The character industry is a high value-added industry, and is one of the strategic industries to be fostered. However, the character industry is struggling due to the lack of national consensus on the importance and value of the character industry. Therefore, in order to resolve this issue, the study used the character Input-Output Table of year 2009 of korea to analyze how much the character industry(Toys and games, Models and decorations) contributes to the national economy by measuring economic spreading effects of character industry on national economy. The results shows that character industry shows that production inducement coefficient is column 1.602, row 1.007, index of the sensitivity of dispersion is 0.543, Index of the power of dispersion is 0.864, value-added coefficient is 0.620, income inducement coefficient is 0.334, tax inducement coefficient is 0.066, employment inducement coefficient is 0.008.
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.
Forest road is an essential infrastructure for forest management such as the composition and management of forest resources, timber and forest byproduct production & transportation. It has recently been utilized forest recreation and forest sports as well as also forest pest control, forest fire prevention and evolution. When you build a forest road, the economic function in the forest is activated, so that it can result in the ripple effect of induced employment, value-added creation and production inducement. The purpose of this study is to analyze the impact caused by forest road construction occurring as the overall economy. For analysis it was applied to inter industry analysis method that is a method for analyzing the quantitative cross-correlation. The data were used in the Input-Output Tables In 2014, the Bank of Korea. When you build a forest road, economic effect due to the construction of the forest road is generated and economic effects are also generated due to the increase in the production of forest products after the construction of the forest road. Therefore, we will analyze the economic impact of the two effects. The estimated economic value of forest products, which is the economic effect of forest product cultivation, was calculated through some assumptions and the economic ripple effect was analyzed. The forest road construction sector is defined as land clearing and reclamation, and irrigation project construction and the forestry forest products sector is defined as the sum of raw timber, edible forest products and misc. forest products. In total, 32 sectors were classified, and except for the two sectors defined as forest road construction and forestry forest products, the remaining sectors were integrated according to the classification system of 30 integrated classifications of the Bank of Korea. As a result, the production inducement coefficient for forest construction was analyzed to be 2.767 and the production inducement coefficient for forestry forest products was analyzed to be 1.565. This means that 2,767 times the production of forest road construction investment is induced in the whole industry and the production of 1.562 times the amount of forestry forest products is caused by the whole industry as the production of forestry forest products increases. The value added inducement coefficient for forest road construction was 0.977 and the value added inducement coefficient for forestry forest products was 0.985. Forest road are essential infrastructure for forestry development and should be continuously invested because they are essential elements of timber production and forest byproduct production with functions such as forest management, forest recreation, forest sports, and town connection.
The film 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 film industry is struggling due to the lack of national consensus on the importance and value of the film industry. Therefore, in order to resolve this issue, the study used the film Input-Output Table of year 2009 of korea to analyze how much the film industry contributes to the national economy. The results shows that film industry induce 82,838.7 billion won of national production, especially the film industry(the sector of film product & distribution and film screenings) shows that production inducement coefficient is 2.324(2.240, 2.478), Index of the power of dispersion is 1.163(1.121, 1.240), index of the sensitivity of dispersion is 0.825(0.825, 0.501), value-added coefficient is 0.884(0.479, 0.547), income inducement coefficient is 0.454(0.211, 0.236), tax inducement coefficient is 0.110(0.090, 0.146) and employment inducement coefficient is 0.017(0.014, 0.022).
Today, the Korean fisheries is undergoing significant hardships, both domestically and internationally. While declining amount of catch, ascending international oil prices and others pose a compelling challenge to the fishing sector, the ever strengthening influence of international institutions related to fisheries and international trade organizations also compel to bring about myriad of changes in the realm of fishery products. Against the backdrop, this study attempted to examine the fisheries catch, aquaculture, service, processing fields in terms of its rippling effect and of how the industry has been changed by analyzing the past and present through an input-output analysis. As for research methods, 168 items of the input-output tables in 2000, 2005, 2009, and 2010 were integrated to form and classify 32 sectors (28 basic sectors + catch, aquaculture, fishery service, processed fishery products) so as to generate production inducement coefficient, sensitivity coefficient, and impact coefficient. The analysis results revealed that : though the linkage effect of fishery industry was not very sizable, the impact coefficient of the processed fishery products was high; the consumption and investment coefficient sector among production inducement coefficient was on an upturn trend ; the export coefficient was tended to decline. In the future research, it is necessary to carry out a study based on the integration of detailed classification (404 sector) and a study and analysis of fishery industry by different regions through the inter-regional input-output tables. The fishery industry is one of the crucial industries in Korea. The fishery industry is not only important in its own right but also significant as it exerts influence over other industries. Therefore, it is required that there should be more investment and supports for the development of the fishery industry, and pay efforts to ensure that the investment and development could lead to mutual growth for both the fishery and other various industries.
