• Title/Summary/Keyword: Employment Inducement Coefficient

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Economic Impact Effect Analysis of Flounder Aquaculture Industry in Jeju (제주넙치 양식산업의 경제파급 효과분석)

  • Kim, Jin-Ock;Kang, Seok-Kyu
    • The Journal of Fisheries Business Administration
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    • v.42 no.1
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    • pp.85-96
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    • 2011
  • We have done the input-output analysis to see the over all impact of flounder industry of Jeju region on the domestic economy of Korea. To do the input-output analysis, we have constructed the data set for the input-output table by using the existing data set in the "2003 input- output table of Jeju regional area" published by the joint work of Jeju branch of Korea bank and the Jeju Development Institute, together with some raw data provided by Jejudo Marine Fish-Culture Cooperative. We have also produced input coefficient of flounder industry by making flounder industrial sector exogenous, separated from intermediate demand. To summarize our empirical results, the inducement effect of production, value added, and employment of Jeju flounder aquaculture industry are 300 billion won, 116 billion won and 1,800 people respectively. In conclusion, the results of this study suggest flounder industry of Jeju region contributes powerfully to not only Jeju economy but also all over the Korea economy.

An Analysis of the Economic Effects of Unmanned Aerial Vehicle(UAV) Industry (무인항공기 산업의 경제적 파급효과 분석)

  • Kim, Kwang-Hoon;Won, Dong-Kyu;Yeo, Woon-Dong
    • 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.

Economic Analysis of the Donghae-Bukppuseon Railway (동해북부선 철도의 경제적 효과)

  • Kim, Sun-Ju
    • Land and Housing Review
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    • v.11 no.4
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    • pp.15-26
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    • 2020
  • This study analyzes the Domestic Economic Ripple Effect (DERE) of the Donghae-Bukpuseon Railway (DBR). Input-Output Analysis and Scenario Analysis are employed. First, the future demand is approximately 6.86 billion people, 1.4 billion tons of logistics, and future forecast production is 1.2 trillion won for passengers, and 0.15 trillion won for logistics. Second, the production inducement (PI) coefficient of the railway industry is 2.080, the value-added inducement (VAI) coefficient is 0.680, the import inducement (II) coefficient is 0.32 and the employment inducement (EI) coefficient is 6.45. Third, for the DERE, PI is 2.846 trillion won, VAI is 0.939 trillion won, II is 0.446 trillion won, and EI is 8,737 people/1 billion won. Fourth, PI is approximately 2.8 trillion won, and the payback period is 35 years. Scenario 1 (a 50% increase in the demand for tourism) takes approximately 27 years, Scenario 2 (an 100% increase), 20 years, and Scenario3 (an 150% increase), 16 years. The successful way of the DBR is to enlarge the linkage effect of trans-railways for which international cooperation and agreements are needed. Also, even if the DBR is isolated due to worsening inter-Korea relations, the development of tourism resources is important for public investment feasibility.

An Economic Ripple Effect Analysis of Domestic Supercomputing Simulation in the Industrial Sector

  • Ko, Mihyun;Kim, Myungil;Park, Sung-Uk
    • Journal of Information Science Theory and Practice
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    • v.10 no.spc
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    • pp.66-75
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    • 2022
  • The manufacturing industry is the foundation that drives economic growth, and manufacturing innovation is essential for sustainable growth advantage and the transition into a digital economy. Therefore, major countries actively support the field of simulations, which incorporate information and communication technologies into manufacturing, and announce various policies at the national level along with increasing investment. Simulation technology virtualizes product development processes to replace physical production and experimentation of products, dramatically reducing time and costs. In South Korea, the Korea Institute of Science and Technology Information (KISTI) has supported manufacturing companies for about 14 years by providing relevant technologies. This study uses the input-output table for the Bank of Korea to analyze the economic ripple effect. First, we identified the domestic industrial sector dealing with the supercomputing-based simulation industry. Then we analyzed its ripple effects by dividing them into the production inducement effect, value-added inducement effect, employment inducement effect, and forward/backward linkage effect. Consequently, when the supercomputing simulation budget of KISTI (28.3 billion won, 2007-2020) was set as an input coefficient, the analysis showed 45.1 billion won as the production inducement effect, 24.7 billion won as the value-added inducement effect, and 282 individuals per 1 billion won as the employment inducement effect. This study is significant in that it derived the effects of the inputs by analyzing the economic ripple effects of the projects of KISTI, which have been supporting South Korean manufacturing companies for the past 14 years with supercomputing-based simulations.

