• Proceedings of the Korean Society of Organic Agriculture Conference
• /
• 2009.12a
• /
• pp.281-281
• /
• 2009

Although national and regional environmentally friend agriculture (EFA) and food development programmes such as the Life-Food Development Plan (LFDP) have been established in Korea, some policy measures in these programmes seem to be unsuitable for Korean organic farming development. Policy measures tend to support external input purchases of organic fertilizers rather than market development actions such as providing consumer information, research, education, training and statistical data collection. The development of an organic action plan (OAP) for Korea is therefore considered essential for the sustainable future of organic farming in Korea. The purposes of OAP are 1) to define and set the clear goals/targets for the organic sector development, 2) to integrate various organic stakeholders and public institutions in partnership, 3)to focus on specific issues with tailored measures and 4) to integrate and develop different policy measures (Stolze, 2005). Most EU member state countries have developed their own OAPs and each reflects its own priorities with regard to organic sector development. This study compares and contrasts the Welsh, England and EU OAP with the Korean Jeonnam Life-Food Development Plan (LFDP) in order to facilitate the development of the organic food and farming sector in Korea. Early action plan, for example, the first Welsh OAP(1999) focused support on developing the supply of organic products whereas later action plans (e.g. England OAPs in 2002 and 2004 and the second Welsh OAP in 2005) focussed more on developing consumer demands for organic products. The EU OAP (2004) also aims at market support related to consumer demand and then organic farming production for its environmental and other social benefits. OAPs not only provide specific issue-solving tools but also perform a role as providing a focus for organic sector development as a whole. The Korean LFDP provides issue-solving tools but plays no regulatory role such as policy development, harmonizing various policy measures and conflicting factors and providing evaluation tools for further development. A national-level OAP could also facilitate international trade of organic products. To achieve better harmonized and sustainable approaches for the Korean organic industry, National- as well as regional- regulatory policy systems are urgently required in the form of an Organic Action Plan.

• Journal of Digital Convergence
• /
• v.18 no.8
• /
• pp.111-118
• /
• 2020

This study conducted an empirical analysis of SSE-listed companies to verify the effects of evaluation and disclosure of internal control systems on the agency costs management and controlling shareholders. Agency costs can affect the valuation of accounting information as asymmetry of information in the relationship between a company and its stakeholders, or induce financial costs as an adverse selection. If the firm's agency costs are reasonable, the valuation of the company can also move in a relatively positive direction. In this study, the evaluation information of the internal control system was analyzed through sales management ratio and equity ratio as substitute variables to analyze the relationship between management and agent costs of the controlling shareholders. In addition, independent control ratio, capital balance ratio, and company scale were used as control variables, as a result of the analysis, the evaluation information of internal control was found to be related to the agency costs of managers and governance structure. This study can be conducted to positive factors in evaluating the reliability and corporate value of accounting information according to the evaluation of internal control of SSE-listed companies and helps to understand the financial reporting environment.

• Journal of Environmental Policy
• /
• v.10 no.2
• /
• pp.3-19
• /
• 2011

Nagoya Protocol designed to establish criteria about material trade of biological genetic resources(ABS) was adopted in the 10th conference of the Parties to the Convention on Biological Diversity. In the course of the negotiation for adoption of the protocol, there was conflict between developed and developing countries, resource-rich and poor countries, and multinational corporations and environmentalists. This study investigates conflict process, subjects, issues and major factors in the negotiation case, and analyzes the negotiation by using the Conflict Management Process. To develope conflict management strategies for various conflict cases, we examine previous studies and analyze the intersectional conflict factors of this case and general cases, such as Fundamental side, Resource-allocation side, and Communication/Information-sharing side. These analyses of conflict prevention/resolution of the ABS negotiation show the importance of building mutual trust among stakeholders, enhancing mediator training, and constructing appropriate legislative/policy systems for successful conflict management.

