• The Journal of the Convergence on Culture Technology
• /
• v.9 no.1
• /
• pp.101-109
• /
• 2023

According to data released by the Covid 19 Self-Employed Emergency Response Committee, 95.6% of small business sales due to Covid 19 have decreased over the past two years, and the damage has further increased due to social distancing for quarantine. However, as all social distancing guidelines have rebeen lifted, and the commercial district has been revitalized, the Seoul Metropolitan Government is pushing for a project to foster local brand commercial districts so that small business owners or prospective founders who have closed their businesses due to the prolonged COVID-19. Therefore, this study propose the model that recommends alley commercial districts suitable for founders among the five alley commercial districts selected for the project to foster local brand commercial districts in Seoul. The Seoul Metropolitan Government's local brand alley commercial recommendation system recommends major population age groups and major industries in the commercial district by combining the population perspective model using Xgboost and the commercial district characteristic model using Decision Tree.

• Korea Trade Review
• /
• v.48 no.1
• /
• pp.83-126
• /
• 2023

The revenue histogram of venture businesses is shifting from bell-shaped normal distribution to power-law distribution, which implies that the fitness landscape of the venture businesses ecosystem is changing to be more rugged terrain. We argue that the firm should adopt both exploitation (fast follower) and exploration (or first mover) strategies not to get stuck in local maxima in the rugged fitness landscape from the complex system perspective. By designing and performing agent-based modeling simulation experiments which consist of three types of agents (new technologies, entrepreneurs, and consumers), we demonstrated that the ambidexterity strategy showed the highest performance score in three of four different environment except 'Fast Widening' case where the exploitation strategy showed the highest performance score under low technology appropriation and fast disruptive technology development speed. By investigating the financial and other statistics of 617 top venture businesses who have earned 100B won or higher annual revenue, we concluded that 82% and 9% of firms are bent on the exploitation and exploration strategy.

• Journal of Intelligence and Information Systems
• /
• v.23 no.1
• /
• pp.23-46
• /
• 2017

Although there have been cases of evaluating the value of specific companies or projects which have centralized on developed countries in North America and Europe from the early 2000s, the system and methodology for estimating the economic value of individual technologies or patents has been activated on and on. Of course, there exist several online systems that qualitatively evaluate the technology's grade or the patent rating of the technology to be evaluated, as in 'KTRS' of the KIBO and 'SMART 3.1' of the Korea Invention Promotion Association. However, a web-based technology valuation system, referred to as 'STAR-Value system' that calculates the quantitative values of the subject technology for various purposes such as business feasibility analysis, investment attraction, tax/litigation, etc., has been officially opened and recently spreading. In this study, we introduce the type of methodology and evaluation model, reference information supporting these theories, and how database associated are utilized, focusing various modules and frameworks embedded in STAR-Value system. In particular, there are six valuation methods, including the discounted cash flow method (DCF), which is a representative one based on the income approach that anticipates future economic income to be valued at present, and the relief-from-royalty method, which calculates the present value of royalties' where we consider the contribution of the subject technology towards the business value created as the royalty rate. We look at how models and related support information (technology life, corporate (business) financial information, discount rate, industrial technology factors, etc.) can be used and linked in a intelligent manner. Based on the classification of information such as International Patent Classification (IPC) or Korea Standard Industry Classification (KSIC) for technology to be evaluated, the STAR-Value system automatically returns meta data such as technology cycle time (TCT), sales growth rate and profitability data of similar company or industry sector, weighted average cost of capital (WACC), indices of industrial technology factors, etc., and apply adjustment factors to them, so that the result of technology value calculation has high reliability and objectivity. Furthermore, if the information on the potential market size of the target technology and the market share of the commercialization subject refers to data-driven information, or if the estimated value range of similar technologies by industry sector is provided from the evaluation cases which are already completed and accumulated in database, the STAR-Value is anticipated that it will enable to present highly accurate value range in real time by intelligently linking various support modules. Including the explanation of the various valuation models and relevant primary variables as presented in this paper, the STAR-Value system intends to utilize more systematically and in a data-driven way by supporting the optimal model selection guideline module, intelligent technology value range reasoning module, and similar company selection based market share prediction module, etc. In addition, the research on the development and intelligence of the web-based STAR-Value system is significant in that it widely spread the web-based system that can be used in the validation and application to practices of the theoretical feasibility of the technology valuation field, and it is expected that it could be utilized in various fields of technology commercialization.

