• The Korean Journal of Applied Statistics
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• v.35 no.2
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• pp.229-250
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• 2022

Since the publication of Markowitz's (1952) mean-variance portfolio model, research on portfolio optimization has been conducted in many fields. The existing mean-variance portfolio model forms a nonlinear convex problem. Applying Dantzig's linear programming method, it was converted to a linear form, which can effectively reduce the algorithm computation time. In this paper, we proposed a Dantzig perturbation portfolio model that can reduce management costs and transaction costs by constructing a portfolio with stable and small (sparse) assets. The average return and risk were adjusted according to the purpose by applying a perturbation method in which a certain part is invested in the existing benchmark and the rest is invested in the assets proposed as a portfolio optimization model. For a covariance estimation, we proposed a Gaussian kernel weight covariance that considers time-dependent weights by reflecting time-series data characteristics. The performance of the proposed model was evaluated by comparing it with the benchmark portfolio with 5 real data sets. Empirical results show that the proposed portfolios provide higher expected returns or lower risks than the benchmark. Further, sparse and stable asset selection was obtained in the proposed portfolios.

• Journal of Industrial Convergence
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• v.21 no.11
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• pp.13-27
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• 2023

This study aims to contribute to the reduction of the failure rate and social costs resulting from business failures by analyzing factors that affect the insolvency of social enterprises, as the role of social enterprises is increasing in our economy. The data used in this study were classified as normal and insolvent companies among social enterprises (including prospective social enterprises) that were established between 2009 and 2018 and received credit guarantees from credit guarantee institutions as of the end of June 2022. Among the collected data, 439 social enterprises with available financial information were targeted; 406 (92.5%) were normal enterprises, and 33 (7.5%) were insolvent enterprises. Through a literature review, eight non-financial factors commonly used for insolvency prediction were selected. The cross-analysis results showed that four of these factors were significant. Logistic regression analysis revealed that two variables, including corporate credit rating and the personal credit rating of the representative, were significant. Financial factors such as debt ratio, sales operating profit rate, and total asset turnover were used as control variables. The empirical analysis confirmed that the two independent variables maintained their influence even after controlling for financial factors. Given that government-led support and development policies have limitations, there is a need to shift policy direction so that various companies aspiring to create social value can enter the social enterprise sector through private and regional initiatives. This would enable the social economy to create an environment where local residents can collaborate to realize social value, and the government should actively support this.

• Journal of Korea Technology Innovation Society
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• v.19 no.3
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• pp.465-482
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• 2016

Previous researches have introduced various ways to analyze the impact of standardization on innovation while the works are not only small in number but based on interview or case study. This paper addresses the impact of standardization activities within South Korean industries on technological innovation applying an empirical analysis of standardization activities and technological innovation. Drawing on Korean Industrial Standards Classification from panel data of 2003 to 2012, we employed corresponding data of each industrial classification: Number of standards, Accumulated number of standards, Number of patents applied in Korea, Sales, Operational profit, Intangible asset, and R&D invest. In the first model, we run panel data models employing the number of patents applied in Korea as an independent variable, and the number of standards, accumulated number of standards, sales, and operational profit as dependent variables to observe industrial impacts upon the relationship between standards and patents, along with time lagged consideration. The result shows that number of standards are revealed to have a negative influence on patent applications in the year of research, and no significant effect appears for the next two years while positive effect shows up on the third year. Meanwhie, accumulated number of standards turned out to have positive effects on patent applications in Korea. This implies it takes time for innovation subjects to embrace newly established standards while having a significant amount of positive effect on technological innovation in the long term. In the second model, we use canonical correlation analysis to find industrial-wide characteristics. The result of this model is equivalent to the result of panel data analysis except in a few industries, where some industry specific characteristics appear. The implications of our results present that Korean policy makers have to take account of industrial effects on standardization to promote technological innovation.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.1-42
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• 2009