• Journal of Distribution Science
• /
• v.12 no.8
• /
• pp.31-42
• /
• 2014

Purpose - Recently, a variety of activities for practicing the continuing management of domestic and foreign companies have been conducted and further, corporate social responsibility for maximizing the value of stakeholders such as customers, cooperative companies, and the local community emerges as a key business strategy. Accordingly, the issue of whether corporate image and customer value through corporate social responsibility activities positively affect customer loyalty and customer attitude is investigated in this study. Research design, data, and methodology - Corporate social responsibility activities are classified into legal and moral activities, environmental protection activities, economic activities, and community service activities; further, customer values are classified into emotional value, functional value, and social value, to determine the parameters. In addition, the strategic approach direction of social responsibility activities is justified as a strategy for effectively achieving the expected results that corporations seek by proving the effect of these parameters on customer loyalty. Results - The study results can be summarized as follows. First, legal and moral activities, environmental protection activities, economic activities, and community service activities are four types of CSR activities affecting meaningful improvements in corporate image. Second, legal and moral activities affect factors that meaningfully improve customer value, including factors such as emotional value, functional value, and social value, while environmental protection activities affect improvements in the factor of social value only. Third, corporate image affects meaningful improvements in customer value. Fourth, corporate image affects improvements in customer loyalty positively. Fifth, the three factors of customer value, that is, emotional value, functional value, and social value affect meaningful improvements in customer loyalty. Sixth, customer value acts to partly mediate the effect of companies' CSR activities on customer loyalty. As shown in the study results above, it was verified that CSR activities affect meaningful improvements in corporate image and customer value and, in turn, corporate image and customer value affect meaningful improvements in customer loyalty. In addition, it was verified that customer value acts to partly mediate the effects of companies' CSR activities on customer value. Conclusions - Accordingly, the results of this study suggests as follows. First, it was clearly verified that customers' recognition of CSR efforts has a positive effect on corporate image, customer value, and loyalty because CSR activities improve the relationships between customers and corporations by providing customers with value. Second, it was suggested that corporations implement social contribution activities strategically according to the theory that the higher the rate of CSR activities, the better the corporate image and repurchase intention would be, which is a theory verified through practical analysis. Corporations should do this by constructing positive relationships from the value perceived by customers. To summarize the study results in a brief manner, it is suggested by the results of the study that a corporation should conduct CSR more actively to make customers recognize the positive image of their products and services.

• Journal of Ginseng Culture
• /
• v.3
• /
• pp.90-118
• /
• 2021

Gaeseong fostered the conditions necessary for modern capitalism, as huge capital was accumulated through the cultivation and trade of ginseng, which were activities that flourished in the 18th century. During the Japanese colonial era, ginseng merchants were not simply limited to acquiring landowner capital from ginseng trade but actively converted such resource to productive and financial capital, thereby becoming modern entrepreneurs. Ginseng merchants led the joint management and investment of Gaeseong Electric Co., Ltd., Daehan Cheonil Bank, Gaeseong Brewing Co., Ltd., and Songgo Textile Company, founded in the early 20th century. They pursued corporate profits and, as leading individuals of society, spearheaded regional development by supporting educational and cultural projects in Gaeseong. These projects included the establishment of the Gaeseong Commercial School, the publication of Goryeo Times, and the operation of the Gaeseong Jwa Theater. Although liberal economics prioritized shareholder interest, the 21st century witnessed an emphasis on social responsibility among stakeholders asthe major purpose of enterprises. A trend that emerged was ESG (environment, social, governance) management, in which non-financial factors are valued more highly than financial performance. A successful business, which was denoted only by high profits in the past, is now defined by whether a company fulfills its social responsibility. In the early 20th century, the corporate activities of ginseng merchants in Gaeseong reflected entrepreneurship and stakeholder-centered ESG management, which later emerged as essential elements of modern business management. The modern management philosophy ahead of its times stemmed from the regionality of Gaeseong. The political discrimination against Gaeseong residents in the Joseon Dynasty precluded them from becoming government officers, and under a strict social hierarchy, yangban ("noblemen"), the intellectuals of the Joseon Dynasty, were forced to serve as merchants. Son Bong-sang and Kong Seong-hak, aside from being representative ginseng merchants, were both Confucian scholars and writers. The second and third generations of ginseng merchant families who had received higher education abroad returned to Gaeseong to carry on with their family businesses, then established modern companies with capital accrued from the ginseng industry. An analysis of the commercial activities of ginseng merchants in the early 20th century confirmed that these individuals were pioneering entrepreneurs who adopted the ESG management philosophy. In ginseng merchants, one sees a dimension of capitalism with a human face, as with ginseng thatsaves human life.

