• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.111-131
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• 2015

There are only a handful number of research conducted on pattern analysis of corporate distress as compared with research for bankruptcy prediction. The few that exists mainly focus on audited firms because financial data collection is easier for these firms. But in reality, corporate financial distress is a far more common and critical phenomenon for non-audited firms which are mainly comprised of small and medium sized firms. The purpose of this paper is to classify non-audited firms under distress according to their financial ratio using data mining; Self-Organizing Map (SOM). SOM is a type of artificial neural network that is trained using unsupervised learning to produce a lower dimensional discretized representation of the input space of the training samples, called a map. SOM is different from other artificial neural networks as it applies competitive learning as opposed to error-correction learning such as backpropagation with gradient descent, and in the sense that it uses a neighborhood function to preserve the topological properties of the input space. It is one of the popular and successful clustering algorithm. In this study, we classify types of financial distress firms, specially, non-audited firms. In the empirical test, we collect 10 financial ratios of 100 non-audited firms under distress in 2004 for the previous two years (2002 and 2003). Using these financial ratios and the SOM algorithm, five distinct patterns were distinguished. In pattern 1, financial distress was very serious in almost all financial ratios. 12% of the firms are included in these patterns. In pattern 2, financial distress was weak in almost financial ratios. 14% of the firms are included in pattern 2. In pattern 3, growth ratio was the worst among all patterns. It is speculated that the firms of this pattern may be under distress due to severe competition in their industries. Approximately 30% of the firms fell into this group. In pattern 4, the growth ratio was higher than any other pattern but the cash ratio and profitability ratio were not at the level of the growth ratio. It is concluded that the firms of this pattern were under distress in pursuit of expanding their business. About 25% of the firms were in this pattern. Last, pattern 5 encompassed very solvent firms. Perhaps firms of this pattern were distressed due to a bad short-term strategic decision or due to problems with the enterpriser of the firms. Approximately 18% of the firms were under this pattern. This study has the academic and empirical contribution. In the perspectives of the academic contribution, non-audited companies that tend to be easily bankrupt and have the unstructured or easily manipulated financial data are classified by the data mining technology (Self-Organizing Map) rather than big sized audited firms that have the well prepared and reliable financial data. In the perspectives of the empirical one, even though the financial data of the non-audited firms are conducted to analyze, it is useful for find out the first order symptom of financial distress, which makes us to forecast the prediction of bankruptcy of the firms and to manage the early warning and alert signal. These are the academic and empirical contribution of this study. The limitation of this research is to analyze only 100 corporates due to the difficulty of collecting the financial data of the non-audited firms, which make us to be hard to proceed to the analysis by the category or size difference. Also, non-financial qualitative data is crucial for the analysis of bankruptcy. Thus, the non-financial qualitative factor is taken into account for the next study. This study sheds some light on the non-audited small and medium sized firms' distress prediction in the future.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.137-154
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• 2018

Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.

• Archives of design research
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• v.18 no.4 s.62
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• pp.105-118
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• 2005

Housing environment for human beings has been diversified and more convenient due to the development of high technology and civilization brought by industrialization in the 20th century. In the 21st century, how to overcome the ecological limit of biased development-centered advancement, that is, how to preserve and hand over a clean and healthy 'sustainable environment' to our next generations has been one of the most-talked about issues. Environmental symbiosis means a wider range of environmental harmony from micro-dimensional perspective to macro one. The three goals of a environmentally friendly house are to preserve global environment, to harmonize with the environment around, and to offer a healthy and comfortable living environment. From the point of view of environmental symbiosis, houses should be designed to save energy and natural resources for preservation of global environment, to collect such natural energy resources as solar heat and wind force, to recycle waste water, and recycle and reduce the amount of the waste matter. Now, the environmentally-friendly house became a new social mission that is difficult to not only challenge but also realize without conversion to a new paradigm, ecologism.

• Journal of Technology Innovation
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• v.24 no.4
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• pp.55-99
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• 2016

The paper investigates X-project, in which the public was invited to participate in a national R&D project, examines how X-project attracted the public's attention and involved them in a national R&D project, and discusses the significance and limitations of X-project. X-project was executed by a 12 citizen-led committee, financially supported by the Ministry of Science, ICT, and Future Planning, and backed by the Science and Technology Policy Institute. People raised 6,212 questions that reflected the severe needs they experienced in their daily lives through the online and offline platforms of X-project. In addition, the committee members, scholars, experts, government officials, and citizens gathered together to select the fifty most provocative and novel of the questions raised by the public, and invited public participation to answer the questions in innovative ways. 310 research teams including professional researchers from universities and institutes, high-school students, lay persons, and corporate workers applied for X-project, and 54 of these teams were finally selected to receive funding from the government. Through planning and conducting X-project, as well as interviewing and surveying the participants in X-project and non-participants, we found that there was an enormous social consensus on the necessity of public participatory national R&D projects. People asserted that science and technology should put a greater focus on solving social problems and satisfying public needs. We also confirmed that the public could take part in national R&D projects. Most of all, we found that the questions raised by the public were very challenging, novel, and complex, and thus researchers need break-through approaches to address them. It can be also argued that through experiencing the X-project citizens can regard themselves as ones who are not only recipients of the benefits of the development of science and technology, but also contributors of the development of them. We finally argue that there are some limitations to X-project in terms of how to provide diverse incentives that attract more participation, how to develop the process in which people got involved in the project in more easy ways, and how to create new ways for lay persons and professional researchers to cooperate in solving social problems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.2
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• pp.279-292
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• 2018