In a knowledge-based society, a firm's intellectual capital represents the wealth of ideas and ability to innovate, which are indispensable elements for the future growth. Therefore, the intellectual capital is evidently recognized as the most valuable asset in the organization. Considered as intangible asset, intellectual capital is the basis based on which firms can foster their sustainable competitive advantage. One of the essential components of the intellectual capital is a social capital, indicating the firm's individual members' ability to build a firm's social networks. As such, social capital is a powerful concept necessary for understanding the emergence, growth, and functioning of network linkages. The more social capital a firm is equipped with, the more successfully it can establish new social networks. By providing a shared context for social interactions, social capital facilitates the creation of new linkages in the organizational setting. This concept of "person-environment fit" has long been prevalent in the management literature. The fit is grounded in the interaction theory of behavior. The interaction perspective has a fairly long theoretical tradition, beginning with proposition that behavior is a function of the person and environment. This view asserts that neither personal characteristics nor the situation alone adequately explains the variance in behavioral and attitudinal variables. Instead, the interaction of personal and situational variables accounts for the greatest variance. Accordingly, the person-environment fit is defined as the degree of congruence or match between personal and situational variables in producing significant selected outcomes. In addition, information systems acceptance factors enable organizations to build large electronic communities with huge knowledge resources. For example, the Intranet helps to build knowledge-based communities, which in turn increases employee communication and collaboration. It is vital since through active communication and collaborative efforts can employees build common basis for shared understandings that evolve into stronger relationships embedded with trust. To this aim, the electronic communication network allows the formation of social network to be more viable to rapid mobilization and assimilation of knowledge assets in the organizations. The purpose of this study is to investigate: (1) the impact of person-environment fit(person-job fit, person-person fit, person-group fit, person-organization fit) on social capital(network ties, trust, norm, shared language); (2) the impact of information systems acceptance factors(availability, perceived usefulness, perceived ease of use) on social capital; (3) the impact of social capital on personal performance(work performance, work satisfaction); and (4) the mediating role of social capital between person-environment fit and personal performance. In general, social capital is defined as the aggregated actual or collective potential resources which lead to the possession of a durable network. The concept of social capital was originally developed by sociologists for their analysis in social context. Recently, it has become an increasingly popular jargon used in the management literature in describing organizational phenomena outside the realm of transaction costs. Since both environmental factors and information systems acceptance factors affect the network of employee's relationships, this study proposes that these two factors have significant influence on the social capital of employees. The person-environment fit basically refers to the alignment between characteristics of people and their environments, thereby resulting in positive outcomes for both individuals and organizations. In addition, the information systems acceptance factors have rather direct influences on the social network of employees. Based on such theoretical framework, namely person-environment fit and social capital theory, we develop our research model and hypotheses. The results of data analysis, based on 458 employee cases are as follow: Firstly, both person-environment fit(person-job fit, person-person fit, person-group fit, person-organization fit) and information systems acceptance factors(availability perceived usefulness, perceived ease of use) significantly influence social capital(network ties, norm, shared language). In addition, person-environment fit is a stronger factor influencing social capital than information systems acceptance factors. Secondly, social capital is a significant factor in both work satisfaction and work performance. Finally, social capital partly plays a mediating role between person-environment fit and personal performance. Our findings suggest that it is vital for firms to understand the importance of environmental factors affecting social capital of employees and accordingly identify the importance of information systems acceptance factors in building formal and informal relationships of employees. Firms also need to reflect their recognition of the importance of social capital's mediating role in boosting personal performance. Some limitations arisen in the course of the research and suggestions for future research directions are also discussed.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.12
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• pp.425-435
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• 2018

The purpose of this study is to investigate the cultural value as well as business value of Juk-Bang-Ryeum(fishing instrument made by bamboo weir) by the investigation of remains in Gyeongnam Sacheon area and reviewing various historical literatures. The research will contribute to make back data necessary for the registration of World Heritage(UNESCO) and Globally Important Agricultural Heritage Systems(FAO). Fisheries, along with agriculture, have been great significance in human history. In particular, the Fisheries has been considered very important industry due to the geopolitical characteristics of our country surrounded by the sea. We can imagine may types of fishing practices and instruments at the agricultural age. Nonetheless, there are a few fishery heritages such as collecting and hunting tools that remains today. Fortunately, there are many Juk-Bang-Ryeum which is actually operate now from the past 500 years ago at the The Sacheon and Namhae areas. We could found some literature records about it in the historical ancient literatures. We could also infer that Juk-Bang-Ryeum was an important fishery resource of the country for a long time. It was built on the basis of scientific principles to capture fishes using the rapid tide of the natural geological straits, and it prove the wisdom of our ancestors. We also could found some unique cultural heritages that was important to the local community. Naturally, it has been managed as an important asset for the residents. In addition to such historical and humanistic values, it also has business and educational value. It can be useful to understand scientific fishery principles as well as fishery experience field. It has business value as an important tourism resource in the region in connection with historical relics and geological environment resources. In conclusion, it is a valuable asset to be handed down as a valuable cultural heritage.

