• Korean small business review
• /
• v.42 no.2
• /
• pp.1-22
• /
• 2020

This paper examines the effect of the adoption of international financial reporting standards(IFRS) on the financial reporting of SMEs. As IFRS is principle-based, management's discretion is needed to reflect the economic substance of transactions, and a sound internal accounting infrastructure is needed to support the judgment process. In the case of SMEs, the internal accounting infrastructure is not well established, which makes it difficult to apply principle-based accounting. The survey analysis of 132 small and medium-sized business accounting managers listed in the domestic stock market showed that the reliability of financial statements has increased due to the introduction of IFRS. In particular, SMEs perceived their financial statements as being more reliable after the adoption of IFRS than midsize companies. However, it was found that the costs and risks from the preparation of financial statements have increased significantly, and conflicts between auditors and supervisory authorities related to the application of the principles have increased. In particular, midsize companies felt the increase in conflict with auditors and supervisory authorities bigger than small companies. As for the practical difficulties in applying IFRS, both small and medium-sized companies have difficulty in interpreting the standards and lacked guidelines. In order to resolve these difficulties, it is necessary to enhance the function of Q&A by the Korea Accounting standard board(KASB) or Financial Supervisory Service(FSS). In conclusion, the reliability of the financial statements of SMEs has improved with the introduction of IFRS. However, we believe that policy and institutional support is needed in order to have better financial reporting for SMEs.

• Journal of Intelligence and Information Systems
• /
• v.28 no.3
• /
• pp.209-235
• /
• 2022

Starting from 2010, blockchain technology, along with the development of artificial intelligence, has been in the spotlight as the latest technology to lead the 4th industrial revolution. Furthermore, previous research regarding blockchain's technological applications has been ongoing ever since. However, few studies have been examined the standards for classifying the blockchain economic ecosystem from a capital market perspective. Our study is classified into a collection of interviews of software developers, entrepreneurs, market participants and experts who use blockchain technology to utilize the blockchain economic ecosystem from a capital market perspective for investing in stocks, and case study methodologies of blockchain economic ecosystem according to application fields of blockchain technology. Additionally, as a way that can be used in connection with equity investment in the capital market, the blockchain economic ecosystem classification methodology was established to form an investment universe consisting of global blue-chip stocks. It also helped construct an intelligent portfolio through quantitative and qualitative analysis that are based on quant and artificial intelligence strategies and evaluate its performances. Lastly, it presented a successful investment strategy according to the growth of blockchain economic ecosystem. This study not only classifies and analyzes blockchain standardization as a blockchain economic ecosystem from a capital market, rather than a technical, point of view, but also constructs a portfolio that targets global blue-chip stocks while also developing strategies to achieve superior performances. This study provides insights that are fused with global equity investment from the perspectives of investment theory and the economy. Therefore, it has practical implications that can contribute to the development of capital markets.

• Information Systems Review
• /
• v.25 no.1
• /
• pp.111-128
• /
• 2023

With the development of artificial intelligence technology, interest in data-based product preference estimation and personalized recommender systems is increasing. However, if the recommendation is not suitable, there is a risk that it may reduce the purchase intention of the customer and even extend to a huge financial loss due to the characteristics of the financial product. Therefore, developing a recommender system that comprehensively reflects customer characteristics and product preferences is very important for business performance creation and response to compliance issues. In the case of financial products, product preference is clearly divided according to individual investment propensity and risk aversion, so it is necessary to provide customized recommendation service by utilizing accumulated customer data. In addition to using these customer behavioral characteristics and transaction history data, we intend to solve the cold-start problem of the recommender system, including customer demographic information, asset information, and stock holding information. Therefore, this study found that the model proposed deep learning-based collaborative filtering by deriving customer latent preferences through characteristic information such as customer investment propensity, transaction history, and financial product information based on customer transaction log records was the best. Based on the customer's financial investment mechanism, this study is meaningful in developing a service that recommends a high-priority group by establishing a recommendation model that derives expected preferences for untraded financial products through financial product transaction data.