Unlike the global art market which experienced rapid recovery from the impacts of the Global Financial Crisis in 2008, the Korean art market has not yet fully recovered. The gallery-oriented distribution system, vulnerable primary art market functions, and the market structure centered on a small number of collectors make it difficult for young and medium artists to enter the market and, as a result, deepen the economic polarization of artists. In addition, the high price of art works limits market participation by restricting the general public. This study began with the idea that the interest of the public in the art market as well as their participation in the market are urgent. To this end, we noted that public awareness of art transactions can be a starting point for improving the constitution of the fragile art market, focusing on the 'Artist-centered Art Fair' rather than existing art fairs. To examine the contribution of such an art fair to the popularization of the art market, we analyzed the case of the 'Visual Artist Market (VAM)' project of the Korea Arts Management Service. Results found that the 'Artist-centered Art Fair' focuses on providing opportunities for market entry to young and medium artists rather than on the interests of distributors, and promotes the popularization of the art market by promoting low-priced works to the general public. Also, the 'Artist-centered Art Fair' seems to play a primary role in the public sector to foster solid groups of artists as well as to establish healty distribution networks of Korean Art market. However, in the long run, it is necessary to promote sustainable development of the 'Artist-centered Art Fair' through indirect support, such as the provision of a publicity platform or consumer finance support, rather than direct support.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.6
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• pp.1-13
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• 2015

There are various performance factors for SMEs in order to survive in the rapid changing market and it is discussing the importance of entrepreneurs' entrepreneurial orientation based on many researches. Thus, it is worth to analyze factors of seize new opportunity and firm's performance to build sustainable competitive advantages, which provide the directions to SMEs. This study investigates through exploratory research that the important factors of entrepreneurial orientation and the influence factors on firm's performance confirmed by empirical study. This study was conducted to explore the relationship between entrepreneurial orientation of SME CEO, learning orientation and corporate performance was verified following section. First, entrepreneurial orientation (pro-activeness, competitive aggressiveness, risk taking, innovativeness) was to examine the effect of learning orientation; Second, entrepreneurial orientation was to examine the impact on firm's performance; and in the last, validated learning orientation affect factors that are mediated between entrepreneurship orientation and firm's performance through empirical research. The results of this study, each SME have shown that they have a different impact on firm's performance based on a variety of entrepreneurial orientation. This result shows that the need for a separate independent study on entrepreneurial orientation of SMEs. In conclusion, this study implicates that entrepreneurial orientation is important role for firm's performance, entrepreneurs of SMEs are innovative rather than competitive aggressive, and risk taking activities positively affect firm's activity. The conclusions of this study would be utilized to develop the entrepreneurial orientation when necessary for entrepreneurs of SMEs.

• Journal of Bio-Environment Control
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• v.9 no.3
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• pp.171-178
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• 2000

Gross photosynthetic rats of leaves of hydroponically grown cucumber plants(Cucumis sativus L. cv. Guwoosalichungjang) were measured under various conditions of photosynthetic photon flux(PPF), ambient $CO_2$ concentration, air temperature and leaf nitrogen contents. Light compensation point of leaf photosynthesis appeared to be in the range of 10~20$\mu$mol.m$^{-2}$ .s$^{-1}$ and light saturation point be above 1000$\mu$mol.m$^{-2}$ .s$^{-1}$ . Gross photosynthetic rates increased persistently and asymptotically as air temperature rose from 12$^{\circ}C$ to 32$^{\circ}C$. However, there were only small differences in gross photosynthetic rates in the range of 24-32$^{\circ}C$, so that the range seemed to be optimal for photosynthesis of cucumber plants at the condition of $CO_2$ concentration of 400$\mu$mol.mol$^{-1}$ and PPF of around 400$\mu$mol.m$^{-2}$ .s$^{-1}$ . $CO_2$ compensation point of leaf photosynthesis appeared to be in the range of 20-40$\mu$mol.mol$^{-1}$ and $CO_2$ saturation point be above 1200$\mu$mol.mol$^{-1}$ . Gross photosynthetic rates increased sigmoidally as leaf nitrogen content increased. These environmental factors interacted synergistically to enhance gross photosynthetic rate, so that the rate increased multiplicatively s level of one factor increased progressively with higher levels of he other factors. Mathematical models wer developed to estimate the gross photosynthetic rate in accordance with the variations of these environmental factors. These modes can be used not only to explain he variation of growth or yield of cucumber plants under different environmental conditions but also as building blocks of plant growth model or expert system of cucumber plants.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.23-48
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• 2021