• Information Systems Review
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• v.25 no.2
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• pp.145-162
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• 2023

Asset management is a complex and difficult field that requires insight into numerous variables and even human psychology. Thus, it has traditionally been the domain of professionals, and these services have been expensive to obtain. Changes are taking place in these markets, and the driving force is the digital revolution, so-called the fourth industrial revolution. Among them, the Robo-Advisor service using artificial intelligence technology is the highlight. The reason is that it is possible to popularize investment advisory services with convenient accessibility and low cost. This study aims to clarify what factors are critically important when selecting robo-advisors for service users and providers in Korea, and what perception differences exist in the selection factors between user and provider groups. The framework of the study was based on the marketing mix 4C model, and the design and analysis of the model used Delphi survey and AHP. Through the study design, 4 main criteria and 15 sub-criteria were derived, and the findings of the study are as follows. First, the importance of the four main criteria was in the order of customer needs > customer convenience > customer cost > customer communication for both groups. Second, looking at the 15 sub-criteria, it was found that investment purpose coverage, investment propensity coverage, fee level and accessibility factors were the most important. Third, when comparing between groups, the user group found that the fee level and accessibility factors were the most important, and the provider group recognized the investment purpose coverage and investment propensity coverage factors as important. This study derived useful implications in practice. First, when designing for the spread of the robo-advisor service, the basis for constructing a user-oriented system was prepared by considering the priority of importance according to the weight difference between the four main criteria and the 15 sub-criteria. In addition, the difference in priority of each sub-criteria shown in the group comparison and the cause of the sub-criteria with large weight differences were identified. In addition, it was suggested that it is very important to form a consensus to resolve the difference in perception of factors between those in charge of strategy and marketing and system development within the provider group. Academically, it is meaningful in that it is an early study that presented various perspectives and perspectives by deriving a number of robo-advisor selection factors. Through the findings of this study, it is expected that a successful user-oriented robo-advisor system can be built and spread in Korea to help users.

• The Journal of Engineering Geology
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• v.17 no.1 s.50
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• pp.15-25
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• 2007

In general, the life and asset casualties that occur due to landslide or slope failure in urban areas are larger than that in rural areas. In order to reduce the casualties, a slope management program is necessary to categorize slopes based on properties and to manage them systematically. The slope management system is the establishment of the data base for the geological and geotechnical factor according to slope stability, and the utilization of the data base to manage slopes. The suitable system must develop to slopes in urban area through the survey, analysis and evaluation process. Based on the above necessity, the slope management program which is applicable to slope management in an urban area has been developed at Hwangryung Mt. in Busan as a target area. The developed slope management program has various functions such as slope ID number of each slope or sub-region of a mountain, making a slope data sheet, analysis and grouping of slope stability, and establishment of a data base. The slope management program is constructed by use of GIS, and the survey, test and analysis data according to all slopes can be input and edited into the program. The program can also be utilized practically by end users due to the convenient input, edition printing, management and operation of slope data. Therefore, the slope management system has been established on the application of the developed program in Busan which is located in slope area. As the system is widely applied to other cities, the slope in urban area can be managed systematically and the slope hazards can be minimized.

• Journal of Korean Clinical Health Science
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• v.2 no.1
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• pp.1-16
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• 2014

Purpose. For a more efficient hospital management, this study aims to provide basic data so that the hospital management and staff in charge of hospital administration may systematically classify and collect hospital information, by analyzing the ordinary characters of an upper-level general hospital system and its common-type balance sheet, common-type profit and loss statement and financial ratio. Methods. By using information about an upper-level general hospital in C Province, provided by Alio(www.alio.go.kr), a public organization information provision site, Health Insurance Review & Assessment Service(www.hira.or.kr) and Ministry of Health and Welfare(www.mw.go.kr), this study analyzed 3 year's data from 2010 to 2012 and provided basic data by analyzing the ordinary characters of an upper-level general hospital system, and its common-type balance sheet, common-type profit and loss statement and financial ratio. Results. After analyzing the ordinary characters, common-type balance sheet, common-type proft and loss statement and financial ration of this general hospital, based on the 2010 to 2012 data, this study came to the following conclusions. Firstly, out of all the 1,069 hospital staff, there were 272 doctors working for 24 medical departments, out of whom the majority was 33 physicians. Most of the nurses were third-class ones, and about 2,000 outpatients and 600 inpatients on average were treated per day. Secondly, as a result of analyzing the common-type balance sheet, this study discovered that intangible assets out of fixed assets accounted for 41%, the majority, out of which usable and profitable donation asset buildings were of great importance, and the liquid assets increased more in 2012 than 2011. In the financial structure, the ratio of liquid liabilities was over 50% out of all the liabilities in 2012, and the ratio of purchase payables was high as well. The ratio of fixed liabilities reached up to 40%, out of which the retirement benefit appropriation fund was quite high. The capital was over 80%, but the surplus was in a deficit state. Compared to the capital, the ratio of total liabilities was about 90%, which indicates the financial structure of this general hospital was vulnerable. Thirdly, as a result of analyzing the common-type profit and loss statement, this study found out that the medical profits from inpatients were higher than profits from outpatients. The material cost was related to the medical quality of this general hospital, and it was as high as 30% out of the total costs and was about 45% of the labor cost. This general hospital showed 10% in the ratio of non-medical profits, and it seemed because of government subsidies. The ratios of medical profits and current net income were gradually changing for the better in 2012, compared to 2011. Lastly, as a result of analyzing the financial ratio, it was found that the liquidity ratio kept decreasing, from 110.7% in 2010 and 102.0% in 2011 to 77.2% in 2012. Besides, it was analyzed that the liquidity ratio and the net working capital ratio greatly decreased, while the quick ratio and the liquid ratio kept decreasing. Conclusions. 1. It is necessary to take the risk management into more consideration, and particularly, it is needed to differentiate and manage the levels of risk in detail. 2. By considering the fact that investments into hospital infrastructures were mostly based on liabilities, it is needed to deal with the scale of losses when evaluating risks. 3. By reflecting the character that investments into hospital infrastructures were based on liabilities, it is necessary to consider the ratio of ordinary profits as well as the ratio of operating profits to sales, and it is also important to consider sales productivity factors, such as the sales amount per a sickbed, by comparing them with other hospitals. As for limitations of this study, there may be some problems in terms of data interpretation because of the lack of information about the number of inpatients and the number of outpatients per year, which are needed for the break-even point analysis. Besides, to suggest a direction for the improvement of hospital management through analyses, non-financial factors should be reflected, such as the trend of economy, medical policies, and politic backgrounds. However, this study only focused on the common-type balance sheet, common-type profit and loss statement and financial ratio, so this study is actually limited to generalizing all the factors by analyzing public data only.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.171-191
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• 2020

