• Land and Housing Review
• /
• v.11 no.4
• /
• pp.15-26
• /
• 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
• /
• v.21 no.4_spc
• /
• pp.381-401
• /
• 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
• /
• v.21 no.12
• /
• pp.363-374
• /
• 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.

• The Journal of the Korea Contents Association
• /
• v.12 no.9
• /
• pp.172-181
• /
• 2012

The film 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 film industry is struggling due to the lack of national consensus on the importance and value of the film industry. Therefore, in order to resolve this issue, the study used the film Input-Output Table of year 2009 of korea to analyze how much the film industry contributes to the national economy. The results shows that film industry induce 82,838.7 billion won of national production, especially the film industry(the sector of film product & distribution and film screenings) shows that production inducement coefficient is 2.324(2.240, 2.478), Index of the power of dispersion is 1.163(1.121, 1.240), index of the sensitivity of dispersion is 0.825(0.825, 0.501), value-added coefficient is 0.884(0.479, 0.547), income inducement coefficient is 0.454(0.211, 0.236), tax inducement coefficient is 0.110(0.090, 0.146) and employment inducement coefficient is 0.017(0.014, 0.022).

• Journal of Information Science Theory and Practice
• /
• v.10 no.spc
• /
• pp.66-75
• /
• 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 Korean Society of Forest Science
• /
• v.106 no.2
• /
• pp.219-229
• /
• 2017

Forest road is an essential infrastructure for forest management such as the composition and management of forest resources, timber and forest byproduct production & transportation. It has recently been utilized forest recreation and forest sports as well as also forest pest control, forest fire prevention and evolution. When you build a forest road, the economic function in the forest is activated, so that it can result in the ripple effect of induced employment, value-added creation and production inducement. The purpose of this study is to analyze the impact caused by forest road construction occurring as the overall economy. For analysis it was applied to inter industry analysis method that is a method for analyzing the quantitative cross-correlation. The data were used in the Input-Output Tables In 2014, the Bank of Korea. When you build a forest road, economic effect due to the construction of the forest road is generated and economic effects are also generated due to the increase in the production of forest products after the construction of the forest road. Therefore, we will analyze the economic impact of the two effects. The estimated economic value of forest products, which is the economic effect of forest product cultivation, was calculated through some assumptions and the economic ripple effect was analyzed. The forest road construction sector is defined as land clearing and reclamation, and irrigation project construction and the forestry forest products sector is defined as the sum of raw timber, edible forest products and misc. forest products. In total, 32 sectors were classified, and except for the two sectors defined as forest road construction and forestry forest products, the remaining sectors were integrated according to the classification system of 30 integrated classifications of the Bank of Korea. As a result, the production inducement coefficient for forest construction was analyzed to be 2.767 and the production inducement coefficient for forestry forest products was analyzed to be 1.565. This means that 2,767 times the production of forest road construction investment is induced in the whole industry and the production of 1.562 times the amount of forestry forest products is caused by the whole industry as the production of forestry forest products increases. The value added inducement coefficient for forest road construction was 0.977 and the value added inducement coefficient for forestry forest products was 0.985. Forest road are essential infrastructure for forestry development and should be continuously invested because they are essential elements of timber production and forest byproduct production with functions such as forest management, forest recreation, forest sports, and town connection.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.7 no.7
• /
• pp.671-678
• /
• 2017

In this paper, we conducted an industry input-output analysis to examine the impact of the advertising industry on the movie industry. As a result, the production inducement effect increased from 1993 to 2008, and it decreased from 2009 to 2012. In 2014, the production inducement effect increased to 0.028 won. Value added effect is found that it fluctuated yearly. As a result of the sensitivity coefficient of the advertising industry, it decreased increasingly. In the case of the influence coefficient for backward linkage effect, it showed a decreasing tendency after 1998, but it increased from the beginning of 2009. This study examines the influence of the advertising industry on the input of the output by analyzing the impact of the advertising industry on the movie industry. As a follow-up study, it is necessary to compare the impact of the advertising industry on the movie industry and other industries such as publishing and broadcasting.

• Journal of Convergence for Information Technology
• /
• v.12 no.3
• /
• pp.85-107
• /
• 2022

This study is to analyze the induced effect, network connectivity, and network visualization of the water transportation industry on the overall economy in relation to all industries. For this, various inducement coefficients of the water transportation industry are analyzed using industry linkage analysis and unit structure matrix, and network visualization analysis is performed using network connectivity and NetDraw using Ucinet 6 that utilizes unit structure matrix and inverse matrix function. As a result of the study, analysis results of input coefficient, production inducement coefficient, value-added inducement coefficient, and inter-industry chain effect were presented as various inducement coefficients in the water transportation industry. content was presented. Through this study, the current position and status of the water transportation industry and its relationship with all industries were confirmed, and the strategic relationship with which industries it should be presented was presented. In the future, it is necessary to further analyze the current status and trends of various induced effects, connectivity (centrality), and network visualization analysis using industry-related analysis published since the 2000s.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.42 no.4
• /
• pp.559-569
• /
• 2022

Infrastructure engineering is a field that supports construction (assembly) as a representative industry that creates high added value and jobs by combining science and technology with knowledge, though its importance is underestimated. According to a report from the Ministry of Land, Infrastructure and Transport (Korea), the value-added rate (65.3%) of the engineering industry and the employment inducement coefficient (14 employees per billion won) are three times higher than in manufacturing. In particular,the forward value chain (such as project management and basic design) accounts for less than 10~15% of the total project cost but determines the overall price and quality of the infrastructure facilities. In this study, a work break-down system, design support module and database development method for road design projects for design platform development is presented. Based on the presented development method, a cloud-based infrastructure design platform's prototype is developed. The developed infrastructure engineering platform is expected to provide a web-based design work environment without time/space restrictions and greatly contribute to winning overseas business orders and securing competitiveness.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.5
• /
• pp.1031-1039
• /
• 2015

This study examines the economic ripple effect on the domestic information security manufacturing and service sectors through input-output analysis. The production inducement coefficient of the manufacturing sector is bigger than the average of whole industry, but that of the service sector is smaller than the average. On the other hand, the service sector is superior to the manufacturing sector in the value added and employment inducement coefficients. Forward and backward linkage effects of manufacturing and service sectors are generally lower than those of the average of whole industry. The information security industry has insignificant contribution to national economy and employment growth overall. In particular, the manufacturing sector records minus contribution to employment growth, which means that a lot of effort for increasing employment must be given further on in the sector.