• The Journal of the Korea Contents Association
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• v.13 no.4
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• pp.350-360
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• 2013

The purpose of this study was to analyze how much the beauty industry contributes to the national economy by measuring economic spreading effects of beauty industry on national economy. To achieve this purpose, the study used the beauty Input-Output Table of year 2009 of korea. The results shows that beauty industry induce 598,453 billion won of national production, especially beauty industry shows that production inducement coefficient is 1.810,Index of the power of dispersion is 0.965, index of the sensitivity of dispersion is 0.534, value-added coefficient is 0.728, and labor inducement coefficient is 0.039. The beauty industry's final demand 11,004 won be put into the national economy, GDP inducement 598,438 one billion won in the beauty industry one billion won 11,029 accounted for 1.8% of the total, and the value-added inducement 4,947 billion(2.3%),tax inducement 23,798.5 billion(3.5 %), income inducement 91,187 billion(2.5%). Regarding the industrial linkage effect, beauty industry has an relatively higher growth potential in the national economy than other the manufacturing industry.

• The Journal of the Korea Contents Association
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• v.13 no.1
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• pp.147-155
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• 2013

The purpose of this study is to analyze how much performance industry contribute to national economy by measuring economic effects of performance industry. To achieve the purpose of the study, the study uses an performance industry(theater, music and other arts, 390 sectors) Input-Output Table of yaer 2009 of korea bank. The results shows that performance industry induce 391.6 trillion won in the national production, 65.1 trillion won in the income inducement, 16.3 trillion won in the tax inducement. Especially the performance industry shows that production inducement coefficient is 1,387, Index of the power of dispersion is 0.020, index of the sensitivity of dispersion is 0.025, value-added inducement coefficient is 0.662, income inducement coefficient is 0.455, tax inducement coefficient is 0.046 and employment inducement coefficient is 0.010.

• Environmental and Resource Economics Review
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• v.32 no.2
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• pp.127-147
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• 2023

This study is trying to analyze the economic effect of replacing thermal power generation, one of the government's carbon-neutral policies, with new and renewable energy. For this analysis, scenario A is set to replace 100% of thermal power generation with new and renewable energy, and scenario B is set to replace 60% of thermal power generation with new and renewable energy. In addition, costs are incurred when replacing thermal power generation with new and renewable energy, and scenario 1 is the same cost as the current cost, and scenario 2 is120% higher than the current cost. Therefore, when converting thermal power generation to new and renewable energy, the scenarios are largely organized into four cases. In the case of replacing thermal power generation with new and renewable energy, the production inducement coefficient of thermal power generation decreased from the current level regardless of the scenario. However, the value-added inducement coefficient and the greenhouse gas emission inducement coefficient are lower than the current level when thermal power is converted to renewable energy by 100%, while the value-added inducement coefficient and greenhouse gas emission inducement coefficient are higher than the current level. In addition, the greenhouse gas emission induction coefficient of most industries was found to decrease, while the production induction coefficient and the value-added induction coefficient increased. Scenario A seems appropriate because the purpose of the government's policy is to reduce greenhouse gas emissions by converting thermal power into new and renewable energy. However, as a result of this, the production inducement coefficient and value-added inducement coefficient of some industries decrease, so the government's support policy is needed to solve this problem

• 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.16 no.8
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• pp.651-660
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• 2016

This study analyzed the contribution of the national economy, China's textile industry by 2010 I-O Table issued by the Chinese Bureau of Statistics 2013. The results shows that the production inducement coefficient of China's textile industry is the column total 3.6228 and in line total 3.5452, is a key industry that leads the industry in China. Second, the index of the power of dispersion of the Chinese textile industry is 1.1982, index of the sensitivity of dispersion is 1.1725. Third, income inducement coefficient of China's textile industry 0.5228, tax inducement coefficient 0.1522, a value-added inducement coefficient 1. Especially China's textile industry induce 2993.6 trillion yuan(textile industry of 8.6 trillion yuan, up 3.0%) in the national production, value-added inducement 97.1 trillion yuan (textile industry 1.7 trillion yuan, up 2.0%), income inducement 42.8 trillion yuan (textile industry 0.9 one trillion yuan, 2.0%), also tax inducement 15.4 trillion yuan (textile industry 0.3 one trillion yuan, 2.0%).

