• Journal of Agricultural Extension & Community Development
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• v.20 no.3
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• pp.777-822
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• 2013

This study attempts to elicit the organizational strategy and operational elements of community-based agricultural management bodies as new main farm management. We analyzed the newest discussion trend, cooperated community management, between Republic of Korea and Japan based on theory of organizing regional agriculture, and also researched on the organization management and business management about cooperated management of community. In this study, the main conclusion of the organizational strategy and operational elements of community-based agricultural management bodies are as following. i) The community-based agricultural management bodies is the cooperation managed individual agriculture resources as joint stock for purposing compound goal, an expansion agricultural income, maintenance farm productivity and rural societies. ii) The domain of cooperative management focus on secondary and tertiary industry like food process, farm produce distribution, rural experience more than farm produce production. The study suggest business promotion system of village unit farmers groups, element of organization management as executive decision organization, business management, operating factor for each steps and management element of cooperation farm working. iii) The policy direction for invigoration community-based agricultural management bodies is to make facilitation for each steps instead of standardized support.

• Journal of agricultural medicine and community health
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• v.34 no.2
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• pp.155-167
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• 2009

Objectives: The purpose of this study was to investigate healthy city project related characteristics to members of the Korea Healthy Cities Partnership(KHCP). Methods: This study analyzed general characteristics of healthy city, characteristics of healthy city(political support, collaboration & citizen participation, healthy city project, infrastructure development, capacity building), self-evaluation of healthy city and etc by self-questionnaires from February to December, 2007, which were distributed to government workers who were in charged in health city project of 23 membership cities of KHCP. Results: The number of urban city was 11(47.8%) and that of rural municipality was 12(52.5%). Public health center was almost in charge of healthy city project(73.9%). As for the characteristics of healthy city, healthy city municipal budget(91.3%), city health profile(91.3%), technical support of cooperative university(82.6%), healthy city regulation(78.3%), citizen participation(78.3%), committee(73.9%), setting approach(69.9%) and healthy city network(69.6%) were good. But intersectoral collaboration(34.8%), long-term healthy city plan(39.1%), administrative policy or campaign promise(43.5%), programs to the vulnerable population(47.8%), department in charge(47.8%) and seminar(47.8%) were not good. Especially, characteristics of healthy city according to the existence of department in charge were significantly different in intersectoral collaboration, citizen participation, setting approach and healthy city network. Conclusions: In spite of rapid expansion in healthy cities, there were great difficulty in political support, collaboration, department in charge and programs of health equity. So we need to go a long way to achieve the vision of healthy cites by its principles and characteristics.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.6
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• pp.17-29
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• 2021

Recently, as social distancing have been raised due to the re-spread of COVID-19, the number of serial entrepreneurs who are closing their business is rapidly increasing. Learning from failure is a source of success, but business failure can result in psychological and economic losses and negative emotions of the serial entrepreneur. At this point, it is very important to find a way to recover the negative emotions caused by business failures of serial entrepreneurs. Recently, a strategic model has emerged to deal with the negative emotions of grief caused by business failures of serial entrepreneurs. This study identified the recovery factors from the grief of business failures of serial entrepreneurs and analyzed Shepherd's(2003) three areas: loss orientation, restoration orientation, and dual process. To this end, individual in-depth interviews were conducted with 12 small business serial entrepreneurs who challenged re-startup to identify the attributes of recovery factors that were not identified with quantitative data. As a result of the study, first, recovery factors were investigated in three areas: individual orientation, family orientation, and network orientation. It was found to help improve recovery in nine categories: self-esteem, persistence, personal competence, hobbies, self-confidence, family support, networks, religion, and social support. Second, recovery obstacle factors were investigated in three areas: psychological, economic, and environmental factors. Nine categories including family, health, social network, business partner, competitor, partner, fund, external environment, and government policy were found to persist negative emotions. Third, the emotional processing process for grief was investigated in three areas: loss orientation, restoration orientation, and dual process. Ten categories such as family, partner support, social member support, government support, hobbies, networks, change of business field, moving, third-party perspective, and meditation were confirmed to enhance rapid recovery in the emotional processing process for grief. The implications of this study are as follows. The process of recovering from the grief caused by business failures of serial entrepreneurs was attempted by a qualitative study. By extending the theory of Shepherd(2003), This study can be applied to help with recovery research. In addition, conceptual models and propositions for future empirical research were presented, which can be discussed in carious academic ways.

