• Journal of the Korean Society for Aviation and Aeronautics
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• v.16 no.3
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• pp.50-57
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• 2008

This paper analyse the economic inducement effects of aviation industry using Input-Output Model. For measuring economic inducement effects of aviation industry on korean economy, this paper divides air transport industry as two - manufacturing industry and service industry. we also use Input-Output Table of year 1990 through 2003 from Bank of Korea. Empirical results tells that aviation manufacturing industry have high product inducement effects to national economy although its low value-added coefficient such as 0.486 for aviation manufacturing industry and 0.447 for aviation service industry. public R&D doesn't have much effect to each of aviation industries.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2000.11a
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• pp.33.2-42
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• 2000

This study probes the necessity of establishing a logistic free zone in Port of Busan. It considers the economic effects of establishing the logistic free zone of Busan Port, and suggests policy prescriptions for introducing the free zone system and improving the logistics functions of Busan Port. Using input-output table data, the regression analysis was able to provide a quantitative prediction on effects of making the Busan Port a tariff-free zone. Influence for the regional economy due to the enforcement of the free zone system this research found that a strong positive effects should be expected on the Busan regional economy once the logistic free zone would be set up at the Port of Busan. The positive economic effects on Busan regional industries might be further strengthened if the value-added logistics function of Busan Port could be supplemented by linking to the hinterland of Busan Port.

• Journal of Information Technology Services
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• v.17 no.2
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• pp.49-67
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• 2018

This study compares economic impact between Software and Medical industry through Input Output Table by Bank of Korea. We classify Software and Medical industry by The ninth Korea Standard Industry Classification and use linkage effects, value added inducement coefficient, and labor inducement coefficient to analyze economic impact. First, software and medical industry have different linkage effects between backward and forward. Second, They have higher value added inducement coefficient than average of all industry. Third, They not only have higher labor inducement coefficient than average of all industry but also simillar effect on labor induction. According to the result of this study, software and medical industry have high economic impact on Korea economy, and therefore are intensively fostered by policy support.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.50
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• pp.313-322
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• 1999

EVA(Economic Value Added) is a management performance evaluation tool that determines whether a business is earning more than its true cost of capital. Leading corporations like Coca-Cola, AT&T and Briggs&Stratton have set up EVA measurement systems throughout their organizations. EVA reflects opportunity cost of equity ignored in calculating accounting profit and emphasizes the efficiency of capital employed by measuring how much the manufacturing and selling activities produce the economic profit in excess of cost of gross capital. In this paper, we define the concept of EVA and present an example to show the usefulness of EVA.

• Journal of the Korean Home Economics Association
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• v.42 no.7
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• pp.131-143
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• 2004

The purpose of this paper is to prepare a satellite account of the household sector that is reflected in the current national income account by approving the economic activities of unpaid household labor as production activity and estimating its value. The study produced three results. First, as different methods of evaluation can be useful according to different study goals or the contents of related policies, it is unreasonable to present a single result for estimating unpaid household labor. This study, therefore, presented the values of housework based on 5 methods, ranging from 124 to 150 trillion won. Second, to input the added value of household production from the fixed capital (household durable goods), this study adopted the declining balance method used in the Korea National Statistical Office. As a result, the total consumption of fixed capital was estimated at approximately 18.8 trillion won. Third, the total added value of unpaid household labor was estimated to range from 143 to 169 trillion wens. The amount is a production value excluded from the SNA which needs to be formed as a separate household satellite account. The ratio of this total value added was 30-35.4 percents to the 1999 GDP in Korea(477 trillion wens).

