• 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.

• 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.

• 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 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.9
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• pp.299-311
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• 2021

The purpose of this study is to analyze the ripple effect of the Chinese education industry on the national economy by using the industry-related table of 2017 by the China Statistical Office to use it as policy data for revitalization of the Chinese education industry in the future. To achieve this purpose, 149 industries in the basic classification of the industry-related table were classified into 32 industries. Based on these classifications, by analyzing the production induction coefficient, sensitivity coefficient, influence coefficient, yield inducement coefficient, production tax induction coefficient, and labor induction coefficient, etc. The purpose of this study is to understand the relationship between different industries and to find out the economic impact of the Chinese education industry. The analysis results show that in 2017, the total production induction coefficient of China's education industry was 1.7188, the row total was 1.0626, the sensitivity coefficient was 0.01211, the influence coefficient was 0.01958, the income induction coefficient was 0.6667, the production tax induction coefficient was 0.035, and the final demand was 1 billion yuan. When this occurs, the labor induction coefficient shows a total of 31,254 persons (indirect 15,541 persons, direct 15,713 persons). Based on the analysis results, this study suggested the implications that government support, technology introduction and application of new operating models, policy regulations, and efficient supervision of the system and president are required for further development of the Chinese education industry.

• Korea Trade Review
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• v.48 no.2
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• pp.175-195
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• 2023

This study is for analyzing the relation between Korean Water transport and the other main countries Water transport. In the Free trade system, Maritime transport has a high impact on the global economy as well as the each countries. The division of labor through the global value chain(GVCs) has became the ordinary activity in business, and in Maritime shipping,, there are the International trade among countries. Therefore, This study analyze relation of Korean water transport and other 13 regions using World Input-Output Table(WIOT) by Asia Development Bank(ADB). The result of analysis, the proportion of intermediate goods in the input structure of Korean water transport is about 70%, and the ratio of using domestic products is higher than the major European countries. However, since 2000, intermediate inputs from foreign countries have steadily increased, and added value has decreased. Countries with a high relation with Korean Water transport industry are United States(USA) on the input structure, Singapore(SIN) and Japan(JPN) on the distribution structure. Analyzing the relation through the production inducement coefficient, Singapore(SIN) has the high relationship with Korean Water transport industry.