• Korea Science and Art Forum
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• v.20
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• pp.455-464
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• 2015

As the recognition toward the Korean design education development to nurture creative talents for the future society has been expanded recently, various supports and promoting strategies are being suggested. This study suggests the orientalism-based new design education platform in design education field to nurture creative talents. To have the competitiveness of creative talent nurturing, the system and education programs to rear creative talents are required. The purpose of this study is to suggest the new platform for the change of direction in design education and search for the methods in detail. The research process can be described as following: First, this study stated about the research background and its boundary. Based on the literature review and the condition of the crisis of Korean design education (Korean Industrial Statistic Investigation), it described the current condition and the characteristics. Second, this study stated about the education which will be disappeared in the information society, the change of direction in design education, and the new platform. In the current study, the change toward the strategies that give priority to the growth strategies on the knowledge-based industry was stated. Third, this study stated about that the future design education should be centered on the orientalism-based creativity in the trend changing to the six conditions for the future talents and the beliefs and values toward Asia, and what methods should be sought to achieve this trend. It suggested focusing on the aim for the direction for College education and its program curriculums as the solutions in detail. Fourth, based on the contents stated earlier in this study, it stated synthetically the direction of practice through the network of the design cluster and derived the implications. In conclusion, based on the recent orientalism-based mind, this study suggested the ways to find the identity of Korean design education itself and have the competitiveness in design education programs. The ways to secure them is to come from the integrated system innovation of the network. By actively applying the design clusters, colleges and universities, designers, studios, government policy organizations, design institutes, corporates, media, and fairs, this study suggests the sustainable education system and the practical methods.

• Korea Trade Review
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• v.48 no.3
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• pp.217-242
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• 2023

This study aims to analyze the factors influencing the logistics demand of inland ports along the Yangtze River and predict future port logistics demand based on these factors. The logistics demand prediction using system dynamics techniques was conducted for a total of six ports, including Chongqing and Yibin ports in the upper reaches, Jingzhou and Wuhan ports in the middle reaches, and Nanjing and Suzhou ports in the lower reaches of the Yangtze River. The logistics demand for all ports showed an increasing trend in the mid-term prediction until 2026. The logistics demand of Chongqing port was mainly influenced by the scale of the hinterland economy, while Yibin port appeared to heavily rely on the level of port automation. In the case of the upper and middle reach ports, logistics demand increased as the energy consumption of the hinterland increased and the air pollution situation worsened. The logistics demand of the middle reach ports was greatly influenced by the hinterland infrastructure, while the lower reach ports were sensitive to changes in the urban construction area. According to the sensitivity analysis, the logistics demand of ports relying on large cities was relatively stable against the increase and decrease of influential factors, while ports with smaller hinterland city scales reacted sensitively to changes in influential factors. Therefore, a strategy should be established to strengthen policy support for Chongqing port as the core port of the upper Yangtze River and have surrounding ports play a supporting role for Chongqing port. The upper reach ports need to play a supporting role for Chongqing port and consider measures to enhance connections with middle and lower reach ports and promote the port industry. The development strategy for inland ports along the Yangtze River suggests the establishment of direct routes and expansion of the transportation network for South Korean ports and stakeholders. It can suggest expanding the hinterland network and building an efficient transportation system linked with the logistics hub. Through cooperation, logistics efficiency can be enhanced in both regions, which will contribute to strengthening the international position and competitiveness of each port.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.185-196
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• 2023