• Journal of Intelligence and Information Systems
• /
• v.23 no.1
• /
• pp.143-159
• /
• 2017

Due to the rapid development of IT in recent years, not only personal information but also the key technologies and information leakage that companies have are becoming important issues. For the enterprise, the core technology that the company possesses is a very important part for the survival of the enterprise and for the continuous competitive advantage. Recently, there have been many cases of technical infringement. Technology leaks not only cause tremendous financial losses such as falling stock prices for companies, but they also have a negative impact on corporate reputation and delays in corporate development. In the case of SMEs, where core technology is an important part of the enterprise, compared to large corporations, the preparation for technological leakage can be seen as an indispensable factor in the existence of the enterprise. As the necessity and importance of Information Security Management (ISM) is emerging, it is necessary to check and prepare for the threat of technology infringement early in the enterprise. Nevertheless, previous studies have shown that the majority of policy alternatives are represented by about 90%. As a research method, literature analysis accounted for 76% and empirical and statistical analysis accounted for a relatively low rate of 16%. For this reason, it is necessary to study the management model and prediction model to prevent leakage of technology to meet the characteristics of SMEs. In this study, before analyzing the empirical analysis, we divided the technical characteristics from the technology value perspective and the organizational factor from the technology control point based on many previous researches related to the factors affecting the technology leakage. A total of 12 related variables were selected for the two factors, and the analysis was performed with these variables. In this study, we use three - year data of "Small and Medium Enterprise Technical Statistics Survey" conducted by the Small and Medium Business Administration. Analysis data includes 30 industries based on KSIC-based 2-digit classification, and the number of companies affected by technology leakage is 415 over 3 years. Through this data, we conducted a randomized sampling in the same industry based on the KSIC in the same year, and compared with the companies (n = 415) and the unaffected firms (n = 415) 1:1 Corresponding samples were prepared and analyzed. In this research, we will conduct an empirical analysis to search for factors influencing technology leakage, and propose an early warning system through data mining. Specifically, in this study, based on the questionnaire survey of SMEs conducted by the Small and Medium Business Administration (SME), we classified the factors that affect the technology leakage of SMEs into two factors(Technology Characteristics, Organization Characteristics). And we propose a model that informs the possibility of technical infringement by using Support Vector Machine(SVM) which is one of the various techniques of data mining based on the proven factors through statistical analysis. Unlike previous studies, this study focused on the cases of various industries in many years, and it can be pointed out that the artificial intelligence model was developed through this study. In addition, since the factors are derived empirically according to the actual leakage of SME technology leakage, it will be possible to suggest to policy makers which companies should be managed from the viewpoint of technology protection. Finally, it is expected that the early warning model on the possibility of technology leakage proposed in this study will provide an opportunity to prevent technology Leakage from the viewpoint of enterprise and government in advance.

• The Journal of Korean Society for Radiation Therapy
• /
• v.20 no.2
• /
• pp.91-102
• /
• 2008

Purpose: To enlarge the efficiency of operation and establish a constituency for development of new radiotherapy treatment through database which is established by arranging and indexing radiotherapy related affairs in well organized manner to have easy access by the user. Materials and Methods: In this study, Access program provided by Microsoft (MS Office Access) was used to operate the data base. The data of radiation oncology was distinguished by a business logs and maintenance expenditure in addition to stock management of accessories with respect to affairs and machinery management. Data for education and research was distinguished by education material for department duties, user manual and related thesis depending upon its property. Registration of data was designed to have input form according to its subject and the information of data was designed to be inspected by making a report. Number of machine failure in addition to its respective repairing hours from machine maintenance expenditure in a period of January 2008 to April 2009 was analyzed with the result of initial system usage and one year after the usage. Results: Radiation oncology database system was accomplished by distinguishing work related and research related criteria. The data are arranged and collected according to its subjects and classes, and can be accessed by searching the required data through referring the descriptions from each criteria. 32.3% of total average time was reduced on analyzing repairing hours by acquiring number of machine failure in addition to its type in a period of January 2008 to April 2009 through machine maintenance expenditure. Conclusion: On distinguishing and indexing present and past data upon its subjective criteria through the database system for radiation oncology, the use of information can be easily accessed to enlarge the efficiency of operation, and in further, can be a constituency for improvement of work process by acquiring various information required for new radiotherapy treatment in real time.

