• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.2
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• pp.62-68
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• 2019

The growth and employment effects of R&D investment were analyzed according to business size, export value and manufacturing sectors so as to suggest improvement directions for effective industry policies. The effect of R&D investment was considered simultaneously from the two perspectives of growth and employment effect, and the causality analysis was carried out by using a path analysis. The result of the path analysis confirmed significant differences in the growth effect of R&D investment depending on business size. However, the effect of increasing employment was difficult to obtain statistically significant results for any various combinations of business size and export value. This is a mixture of directions for the effects of R&D investment on employment, which could be due to the failure to consider appropriate time lags between investment and effect. Efficiency analysis by industry sectors confirmed significant differences in efficiency depending on business size, but differences depending on export value were difficult to identify. In order to derive improvement policy by industry sector according to business size and export value, the direction of selective support policy and universal support policy was derived for six industry groups by combining the return to scale in the efficiency analysis and R&D concentration. Hirschman-Herfindahl index is used for calculating R&D concentration.

• Management & Information Systems Review
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• v.27
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• pp.53-69
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• 2008

In this paper we analyse performance of value strategy and moving average method among the non-financial listed companies whose fiscal year ends at December in the Korean Stock Exchange between 1996 and 2005. And we analyse combination investment performance of value investment and moving average method. After the analysis objective enterprises divide with the value stock and the growth stock, in accordance with moving average method we divide ascending stock and descending stock. And we compose 6 portfolios with combination of value stock, growth stock, ascending stock and descending stock. Using the difference of investment performance of these portfolios, when fundamental analysis and technical analysis method all considering we measure investment performance. The major findings of this research are as follows: First, the value strategy of buying value stocks and selling growth stocks were effective in the long-term investment. Second, using the moving average method, technical analysis were effective in the case of the short-term investment. Third, the portfolios combined fundamental analysis and technical analysis were more effective than investment performance of technical analysis.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.2
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• pp.104-110
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• 2017

When evaluating effectiveness of a R&D program, there is a tendency to simply compare the performances of the beneficiaries before and after the program or to compare the differences in the performances of the beneficiaries and the non-beneficiaries before-after the program. However, these ways of evaluating effectiveness of a program have some problems because they can not differentiate between complement effect, which facilitates corporate R&D investment, and substitute effect, which, literally, substitutes corporate R&D investment. Therefore, these problems could bring about wrong policies concerning R&D programs. In this paper, a new approach using path analysis is suggested as a means to overcome these problems and it is utilized, as an application, to evaluate the effectiveness of Plant Engineering Program conducted by Ministry of Trade, Industry & Energy, Korea. First, the direct impact of government R&D investment on corporate R&D investment is analyzed, through which it is identified which of crowding-in effect (complement effect) and crowding-out effect (substitute effect) is dominant. Next, the direct effect of government R&D investment on corporate performance and the direct effect of corporate R&D investment on corporate performance is analyzed respectively. Finally, by combining the two previous analysis, the total effect of government R&D investment on corporate performance is identified. As a result, it turns out that, in Plant Engineering Program, crowding-in effect is more dominant than crowding-out effect and that Plant Engineering Program has definitely positive effect on the beneficiary in terms of corporate performance indirectly and directly.

• Journal of the Korea Safety Management & Science
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• v.3 no.4
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• pp.1-9
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• 2001

Cost-benefit analysis was investigated to propose the analysis method of the effect of investment and the optimum investment level of safety management cost for preventing gas accident in the B governor station. From five classifications of safety management costs consisting of cost items with similar characters and potential accident costs calculated by risk assessments(FMEA/HAZOP), we found that the order of the benefit(the reduction cost of the potential accident cost) was the instrument increase and repair cost > the safety checking and inspection cost > the labor and training cost > the safety equipment and corresponding cost > the research and development cost. As the benefit was increased with increasing the investment cost, the effect of investment was increased with decreasing the Investment cost. As a result, the optimum safety management cost was estimated and the investment level was analyzed by the model of optimum investment level.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.845-853
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• 2021

The stock market shows the current health of an economy, and investment performance represents it. This study aims to clarify the relationship between financial behavior and investment decisions as well as its impact on investment results. Determine the influence of behavioral factors on individual investors' investment decisions and investment performance on the Vietnam stock market. The study surveyed 250 investors. The main analytical methods used are Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM). Research results show that Heuristic, Prospect, Market, and Herding directly and positively affect investment decision-making. Besides, the above factors have a direct and positive effect on investment performance. In particular, the Prospect factor has the strongest influence on investment decision-making and investment performance. The major findings of this study suggested that the important role of Heuristic, Prospect, Market, and Herding on Investment Decision-making and Investment Performance. Prospect had the strongest impact on Investment decision-making (β = 0.275). Heuristic had the second strongest impact (β = 0.257), then Herding (β = 0.202), and finally Market (β = 0.189) had the weakest effect. Regarding Investment Performance, the Prospect factor has a higher degree of impact than Heuristic Herding and Market.