This paper investigates the effects of entrepreneurs' cognitive biases on business opportunity evaluation, given their strong entrepreneurial spirit, which is characterized by innovation, proactivity, and risk-taking. When making decisions related to business activities, entrepreneurs typically make rational judgments based on their knowledge, experience, and the advice of external experts. However, in situations of extreme stress or when quick decisions are required, they often rely on heuristics based on their cognitive biases. In particular, we often see cases where entrepreneurs fail because they make decisions based on heuristics in the process of evaluating and selecting new business opportunities that are planned to guarantee the growth and sustainability of their companies. This study was conducted in response to the need for research to clarify the effects of entrepreneurs' cognitive biases on new business opportunity evaluation, given that the cognitive biases of entrepreneurs, which are formed by repeated successful experiences, can sometimes lead to business failure. Although there have been many studies on the effects of cognitive biases on entrepreneurship and opportunity evaluation among university students and general people who aspire to start a business, there have been few studies that have clarified the relationship between cognitive biases and social networks among entrepreneurs. In contrast to previous studies, this study conducted empirical surveys of entrepreneurs only, and also conducted research on the relationship with social networks. For the study, a survey was conducted using a parallel survey method using online mobile surveys and self-report questionnaires from 150 entrepreneurs of small and medium-sized enterprises. The results of the study showed that 'overconfidence' and 'illusion of control', among the independent variables of entrepreneurs' cognitive biases, had a statistically significant positive(+) effect on business opportunity evaluation. In addition, it was confirmed that the moderating variable, social network, moderates the effect of overconfidence on business opportunity evaluation. This study showed that entrepreneurs' cognitive biases play a role in the process of evaluating and selecting new business opportunities, and that social networks play a role in moderating the structural relationship between entrepreneurs' cognitive biases and business opportunity evaluation. This study is expected to be of great help not only to entrepreneurs, but also to entrepreneur education and policy making, by showing how entrepreneurs can use cognitive biases in a positive way and the influence of social networks.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.83-102
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• 2021

