• 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.28 no.1
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• pp.45-68
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• 2022

The central and local governments of the Republic of Korea provided information necessary for disaster response through wireless emergency alerts (WEAs) in order to overcome the pandemic situation in which COVID-19 rapidly spreads. Among all channels for delivering disaster information, wireless emergency alert is the most efficient, and since it adopts the CBS(Cell Broadcast Service) method that broadcasts directly to the mobile phone, it has the advantage of being able to easily access disaster information through the mobile phone without the effort of searching. In this study, the characteristics of wireless emergency alerts sent to Seoul during the past year and one month (January 2020 to January 2021) were derived through various text mining methodologies, and various types of information contained in wireless emergency alerts were analyzed. In addition, it was confirmed through the population mobility by age in the districts of Seoul that what kind of influence it had on the movement behavior of people. After going through the process of classifying key words and information included in each character, text analysis was performed so that individual sent characters can be used as an analysis unit by applying a document cluster analysis technique based on the included words. The number of WEAs sent to the Seoul has grown dramatically since the spread of Covid-19. In January 2020, only 10 WEAs were sent to the Seoul, but the number of the WEAs increased 5 times in March, and 7.7 times over the previous months. Since the basic, regional local government were authorized to send wireless emergency alerts independently, the sending behavior of related to wireless emergency alerts are different for each local government. Although most of the basic local governments increased the transmission of WEAs as the number of confirmed cases of Covid-19 increases, the trend of the increase in WEAs according to the increase in the number of confirmed cases of Covid-19 was different by region. By using structured econometric model, the effect of disaster information included in wireless emergency alerts on population mobility was measured by dividing it into baseline effect and accumulating effect. Six types of disaster information, including date, order, online URL, symptom, location, normative guidance, were identified in WEAs and analyzed through econometric modelling. It was confirmed that the types of information that significantly change population mobility by age are different. Population mobility of people in their 60s and 70s decreased when wireless emergency alerts included information related to date and order. As date and order information is appeared in WEAs when they intend to give information about Covid-19 confirmed cases, these results show that the population mobility of higher ages decreased as they reacted to the messages reporting of confirmed cases of Covid-19. Online information (URL) decreased the population mobility of in their 20s, and information related to symptoms reduced the population mobility of people in their 30s. On the other hand, it was confirmed that normative words that including the meaning of encouraging compliance with quarantine policies did not cause significant changes in the population mobility of all ages. This means that only meaningful information which is useful for disaster response should be included in the wireless emergency alerts. Repeated sending of wireless emergency alerts reduces the magnitude of the impact of disaster information on population mobility. It proves indirectly that under the prolonged pandemic, people started to feel tired of getting repetitive WEAs with similar content and started to react less. In order to effectively use WEAs for quarantine and overcoming disaster situations, it is necessary to reduce the fatigue of the people who receive WEA by sending them only in necessary situations, and to raise awareness of WEAs.

• Korean Journal of Ecology and Environment
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• v.50 no.2
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• pp.216-237
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• 2017

