• 한국벤처창업학회:학술대회논문집
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• 2008.04a
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• pp.179-208
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• 2008

In this research, an empirical analysis was performed to determine the correlation between management performance and R&D investment for domestic venture businesses in each industry. Specifically, an empirical analysis for each industry was attempted not only to clarify the general hypothesis on the relationship between management performance and R&D investment for venture businesses but also to demonstrate that differences exist for each industry. Empirical analysis was conducted for eight industries with respect to the $2002{\sim}2006$ panel data extracted as investigative results from the "Investigation Report on Science and Technology R&D Activities" published by the Ministry of Science and Technology. Industrial classification was limited to the middle-level classification (2-digit) in the Korea Standard Industry Code (KSIC) owing to the limited number of panels. Although this research only verified the overall positive effect of R&D activities and funds for existing research on corporate value or productivity and management performance, it was able to document the difference for each individual industry and each business size unlike existing research.Furthermore, the reliability of the research results was enhanced by targeting companies that have been continuously conducting R&D and management activities using consistent 5-year panel data in the analysis. Again, this was something that existing research did not have. Finally, through the use of recent data from 2002 after the IMF economic crisis up to 2006 in the empirical analysis, this research proposed the problems due to the prevailing circumstances at the time of entering the advanced nation stage based on an empirical analysis; the prevailing problems during the pursuit of advanced nation status before the IMF crisis broke out were not tackled. The key empirical analysis yielded several results. First, capital and size of the labor force have a positive correlation with the management performance for the entire company or the venture business. This applies to all eight industries as the subjects of the analysis. Second, although the number of years since a company has been established can have positive or negative correlation with management performance for the entire company or venture business in specific industries, a definite overall trend cannot be identified. Third, R&D investment can be said to have an overall positive effect on corporate management performance. Fourth, the size of the research staff cannot be said to be a factor unilaterally affecting the management performance of the entire company or the venture business. Fifth, the number of years a research institute has been in operation, which was assumed to have a positive effect on the management performance of a company because of the accumulated R&D know-how -- definitely acts as a positive factor contributing to the management performance of a company.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.3 no.1
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• pp.1-28
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• 2008

In this research, an empirical analysis was performed to determine the correlation between management performance and Empirical Research on the R&D investment for domestic venture businesses in each industry. Specifically, an empirical analysis for each industry was attempted not only to clarify the general hypothesis on the relationship between management performance and R&D investment for venture businesses but also to demonstrate that differences exist for each industry. Empirical analysis was conducted for eight industries with respect to the $2002{\sim}2006$ panel data extracted as investigative results from the "Investigation Report on Science and Technology R&D Activities" published by the Ministry of Science and Technology. Industrial classification was limited to the middle-level classification (2-digit) in the Korea Standard Industry Code (KSIC) owing to the limited number of panels. Although this research only verified the overall positive effect of R&D activities and funds for existing research on corporate value or productivity and management performance, it was able to document the difference for each individual industry and each business size unlike existing research. Furthermore, the reliability of the research results was enhanced by targeting companies that have been continuously conducting R&D and management activities using consistent 5-year panel data in the analysis. Again, this was something that existing research did not have. Finally, through the use of recent data from 2002 after the IMF economic crisis up to 2006 in the empirical analysis, this research proposed the problems due to the prevailing circumstances at the time of entering the advanced nation stage based on an empirical analysis; the prevailing problems during the pursuit of advanced nation status before the IMF crisis broke out were not tackled. The key empirical analysis yielded several results. First, capital and size of the labor force have a positive correlation with the management performance for the entire company or the venture business. This applies to all eight industries as the subjects of the analysis. Second, although the number of years since a company has been established can have positive or negative correlation with management performance for the entire company or venture business in specific industries, a definite overall trend cannot be identified. Third, R&D investment can be said to have an overall positive effect on corporate management performance. Fourth, the size of the research staff cannot be said to be a factor unilaterally affecting the management performance of the entire company or the venture business. Fifth, the number of years a research institute has been in operation, which was assumed to have a positive effect on the management performance of a company because of the accumulated R&D know-how -- definitely acts as a positive factor contributing to the management performance of a company.

