (35%). In case of non-believer, their attitude toward death were largely determined through their own thinking meditation (45%). People aged 20 or thereunder revealed that they wished to know the day of their own death to be occurred (58%). However, the older the less thor wanted to know. (3) As to the choosing the time of death, 57% preferred senility, and 30% preferred the time in mediately following the prime period of their lives in general. In terms of religion, 85% of the believer in the oriental religion preferred senility, and 67% in the western religion, 58% in others, Therefore. the desiring of their lives to be terminated in earlier stage, not by the natural senility. sequenced as follows : Others, western religions and oriental religions. (4) Referring to the disposal of the corpse under the assumption that it had already occurred, majority desired the burial system. There has been seen a slight tendency to consider the importance of holding funeral services for the sake of survivors. Concerning the life insurance policy, it showed that the nurse had less belief in it than the patient (5) Upon the subject of life-after-death. religion wise, 72% of western religion believers preferred to have an existence of life-after-death: Among the believers of oriental regions, 35% desired this category, 30% did not mind either way. and 35% did not desire the existence of such a life-after-death. In others, 53% did not mind whether or not such a life existed. (6) In general, serious thoughts were not being attended to the commitment of suicide. 37% emphasized that such an act should be prevented. However, 30% insisted that such commitment should not be bothered, and that society possesses no right to prevented it. More male wished to commit suicide (13%) than females (9%). 2. Nurse's attitudes toward terminal patients and patient's needs. In the instance where the patient realized that their death is imminent, most of them showed desire to discuses mainly on the problems of life. When faced a situation of this nature, it is revealed that 40% of nurses could not furnish appropriate care for them.

• Journal of Global Scholars of Marketing Science
• /
• v.19 no.2
• /
• pp.5-16
• /
• 2009

Against the backdrop of the increasing trend towards economic globalisation, many international firms are indicating that decisions on how to enter foreign markets remains one of the key strategic challenges confronting them. Despite the rich body of literature on the topic, the fact that these challenges have continued to dominate global marketing strategy discourses point to someevident lacunae. Accordingly, this paper considers the variables, categorised in terms of firm contexts (standardisation, market research, competition, structure, competitive advantage) and host country-contexts (economic development, cultural differences, regulation and political risk), which influence the degree of involvement of UK companies in overseas markets. Following hypotheses were drawn from literature review: H1: The greater the level of competition, the higher the degree of involvement in the overseas market. H2: The more centralised the firm's organisation structure, the higher the degree of involvement in the overseas market. H3a: The adoption of a low cost-approach to competitive advantage will lead to a higher degree of involvement. H3b: The adoption of an innovation-approach to competitive advantage will lead to a higher degree of involvement. H3c: The adoption of a market research approach to competitive advantages will lead to a higher degree of involvement. H3d: The adoption of a breadth of strategic target-approach to competitive advantage will lead to a lower degree of involvement. H4: The higher the degree of standardisation of the international marketing mix the higher the degree of involvement. H5: The greater the degree of economic development in the host market, the higher the degree of involvement. H6: The greater the cultural differences between home and host countries, the lower the degree of involvement. H7: The greater the difference in regulations between the home country and the host country, the lower the degree of involvement. H8: The higher the political risk in the host country, the lower the degree of involvement. A questionnaire instrument was constructed using, wherever possible, validated measures of the concepts to serve the aims of this study. Following two sets of mailings, 112 usable completed questionnaires were returned. Correlation analysis and multiple regression analysis were used to analyze data. Statistically, the paper suggests that factors relating to the level of competition, competitive advantages and economic development are strong in influencing foreign market involvements. On the other hand, unexpectedly, cultural factors (especially individualism/collectivism and low and high power distance dimensions) proved to have weak moderating effects. The reason for this, in part, is due to the pervading forces of globalisation and the attendant effect on global marketing. This paper has contributed to the general literature in a way that point to two mainimplications. First, with respect to research on national systems, the study may hold out some important lessons especially for developing nations. Most of these nations are known to be actively seeking to understand what it takes to attract foreign direct investment, expand domestic market and move their economies from the margin to the mainstream global economy. Second, it should be realised that competitive conditions remain in constant flux (even in mature industries and mature economies). This implies that a range of home country factors may be as important as host country factors in explaining firms' strategic moves and the degree of foreign market involvement. Further research can consider the impact of the home country environment on foreign market involvement decisions. Such an investigation will potentially provide further perspectives not only on the influence of national origin but also how home country effects are confounded with industry effects.

