• 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.

• Journal of Information Technology Services
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• v.13 no.3
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• pp.165-181
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• 2014

This study proposes the accurate labor inducement coefficient (employment inducement coefficient/hiring inducement coefficient) of Korea software industry by analyzing the inter-industry relation using the modified inter-industry table. To rewrite the inter-industry table of Korea, some previous studies related to the inter-industry analysis were reviewed and the key problems were identified. First, in the current inter-industry table published by the Bank of Korea, the output of software industry includes not only the pure software related output but also the output of non-software section due to the misclassification of the industry. This causes the output to become bigger than the actual output of software industry. Therefore, if the inter-industry table is not modified, the labor inducement coefficient would be overestimated too much. 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 labor inducement coefficient to be over or underestimated. This study tries to correct these problems to get the more accurate labor inducement coefficient 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 followings are the labor inducement coefficient obtained when the output is divided into the pure software section (package software, and IT service) and non-software section. As of 2011, the employment inducement coefficients of pure software section, package software section and IT service of Korea were 8.616, 13.998, and 7.773 respectively while the labor inducement coefficients of pure software section, package software section and IT service of Korea were 7.979, 13.332, and 7.083, respectively.

• 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 Convergence for Information Technology
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• v.11 no.1
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• pp.175-182
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• 2021

The purpose of this study is to establish the direction of industrial policy by comparing the employment inducement effect on the related industries of the digital bio-healthcare industry. The analysis data used the three-year input-output table measured by the Bank of Korea. First, the research method was rewritten into 7 major industries to compare statistical data by period. Second, the Bank of Korea's industry-related analysis methodology was utilized. Third, the weight was reflected and compared by employment, production, and investment sectors of the digital bio-healthcare industry. As a result of the analysis, first, the employment sector had a higher effect than the average of the entire industry, second, the production sector was low, and third, the investment sector required investment in the service sector. The conclusions drawn from the analysis showed that direct investment and continuous investment are required in the employment sector, the development of professional manpower is urgent, and direct investment and long-term investment are effective in the production sector.

• 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 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 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.

• Journal of Korea Technology Innovation Society
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• v.17 no.4
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• pp.651-672
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• 2014

Under the diagnosis of low employment rate and low growth, the government regards the creation of new jobs through the creative and innovative R&D as an important national plans. This study attempts to measure the employment creation effect of R&D investment of industrial technology by using input-output analysis used in domestic and international broadly. The employment effect can be divided into employment inducement effect and direct employment effect. As a result of the analysis, The employment creation effect of R&D investment of government industrial technology is measured to be 8-12 peoples per 1 billion KRW investment. This results mean that government R&D investment is a effective policy for employment creation. And it is necessary to establish R&D policies that reflect the technical characteristics of the employment creation effect. In short term, it is important that the government invest the superior technology of total employment and direct employment as essential means of employment creation by selection and concentration strategy. In mid-long term, the government should focus on technology spread as technology transfer and opening innovation strategy for employment creation to support superior technology of employment inducement. The results of this study can be used in analysis on the employment creation effect related to industrial technology R&D.

• 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.