Thermal effluent of the hot spring has long been a field of interest in the relationship between temperature gradient and freshwater algae in geology, limnology and aquatic ecology throughout the world. On the other hand, many artificial hot springs have been developed in Korea, but the research on them has not been still active. This study was performed every month from December 2015 to September 2016, to elucidate the spatiotemporal effects of thermal wastewater effluent (TWE) on the ecosystem of benthic algal assemblage in four stations(BSU (upstream), HSW (hot spring wastewater outlet), BSD1~2 (downstream)) of the upstream reach of the Buso Stream, a tributary located in the Hantan River basin. During the survey, the influencing distance of temperature on TWE was <1.0 km, and it was the main source of N P nutrients at the same time. The effects of TWE were dominant at low temperature and dry season (December~March), but it was weak at high temperature and wet season (July~September), reflecting some seasonal characteristics. Under these circumstances, the attached algal communities were identified to 59 genera and 143 species. Of these, the major phylum included 21 genera 83 species of diatoms(58.0%), 9 genera 21 species of blue-green algae (14.7%) and 25 genera 32 species of green algae (22.4%), respectively. The spatiotemporal distribution of them was closely related to water temperature ($5^{\circ}C$ and $15^{\circ}C$) and current ($0.2m\;s^{-1}$ and $0.8m\;s^{-1}$). In the basic environment maintaining a high water temperature throughout the year round, the flora favoring high affinity to $PO_4$ in the water body or preferring stream habitat of abundant $NO_3-PO_4$ was dominant. As a result, when compared with the outcomes of previous algal ecology studies conducted in Korea, the Buso Stream was evaluated as a serious polluted state due to persistent excess nutrient supply and high thermal pollution throughout the year round by TWE. It can be regarded as a dynamic ecosystem in which homogeneity (Summer~Autumn) and heterogeneity (Winter~Spring) are repeated between upstream and downstream.

• Korean Journal of Poultry Science
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• v.45 no.3
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• pp.229-236
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• 2018

The aim of this study was to evaluate the genetic diversity and relationships of Ogye populations in Korea. A total of 243 genomic DNA samples from 6 Ogye population (Yeonsan Ogye; YSO, Animal Genetic Resources Research Center Ogye; ARO, Chungbuk Ogye; CBO, Chungnam Ogye; CNO, Gyeongbuk Ogye; GBO, Seoul National University Ogye; SUO) and 3 introduced chicken breeds (Rhode Island Red; RIR, White Leghorn; LG, Cornish; CN) were used. Sizes of 25 microsatellite markers were decided using GeneMapper Software(v 5.0) after analyzing ABI 3130XL. A total of 153 alleles were observed and the range was 2 to 10 per each locus. The mean of expected and observed heterozygosity and PIC (Polymorphism Information Content) value was 0.53, 0.50, 0.46 respectively. The lowest genetic distance (0.073) was observed between YSO and SUO, and the highest distance (0.937) between the RIR and CBO. The results of clustering analysis suggested 3 clusters (${\Delta}K=7.96$). Excluding GBO population, 5 Ogye populations (YSO, ARO, CBO, CNO, SUO) were grouped in same cluster with high genetic uniformity (0.990, 0.979, 0.989, 0.994, 0.985 respectively). But GBO population was grouped in cluster 1 with low genetic uniformity (0.340). The results of this study can be use to basic data for the genetic evaluation and management of Ogye populations in Korea.

• Journal of the Korean Society of Groundwater Environment
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• v.4 no.3
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• pp.130-143
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• 1997

To investigate geochemical characteristics and the sources of the dissolved ion species in the river water in the Han river drainage basin, samples were collected at 60 sites from the Han river drainage basin. The data for. pH, conductivity, TDS (total dissolved solid), temperature, and concentrations of dissloved ions were obtained as follows : (1) The geochemical characteristics of the surface water in the South and North Han river drainage basins are mainly controlled by bed rock geology in the drainage basin and in the main stream of the Han river considerably affected by anthropogenic pollution. The South Han river water samples have high concentrations of $Ca^{2＋}$ (ave. 15.42 ppm), $Mg^{2＋}$ (ave. 2.74 ppm), HC $O_3$$^{[-10]}$ (ave. 51.9 ppm), which evidently indicates that the bed rock geology in a limestone area mainly controls the surface water chemistry. The concentration of S $O_4$$^{2-}$ is remarkably high (SHR10-2 : 129.9 ppm) because of acid mine drainage from the metal and coal mines in the upper reaches of the South Han river. (2) The South Han river and the North Han river join the Han river. in the Yangsuri, Kyounggido and flow through Seoul metropolitan city. The mixing ratio is about 60:40 at the meeting point (sample number HRl0). (3) The result of factor analysis suggests that the pollution factor accounts for about 79% and the bed rock type factor accounts for about 7% of the data variation. This means that the geochemical characteristics of the Han river water mainly controlled by anthropogenic pollution in the South Han river and main stream of the Han river drainage basin. (4) The chemical data for four tributaries such as the Wangsukcheon, the Tancheon, the Zunuangcheon, and the Anyangcheon show that the concentration of pollution elements such as N $O_2$, C $l^{－}$, P $O_4$$^{3-}$, S $O_4$$^{2-}$ and Mn are high due to municipal waste disposal.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.5
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• pp.1-15
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• 2020