• Journal of Korean Society of Forest Science
• /
• v.85 no.4
• /
• pp.596-604
• /
• 1996

This study was carried out to offer the successive method of cultivation and increase the productivity of mushroom yield with good quality through the elevation of rate of spawn development for Lentinus edodes. Studied about the analysis of current management of actural cultivation, a base of these, researched and presented for the upward method of productivity through an experiment of the high rate of spawn development and cultivation, putting first cultural environment. The results obtained were as follows ; 1. As the result of the analysis of current management in actural cultivation, many cultivators had a tendency to neglect managements of cultivation. These were reason for the deficiency of labour, funds and the lack of knowledge of cultivation, etc. 2. Water contents in bed logs according to the date of inoculation was shown as the decreasing order of 28.63%(3/12), 25.20%(3/25) and 23.19%(4/10). For the purpose of the maintenance of the water contents, the full-development of mycelium in bed logs and the dispersion of labour, the date of inoculation should be started in the early March. 3. The difference of the rate of spawn development among species was not shown, 100%(Mori 465). 98.98%(Mori 3046) on the spawn in high temperature and 98.97%(Mori 290) on the spawn in low temperature. The relative rate of spawn development was 97.70%(Mori 465), 82.45%(Mori 3046) on the spawn in high temperature and 88.87%(Mori 290) on the spawn in low temperature, it showed the difference. The spawn should be selected carefully in the future, as the spawn of cultivater's preference showed the difference for the development of mycelium. 4. The rate of spawn development following the date of inoculation was 100.0%(3/12), 98.98%(3/25) and 96.79%(4/10) on the spawn in high temperature and 99.09%(3/12), 98.97%(3/25) and 97.89% (4/10) in low temperature, it showed little difference. And the relative rate of spawn development was 97.70%(3/12), 82.45%(3/25) and 81.42%(4/10) on the spawn in high temperature and 93.27%(3/12), 89.67%(3/25) and 88.87%(4/10) that in low temperature, As the result of the relative rate, the time of inoculation of spawn should begin in the early March. 5. The height of stock logs on temporary placing should be less than 60cm at most on the surface, because of the low rate of water contents.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.14 no.2
• /
• pp.1-13
• /
• 2019

As a way to find new and innovative technologies, many companies have invested in and acquired skilled startups. Because startups are usually small in size and have a small history of past business experience, there are many risks involved in acquiring them as they have limited technical skills and business feasibility verification methods. Thus, venture capital plays an important role in discovering and investing competitive startups. While Independent Venture Capital generally values financial returns, Corporate Venture Capital, which plays investment roles in the firm, values business synergies with the parent company from a strategic perspective. In an industry sector where development of technology is rapid and whether new technology is held determines a company's competitiveness, existing companies incorporate startups with innovative technologies into their investment portfolios, collaborate together, and take over for comprehensive cooperation. In addition, new investments and acquisitions are carried out through the management of portfolio companies to obtain and utilize industry information. In this paper, major U.S. companies listed in the U.S. verified their investment activities through corporate venture capital and their impact on parent companies and startups through regression, while the parent company's acquisition performance was analyzed through an event study based on a stock price analysis. The criteria for startup were defined as companies with less than 12 years of experience, and the analysis showed that the parent companies with corporate venture capital with a larger number of investments actively take over startups. In addition, increasing corporate venture capital's financial investment activities shows a negative impact on the parent companies' acquisition activities, and the acquisition performance increased when the parent companies took over startups in its portfolio.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.18 no.5
• /
• pp.63-75
• /
• 2023

This study conducted empirical analysis on the factors affecting the investment performance of 205 domestic venture funds (with a total liquidation amount of 7.25 trillion KRW) newly formed from 2007 to 2017 and completely liquidated as of the end of 2022. Due to the nature of private equity funds, obtaining empirical data is extremely challenging, especially for data post-COVID-19 era liquidations. Nevertheless, despite these challenges, it is meaningful to analyze the impact on the investment returns of domestic venture funds using the most recent data available from the past 10 years. This study categorized the factors influencing venture fund performance into external environmental factors and internal factors. External environmental factors included "economic cycles," "stock markets," "venture markets," and "exit markets," while internal factors included the fund management company's capabilities in terms of "experience," "professional personnel," and "assets under management (AUM)." The fund structure was also categorized into "fund size" and "fund length" for comparative analysis. In summary, the analysis yielded the following results: First, the 3-year government bond yield, which represents economic cycles well, was found to have a significant impact on fund performance. Second, the average 3-month KOSDAQ index return after fund formation had a statistically significant positive effect on fund performance. Third, the number of IPOs, indicating the competition intensity at the time of venture fund liquidation, was shown to have a negative effect on fund performance. Fourth, it was observed that the larger the AUM of the fund management company, the better the fund's returns. Finally, venture fund returns showed variations depending on the year of formation (Vintage). Therefore, when individuals consider investing in venture funds, it is considered a highly effective investment strategy to construct an investment portfolio taking into account not only external environmental factors and internal fund factors but also the vintage year.