• Korean Security Journal
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• no.29
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• pp.7-34
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• 2011

Achieving high-level technology in fields such as IT-related industry, semiconductors, mobile phones, LCD, automobile, shipbuilding, etc., Korea has become an international market leader in those fields. In results, there are the increasing numbers of technology leakage attempts in various manners. Recently, technology leakages are not limited to illegal industrial espionage, but also occur during usual corporate proceedings such as technology transfer, joint research and M&A. In fact, there was a technology leakage issue in the M&A between Ssangyong Motors of Korea and Shanghai Motors of China. Current M&A regulations of Korea are not independent laws, but are spread over various laws, such as commercial law, Capital Markets and the Financial Investment Services Act, Foreign Trade Act, etc. This paper focuses on whether the current Korean regulations regarding M&A are able to effectively restrict the leakage of major information of corporate during M&A and seeks the complements.

• International Area Studies Review
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• v.22 no.3
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• pp.175-200
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• 2018

Since the 1990s rising intangible asset has become one of the main driving forces of investment stagnation and jobless growth in advanced income countries. We investigate how does the impact of firms' profitability on employment growth depends on the intangibility and whether the relationship between profitability and tangibility has complementarity. With data on Korean firms over the period 1988~2017 we investigate the effects of intangibility and profitability on employment growth based on the econometric approach of system GMM. The empirical results are as follows. (1) the profit rate has gradually led to lower employment growth, while it had positive effect on employment before the period of financial crisis. The estimated values and signs of profit rate coefficients varies from traditional industries to high/medium tech. industries. (2) the effect of increasing asset intangibility ratio on employment growth is negative and statistically significant. (3) the coefficients of interaction term of (profit rate ${\times}$ intangibility ratio) have significant negative values. It means employment effect of profit rate are becoming higher(lower) as intangibility ratio is at the lower(higher) level; profits rate and intangibility are not complement with each other. The results imply that to boost employment industrial policy which has the capacity to coordinate business intangibility is preferred to expansionary demand policy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.11C
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• pp.1178-1188
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• 2002

Local Loop Unbundling(LLU) has been understood as the way of facilitate the competition on the access and the local telephone service market. There are major benefits of stimulating the competition in the local service, avoiding access network duplication and reducing in environmental disruption. However, LLU has several disadvantages such as removing incentives for building alternative access networks, undermining existing investment in alternative access networks, introducing new substantial costs to the industry and requiring prolonged and detailed regulatory intervention. The economic effects of LLU generally will be different according to the special situation of each countries and the object of LLU. In case of EU, most of countries have already introduced and implemented LLU. But EU can't expect the economic effects on LLU emerged in the early stage of introducing it and faced with dilemma. To be realized the successful implementation of LLU, I think, it is required to be reviewed about the main issues such as the problem of regulation, the reasonable level of LLU pricing and the technical & operational problems.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.5
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• pp.67-80
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• 2022

This study was conducted to derive policy measures such as fostering and supporting by examining the actual conditions of domestic startups. The subject of this study was the start-ups located in Seongnam-si, where Pangyo Techno Valley, which is the highest-level innovation cluster in Korea and is evaluated as a start-up mecca. Startups were defined as startups under 7 years old based on new technologies such as IT, BT, and CT, and the subjects of the study were selected. This can be seen as a step forward from previous research in that it embodies the concept of a startup that was previously abstract in a quantitatively measurable way. As a result of the analysis, about 94% of startups are distributed in the so-called "Death Valley" growth stage, and startups above scale-up, which means full-scale growth beyond BEP, account for about 6%. appeared to be occupied. He cited the problem of start-up funds as the biggest difficulty in the early stages of startups, and cited the loan evaluation method that prioritizes sales or collateral in raising funds as the biggest problem. In addition, start-ups rated the access to private investment capital such as VC, AC, and angel investors at a low level compared to policy funds, which are public funds. Most startups showed a lot of interest in overseas expansion, and they chose matching overseas investors such as overseas VCs as the biggest support for overseas expansion. The overall competitiveness in the overseas market was 49.6 points, which is less than 50 points out of 100, indicating that the overall competitiveness was somewhat inferior. It was analyzed that public support and investment in overseas sales channels (sales channels, distribution networks, etc.) should be prioritized along with enhancement of technological competitiveness in order for domestic startups to increase their competitiveness in overseas markets as well as in the domestic market.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1623-1636
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• 2009

