• 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.

• 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 Forest and Environmental Science
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• v.30 no.1
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• pp.145-151
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• 2014

The study examines the feasibility of hosting the International Wood Industry EXPO as a part of the effort to establish Wood Industry Cluster in Jeollanam-do. The provisional EXPO period suggested by the study is 30 days between July 23 (Saturday) and August 21 (Sunday) 2016 and the proposed venues are Namdo International Education Center, Woodland, and Woodcraft Center, Jangheung-gun, Jeollanam-do, and so on. According to the study, it is calculated that the expected investment cost amounts to around 4.5 billion won and the number of total potential visitors reaches 1,627,478. The study also predicts that the EXPO generates various economic effects and outputs that can be quantified as following; a production inducement effect equivalent of 344.5 billion won, an income inducement effect of 77 billion won, an employment inducement effect corresponding to 3,899 jobs, a value-added inducement effect equivalent of 143 billion won, and an indirect tax inductive effect of 32 billion won. Then, emphasizing the need for the organizing committee that can play an important role in managing the overall EXPO events, the study, based on the figures, concludes that the International Wood Industry EXPO 2016 is to be promoted at the regional and national level.

• 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.

• Journal of the Korea Safety Management & Science
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• v.14 no.4
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• pp.313-319
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• 2012

SW industry is important at entire industry in Korea and also one of new growth engine industry. This paper deals with the economic effect of SW industry through input-output analysis. We reconstruct the SW industry by extracting and combining SW portion from other industries of the inter-industry relation table. We obtain that production inducement coefficients, value added inducement coefficients, employment inducement coefficients, and job position inducement coefficients are higher than average inducement coefficients of all industries.

• Journal of Digital Convergence
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• v.13 no.4
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• pp.61-68
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• 2015

This study aims to estimate the economic effects of the simulation golf industry. Two steps are taken. Step 1 is to calculate the direct effect which includes input required to install the facility and consumer's fee to pay for the simulation golf, and the indirect effect which includes the introduction of the field golf course derived from simulation golf. Step 2 is to calculate the production, value added and employment inducement effect. As a result of this calculation, total production inducement effect is 3.6 trillion won, value-added inducement effect is calculated at about 1.66 trillion won, while employment inducement effect is 34.6 thousand people in 2011. This study is expected to contribute to providing a basis for the policy to support the simulation industry and for estimation of the economic effect in the different simulation industry such as the simulation baseball.

• The Journal of Fisheries Business Administration
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• v.51 no.4
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• pp.123-136
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• 2020

This study attempted to propose a method of determining a project implementation area according to the purpose of the Offshore Project for Fishery Stock Enhancement after analyzing the regional economic effects in advance targeting the candidate regions for the Offshore Project for Fishery Stock Enhancement. The main results of this study can be summarized as follows: first, in comparison with the overall effect of the Offshore Project for Fishery Stock Enhancement to 2013, the production inducement coefficient increased by 0.08 in the region, but decreased by 0.39 in other regions and by 0.33 in the whole country. The value-added inducement coefficient increased by 0.01 in the region and by 0.06 in other regions, increasing 0.27 for the whole country. In the case of the employment inducement coefficient, the number of workers in the region decreased by 9.48 and increased by 0.3 in other regions, resulting in a decrease of 9.1 people in the whole country. Second, depending on the purpose of the Offshore Project for Fishery Stock Enhancement, an aggregating indicator of economic effects within the region, an aggregating indicator of economic effects in other regions, and an aggregating indicator of economic effects across the country were prepared to be used to determine the priority of the project implementation region. There was a little difference between the 2013 and 2015 regional rankings according to the standardization method, indicating that the analysis results were somewhat consistent. In conclusion, the results of this study may contribute to determine the project implementation area according to the purpose of a specific project after analyzing the regional economic effect in advance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.86-87
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• 2014

Although the importance of information security industry has been growing these days, the research of industrial respect for the industry has been rarely performed. This paper provides one definition of the information security industry and the industry classification system according to the definition. The purpose of this study is to provide the basic data for the industry development strategy by analyzing economic ripple effect on the domestic information security 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.

• 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.