• The Korean Journal of Financial Management
• /
• v.25 no.2
• /
• pp.165-190
• /
• 2008

The degree of informational asymmetry relating to the expiration of index derivatives is usually increased as an expiration day of index derivatives approaches. The increase in the degree of informational asymmetry may have some effects on trading behavior of investors. To examine what the effects look like, 'life cycle of index derivatives' in this study is defined as three adjacent periods around expiration day: pre-expiration period(a week before the expiration day), post-expiration period(a week after the expiration day), and remaining period. It is inspected whether stock investor's trading behavior is changed according to the life cycle of KOSPI200 derivatives and what the reason of the changing behavior is. We have four results. First, trading behavior of each investor group is categorized into three patterns: ㄱ-pattern, L-pattern and U-pattern. The level of trading activity is low for pre-expiration period and normal for other periods in the ㄱ-pattern. L-pattern means that the level of trading activity is high for post-expiration period and normal for other periods. In the U-pattern, the trading activity is reduced for remaining period compared to other periods. Second, individual investors have ㄱ-pattern of trading large stocks according to the life cycle of KOSPI200 index futures while they show U-pattern according to the life cycle of KOSPI200 index options. Their trading behavior is consistent with the prediction of Foster and Viswanathan(1990)'s model for strategic liquidity investors. Third, trading pattern of foreign investors in relation to life cycle of index derivatives is partially explained by the model, but trading pattern of institutional investors has nothing to do with the predictions of the model.

• Journal of Intelligence and Information Systems
• /
• v.24 no.3
• /
• pp.157-176
• /
• 2018

The purpose of this research is to develop a detection model for companies designated as administrative issue in KOSDAQ market using financial data. Administration issue designates the companies with high potential for delisting, which gives them time to overcome the reasons for the delisting under certain restrictions of the Korean stock market. It acts as an alarm to inform investors and market participants of which companies are likely to be delisted and warns them to make safe investments. Despite this importance, there are relatively few studies on administration issues prediction model in comparison with the lots of studies on bankruptcy prediction model. Therefore, this study develops and verifies the detection model of the companies designated as administrative issue using financial data of KOSDAQ companies. In this study, logistic regression and decision tree are proposed as the data mining models for detecting administrative issues. According to the results of the analysis, the logistic regression model predicted the companies designated as administrative issue using three variables - ROE(Earnings before tax), Cash flows/Shareholder's equity, and Asset turnover ratio, and its overall accuracy was 86% for the validation dataset. The decision tree (Classification and Regression Trees, CART) model applied the classification rules using Cash flows/Total assets and ROA(Net income), and the overall accuracy reached 87%. Implications of the financial indictors selected in our logistic regression and decision tree models are as follows. First, ROE(Earnings before tax) in the logistic detection model shows the profit and loss of the business segment that will continue without including the revenue and expenses of the discontinued business. Therefore, the weakening of the variable means that the competitiveness of the core business is weakened. If a large part of the profits is generated from one-off profit, it is very likely that the deterioration of business management is further intensified. As the ROE of a KOSDAQ company decreases significantly, it is highly likely that the company can be delisted. Second, cash flows to shareholder's equity represents that the firm's ability to generate cash flow under the condition that the financial condition of the subsidiary company is excluded. In other words, the weakening of the management capacity of the parent company, excluding the subsidiary's competence, can be a main reason for the increase of the possibility of administrative issue designation. Third, low asset turnover ratio means that current assets and non-current assets are ineffectively used by corporation, or that asset investment by corporation is excessive. If the asset turnover ratio of a KOSDAQ-listed company decreases, it is necessary to examine in detail corporate activities from various perspectives such as weakening sales or increasing or decreasing inventories of company. Cash flow / total assets, a variable selected by the decision tree detection model, is a key indicator of the company's cash condition and its ability to generate cash from operating activities. Cash flow indicates whether a firm can perform its main activities(maintaining its operating ability, repaying debts, paying dividends and making new investments) without relying on external financial resources. Therefore, if the index of the variable is negative(-), it indicates the possibility that a company has serious problems in business activities. If the cash flow from operating activities of a specific company is smaller than the net profit, it means that the net profit has not been cashed, indicating that there is a serious problem in managing the trade receivables and inventory assets of the company. Therefore, it can be understood that as the cash flows / total assets decrease, the probability of administrative issue designation and the probability of delisting are increased. In summary, the logistic regression-based detection model in this study was found to be affected by the company's financial activities including ROE(Earnings before tax). However, decision tree-based detection model predicts the designation based on the cash flows of the company.