• Journal of Korea Technology Innovation Society
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• v.21 no.4
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• pp.1296-1312
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• 2018

The wave of the Fourth Industrial Revolution was spreaded in Moon Jae-in Government. The efficiency of the R&D budget of government began to pay attention, the role of the National Science & Technology Information Service (NTIS) which provides all national R&D information in real time World's first R&D information portal has been emphasized. NTIS provides information on national R&D projects with their participating researchers, outcomes, and facilities & equipment through of information from each ministry and institution. NTIS supports to build science and technology policies, to enable transparent and efficient management of national R&D projects and to promote joint utilization of the R&D data among researchers and industrial utilization of the R&D data. NTIS provides since 2005. In this paper, I have analyzed the economic ripple effect of NTIS using the Input-Output model technique based on the input-output tables published by the Bank of Korea. When I set the NTIS R&D budget (about 120M$ for the last 13 years) as input coefficients, the effect on production inducement, value added inducement and employment inducement was analyzed by 211M$, 100M$ and 1,882 respectively.

• Journal of Distribution Science
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• v.19 no.4
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• pp.37-51
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• 2021

Purpose: The purpose of this study is to provide a basis for establishing a policy to promote the export of Korean goods through the economic ripple effect of the Korean Wave. From 2001 to 2017, cultural goods exports and consumer goods exports data to 102 countries were used to estimate the effect of cultural goods exports on domestic consumer goods exports. Research design, data and methodology: Based on the Gravity Model, we analyzed the effects of domestic film, publishing, music, broadcasting, clothing, cosmetics, processed food, IT products, and automobiles on the export of consumer goods. Results: The empirical analysis estimated the trade creation effect of exports of cultural products driving exports of consumer goods and found that a 1% increase in exports of cultural products increased 0.136% in exports of consumer goods. Conclusions: The average rate of change in consumer goods exports due to changes in cultural product exports was 22.44, which could be interpreted as an increase of $2,244 in exports of consumer goods such as IT products, cosmetics, clothing, and processed foods. According to the analysis of export-driven effects of each consumer item by dividing cultural products by sector, the effects of export of processed foods, clothing, cosmetics, IT products, and film, music, publishing exports were statistically significant.

• Environmental and Resource Economics Review
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• v.23 no.4
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• pp.689-718
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• 2014

This study analyzes the ripple effects on the national economy of the flood damage using a perfect foresight dynamic CGE model for 2010 as the base year in case that the flood damage reduces the capital of the relevant industrial sectors. The analysis is limited to the items of physical damage such as agricultural land, ships and public facilities, for which statistical data can be obtained. As flood damage scenarios we adopt the minimum, maximum and average value of flood damage's historical data over the period 1991~2010 for each item. The results show that the largest production decline happens to the industry of fishing and transport and the next largest to the agricultural and forestry industry. The GDP reduction in the base year turns out to be from 0.001 to 0.057 percent compared to the benchmark and 11 percent compared to the exogenous shock to capital stock. Dynamically, the GDP gradually decreases until the year of 2030, which shows the long-lasting impact on the national economy of flood damage via the chanel of the capital damage.

• Journal of Technology Innovation
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• v.31 no.2
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• pp.59-82
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• 2023

The purpose of this research is to conduct the empirical analysis of the short- and long-term causal relationship between public R&D investment, corporate R&D investment, and university R&D investment on economic growth in Korea. To this end, based on the time series data from 1976 to 2020, a causality test was conducted through the unit root test, cointegration test, and vector error correction model (VECM). As a result, it was found that there is a long-run equilibrium relationship between economic growth in Korea, public R&D investment, corporate R&D investment, and university R&D investment, in which a causal relationship exists in the long run. Also, while public R&D investment has a short-term effect on economic growth, corporate and university R&D investment does not have a short-term effect on economic growth. In addition, the results shows that there is a bidirectional causal relationship between economic growth and public R&D investment, corporate R&D investment and public R&D investment, and university R&D investment and public R&D investment in the short term. Through this research, it was empirically found that a highly mutual relationship exists between public R&D investment, corporate R&D investment, university R&D investment and economic growth. In order to increase the ripple effect of R&D investment on economic growth in the future, R&D investment between universities and corporations should be mutually promoted, and R&D investment by corporations should have a positive effect on public R&D investment so that public R&D investment can contribute to future economic growth.