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

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

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.23 no.4
• /
• pp.235-250
• /
• 2021

The overarching question of this study is how a typical rice cultivation system in Gimje, Korea was keeping up with the triple-win challenge of climate-smart agriculture (CSA). To answer this question, we have employed (1) quantitative data from direct measurement of energy, water, carbon and information flows in and out of a rice cultivation system and (2) appropriate metrics to assess production, efficiency, GHG fluxes, and resilience. The study site was one of the Korean Network of Flux measurement (KoFlux) sites (i.e., GRK) located at Gimje, Korea, managed by National Academy of Agricultural Science, Rural Development Administration. Fluxes of energy, water, carbon dioxide (CO₂) and methane (CH₄) were directly measured using eddy-covariance technique during the growing seasons of 2011, 2012 and 2014. The production indicators include gross primary productivity (GPP), grain yield, light use efficiency (LUE), water use efficiency (WUE), and carbon uptake efficiency (CUE). The GHG mitigation was assessed with indicators such as fluxes of carbon dioxide (F_CO2), methane (F_CH4), and nitrous oxide (F_N2O). Resilience was assessed in terms of self-organization (S), using information-theoretic approach. Overall, the results demonstrated that the rice cultivation system at GRK was climate-smart in 2011 in a relative sense but failed to maintain in the following years. Resilience was high and changed little for three year. However, the apparent competing goals or trade-offs between productivity and GHG mitigation were found within individual years as well as between the years, causing difficulties in achieving the triple-win scenario. The pursuit of CSA requires for stakeholders to prioritize their goals (i.e., governance) and to practice opportune interventions (i.e., management) based on the feedback from real-time assessment of the CSA indicators (i.e., monitoring) - i.e., a purpose-driven visioneering.

• Journal of Venture Innovation
• /
• v.4 no.2
• /
• pp.57-75
• /
• 2021

KHNP's shared growth activities are based on such public good. Reflecting the characteristics of a comprehensive energy company, a high-tech plant company, and a leading company for shared growth, it presents strategies to link performance indicators with its partners and implements various measures. Key tasks include maintaining the nuclear power plant ecosystem, improving management conditions for partner companies, strengthening future capabilities of the nuclear power plant industry, and supporting a virtuous cycle of regional development. This is made by reflecting the specificity of nuclear power generation as much as possible, and is designed to reflect the spirit of shared growth through win-win and cooperation in order to solve the challenges of the times while considering the characteristics as much as possible as possible. KHNP's shared growth activities can be said to be the practice of the spirit of the times(Zeitgeist). The spirit of the times given to us now is that companies should strive for sustainable growth as social air. KHNP has been striving to establish a creative and leading shared growth ecosystem. In particular, considering the positions of partners, it has been promoting continuous system improvement to establish a fair trade culture and deregulation. In addition, it has continuously discovered and implemented new customized support projects that are effective for partner companies and local communities. To this end, efforts have been made for shared growth through organic collaboration with partners and stakeholders. As detailed tasks, it also presents fostering new markets and new industries, maintaining supply chains, and emergency support for COVID-19 to maintain the nuclear power plant ecosystem. This reflects the social public good after the recent COVID-19 incident. In order to improve the management conditions of partner companies, productivity improvement, human resources enhancement, and customized funding are being implemented as detailed tasks. This is a plan to practice win-win growth with partner companies emphasized by corporate social responsibility (CSR) and ISO 26000 while being faithful to the main job. Until now, ESG management has focused on the environmental field to cope with the catastrophe of climate change. According to KHNP is presenting a public enterprise-type model in the environmental field. In order to strengthen the future capabilities of the nuclear power plant industry as a state-of-the-art energy company, it has set tasks to attract investment from partner companies, localization and new technologies R&D, and commercialization of innovative technologies. This is an effort to develop advanced nuclear power plant technology as a concrete practical measure of eco-friendly development. Meanwhile, the EU is preparing a social taxonomy to focus on the social sector, another important axis in ESG management, following the Green Taxonomy, a classification system in the environmental sector. KHNP includes enhancing local vitality, increasing income for the underprivileged, and overcoming the COVID-19 crisis as part of its shared growth activities, which is a representative social taxonomy field. The draft social taxonomy being promoted by the EU was announced in July, and the contents promoted by KHNP are consistent with this, leading the practice of social taxonomy

• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.195-220
• /
• 2018

In this study, we conducted an empirical analysis of the factors that affect the change of Bitcoin Closing Price. Previous studies have focused on the security of the block chain system, the economic ripple effects caused by the cryptocurrency, legal implications and the acceptance to consumer about cryptocurrency. In various area, cryptocurrency was studied and many researcher and people including government, regardless of country, try to utilize cryptocurrency and applicate to its technology. Despite of rapid and dramatic change of cryptocurrencies' price and growth of its effects, empirical study of the factors affecting the price change of cryptocurrency was lack. There were only a few limited studies, business reports and short working paper. Therefore, it is necessary to determine what factors effect on the change of closing Bitcoin price. For analysis, hypotheses were constructed from three dimensions of consumer, industry, and macroeconomics for analysis, and time series data were collected for variables of each dimension. Consumer variables consist of search traffic of Bitcoin, search traffic of bitcoin ban, search traffic of ransomware and search traffic of war. Industry variables were composed GPU vendors' stock price and memory vendors' stock price. Macro-economy variables were contemplated such as U.S. dollar index futures, FOMC policy interest rates, WTI crude oil price. Using above variables, we did times series regression analysis to find relationship between those variables and change of Bitcoin Closing Price. Before the regression analysis to confirm the relationship between change of Bitcoin Closing Price and the other variables, we performed the Unit-root test to verifying the stationary of time series data to avoid spurious regression. Then, using a stationary data, we did the regression analysis. As a result of the analysis, we found that the change of Bitcoin Closing Price has negative effects with search traffic of 'Bitcoin Ban' and US dollar index futures, while change of GPU vendors' stock price and change of WTI crude oil price showed positive effects. In case of 'Bitcoin Ban', it is directly determining the maintenance or abolition of Bitcoin trade, that's why consumer reacted sensitively and effected on change of Bitcoin Closing Price. GPU is raw material of Bitcoin mining. Generally, increasing of companies' stock price means the growth of the sales of those companies' products and services. GPU's demands increases are indirectly reflected to the GPU vendors' stock price. Making an interpretation, a rise in prices of GPU has put a crimp on the mining of Bitcoin. Consequently, GPU vendors' stock price effects on change of Bitcoin Closing Price. And we confirmed U.S. dollar index futures moved in the opposite direction with change of Bitcoin Closing Price. It moved like Gold. Gold was considered as a safe asset to consumers and it means consumer think that Bitcoin is a safe asset. On the other hand, WTI oil price went Bitcoin Closing Price's way. It implies that Bitcoin are regarded to investment asset like raw materials market's product. The variables that were not significant in the analysis were search traffic of bitcoin, search traffic of ransomware, search traffic of war, memory vendor's stock price, FOMC policy interest rates. In search traffic of bitcoin, we judged that interest in Bitcoin did not lead to purchase of Bitcoin. It means search traffic of Bitcoin didn't reflect all of Bitcoin's demand. So, it implies there are some factors that regulate and mediate the Bitcoin purchase. In search traffic of ransomware, it is hard to say concern of ransomware determined the whole Bitcoin demand. Because only a few people damaged by ransomware and the percentage of hackers requiring Bitcoins was low. Also, its information security problem is events not continuous issues. Search traffic of war was not significant. Like stock market, generally it has negative in relation to war, but exceptional case like Gulf war, it moves stakeholders' profits and environment. We think that this is the same case. In memory vendor stock price, this is because memory vendors' flagship products were not VRAM which is essential for Bitcoin supply. In FOMC policy interest rates, when the interest rate is low, the surplus capital is invested in securities such as stocks. But Bitcoin' price fluctuation was large so it is not recognized as an attractive commodity to the consumers. In addition, unlike the stock market, Bitcoin doesn't have any safety policy such as Circuit breakers and Sidecar. Through this study, we verified what factors effect on change of Bitcoin Closing Price, and interpreted why such change happened. In addition, establishing the characteristics of Bitcoin as a safe asset and investment asset, we provide a guide how consumer, financial institution and government organization approach to the cryptocurrency. Moreover, corroborating the factors affecting change of Bitcoin Closing Price, researcher will get some clue and qualification which factors have to be considered in hereafter cryptocurrency study.