A currently domestic governmental R&D business is early to 100. And this is each managed individually in 15 professional organizations of research and management by characteristics of a business. For this Reason, A redundant investment issue regarding national R&D occurs, and an issue regarding efficiency of R&D investment by insufficiency of systematic R&D research project and result management is continuously raised. Ministry of Education Science and Technology establishing National Science & Technology Information Service(NTIS) in order to solve these issues. NTIS is the national R&D Portal System which can support efficiency of research and development to result utilization in planning of national research and development. As data of the same meaning are named particularly in each organizations, and that made to different data types, It is an issue to be difficult to achieve high level qualify, accuracy of integrated data in case of integration of distributed data like NTIS In this paper We consider integrated DB constructions and Information Linking of R&D Participants/Projects/Results information in a NTIS system for data qualify Improvement, and then We analyze the cause of the data quality problem, and we propose the improvement plan for data quality elevation of NTIS system.

• The Journal of the Convergence on Culture Technology
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• v.4 no.3
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• pp.247-252
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• 2018

The problem of the environment is urgently coming to the world as a problem that humanity must solve. In particular, Korea is directly affected by air pollution and marine pollution due to its geopolitical position with China, and is also exposed to a great deal of pollution due to air, water, soil, and weather. In this situation, due to the disconnection between the management domain / service (system) related to the environment, the ability to quickly identify causes and cope with situations in the event of environmental pollution or disasters is weak, and duplication and investment are being faced. The development of a service platform for smart environment disaster management is designed to detect environmental disasters in an early stage through the management of smart environment disaster management at the national level, It will be a way to predict complex environmental disasters.

• Korean small business review
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• v.31 no.4
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• pp.67-93
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• 2009