The government recently announced various policies for developing big-data and artificial intelligence fields to provide a great opportunity to the public with respect to disclosure of high-quality data within public institutions. KSURE(Korea Trade Insurance Corporation) is a major public institution for financial policy in Korea, and thus the company is strongly committed to backing export companies with various systems. Nevertheless, there are still fewer cases of realized business model based on big-data analyses. In this situation, this paper aims to develop a new business model which can be applied to an ex-ante prediction for the likelihood of the insurance accident of credit guarantee. We utilize internal data from KSURE which supports export companies in Korea and apply machine learning models. Then, we conduct performance comparison among the predictive models including Logistic Regression, Random Forest, XGBoost, LightGBM, and DNN(Deep Neural Network). For decades, many researchers have tried to find better models which can help to predict bankruptcy since the ex-ante prediction is crucial for corporate managers, investors, creditors, and other stakeholders. The development of the prediction for financial distress or bankruptcy was originated from Smith(1930), Fitzpatrick(1932), or Merwin(1942). One of the most famous models is the Altman's Z-score model(Altman, 1968) which was based on the multiple discriminant analysis. This model is widely used in both research and practice by this time. The author suggests the score model that utilizes five key financial ratios to predict the probability of bankruptcy in the next two years. Ohlson(1980) introduces logit model to complement some limitations of previous models. Furthermore, Elmer and Borowski(1988) develop and examine a rule-based, automated system which conducts the financial analysis of savings and loans. Since the 1980s, researchers in Korea have started to examine analyses on the prediction of financial distress or bankruptcy. Kim(1987) analyzes financial ratios and develops the prediction model. Also, Han et al.(1995, 1996, 1997, 2003, 2005, 2006) construct the prediction model using various techniques including artificial neural network. Yang(1996) introduces multiple discriminant analysis and logit model. Besides, Kim and Kim(2001) utilize artificial neural network techniques for ex-ante prediction of insolvent enterprises. After that, many scholars have been trying to predict financial distress or bankruptcy more precisely based on diverse models such as Random Forest or SVM. One major distinction of our research from the previous research is that we focus on examining the predicted probability of default for each sample case, not only on investigating the classification accuracy of each model for the entire sample. Most predictive models in this paper show that the level of the accuracy of classification is about 70% based on the entire sample. To be specific, LightGBM model shows the highest accuracy of 71.1% and Logit model indicates the lowest accuracy of 69%. However, we confirm that there are open to multiple interpretations. In the context of the business, we have to put more emphasis on efforts to minimize type 2 error which causes more harmful operating losses for the guaranty company. Thus, we also compare the classification accuracy by splitting predicted probability of the default into ten equal intervals. When we examine the classification accuracy for each interval, Logit model has the highest accuracy of 100% for 0~10% of the predicted probability of the default, however, Logit model has a relatively lower accuracy of 61.5% for 90~100% of the predicted probability of the default. On the other hand, Random Forest, XGBoost, LightGBM, and DNN indicate more desirable results since they indicate a higher level of accuracy for both 0~10% and 90~100% of the predicted probability of the default but have a lower level of accuracy around 50% of the predicted probability of the default. When it comes to the distribution of samples for each predicted probability of the default, both LightGBM and XGBoost models have a relatively large number of samples for both 0~10% and 90~100% of the predicted probability of the default. Although Random Forest model has an advantage with regard to the perspective of classification accuracy with small number of cases, LightGBM or XGBoost could become a more desirable model since they classify large number of cases into the two extreme intervals of the predicted probability of the default, even allowing for their relatively low classification accuracy. Considering the importance of type 2 error and total prediction accuracy, XGBoost and DNN show superior performance. Next, Random Forest and LightGBM show good results, but logistic regression shows the worst performance. However, each predictive model has a comparative advantage in terms of various evaluation standards. For instance, Random Forest model shows almost 100% accuracy for samples which are expected to have a high level of the probability of default. Collectively, we can construct more comprehensive ensemble models which contain multiple classification machine learning models and conduct majority voting for maximizing its overall performance.

• The Korean Journal of Air & Space Law and Policy
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• v.30 no.2
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• pp.469-497
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• 2015