Journal of the Economic Geographical Society of Korea
/
v.21
no.2
/
pp.77-89
/
2018
The purpose of this paper is to analyze the industrial linkage between manufacturing and service industries in Seoul and Busan. In this paper, the industrial linkage between the manufacturing and the service industry is analyzed through input-output coefficient and production inducement coefficient. The results are as follows. First, the linkage of the service industry to the manufacturing in Seoul was higher than that of Busan. Second, Busan had a low input proportion of the service industry supplied by its own area to the manufacturing, so that the effect of the growth of Busan manufacturing on the regional economy is limited. Third, the linkage of manufacturing to service industry in Busan was found to be higher than that of Seoul. Finally, policy directions for improving the industrial linkage between manufacturing and service industries were suggested based on the results.
Journal of The Korean Institute of Defense Technology
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v.5
no.4
/
pp.1-8
/
2023
In this study the economic impact of each plan for introducing Korea unclear-powered submarines were analyzed. This study conducted a preliminary investigation into foreign countries cases of unclear-powered submarines and classified three introduction plans. In order to analyze the economic impact of each introduction plan, a multiple-level survey was conducted targeting experts with experience in developing and operating ship weapon systems, and quantitative results were calculated for subcategory items with industrial relevance for industrial correlation analysis. The value added inducement coefficient and production inducement coefficient and employment inducement coefficient were calculated for each introduction method, and a favorable introduction method was derived. It is hoped that the results of this study will serve as a reference for policy decision-making during prior research for the introduction of korea nuclear submarines.
The purpose of this research is to analyze the Spill-over economic effect of the cultural and creative industries(CCI) in Henan Province, China. The research object is the CCI of Henan Province, which is mainly based on five sectors out of 42 industries in the industrial association table of the Statistical Bureau of Henan Province, China in 2017 (culture, sports; recreation and research sector; experimental development and integrated technical services sector; information transmission, computer services and software sector; education sector, etc), and is analyzed through secondary integration and redefinition of the CCI of Henan Province. Through the analysis of Henan Province Industry Association Table, this paper provides some enlightenment to the future direction of the cultural and creative industries. The main analysis results are as follows. The total production inducement of the CCI in Henan province is 48,848 billion yuan, and in particular, the production inducement coefficient of the industry in Henan province is 2.72809, 2.23909 (total of columns and rows), Index of the power of dispersion is 0.26325, and the index of the sensitivity of dispersion is 0.87535. Income induction coefficient is 0.55211, production tax induction coefficient is 0.09291. Because CCI of Henan Province has full development potential, the government needs to provide active support and policy support, in addition to the need for legal provisions and supervision of market management. In order to improve the innovative development of the CCI, it is necessary to develop a new model of "CCI+X".
This study examined the feasibility on the construction of a wood industrialization service center for a wood industry cluster establishment in Jeollanam-do. Construction of the wood industrialization service center is based on a discount rate of 3.5%, an investment period of 4 years, a business operations period of 16 years and an investment cost of 24600 million won; the total amount of the net present value, the cost-benefit ratio and the internal rate of return were assumed to be 2.579 million won, 2.51%, and 10.1%, respectively. In addition, the production inducement coefficient, the induced production effect, the income-induced coefficient, the income inducement effect, the employment inducement coefficient, and the employment inducement effect were estimated 1.4345, 35287 million won, 0.1655, 4000.7 million won, and 0.4665, 1,145 people, in the effects of the wood related industries using the multi-regional input-output model, respectively. Financial independence of operating income to cover its own costs incurred in accordance with the operating project might be practicable.
Journal of Agricultural Extension & Community Development
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v.23
no.3
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pp.285-293
/
2016
The increase in demand for leisure time by the public and the vitalization of agricultural tourism resulting from the expansion of the five-day work week are expected to greatly contribute to the rural economy, but actual studies analyzing the ripple effect of the agricultural tourism industry are lacking. In order to analyze the economic ripple effect, tourism or agricultural tourism must become an independent sector in the inter-industry relations table's sector classification, but because it is not, the study uses a method of analysis which involves creating a satellite account. However, because agricultural tourism has a clear main agent in farms unlike general tourism which does not, there is one method in which provisions are made by farms or farm villages and another method in which outside products are used. The purpose of the present is to measure the economic ripple effect of agricultural tourism with a focus on 162 subclasses by applying positive data from the education sector input into agricultural tourism. Satellite accounts which considered intermediate input were created and applied to positive data, the analysis of which revealed agricultural tourism to account for 462 billion won, which is 0.01% of the total production amount of 3,503,480 billion won, while the production inducement coefficient was 3.2895 units when the final demand of agricultural tourism occurs. When the production inducement coefficient is at 3.2895 units, highest sector was agricultural tourism at 0.9968 units followed by restaurants and bars at 0.3325 units, roadt transportation services at 0.3183 units, lodging services at 0.1520 units, and petroleum products at 0.1290 units.
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