• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.651-660
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• 2016

This study analyzed the contribution of the national economy, China's textile industry by 2010 I-O Table issued by the Chinese Bureau of Statistics 2013. The results shows that the production inducement coefficient of China's textile industry is the column total 3.6228 and in line total 3.5452, is a key industry that leads the industry in China. Second, the index of the power of dispersion of the Chinese textile industry is 1.1982, index of the sensitivity of dispersion is 1.1725. Third, income inducement coefficient of China's textile industry 0.5228, tax inducement coefficient 0.1522, a value-added inducement coefficient 1. Especially China's textile industry induce 2993.6 trillion yuan(textile industry of 8.6 trillion yuan, up 3.0%) in the national production, value-added inducement 97.1 trillion yuan (textile industry 1.7 trillion yuan, up 2.0%), income inducement 42.8 trillion yuan (textile industry 0.9 one trillion yuan, 2.0%), also tax inducement 15.4 trillion yuan (textile industry 0.3 one trillion yuan, 2.0%).

• 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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.9
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• pp.739-744
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• 2014

Space exploration project usually consists of so many fields of sub projects that it has a diverse ripple effect throughout the economy. Further studies could not consider the complexity of the space exploration project because they regarded it as one project in spite of the diversity. This study found a way to consider complexity of space exploration project using the concept of WAC(weighted average coefficient). The moon exploration project (2014~2020) is the subject of this study. We classified the moon exploration project into 8 industries and calculated the WAC of production inducement coefficient, value added inducement coefficient, and employment inducement coefficient. The result of analysis using these WACs is that production inducement effect amounts to 1,229.6 billion won, value added inducement effect 324.6 billion won, employment inducement effect 4,844 men. And the linkage effect analysis shows that moon exploration project has more backward linkage effect than forward linkage effect.

• Journal of Distribution Science
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• v.19 no.3
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• pp.25-34
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• 2021

Purpose: The purpose of this study is to analyze the economic ripple effect(ERE) of logistics industry by construction of Trans-Korea Railway (TKR) and present policy measures to minimize the economic loss of South Korea (SK). Research design, data and methodology: As the analysis method, exponential smoothing was used for demand forecasting, Input-Output analysis was used to estimate the economic ripple effect coefficient, and scenario analysis was used to an efficient way to invest in TKR to minimize SK's economic losses. Results: 1) the production(logistics fares) of TKR for 10 years after its completion is about 11.42 trillion won in positive relations, and 26.89 billion won in negative relations. 2) the ERE of SK in positive relations is 24.32 trillion won in production inducement effect, 8.1 trillion won in value-added inducement effect, 3.54 trillion won in import inducement effect, and 70,930 persons in employment inducement effect. But the ERE was insufficient in the negative relations. 3) SK's efficient investment method is providing materials and equipment by SK and building the TKR by North Korea in positive inter-Korea relations. Conclusions: For the successful operation of TKR, international cooperation, legalization and stable peace settlement on the Korean Peninsula are required.

• 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.

• 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.

• 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.

• 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.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.363-374
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• 2021

The purpose of this study is to analyze how much the mining industry contributes to the Mongolian national economy using the 2019 input-output table released by Asian development bank/ERCD in 2021 to understand the characteristics of the Mongolian economy and to use it as a reference. For this study, the Mongolian economy was classified into 35 industries and the contribution of the national economy was analyzed. As a result of the analysis, the total production inducement amount of the Mongolian mining industry was $38,418 million, the total production inducement coefficient was 1.473, the index of sensitivity of dispersion was 1.696, the value added inducement coefficient was 0.707, and the production inducement coefficient was 1.473. It can be seen that the Mongolian mining industry has a higher production inducement effect than other industries, and has great potential for development as a strategic industry leading other industries.