• The Journal of Information Systems
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• v.20 no.3
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• pp.187-207
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• 2011

As the IT labor captures an increasing proportion of the total labor, it is important to analyze the contribution of IT labor to national economy. Although there has been abundant research about the effect of IT investments, it is difficult to find a research about IT labor's economic contribution. Most prior studies on the effect of IT investment have focused on the effect of IT capital investment. This paper empirically explores whether and how IT labor makes contribution to Korean economy. And also this paper examines the economic contribution of IT experts and semi-experts in Korean industries over the 2000 to 2007 period, using production function framework and panel data set for 24 industries constructed from 'Input-Output table' and 'Research on Wage Structure Survey'. Based on the full sample of 120 observations, this study finds that a 1% increase in IT labor wage is associated with 0.042190% increase in added value. In the case of non-manufacturing industries on the sample of 50 observations, this study finds that a 1% increase in IT labor wage is associated with 0.074908% increase in added value. And in the case of IT experts (separated from IT semi-experts), this study finds that a 1% increase in IT expert's labor wage is associated with 0.013957% increase in added value of all industry. This study provides implication for policy makers and managers. The results suggests that non-manufacturing industries can capture further benefits by increasing investment in IT labor. Building on this study, future research should examine the impact of IT labor at a more detailed industry level and the firm level.

• Journal of Navigation and Port Research
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• v.41 no.4
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• pp.243-250
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• 2017

Seaports are not longer considered to be single entities for which the main activity is to load and discharge cargo, but rather as fundamental hubs within a complex supply chain serving global production networks. From a public perspective, they hold a key role in terms of their economic impact at the local, regional and national level by generating value added activity and employment. This issue is becoming increasingly pivotal for ports and their stakeholders. The objective of the study is to estimate a regression model of the value added activity and employment figures of 17 Italian ports for which there are no publications available. Concerning port system reform in Italy, the research intends to provide policy makers with a tool to measure the effects produced by ports and their importance to local communities and regions. The paper finds that in all Italian ports, the direct effects are larger than the indirect effects, and the bigger socio-economic effects are found in the biggest ports.

• Journal of Korea Port Economic Association
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• v.24 no.2
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• pp.265-287
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• 2008

This paper studies the economic effects of port-liquid freight by focusing on Ulsan port and its regional economic effects. The direct industrial effects of port-liquid freight are analysed to be an increase in about 1billion dollars' worth of production of the regional port-logistic industry, an increase in about 0.22billion dollars' worth of value-added of the industry, and the creation of about 2,600 employment in the industry. Including the indirect effects, the total effects on Ulsan regional economy are estimated to be an increase in about 1.9billion dollars worth of production, an increase in about 0.51billion dollars' worth of value-added and an increase in about 6,442 employment.

• East Asian Economic Review
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• v.21 no.4
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• pp.295-315
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• 2017

This paper derives the gravity equation with intermediate goods trade. We extend a standard monopolistic competition model to incorporate intermediate goods trade, and show that the gravity equation with intermediates trade is identical to the one without it except in that gross output should be used as the output measure instead of value added. We also show that the output elasticity of trade is significantly underestimated when value added is used as the output measure. This implies that with the conventional gravity equation, the contribution of output growth can be substantially underestimated and the role of trade costs reduction can be exaggerated in explaining trade expansion, as we demonstrate for the case of Korea's trade growth between 1995 and 2007.

• The Journal of the Korea Contents Association
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• v.18 no.2
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• pp.216-230
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• 2018

In this paper, we analyze the economic ripple effects of technology related to the unmanned aerial vehicle industry by applying industry association analysis. Specifically, the effects of employment creation, value added inducement, sensitivity coefficient, and influence coefficient can be calculated, and implications for the analysis result are presented. As a result, the employment inducement effect was confirmed to be 10.017 persons per 1 billion won of investment. The value added inducement effect was much higher than the other manufacturing industry average (employment inducement coefficient: 2.285, value added inducement coefficient: 0.581) when the 1 won budget was added, resulting in 0.9771 won added value. In the unmanned aerial vehicle industry, the coefficient of sensitivity, which means the front chain effect, is 0.7870, which is lower than the manufacturing average (sensitivity coefficient 1.125), and the coefficient of influence, which means the backward chain effect, is 1.161, which is higher than the manufacturing average (influence coefficient: 1.116). Therefore, it is classified as the final demand manufacturing industry. This means that the unmanned aerial vehicle industry is an industry that is less affected by economic fluctuations and can be interpreted as an industry with a greater economic impact than other sectors. Based on these data, it can be used to establish the R&D investment direction policy of the unmanned aerospace industry.