The Korean economy has achieved continuous economic growth for the past several decades thanks to the government's export strategy policy. This increase in exports is playing a leading role in driving Korea's economic growth by improving economic efficiency, creating jobs, and promoting technology development. Traditionally, the main factors affecting Korea's exports can be found from two perspectives: economic factors and industrial structural factors. First, economic factors are related to exchange rates and global economic fluctuations. The impact of the exchange rate on Korea's exports depends on the exchange rate level and exchange rate volatility. Global economic fluctuations affect global import demand, which is an absolute factor influencing Korea's exports. Second, industrial structural factors are unique characteristics that occur depending on industries or products, such as slow international division of labor, increased domestic substitution of certain imported goods by China, and changes in overseas production patterns of major export industries. Looking at the most recent studies related to global exchanges, several literatures show the importance of cultural aspects as well as economic and industrial structural factors. Therefore, this study attempted to develop a forecasting model by considering cultural factors along with economic and industrial structural factors in calculating the import volume of each country from Korea. In particular, this study approaches the influence of cultural factors on imports of Korean products from the perspective of PUSH-PULL framework. The PUSH dimension is a perspective that Korea develops and actively promotes its own brand and can be defined as the degree of interest in each country for Korean brands represented by K-POP, K-FOOD, and K-CULTURE. In addition, the PULL dimension is a perspective centered on the cultural and psychological characteristics of the people of each country. This can be defined as how much they are inclined to accept Korean Flow as each country's cultural code represented by the country's governance system, masculinity, risk avoidance, and short-term/long-term orientation. The unique feature of this study is that the proposed final prediction model can be selected based on Design Principles. The design principles we presented are as follows. 1) A model was developed to reflect interest in Korea and cultural characteristics through newly added data sources. 2) It was designed in a practical and convenient way so that the forecast value can be immediately recalled by inputting changes in economic factors, item code and country code. 3) In order to derive theoretically meaningful results, an algorithm was selected that can interpret the relationship between the input and the target variable. This study can suggest meaningful implications from the technical, economic and policy aspects, and is expected to make a meaningful contribution to the export support strategies of small and medium-sized enterprises by using the import forecasting model.

• Journal of Technology Innovation
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• v.31 no.1
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• pp.29-63
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• 2023

The purpose of this study is to analyze the process of changes in regional science and technology policies in Korea and to seek future development directions. In Korea, regional science and technology policies have been implemented since the introduction of the local autonomy system. Since then, it has been implemented in earnest with the establishment of a central government-level plan. The regional science and technology policies have been developed to this day by interacting with national science and technology policies and regional development policies. Nevertheless, due to the path dependence and lock-in effect in the accumulated process, the regional science and technology policies are still subordinate to central government policies. Thus, the establishment of an independent ecosystem for local science and technology is still insufficient. Furthermore, the gap between regions is deepening, such as the growing of aging population, population decline due to low birth rates, job losses due to the recession of local key industry, and the concentration of the youth population in the metropolitan area. The transformation path such as digital transformation and carbon neutrality paradigm is expected to further widen regional disparities. In order to address a comprehensive problem, the implementing system of regional science and technology policies need to be newly established. A framework for reinvention of regional science and technology policy needed in the era of grand societal challenges have to be developed.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.185-209
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• 2023

With the advent of the 4th industrial revolution, various technologies have received much attention. Technologies related to the 4th industry include the Internet of Things (IoT), big data, artificial intelligence, virtual reality (VR), 3D printers, and robotics, and these technologies are often converged. In particular, the robotics field is combined with technologies such as big data, artificial intelligence, VR, and digital twins. Accordingly, much research using robotics is being conducted, which is applied to distribution, airports, hotels, restaurants, and transportation fields. In the given situation, research on human-robot interaction is attracting attention, but it has not yet reached the level of user satisfaction. However, research on robots capable of perfect communication is steadily being conducted, and it is expected that it will be able to replace human emotional labor. Therefore, it is necessary to discuss whether the current human-robot interaction technology can be applied to business. To this end, this study first examines the trend of human-robot interaction technology. Second, we compare LDA (Latent Dirichlet Allocation) topic modeling and BERTopic topic modeling methods. As a result, we found that the concept of human-robot interaction and basic interaction was discussed in the studies from 1992 to 2002. From 2003 to 2012, many studies on social expression were conducted, and studies related to judgment such as face detection and recognition were conducted. In the studies from 2013 to 2022, service topics such as elderly nursing, education, and autism treatment appeared, and research on social expression continued. However, it seems that it has not yet reached the level that can be applied to business. As a result of comparing LDA (Latent Dirichlet Allocation) topic modeling and the BERTopic topic modeling method, it was confirmed that BERTopic is a superior method to LDA.