This study focused on digital music, which is the most valuable cultural asset in the modern society and occupies a particularly important position in the flow of the Korean Wave. Digital music was collected based on the "Gaon Chart," a well-established music chart in Korea. Through this, the changes in the ranking of the music that entered the chart for 73 weeks were collected. Afterwards, patterns with similar characteristics were derived through time series cluster analysis. Then, a descriptive analysis was performed on the notable features of each pattern. The research process suggested by this study is as follows. First, in the data collection process, time series data was collected to check the ranking change of digital music. Subsequently, in the data processing stage, the collected data was matched with the rankings over time, and the music title and artist name were processed. Each analysis is then sequentially performed in two stages consisting of exploratory analysis and explanatory analysis. First, the data collection period was limited to the period before 'the music bulk buying phenomenon', a reliability issue related to music ranking in Korea. Specifically, it is 73 weeks starting from December 31, 2017 to January 06, 2018 as the first week, and from May 19, 2019 to May 25, 2019. And the analysis targets were limited to digital music released in Korea. In particular, digital music was collected based on the "Gaon Chart", a well-known music chart in Korea. Unlike private music charts that are being serviced in Korea, Gaon Charts are charts approved by government agencies and have basic reliability. Therefore, it can be considered that it has more public confidence than the ranking information provided by other services. The contents of the collected data are as follows. Data on the period and ranking, the name of the music, the name of the artist, the name of the album, the Gaon index, the production company, and the distribution company were collected for the music that entered the top 100 on the music chart within the collection period. Through data collection, 7,300 music, which were included in the top 100 on the music chart, were identified for a total of 73 weeks. On the other hand, in the case of digital music, since the cases included in the music chart for more than two weeks are frequent, the duplication of music is removed through the pre-processing process. For duplicate music, the number and location of the duplicated music were checked through the duplicate check function, and then deleted to form data for analysis. Through this, a list of 742 unique music for analysis among the 7,300-music data in advance was secured. A total of 742 songs were secured through previous data collection and pre-processing. In addition, a total of 16 patterns were derived through time series cluster analysis on the ranking change. Based on the patterns derived after that, two representative patterns were identified: 'Steady Seller' and 'One-Hit Wonder'. Furthermore, the two patterns were subdivided into five patterns in consideration of the survival period of the music and the music ranking. The important characteristics of each pattern are as follows. First, the artist's superstar effect and bandwagon effect were strong in the one-hit wonder-type pattern. Therefore, when consumers choose a digital music, they are strongly influenced by the superstar effect and the bandwagon effect. Second, through the Steady Seller pattern, we confirmed the music that have been chosen by consumers for a very long time. In addition, we checked the patterns of the most selected music through consumer needs. Contrary to popular belief, the steady seller: mid-term pattern, not the one-hit wonder pattern, received the most choices from consumers. Particularly noteworthy is that the 'Climbing the Chart' phenomenon, which is contrary to the existing pattern, was confirmed through the steady-seller pattern. This study focuses on the change in the ranking of music over time, a field that has been relatively alienated centering on digital music. In addition, a new approach to music research was attempted by subdividing the pattern of ranking change rather than predicting the success and ranking of music.