In 2009 Iridium 33, a satellite owned by the American Iridium Communications Inc. and Kosmos-2251, a satellite owned by the Russian Space Forces, collided at a speed of 42,120 km/h and an altitude of 789 kilometers above the Taymyr Peninsula in Siberia. NASA estimated that the satellite collision had created approximately 1,000 pieces of debris larger than 10 centimeters, in addition to many smaller ones. By July 2011, the U.S. Space Surveillance Network(SSN) had catalogued over 2,000 large debris fragments. On January 11, 2007 China conducted a test on its anti-satellite missile. A Chinese weather satellite, the FY-1C polar orbit satellite, was destroyed by the missile that was launched using a multistage solid-fuel. The test was unprecedented for having created a record amount of debris. At least 2,317 pieces of trackable size (i.e. of golf ball size or larger) and an estimated 150,000 particles were generated as a result. As far as the Space Treaties such as 1967 Outer Space Treaty, 1968 Rescue Agreement, 1972 Liability Convention, 1975 Registration Convention and 1979 Moon Agreement are concerned, few provisions addressing the space environment and debris in space can be found. In the early years of space exploration dating back to the late 1950s, the focus of international law was on the establishment of a basic set of rules on the activities undertaken by various states in outer space.. Consequently environmental issues, including those of space debris, did not receive the priority they deserve when international space law was originally drafted. As shown in the case of the 1978 "Cosmos 954 Incident" between Canada and USSR, the two parties settled it by the memorandum between two nations not by the Space Treaties to which they are parties. In 1994 the 66th conference of International Law Association(ILA) adopted "International Instrument on the Protection of the Environment from Damage Caused by Space Debris". The Inter-Agency Space Debris Coordination Committee(IADC) issued some guidelines for the space debris which were the basis of "the UN Space Debris Mitigation Guidelines" which had been approved by the Committee on the Peaceful Uses of Outer Space(COPUOS) in its 527th meeting. On December 21 2007 this guideline was approved by UNGA Resolution 62/217. The EU has proposed an "International Code of Conduct for Outer Space Activities" as a transparency and confidence-building measure. It was only in 2010 that the Scientific and Technical Subcommittee began considering as an agenda item the long-term sustainability of outer space. A Working Group on the Long-term Sustainability of Outer Space Activities was established, the objectives of which include identifying areas of concern for the long-term sustainability of outer space activities, proposing measures that could enhance sustainability, and producing voluntary guidelines to reduce risks to long-term sustainability. By this effort "Guidelines on the Long-term Sustainability of Outer Space Activities" are being under consideration. In the case of "Declaration of Legal Principles Governing the Activities of States in the Exp1oration and Use of Outer Space" adopted by UNGA Resolution 1962(XVIII), December 13 1963, the 9 principles proclaimed in that Declaration, although all of them incorporated in the Space Treaties, could be regarded as customary international law binding all states considering the time and opinio juris by the responses of the world. Although the soft law such as resolutions, guidelines are not binding law, there are some provisions which have a fundamentally norm-creating character and customary international law. In November 12 1974 UN General Assembly recalled through a Resolution 3232(XXIX) "Review of the role of International Court of Justice" that the development of international law may be reflected, inter alia, by the declarations and resolutions of the General Assembly which may to that extend be taken into consideration by the judgements of the International Court of Justice. We are expecting COPUOS which gave birth 5 Space Treaties that it could give us binding space debris mitigation measures to be implemented based on space debris mitigation soft law in the near future.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.79-96
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• 2012

As the pace of competition dramatically accelerates and the complexity of change grows, a variety of research have been conducted to improve firms' short-term performance and to enhance firms' long-term survival. In particular, researchers and practitioners have paid their attention to identify promising technologies that lead competitive advantage to a firm. Discovery of promising technology depends on how a firm evaluates the value of technologies, thus many evaluating methods have been proposed. Experts' opinion based approaches have been widely accepted to predict the value of technologies. Whereas this approach provides in-depth analysis and ensures validity of analysis results, it is usually cost-and time-ineffective and is limited to qualitative evaluation. Considerable studies attempt to forecast the value of technology by using patent information to overcome the limitation of experts' opinion based approach. Patent based technology evaluation has served as a valuable assessment approach of the technological forecasting because it contains a full and practical description of technology with uniform structure. Furthermore, it provides information that is not divulged in any other sources. Although patent information based approach has contributed to our understanding of prediction of promising technologies, it has some limitations because prediction has been made based on the past patent information, and the interpretations of patent analyses are not consistent. In order to fill this gap, this study proposes a technology forecasting methodology by integrating patent information approach and artificial intelligence method. The methodology consists of three modules : evaluation of technologies promising, implementation of technologies value prediction model, and recommendation of promising technologies. In the first module, technologies promising is evaluated from three different and complementary dimensions; impact, fusion, and diffusion perspectives. The impact of technologies refers to their influence on future technologies development and improvement, and is also clearly associated with their monetary value. The fusion of technologies denotes the extent to which a technology fuses different technologies, and represents the breadth of search underlying the technology. The fusion of technologies can be calculated based on technology or patent, thus this study measures two types of fusion index; fusion index per technology and fusion index per patent. Finally, the diffusion of technologies denotes their degree of applicability across scientific and technological fields. In the same vein, diffusion index per technology and diffusion index per patent are considered respectively. In the second module, technologies value prediction model is implemented using artificial intelligence method. This studies use the values of five indexes (i.e., impact index, fusion index per technology, fusion index per patent, diffusion index per technology and diffusion index per patent) at different time (e.g., t-n, t-n-1, t-n-2, ${\cdots}$) as input variables. The out variables are values of five indexes at time t, which is used for learning. The learning method adopted in this study is backpropagation algorithm. In the third module, this study recommends final promising technologies based on analytic hierarchy process. AHP provides relative importance of each index, leading to final promising index for technology. Applicability of the proposed methodology is tested by using U.S. patents in international patent class G06F (i.e., electronic digital data processing) from 2000 to 2008. The results show that mean absolute error value for prediction produced by the proposed methodology is lower than the value produced by multiple regression analysis in cases of fusion indexes. However, mean absolute error value of the proposed methodology is slightly higher than the value of multiple regression analysis. These unexpected results may be explained, in part, by small number of patents. Since this study only uses patent data in class G06F, number of sample patent data is relatively small, leading to incomplete learning to satisfy complex artificial intelligence structure. In addition, fusion index per technology and impact index are found to be important criteria to predict promising technology. This study attempts to extend the existing knowledge by proposing a new methodology for prediction technology value by integrating patent information analysis and artificial intelligence network. It helps managers who want to technology develop planning and policy maker who want to implement technology policy by providing quantitative prediction methodology. In addition, this study could help other researchers by proving a deeper understanding of the complex technological forecasting field.