• Korean Journal of Culture and Social Issue
• /
• v.21 no.4
• /
• pp.617-647
• /
• 2015

The purposes of this study was to develop a valid scale measuring organization-related anxiety and to use this scale to examine the relation of organizational anxiety to demographic variables, job satisfaction and organizational committment. A series of studies were conducted to develop a scale for organizational anxiety. Initially, the 97 items were adopted by expert ratings. A exploratory factor analysis with a sample of 435 workers yielded a preliminary version of organizational anxiety scale with 28 items. Subsequently, a confirmatory factor analysis was conducted with a sample of 566 workers, leaving 20 items. The final version of the organizational anxiety scale consisted of 4 sub-factors: perception of future uncertainty, perception of locus of control, interpersonal anxiety, and perception of alternatives. In this study, the examined demographic characteristics included sex, age, type of occupation, type of industry, occupational position, monthly income and educational level. Organizational effectiveness was composed of job satisfaction and organizational commitment. As mediators, organizational culture, life satisfaction, self efficacy, and social support were explored. The negative relationship was observed between organizational anxiety and organizational effectiveness. The results showed the significant differences in organizational anxiety by demographic characteristics. The mediators were explored for the relationship between organizational anxiety and job satisfaction and between organizational anxiety and organizational commitment. The negative relationship between organizational anxiety and job satisfaction was mediated by the group culture, the developmental culture, the rational culture, life satisfaction, self-efficacy, and social support. Individuals with the higher level of these mediators reported greater job satisfaction even if they experienced organizational anxiety. The partial mediation effect of the group culture, the developmental culture, the rational culture, life satisfaction, and social support was observed on the negative relationship between organizational anxiety and organizational commitment. These results implies that job satisfaction and organizational commitment can be improved with the interventions on organizational cultures, self-efficacy, and social support despite the presence of organizational anxiety. Based on these results, the implication and limitations of this study and the directions for future research discussed.

• Journal of Korea Entertainment Industry Association
• /
• v.14 no.7
• /
• pp.633-640
• /
• 2020

The purpose of this study was to research the prevalence and related factors for the life care of knee osteoarthritis in Koreans agricultural and fishery population. Among the agricultural and fishery population over the age of 50, 816 people were chosen to analyze the prevalence of knee osteoarthritis and the prevalence odds ratio of social demographic or health related factors based on the primitive data of the 5th National Health and Nutrition Examination Survey (2010-2012). The prevalence of knee osteoarthritis was 26.3% and, in demographic terms, female, elders, and individuals with low level of educational attainment and monthly income showed higher prevalence of knee osteoarthritis. In health related factors, nonsmokers and people with higher BMI showed higher prevalence of knee osteoarthritis. The present cross-sectional study showing the prevalence ratio and the prevalence odd ratio revealed a high incidence of knee osteoarthritis in Korean agricultural and fishery populations.

• Journal of Industrial Convergence
• /
• v.21 no.6
• /
• pp.1-11
• /
• 2023

The purpose of this study is to verify the factors affecting corporate bankruptcy by using non-financial information of companies invested by credit guarantee institutions. In this study, 594 companies (525 normal companies, 69 insolvent companies) invested in by the Korea Credit Guarantee Fund from March 2014 to the end of December 2022 were selected as samples. Non-financial information of companies was divided into founder characteristics information, company characteristics information, and corporate investment information, and cross-analysis and logistic regression analysis were conducted. As a result of the cross-analysis, personal credit rating, industry, and joint investment were selected as significant variables, and logistic regression analysis was conducted for those variables, and two variables, personal credit rating and joint investment, were selected as important factors for bankruptcy. In business management, the founder's personal credit and the importance of joint investment in investment support were found out. It will help to minimize bankruptcy if institutions that support investment in SMEs reflect these results in their screening and systematically build cooperative relationships with private investment institutions. It is hoped that this study will provide an opportunity to pay more attention to the factors that affect the bankruptcy of companies that receive direct investment from public institutions.

• Journal of Fisheries and Marine Sciences Education
• /
• v.10 no.2
• /
• pp.139-161
• /
• 1998

This thesis includes a study on the legal regulation, the system and formalities on the control of illegal fishing. And the author analyzed the details of the lists of illegal fishing controlled by fishing patrol vessels of Ministry of Maritime Affairs and Fisheries from 1994 to 1996 in adjacent sea area of Korea. The results are summarized as follows ; 1. The fishing patrol vessels controlled total 826 cases in 2,726 days of 292 voyages by 17 vessels in 1994, total 1,086 cases in 3,060 days of 333 voyages by 18 vessels in 1995 and total 933 cases in 3,126 days of 330 voyages by 19 vessels in 1996. 2. The fishing period of illegal fishing was generally concentrated from April to September. But year after year, illegal fishing was scattered throughout the year. 3. The most controlled sea area of illegal fishing was the south central sea area in the sea near Port of Tongyeong. The sea area occupied about 36~51% of totality and the controlled cases were gradually increased every year. The second was the south western sea area in the sea near Port of Yosu. The sea area occupied about 18-27% and the controlled cases were a little bit increased every year. The third was the south eastern sea area in the sea near Pusan. The sea area occupied about 13~23% and the controlled cases were gradually decreased year by year. 4. The most controlled kind of illegal fishing was the small size bottom trawl. This occupied about 81-95% of totality and the controlled cases were gradually increased year by year. The second was the medium size bottom trawl. This occupied about 4-7% and the controlled cases were gradually decreased year by year. The third was the trawl of the coastal sea, this occupied about 2~4% and the controlled cases were a little bit decreased every year. 5. The most controlled address of illegal fishing manager was Pusan city which occupied about 33-51% of totality. The second was Cheonnam which occupied about 24-29%. The third was Kyungnam which occupied about 16~35%. 6. The most controlled violation of regulations was Article 57 of the Fisheries Act which occupied about 56-64% of totality. The second was Article 23 of Protectorate for Fisheries Resources which occupied about 21-36%. And the controlled cases by it were gradually increased every year.