• 지역과문화
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• v.4 no.2
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• pp.1-23
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• 2017

The regional development plan by the city of Andong in establishing the foundation for cultural eco-tourism in the cultural area of confucianism(2010-2020) consists of 2 leading projects (the World Confucian Scholar Culture Park, the Korean Culture Theme Park) and 2 strategic projects (the Confucian Scholars' Literature Park, the Sunsunghyun Culture Complex, the Traditional Bittarae Weaving Village). By inter-regional input-output analysis, their multiplier effects of output, value-added, income and employment are estimated respectively 990.2 billion won(multiplier 2.23), 318.2 billion won(multiplier 0.72), 187.7 billion won(multiplier 0.42), and 4,791 workers(multiplier 10.6 workers/billion won). The ongoing project has been, however, delayed due to various issues and has hit a ceiling towards achieving the original objectives of the familiarization, industrialization and globalization of Confucian culture. To overcome these problems, the associated plans of constructing the Korean SMART LINK LINE, of developing contents blending traditional culture and ICT, of establishing tourist complexes and infrastructure around Lake Andong, and of constructing interactive attractions of traditional culture were proposed as new growth-leading plans.

• The Journal of the Korea Contents Association
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• v.16 no.11
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• pp.358-368
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• 2016

The kimchi industry is a high value-added industry, boosts the self-esteem of the people as a measure of a country's culture industry, and is one of the strategic industries to be fostered. However, the kimchi industry is struggling due to the lack of national consensus on the importance and value of the kimchi industry. Therefore, the purpose of this study was to analyze how much the kimchi industry contributes to the national economy by measuring economic effects of the kimchi industry on national economy. To achieve this purpose, the study used the kimchi industry Input-Output Table of year 2013 of korea. The results shows that kimchi industry induce 510,013 billion won of national production, especially the retail trade distribution industry shows that production inducement coefficient is 1.8418(row), 1.1760(column), Index of the power of dispersion is 0.9611, index of the sensitivity of dispersion is 0.6136, income inducement coefficient is 0.1820, tax inducement coefficient is 0.0084 and employment inducement coefficient is 0.003. With the help of information technology.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.1
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• pp.72-80
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• 2020

The information security industry is increasing in importance and market size due to the development of the fourth industry such as artificial intelligence, IoT and etc. This paper was analyzed the impact of the increasing information security industry on the domestic economy by using the Input-Output table. It was classified industrial sectors into information security products and information security services industries, and then reclassified the Input-Output table into 35 industries. And it was estimated the production inducement coefficient, the value-added inducement coefficient, employment inducement coefficient, and etc. The production inducement coefficients of the information security product and service industry are each 1.571, 1.802, and the value-added inducement coefficients of them are each 0.632, 0.997, and the employment inducement coefficients of them are each 2.494, 7.361. Only the value-added inducement coefficient of the information security service industry is slightly higher than the total industry, and the remaining inducement coefficients are all lower than the total industry. In addition, the information security product industry has no the forward and backward linkage effect, and the information security service industry has no the backward linkage effect. But it has the forward linkage effect. As a result of analyzing the economic ripple effect of the information security industry, the production inducement amounted to 359.9 trillion won, value-added inducement amounted to 164.8 trillion won, and employment inducement amounted to 803 thousand people.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.363-374
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• 2021

The purpose of this study is to analyze how much the mining industry contributes to the Mongolian national economy using the 2019 input-output table released by Asian development bank/ERCD in 2021 to understand the characteristics of the Mongolian economy and to use it as a reference. For this study, the Mongolian economy was classified into 35 industries and the contribution of the national economy was analyzed. As a result of the analysis, the total production inducement amount of the Mongolian mining industry was $38,418 million, the total production inducement coefficient was 1.473, the index of sensitivity of dispersion was 1.696, the value added inducement coefficient was 0.707, and the production inducement coefficient was 1.473. It can be seen that the Mongolian mining industry has a higher production inducement effect than other industries, and has great potential for development as a strategic industry leading other industries.

• Proceedings of the Korea Contents Association Conference
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• 2011.05a
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• pp.273-274
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• 2011

관광산업의 산업연관분석은 최근의 서비스산업에 대한 정책적 관심이 증가하고 있는 상황에서 경제적 효과를 측정하는 수단으로 유용성이 높다. 2008년 산업연관표를 통하여 투입계수, 중간투입물과 부가가치율, 생산유발계수, 영향력계수와 감응도계수, 취업계수와 취업유발계수를 도출한다.