• The Journal of the Korea Contents Association
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• v.21 no.9
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• pp.299-311
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• 2021

The purpose of this study is to analyze the ripple effect of the Chinese education industry on the national economy by using the industry-related table of 2017 by the China Statistical Office to use it as policy data for revitalization of the Chinese education industry in the future. To achieve this purpose, 149 industries in the basic classification of the industry-related table were classified into 32 industries. Based on these classifications, by analyzing the production induction coefficient, sensitivity coefficient, influence coefficient, yield inducement coefficient, production tax induction coefficient, and labor induction coefficient, etc. The purpose of this study is to understand the relationship between different industries and to find out the economic impact of the Chinese education industry. The analysis results show that in 2017, the total production induction coefficient of China's education industry was 1.7188, the row total was 1.0626, the sensitivity coefficient was 0.01211, the influence coefficient was 0.01958, the income induction coefficient was 0.6667, the production tax induction coefficient was 0.035, and the final demand was 1 billion yuan. When this occurs, the labor induction coefficient shows a total of 31,254 persons (indirect 15,541 persons, direct 15,713 persons). Based on the analysis results, this study suggested the implications that government support, technology introduction and application of new operating models, policy regulations, and efficient supervision of the system and president are required for further development of the Chinese education industry.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.4
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• pp.771-778
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• 2014

In this study, we have measured the effects on production inducement, added value inducement, employment inducement and backward and forward linkage regarding the knowledge service industry in Korea. It turns out that the knowledge service industry greatly contributes to increase of added value and employment creation while highly withholds to effect on production inducement and backward and forward linkage effects. In recent, government seeks out new growth driver out of the knowledge service industry. We have found the fact that its direction should be 'production growth of the knowledge service industry' through this study.

• Journal of the Korea Convergence Society
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• v.9 no.10
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• pp.325-338
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• 2018

This study investigated the effects of $6^{th}$ industry, which can be developed in various forms, on the Korean economy by classifying it as distribution and tourism type, and compared the difference between industrial characteristics and economic effect by $6^{th}$ industry type. To this end, the effects of production inducing effects, value added inducing effects, supply shortage effects and price ripple were analyzed using domestic input-output table to the latest published in 2014. As a result of the analysis, in the case of production inducing effect, the tourism in the $6^{th}$ industry as a whole was 0.4094KRW, the distribution was 0.4673KRW, and the tourism was 0.4715KRW. The value added inducing effect was 0.1527KRW in the $6^{th}$ industry, 0.1738KRW in distribution and 0.1696KRW in tourism. In the case of supply shortage effect, distribution effect was larger than that of production inducing effect and value added inducing effect, which was 0.5254KRW in the $6^{th}$ industry, 0.6704KRW in distribution, and 0.5070KRW in tourism. Finally, the effect of price ripple was 0.0959% for the $6^{th}$ industry, 0.0981% for distribution, and 0.0617% for tourism, which was lower than other $6^{th}$ industry types.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.5
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• pp.984-990
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• 2017

The domestic cultural contents industry has been growing rapidly since the 2000s. The government has designated the cultural content industry as the next generation domestic growth industry. In order to cultivate this, various regulations are made and the budget is supported. Local governments are preparing various policies of cultural contents industry. This study presents the economic ripple effect by analyzing the status level and competence of the cultural contents industry in region based on LQ(location quotient) analysis and GAP analysis. Through this, this study will examine the competitiveness of the cultural content industry with high added value in Busan and draw out the plan for activation of cultural contents. Also, this study will compare competitiveness of Busan with other regions and show the economic contribution of Busan City.

• Journal of Korea Port Economic Association
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• v.24 no.2
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• pp.193-208
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• 2008

This study aims to analyse the ripple effect of Physical distribution service industry on national economy using input-output tables and present the results as data for political plans in this field. For the analysis, it uses input-output tables developed and published by Sank of Korea in 1998, 2000, and 2003. To sum up the results, production inducement effects are 1757 for railroad transport, 1688 for road transport and 1617 for loading. Import inducement effects of assistant services, loading, storage, warehouse and other transport-related services are low while the effects of water and air transport are high as follows: 0.679 and 0.558 respectively. Then, added-value inducement effects are presented as follows: 0.841 for railway transport, 0.828 for road transport, 0.962 for transport assistant service, 0.939 for loading, 0.938 for storage and warehouse, and 0.942 for other transport-related services. Sensitivity dispersion index of road transport is high while that of water transport, storage and warehouse is low. And influence coefficient of railway and road transport is high while that of water and air transport is low. In respect to the employment structure of Physical distribution service industry, 744,000 are employed for road transport industry, which is the largest number, 19,000 for air transport and 20,000 for assistant services, which is the least number.