• Journal of agricultural medicine and community health
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• v.26 no.2
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• pp.59-78
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• 2001

Data on reported cancer mortality in the Gyeongsangbuk- do province from 1991 to 1998 were collected and analyzed using the existing mortality reporting system as well as the public health network to furnish accurate data on reported cancer death and to collect data to establish a high quality district health plan. The overall crude death rate in Gyeongsangbuk province in 1991 was 74.56 deaths per 100,000-person but this rate increased to 79.22 in 1998. Among the deaths, the overall death rate of cancer was 16.7% in 1991, which increased to 19.3% in 1998; specifically the death rate of men increased from 19.4% in 1991 to 22.3% in 1998 while that of women increased from 12.4% in 1991 to 15.5% in 1998, showing a more increase among women. The types of cancer and associated death rates in 1991 were gastric cancer(41.5%), followed by liver cancer (28.8%), and lung and bronchogenic carcinoma(8.7%) and in 1998, gastric cancer (24.7%), followed by liver cancer(22.7%), lung and bronchogenic carcinoma(19.3%), showing the same order. For men and women, gastric cancer(40.2% and 44.7%, respectively) was the most common cancer death, followed by liver cancer(33.7% and 16.7%, respectively), and lung and bronchogenic carcinoma(10.2% and 5.0%, respectively) in 1991. However, in 1998, gastric cancer(27.8%) was still the most common type among both men and women, followed by liver cancer (18.5%) and lung and bronchogenic carcinoma(12.7%), showing the most decrease in gastric cancer but most increase in lung and bronchogenic carcinoma. The age- adjusted mortality rates by gastric cancer, hepatoma, laryngeal carcinoma were decreased in both male and female, and also uterine cancer was decreased in female. The age- adjusted mortality rates by lung and bronchogenic carcinoma, pancreatic cancer, rectal cancer were increased in both male and female, and also breast cancer was increased in female. The calculated overall age-adjusted death rate based on the 1995 population was 84.25 in 1991, which decreased to 77.67 in 1998. Male death rate decreased significantly from 119.81 in 1991 to 101.82 in 1998 while the female death rate increased from 48.64 in 1991 to 53.80 in 1998. A census of cancer death rate using accurate death records is important for the establishment of proper and high-quality district health and medical plan and policy. The effort to improve the accuracy of death reports using the health facility network, as had been attempted by this study, can be continued. Furthermore, there must be a way for the Health and Welfare Department to use the death reports to improve the present reporting system. Lastly, additional studies need to be conducted to investigate how much the accuracy was improved by the supplemented death reports in this study.