• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• Spatial Information Research
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• v.21 no.1
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• pp.37-44
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• 2013

This study sets the boundary of U-City industry based on expert surveys. Based on this U-City industry boundary, an appropriate inter-industry analysis is performed. The result shows production inducement coefficients, value added inducement coefficients, employment & enter employment inducement coefficients, influence coefficients and induction coefficients. Based on these coefficients, overall characteristics and spillover effects of U-City industry are examined. The result of this study shows that U-City industry has bigger value added-induced effects and employee-induced effects than other industry. The result also shows that U-City industry also has a great forward linkage effect. This study has a meaning that could be used to make political decisions as a basic data.

• Informatization Policy
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• v.17 no.2
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• pp.86-103
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• 2010

This paper computes the economic impact of handset subsidies using the recent Input-Output Tables and compares the results with other alternatives which telecommunications companies can choose. The first scenario is that telecommunications companies give handset subsidies to consumers and sales agents. The second is that the companies do not give the subsidies to them, but instead spend the same amount of subsidy on facility investment. The third is that the companies lower the prices of their mobile communications services and consumers spend the saved expenses on other goods and services. The result is that the production, value added, import, job, employment inducement coefficients of the first scenario is larger than those of the second and third scenarios. The reason is as follows. The handset subsidy results in the incentive to consumers for handset purchase or the incentive for sales agents to sell the telecommunication services of the companies. The former has larger production and import inducement effect, and the latter also has larger value-added, job, and employment inducement effect than those of other scenarios.