• Journal of Korean Society for Quality Management
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• v.18 no.1
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• pp.84-95
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• 1990

The objective of this study is to understand the effect of measurement-related investment. That is, this study aims at verifying the correlation between the measurement-related investment and inferiority rate of products by statistical analysis. The samples of this study are 376 industrial companies in Korea, and the research data was analysed on inferiority state of industrial companies with a measurement standard laboratory. The analysis was made by the elementary statistics, the correlation analysis and the regression analysis. The results are summarized as follows : First, the inferioriy rate of the industrial companies with a measurement standard laboratory was relatively lower than that of the other companies without the laboratory by statistical significance. Second, the increment on measurement-related investment had a negative correlation with the increment of inferiority rate, and the increase of measurement-related investment showed decrease of the inferiority rate by regression analysis.

• Korea Trade Review
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• v.46 no.2
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• pp.337-354
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• 2021

Several previous studies have not been able to derive consistent research results on the impact of the level of corruption in local countries on foreign direct investment. Therefore, in order to suggest that this study should consider the relative level of corruption rather than the level of absolute corruption, 1) first, examine the moderating effect of the absolute level of corruption on the determinants of foreign direct investment, and 2) examine the moderating effect of the relative corruption on the determinants of foreign direct investment. This study collected 9-year data from 2012 to 2020 based on the Corruption Perceptions Index (CPI) published by Transparency International. A total of 549 observations (country-year) from 82 countries were sampled and a generalized estimation equation (GEE) analysis was performed. As a result of empirical analysis, it was found that the moderating effect of absolute corruption did not appear, whereas the moderating effect of relative corruption reversed the negative (-) relationship between cultural distance and foreign direct investment into a positive (+) relationship. Based on these empirical results, this study suggest that Korean companies need to consider the relative level of corruption with Korea instead of the absolute level of corruption of the investee when conducting foreign direct investment.

• Journal of Convergence for Information Technology
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• v.11 no.1
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• pp.175-182
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• 2021

The purpose of this study is to establish the direction of industrial policy by comparing the employment inducement effect on the related industries of the digital bio-healthcare industry. The analysis data used the three-year input-output table measured by the Bank of Korea. First, the research method was rewritten into 7 major industries to compare statistical data by period. Second, the Bank of Korea's industry-related analysis methodology was utilized. Third, the weight was reflected and compared by employment, production, and investment sectors of the digital bio-healthcare industry. As a result of the analysis, first, the employment sector had a higher effect than the average of the entire industry, second, the production sector was low, and third, the investment sector required investment in the service sector. The conclusions drawn from the analysis showed that direct investment and continuous investment are required in the employment sector, the development of professional manpower is urgent, and direct investment and long-term investment are effective in the production sector.

• International Commerce and Information Review
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• v.11 no.2
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• pp.111-126
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• 2009

This study analysed determinants of Foreign Direct Investment to ASEAN+ 3 member nations using panel data for which cross-sectional data are combined with time series data. The data for the analysis included the amount of FDI, GDP, and indexes of economic independence. This study collected data from six nations(Indonesia, Malaysia, Philippines, Singapore, Thailand, Vietnam) whose data were easily available, China and Japan from 2003 to 2007 and analysed them. The results are summarized as follows: Using the pooled OLS method, we found Model 2 had the highest explanatory power whose adjusted R-squared was 89.4%, which accounted for about 89% of foreign investment. Using the fixed effect model, Model 2 had the highest explanatory power whose adjusted R-squared was 96.8%, which accounted for about 97% of foreign investment. Using the probability effect model, Model 5 had the highest explanatory power, but in respect to its statistical significance, only GDP was 1% significant and the rest variables had no significance.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.7
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• pp.407-413
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• 2003

Before expanding of distribution automation application to distribution network, we must examine whether there are economical effect. Investment expense for distribution automation can be divided into facility investment expense, maintenance expense, communication expense, investment expense etc. Effect of distribution automation can classify by effect that can convert into money and effect that can not convert into money. Representative effect is outage time decrease effect, distribution line loss decrease effect, main transformer upload effect, distribution line upload effect, work environment improvement effect of lineman and so on. This paper studied economical effect and break-even Point for investment expense by using data that acquire in KEPCO's distribution network.