The Analysis of Economic Contribution of Beauty Industry by Input-Output Table (산업연관분석에 의한 캐릭터 산업의 경제적 효과 분석)

  • Lee, Yu-Bin;Jin, Yanjun;Bae, Ki-Hyung
    • The Journal of the Korea Contents Association
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    • v.13 no.12
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    • pp.945-956
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    • 2013
  • 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.

New Growth Power, Economic Effect Analysis of Software Industry (신성장 동력, 소프트웨어산업의 경제적 파급효과 분석)

  • Choi, Jinho;Ryu, Jae Hong
    • Journal of Information Technology Applications and Management
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    • v.21 no.4_spc
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    • pp.381-401
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    • 2014
  • This study proposes the accurate economic effect (employment inducement coefficient, hiring inducement coefficient, index of the sensitivity of dispersion, index of the power of dispersion, and ratio of value added) of Korea software industry by analyzing the inter-industry relation using the modified inter-industry table. Some previous studies related to the inter-industry analysis were reviewed and the key problems were identified. First, in the current inter-industry table publishedby the Bank of Korea, the output of software industry includes not only the output of pure software industry (package software and IT services) but also the output of non-software industry due to the misclassification of the industry. This causes the output to become bigger than the actual output of the software industry. Second, during rewriting the inter-industry table, the output is changing. The inter-industry table is the table in the form of rows and columns, which records the transactions of goods and services among industries which are required to continue the activities of each industry. Accordingly, if only an output of a specific industry is changed, the reliability of the table would be degraded because the table is prepared based on the relations with other industries. This possibly causes the economic effect coefficient to degrade reliability, over or under estimated. This study tries to correct these problems to get the more accurate economic effect of the software industry. First, to get the output of the pure software section only, the data from the Korea Electronics Association(KEA) was used in the inter-industry table. Second, to prevent the difference in the outputs during rewriting the inter-industry table, the difference between the output in the current inter-industry table and the output from KEA data was identified and then it was defined as the non-software section output for the analysis. The following results were obtained: The pure software section's economic effect coefficient was lower than the coefficient of non-software section. It comes from differenceof data to Bank of Korea and KEA. This study hasa signification from accurate economic effect of Korea software industry.

International competitiveness of Korea's knowledge service industry (한국의 지식서비스산업의 국제경쟁력)

  • Kim, Pang-ryong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.05a
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    • pp.121-122
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    • 2017
  • In this study, the economic ripple effect of knowledge service industry were compared and analyzed in four countries of USA, UK, Japan and Korea. The production induction coefficient is the largest in Japan, followed by the United Kingdom, the United States, and Korea. On the other hand, the employment inducement coefficient of the knowledge service industry was the highest in all countries except the UK. This implies that the proportion of employment is significantly increased compared to other industries as the role and importance of knowledge service industry increases in the economic and social structure on which knowledge is based.

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Feasibility Study on the Construction of a Wood Industrialization Services Center for a Wood Industry Cluster Establishment in Jeollanam-do (전라남도 지역의 목재산업 클러스터 구축을 위한 목재산업화지원센터 설립의 타당성 검토를 위한 연구)

  • An, Ki-Wan;Park, Kyung-Seok;Ahn, Young Sang
    • Journal of Korean Society of Forest Science
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    • v.102 no.4
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    • pp.506-514
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    • 2013
  • 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.

Economic ripple effect and growth contribution of information security industry (정보보호 산업의 경제적 파급효과 및 기여도 분석)

  • Kim, Pang-ryong;Hong, Jae-pyo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.5
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    • pp.1031-1039
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    • 2015
  • This study examines the economic ripple effect on the domestic information security manufacturing and service sectors through input-output analysis. The production inducement coefficient of the manufacturing sector is bigger than the average of whole industry, but that of the service sector is smaller than the average. On the other hand, the service sector is superior to the manufacturing sector in the value added and employment inducement coefficients. Forward and backward linkage effects of manufacturing and service sectors are generally lower than those of the average of whole industry. The information security industry has insignificant contribution to national economy and employment growth overall. In particular, the manufacturing sector records minus contribution to employment growth, which means that a lot of effort for increasing employment must be given further on in the sector.

Estimation of Economic Value of the Film Industry in the National Economy (영화산업의 경제적 파급효과 분석)

  • Bae, Ki-Hyung
    • The Journal of the Korea Contents Association
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    • v.12 no.9
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    • pp.172-181
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    • 2012
  • 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).