The purpose of this paper is to explore the relations between financial constraints and dividend smoothing of innovative small and medium sized enterprises(SMEs) listed on Korea Securities Market and Kosdaq Market of Korea Exchange. The innovative SMEs is defined as the firms with high level of R&D intensity which is measured by (R&D investment/total sales) ratio, according to Chauvin and Hirschey (1993). The R&D investment plays an important role as the innovative driver that can increase the future growth opportunity and profitability of the firms. Therefore, the R&D investment have large, positive, and consistent influences on the market value of the firm. In this point of view, we expect that the innovative SMEs can adjust dividend payment faster than the noninnovative SMEs, on the ground of their future growth opportunity and profitability. And also, we expect that the financial unconstrained firms can adjust dividend payment faster than the financial constrained firms, on the ground of their financing ability of investment funds through the market accessibility. Aivazian et al.(2006) exert that the financial unconstrained firms with the high accessibility to capital market can adjust dividend payment faster than the financial constrained firms. We collect the sample firms among the total SMEs listed on Korea Securities Market and Kosdaq Market of Korea Exchange during the periods from January 1999 to December 2007 from the KIS Value Library database. The total number of firm-year observations of the total sample firms throughout the entire period is 5,544, the number of firm-year observations of the dividend firms is 2,919, and the number of firm-year observations of the non-dividend firms is 2,625. About 53%(or 2,919) of these total 5,544 observations involve firms that make a dividend payment. The dividend firms are divided into two groups according to the R&D intensity, such as the innovative SMEs with larger than median of R&D intensity and the noninnovative SMEs with smaller than median of R&D intensity. The number of firm-year observations of the innovative SMEs is 1,506, and the number of firm-year observations of the noninnovative SMEs is 1,413. Furthermore, the innovative SMEs are divided into two groups according to level of financial constraints, such as the financial unconstrained firms and the financial constrained firms. The number of firm-year observations of the former is 894, and the number of firm-year observations of the latter is 612. Although all available firm-year observations of the dividend firms are collected, deletions are made in the case of financial industries such as banks, securities company, insurance company, and other financial services company, because their capital structure and business style are widely different from the general manufacturing firms. The stock repurchase was involved in dividend payment because Grullon and Michaely (2002) examined the substitution hypothesis between dividends and stock repurchases. However, our data structure is an unbalanced panel data since there is no requirement that the firm-year observations data are all available for each firms during the entire periods from January 1999 to December 2007 from the KIS Value Library database. We firstly estimate the classic Lintner(1956) dividend adjustment model, where the decision to smooth dividend or to adopt a residual dividend policy depends on financial constraints measured by market accessibility. Lintner model indicates that firms maintain stable and long run target payout ratio, and that firms adjust partially the gap between current payout rato and target payout ratio each year. In the Lintner model, dependent variable is the current dividend per share(DPS_t), and independent variables are the past dividend per share(DPS_t-1) and the current earnings per share(EPS_t). We hypothesized that firms adjust partially the gap between the current dividend per share(DPS_t) and the target payout ratio(Ω) each year, when the past dividend per share(DPS_t-1) deviate from the target payout ratio(Ω). We secondly estimate the expansion model that extend the Lintner model by including the determinants suggested by the major theories of dividend, namely, residual dividend theory, dividend signaling theory, agency theory, catering theory, and transactions cost theory. In the expansion model, dependent variable is the current dividend per share(DPS_t), explanatory variables are the past dividend per share(DPS_t-1) and the current earnings per share(EPS_t), and control variables are the current capital expenditure ratio(CEA_t), the current leverage ratio(LEV_t), the current operating return on assets(ROA_t), the current business risk(RISK_t), the current trading volume turnover ratio(TURN_t), and the current dividend premium(DPREM_t). In these control variables, CEA_t, LEV_t, and ROA_t are the determinants suggested by the residual dividend theory and the agency theory, ROA_t and RISK_t are the determinants suggested by the dividend signaling theory, TURN_t is the determinant suggested by the transactions cost theory, and DPREM_t is the determinant suggested by the catering theory. Furthermore, we thirdly estimate the Lintner model and the expansion model by using the panel data of the financial unconstrained firms and the financial constrained firms, that are divided into two groups according to level of financial constraints. We expect that the financial unconstrained firms can adjust dividend payment faster than the financial constrained firms, because the former can finance more easily the investment funds through the market accessibility than the latter. We analyzed descriptive statistics such as mean, standard deviation, and median to delete the outliers from the panel data, conducted one way analysis of variance to check up the industry-specfic effects, and conducted difference test of firms characteristic variables between innovative SMEs and noninnovative SMEs as well as difference test of firms characteristic variables between financial unconstrained firms and financial constrained firms. We also conducted the correlation analysis and the variance inflation factors analysis to detect any multicollinearity among the independent variables. Both of the correlation coefficients and the variance inflation factors are roughly low to the extent that may be ignored the multicollinearity among the independent variables. Furthermore, we estimate both of the Lintner model and the expansion model using the panel regression analysis. We firstly test the time-specific effects and the firm-specific effects may be involved in our panel data through the Lagrange multiplier test that was proposed by Breusch and Pagan(1980), and secondly conduct Hausman test to prove that fixed effect model is fitter with our panel data than the random effect model. The main results of this study can be summarized as follows. The determinants suggested by the major theories of dividend, namely, residual dividend theory, dividend signaling theory, agency theory, catering theory, and transactions cost theory explain significantly the dividend policy of the innovative SMEs. Lintner model indicates that firms maintain stable and long run target payout ratio, and that firms adjust partially the gap between the current payout ratio and the target payout ratio each year. In the core variables of Lintner model, the past dividend per share has more effects to dividend smoothing than the current earnings per share. These results suggest that the innovative SMEs maintain stable and long run dividend policy which sustains the past dividend per share level without corporate special reasons. The main results show that dividend adjustment speed of the innovative SMEs is faster than that of the noninnovative SMEs. This means that the innovative SMEs with high level of R&D intensity can adjust dividend payment faster than the noninnovative SMEs, on the ground of their future growth opportunity and profitability. The other main results show that dividend adjustment speed of the financial unconstrained SMEs is faster than that of the financial constrained SMEs. This means that the financial unconstrained firms with high accessibility to capital market can adjust dividend payment faster than the financial constrained firms, on the ground of their financing ability of investment funds through the market accessibility. Futhermore, the other additional results show that dividend adjustment speed of the innovative SMEs classified by the Small and Medium Business Administration is faster than that of the unclassified SMEs. They are linked with various financial policies and services such as credit guaranteed service, policy fund for SMEs, venture investment fund, insurance program, and so on. In conclusion, the past dividend per share and the current earnings per share suggested by the Lintner model explain mainly dividend adjustment speed of the innovative SMEs, and also the financial constraints explain partially. Therefore, if managers can properly understand of the relations between financial constraints and dividend smoothing of innovative SMEs, they can maintain stable and long run dividend policy of the innovative SMEs through dividend smoothing. These are encouraging results for Korea government, that is, the Small and Medium Business Administration as it has implemented many policies to commit to the innovative SMEs. This paper may have a few limitations because it may be only early study about the relations between financial constraints and dividend smoothing of the innovative SMEs. Specifically, this paper may not adequately capture all of the subtle features of the innovative SMEs and the financial unconstrained SMEs. Therefore, we think that it is necessary to expand sample firms and control variables, and use more elaborate analysis methods in the future studies.