This study was designed to come up with a way of managing a cultural landscape forest by conducting research on the vegetation structure and growth characteristics. This study's target site, which was 45,201㎡ in size, was Pinus densiflora forest for Sugumagi placed at the entrance of Unmun Temple, Sinwon-ri, Unmun-myeon, and Cheongdo-gun in the southernmost part of Gyeongsangbuk-do, Korea. Sugumagi means the water of the valley flows far away, and where no downstream is visible according to feng shui. The historical sources of the Sugumagi Pinus densiflora forest at the entrance of Unmun Temple isn't clear. It waw only found at that location. The Pinus densiflora forest at the entrance of Unmun Temple is located in the waterway in terms of Feng Shui. The present condition of growth was investigated through a grid surveys of 98 trees and Pinus densiflora growth. As a result of the analysis of growth status, Pinus densiflora, Larix leptolepis, Zelkova serrata, Celtis sinensis, and Rhus javanica were distributed in the conopy layer, and 28 species including Ailanthus altissima were grown in the understroy layer, and 92 species, including Ampelopsis brevipedunculata, in the shrub layer. The plant community structure was divided into low, medium and high-density Pinus densiflora forests in the study area, based on the number in the conopy layer and the grade of and the trees analyzed. As a result of the analysis, the Pinus densiflora dominated the low, medium and high-density Pinus densiflora forests, and there were no competitive species. The relative dominance of the low-density Pinus densiflora forests was 46.9% on average, medium-density was 62.6% and 50.2% was found in high-density. The mean species diversity of Shannon in the low-density study was 0.7055, medium-density study was 0.8966 and the average species diversity of Shannon in the high-density study was 0.8317. The analysis of the age and growth of 25 sample trees in the Sugumagi Pinus densiflora forest shows that the distribution of the chest diameter (DBH) of the sample Pinus densiflora is 38 to 77cm with the average chest diameter being 61.1cm. The age was 84-161 years and the average was 114 years. In the Pinus densiflora forest, most(670,659, or 98.3%) of the tree trunk wound was collected for rosins during the Japanese colonia Era, Of the total 670, 659 were Pinus densiflora, 98.3% of the total. 394 were surgically repaired in 2005. For the preservation of the Sugumagi Pinus densiflora forest, dead trees should be replaced with substitute trees appropriate to the middle and south topography. It is demanded that foreign species such as Larix leptolepis in the research area should be removed and Pinus densiflora that underwent surgical operations should be regularly sterilized. It is also emphasized that the management of insecticide is important.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.4
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• pp.129-144
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• 2013