• Korean Security Journal
• /
• no.51
• /
• pp.103-124
• /
• 2017

The purpose of this study is to analyze regional clusters and discrimination on size and sector of private security in national 16 areas in 2015. The results of the study using hierarchical cluster analysis and discriminant analysis are as follows. First, we can classify national 16 areas into 3 clusters, such as Large Area(1), Medium Area(2), and Small Area(3) according to the size of private security. The discriminant functions D for each cluster is as follows: (1) Large Area(1) = -383.981 + (.108 ${\times}$ number of security companies) + (.016 ${\times}$ number of guards), (2) Medium Area(2) = -35.570 + (.029 ${\times}$ number of security companies) + (.005 ${\times}$ number of guards), and (3) Small Area(3) = -5.381 + (.012 ${\times}$ number of security companies) + (.002 ${\times}$ number of guards). Second, we can classify national 16 areas into 3 clusters, such as Large Area(1), Medium Area(2), and Small Area(3) according to the sector of private security. The discriminant function D for each cluster is as follows: (1) Large Area(1) = -2224.402 + (-.562 ${\times}$ facilities security) + (1.245 ${\times}$ protection security) + (171.142 ${\times}$ convoy security) + (-2.722 ${\times}$ electronic security) + (2.020 ${\times}$ special security), (2) Medium Area(2) = -4.762 + (.052 ${\times}$ facilities security) + (.063 ${\times}$ protection security) + (-3.819 ${\times}$ convoy security) + (.110 ${\times}$ electronic security) + (-.165 ${\times}$ special security), and (3) Small Area(3) = -125.742 + (-.009 ${\times}$ facilities security) + (.432 ${\times}$ protection security) + (5.748 ${\times}$ convoy security) + (5.530 ${\times}$ electronic security) + (-.901 ${\times}$ special security).

• Knowledge Management Research
• /
• v.24 no.1
• /
• pp.245-271
• /
• 2023

The change to the data economy requires a new analysis beyond ordinary research in the management field. Data matching refers to a technique or processing method that combines data sets collected from different samples with the same population. In this study, statistical matching was performed using random hotdeck and Mahalanobis distance functions using 2020 Survey of Korea Venture Firms and 2020 Korea Innovation Survey datas. Among the variables used for statistical matching simulation, the industry and the number of workers were set to be completely consistent, and region, business power, listed market, and sales were set as common variables. Simulation verification was confirmed by mean test and kernel density. As a result of the analysis, it was confirmed that statistical matching was appropriate because there was a difference in the average test, but a similar pattern was shown in the kernel density. This result attempted to expand the spectrum of the research method by experimenting with a data matching research methodology that has not been sufficiently attempted in the management field, and suggests implications in terms of data utilization and diversity.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.9 no.1
• /
• pp.119-132
• /
• 2014

This study analyzed the failure prediction model of the firms listed on the KOSDAQ by considering whether there are embezzlement, malpractice and the largest shareholder changes or not. This study composed a total of 166 firms by using two-paired sampling method. For sample of failed firm, 83 manufacturing firms which delisted on KOSDAQ market for 4 years from 2009 to 2012 are selected. For sample of normal firm, 83 firms (with same item or same business as failed firm) that are listed on KOSDAQ market and perform normal business activities during the same period (from 2009 to 2012) are selected. This study selected 80 financial ratios for 5 years immediately preceding from delisting of sample firm above and conducted T-test to derive 19 of them which emerged for five consecutive years among significant variables and used forward selection to estimate logistic regression model. While the precedent studies only analyzed the data of three years immediately preceding the delisting, this study analyzes data of five years immediately preceding the delisting. This study is distinct from existing previous studies that it researches which significant financial characteristic influences the insolvency from the initial phase of insolvent firm with time lag and it also empirically analyzes the usefulness of data by building a firm's fail prediction model which considered embezzlement/malpractice and the largest shareholder changes as dummy variable(non-financial characteristics). The accuracy of classification of the prediction model with dummy variable appeared 95.2% in year T-1, 88.0% in year T-2, 81.3% in year T-3, 79.5% in year T-4, and 74.7% in year T-5. It increased as year of delisting approaches and showed generally higher the accuracy of classification than the results of existing previous studies. This study expects to reduce the damage of not only the firm but also investors, financial institutions and other stakeholders by finding the firm with high potential to fail in advance.