• Proceedings of the Safety Management and Science Conference
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• 2011.04a
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• pp.731-746
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• 2011

The successful and sustainable growth of SMEs depends on their ability of strengthen their competitiveness in quality and cost and service more than anything else as a fundamental of operation. Among these key competitive factors of SMEs, quality is the most critical factor in manufacturing business fields. Because quality strongly influence cost and service performance on this manufacturing business field. There are many different ways to improve the quality performance but it needs proper management decision to choose the best way what can maximize outputs with minimum inputs. And it needs effective measurement methods and some indicators to analysis the quality performance properly. The quality cost is one of the simplest key indicators to measure the quality performance and the effectiveness of quality related management decisions. The major purpose of this study is to diagnose the categorized current level of actual quality cost of local SMEs to maximize their quality management effectiveness through comparing their level with others what's expressed in early studies. In this study, through survey on local SMEs, we found that their average annual quality cost ratio versus turnover - Total amount of annual quality cost divided by annual turnover - is around 3.69% excluded some SME's performances what have different quality control measures with others. And we found some results what corresponded with the early studies on the correlations between those categorized quality costs factors and some discrepancies between some of the literature model and the early case study results as follows. There were negative correlations between the Prevention costs and the External failure costs, and the Appraisal costs and the External failure costs, and there was positive correlation between the Appraisal costs and Internal failure costs same as early studies. But, we couldn't found any strong negative correlations between the Cost of control - Preventive costs & Appraisal costs - and the Cost of Failure of control - Internal & External failure costs -. It reveals not only the lack of effectiveness on their preventive or appraisal activities but also it can reveal there were so many effective ways to prevent the failure costs properly such as some innovative investment on Factory automation includes Error Proofing and more preventive actions to improve the effectiveness of the typical management methods likes CE (Concurrent Engineering), APQP (Advanced Product Quality Planning), FMEA (Failure Mode & Effect Analysis) etc.