• Journal of Intelligence and Information Systems
• /
• v.21 no.2
• /
• pp.151-171
• /
• 2015

This study examined the concepts of the Internet of Things(IoT), the major issue and IoT trend in the domestic and international market. also reviewed the advent of IoT era which caused a 'Paradigm Shift'. This study proposed a solution for the appropriate corresponding strategy in terms of Enterprise. Global competition began in the IoT market. So, Businesses to be competitive and responsive, the government's efforts, as well as the efforts of companies themselves is needed. In particular, in order to cope with the dynamic environment appropriately, faster and more efficient strategy is required. In other words, proposed a management strategy that can respond the IoT competitive era on tipping point through the vision of paradigm shift. We forecasted and proposed the emergence of paradigm shift through a comparative analysis of past management paradigm and IoT management paradigm as follow; I) Knowledge & learning oriented management, II) Technology & innovation oriented management, III) Demand driven management, IV) Global collaboration management. The Knowledge & learning oriented management paradigm is expected to be a new management paradigm due to the development of IT technology development and information processing technology. In addition to the rapid development such as IT infrastructure and processing of data, storage, knowledge sharing and learning has become more important. Currently Hardware-oriented management paradigm will be changed to the software-oriented paradigm. In particular, the software and platform market is a key component of the IoT ecosystem, has been estimated to be led by Technology & innovation oriented management. In 2011, Gartner announced the concept of "Demand-Driven Value Networks(DDVN)", DDVN emphasizes value of the whole of the network. Therefore, Demand driven management paradigm is creating demand for advanced process, not the process corresponding to the demand simply. Global collaboration management paradigm create the value creation through the fusion between technology, between countries, between industries. In particular, cooperation between enterprises that has financial resources and brand power and venture companies with creative ideas and technical will generate positive synergies. Through this, The large enterprises and small companies that can be win-win environment would be built. Cope with the a paradigm shift and to establish a management strategy of Enterprise process, this study utilized the 'RTE cyclone model' which proposed by Gartner. RTE concept consists of three stages, Lead, Operate, Manage. The Lead stage is utilizing capital to strengthen the business competitiveness. This stages has the goal of linking to external stimuli strategy development, also Execute the business strategy of the company for capital and investment activities and environmental changes. Manege stage is to respond appropriately to threats and internalize the goals of the enterprise. Operate stage proceeds to action for increasing the efficiency of the services across the enterprise, also achieve the integration and simplification of the process, with real-time data capture. RTE(Real Time Enterprise) concept has the value for practical use with the management strategy. Appropriately applied in this study, we propose a 'IoT-RTE Cyclone model' which emphasizes the agility of the enterprise. In addition, based on the real-time monitoring, analysis, act through IT and IoT technology. 'IoT-RTE Cyclone model' that could integrate the business processes of the enterprise each sector and support the overall service. therefore the model be used as an effective response strategy for Enterprise. In particular, IoT-RTE Cyclone Model is to respond to external events, waste elements are removed according to the process is repeated. Therefore, it is possible to model the operation of the process more efficient and agile. This IoT-RTE Cyclone Model can be used as an effective response strategy of the enterprise in terms of IoT era of rapidly changing because it supports the overall service of the enterprise. When this model leverages a collaborative system among enterprises it expects breakthrough cost savings through competitiveness, global lead time, minimizing duplication.

• Journal of the Korean earth science society
• /
• v.39 no.5
• /
• pp.419-435
• /
• 2018

The purpose of this study is to understand meteorological and climatological factors that have influence on the garlic product in Seosan and Taean, and to analyze the economic value according to the use of climatical information data for garlic farmers. The climatological characteristics and trends in this area are analyzed using the meteorological data at the Seosan local meteorological agency from 1984 to 2013, the national statistical data for the product of garlic from 1989 to 2013, and the scenario data for climate change (RCP 4.5 and 8.5) for the period from 2001 to 2100. The results are as follows. First, the condition of lower temperature for garlic growth in winter season is satisfied with the mean air temperature. The wind speed are lower and stronger in Seosan and Taean than other garlic area. The suitable condition for the growth of northern type of garlic shows the decreasing trend in the accumulated precipitation in May. However, the area of growing the northern type garlic in the future is likely diminished because mean air temperature, accumulated precipitation, and mean wind speed are strong in the harvest time of garlic. Second, the seedtime of the northern and southern type of garlic using climate change scenarios (RCP 4.5, 8.5) in Seosan and Taean is getting late as time passes. and the harvest time gets faster, which indicates s that the period of garlic cultivation becomes shorter from 50 days to around 90 in the next 100 years. Third, the beginning days of white rot and delia platura of garlic are estimated by applying to the meteorological algorithm using mean air temperature and soil humidity. Especially, the beginning day of white rot garlic is shown to be faster according to the scenarios of RCP 4.5 and RCP 8.5. Fourth, the product of garlic (kg/10a) shows a high correlation with the minimum air temperature of a wintering time, the mean wind speed of a wintering time, the accumulated precipitation of a corpulent time, and the mean relative humidity of corpulent time of garlic. On the other hand, the analysis of garlic product when using the meteorological information data in cultivating garlic in Seosan and Taean reveals that the economic value increases up to 9% in total.