The consumption of coffee has been drastically increased last two decades. Now almost all the Korean adult people enjoy the coffee and diverse cultures related coffee have been spread widely in Korea. Therefore new marketing strategies are necessary to satisfy consumers according to ages, attitudes, and other characters. It has been continuously discussed whether the coffee gives negative impacts to health. Regardless of the discussions of the effects to health, now coffee became a part of modern daily lives. In this study the motivations of coffee consumption were classified to five; wellbeing motivation, refreshment motivation, social motivation, habitual motivation, and emotional motivation. Future intention of coffee consumption were also classified to five factors: sound mental intention, addictive intention, side-effect recovery intention, economic intention, and psychological intention. The survey was conducted in Seoul City and Kyeongki Province from January 3 to February 2, 2013. Total 500 questionaries were distributed and 450 were collected and 428 samples were used for the analysis of this study. The data were analyzed by SPSS Win 18 Version. The methods used in this study were factors analysis test, reliability test, validity test, t-testy, One-Way ANOVA, and regression analysis. The hypnosis in this study were as follows. First, The motivations of coffee consumption would influence to the intention of coffee consumption. Second, there would be statistical differences to the intention of coffee consumption according to the demographic characteristics. According to the result of the study, the motivation of coffee partially affected to the intention of coffee consumption. And there were statistical differences according to age, occupations, educational levels, and monthly incomes. The implications of this study were the factors related health and emotional feeling were considered more important than tastes and characters of coffee-shop that people thought more important before.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.4
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• pp.338-346
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• 2017

Natural seaweed beds and habitat environments were investigated using quantitative and qualitative methods from May to December 2015 at 3 sites in Gangneung, Uljin, and Busan along the eastern coast of Korea. In total, 9 green, 23 brown, and 64 red algal taxa were identified. The biomass of the seaweed at Gangneung was 173.2 to $613.8wet\;wt.g/m^2$ of Dictyota divaricata, 360.8 to $520.4wet\;wt.g/m^2$ of Symphyocladia linearis, and 25.9 to $470.8wet\;wt.g/m^2$ of Undaria pinnatifida. At Uljin, these numbers were 5.5 to $256.2wet\;wt.g/m^2$ of Plocamium telfarirae and 46.8 to $241.5wet\;wt.g/m^2$ of Agarum clathratum. The biomass of Sargassum coreanum and Ecklonia cava were 388.1 to $6,972.4wet\;wt.g/m^2$ and 194.9 to $958.5wet\;wt.g/m^2$, respectively, at Busan. S. coreanum and E. cava showed higher biomass compared to other seaweed at Busan. The biomass rate represented an average of 19.2 percent of the total population, ranging from 0.0 to 55.5 percent in Gangneung. In Uljin, the average was calculated as 63.8 percent, and this figure was 48.5 percent in Busan. The percentage of barren ground averaged 46.7 percent in Gangneung and 91.1 percent in Uljin. Uljin showed the highest percentage of barren ground compared to other regions. Sea urchin density appeared to be $6.0ind./m^2$ in Gangneung, $7.0ind./m^2$ in Uljin, and $2.0ind./m^2$ in Busan, with the lowest sea urchin density being that of Busan. In conclusion, the composition of species, appearance ratio, and abundance of vegetation found were similar to previous studies, but it is thought that continuous monitoring is needed due to concerns about physical and chemical pollution caused by global warming, climate change, and coastal development.

• Journal of Distribution Science
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• v.10 no.2
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• pp.53-62
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• 2012

Well-being is a reflection of current sociocultural trends that focus on the quality of life based on economic growth. Furthermore, organic food is believed to help people maintain good health and therefore leads to increased consumption of organic foods. Therefore, consumer interest in organic food is increasing, causing its market to grow, and this trend will be maintained in the future. The abuse of agricultural pesticides, gene manipulation, and bovine spongiform encephalopathy has caused consumers to worry about food safety. The well-being trend has also contributed to consumers' growing interest inorganic food and organic agricultural products. A consumer's choice offood is a complex processes affected by various factors. In particular, organic food is considered an individualistic merit good, considering the consumers' preferences related to certification policies. Therefore, various factors such as personal characteristics and sense of value could affect consumers' decisions. This research focused on an analysis of the factors influencing consumers' purchasing intention for organic food on the basis of an increase in organic food consumption. The research method was based on the theory of planned behavior (TPB). Factors such as consumer characteristics regarding food consumption, purchasing frequency, and other factors affecting purchasing intention were presented. The hypothesis was set using advanced research and stated that it is easier to forecast purchasing intentions by combining the theory of planned behavior and personal characteristics of consumer. The results show that two dimensions, attitude and perceived behavioral control, have statistically significant influence on the purchasing intention. It can be said that a positive attitude toward organic foods in particular increases the possibility of purchasing intention. In addition, consumers who consume more organic food products are more likely to have positive attitudes, and, in the past, purchasing frequency has positively influenced purchasing intention of organic foods. Consumers' negative feelings about the non-purchase of organic foods also showed a negative influence on purchasing intentions. In other words, even though consumers feel uncomfortable when not consuming organic food products, they do not try to purchase such products because of this feeling of discomfort. Furthermore, the subjective norm and the behavioral control of food-related involvement do not have a statistically significant influence on the purchasing intention or attitudes. This research verified the influence of factors related to purchasing intention. This study has several limitations: (1) even though consumers' responses can change based on the type of food, the types of food were not classified in this study; (2) future studies are necessary to analyze the attitudes of consumers on the basis of their purchasing experiences with organic foods.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.305-316
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• 2011

Recommender system is the system which, by using automated information filtering technology, recommends products or services to the customers who are likely to be interested in. Those systems are widely used in many different Web retailers such as Amazon.com, Netfix.com, and CDNow.com. Various recommender systems have been developed. Among them, Collaborative Filtering (CF) has been known as the most successful and commonly used approach. CF identifies customers whose tastes are similar to those of a given customer, and recommends items those customers have liked in the past. Numerous CF algorithms have been developed to increase the performance of recommender systems. However, the relative performances of CF algorithms are known to be domain and data dependent. It is very time-consuming and expensive to implement and launce a CF recommender system, and also the system unsuited for the given domain provides customers with poor quality recommendations that make them easily annoyed. Therefore, predicting in advance whether the performance of CF recommender system is acceptable or not is practically important and needed. In this study, we propose a decision making guideline which helps decide whether CF is adoptable for a given application with certain transaction data characteristics. Several previous studies reported that sparsity, gray sheep, cold-start, coverage, and serendipity could affect the performance of CF, but the theoretical and empirical justification of such factors is lacking. Recently there are many studies paying attention to Social Network Analysis (SNA) as a method to analyze social relationships among people. SNA is a method to measure and visualize the linkage structure and status focusing on interaction among objects within communication group. CF analyzes the similarity among previous ratings or purchases of each customer, finds the relationships among the customers who have similarities, and then uses the relationships for recommendations. Thus CF can be modeled as a social network in which customers are nodes and purchase relationships between customers are links. Under the assumption that SNA could facilitate an exploration of the topological properties of the network structure that are implicit in transaction data for CF recommendations, we focus on density, clustering coefficient, and centralization which are ones of the most commonly used measures to capture topological properties of the social network structure. While network density, expressed as a proportion of the maximum possible number of links, captures the density of the whole network, the clustering coefficient captures the degree to which the overall network contains localized pockets of dense connectivity. Centralization reflects the extent to which connections are concentrated in a small number of nodes rather than distributed equally among all nodes. We explore how these SNA measures affect the performance of CF performance and how they interact to each other. Our experiments used sales transaction data from H department store, one of the well?known department stores in Korea. Total 396 data set were sampled to construct various types of social networks. The dependant variable measuring process consists of three steps; analysis of customer similarities, construction of a social network, and analysis of social network patterns. We used UCINET 6.0 for SNA. The experiments conducted the 3-way ANOVA which employs three SNA measures as dependant variables, and the recommendation accuracy measured by F1-measure as an independent variable. The experiments report that 1) each of three SNA measures affects the recommendation accuracy, 2) the density's effect to the performance overrides those of clustering coefficient and centralization (i.e., CF adoption is not a good decision if the density is low), and 3) however though the density is low, the performance of CF is comparatively good when the clustering coefficient is low. We expect that these experiment results help firms decide whether CF recommender system is adoptable for their business domain with certain transaction data characteristics.