• International Commerce and Information Review
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• v.17 no.1
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• pp.241-264
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• 2015

This study analyzed backward and forward linkage effects among Korea, China and Japan by International Input-Output(I-O) tables. Index of dispersion power and sensitivity degrees were measured after making 'Korea, China and Japan International Input-Output(I-O) Table'. The study showed that the inter-dependency between Korea and China was increased while the influences of Japanese was decreased among the 3 countries. Under the de-industrialization, the 3 countries decreased influences over their domestic industry but increased the inter-dependency over the other countries. In addition, backward and forward linkage effects was significantly high in some industrial sectors such as petroleum, transportation, machinery equipment, service and public administration in 3 countries. In the case of service, the linkage effects among the 3 countries increased which means that the roles and inter-dependency of service was also gradually increasing in 3 countries.

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.40-45
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• 2015

Online social networks(OSN) are very popular nowadays. As OSNs grows, the commercial markets are expanding their social commerce by applying Influence Maximization. However, in reality, there exist more than two players(e.g., commercial companies or service providers) in this same market sector. To address the Influence Maximization problem between adversaries, we first introduced Influence Maximization against the social adversaries' problem. Then, we proposed an algorithm that could efficiently solve the problem efficiently by utilizing social network properties such as Betweenness Centrality, Clustering Coefficient, Local Bridge and Ties and Triadic Closure. Moreover, our algorithm performed orders of magnitudes better than the existing Greedy hill climbing algorithm.

• Journal of Korea Port Economic Association
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• v.27 no.3
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• pp.311-329
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• 2011

This study examined economic ripple effect of marine transport and port industry using Input-Output Tables. The results of the study are summarized as follows: first, in 2005 production inducement coefficients of harbour facilities was the highest(1.958), followed by coast and inland water transportation(1.857), load and unload(1.842), other transportation services(1.768), storage and warehouse(1.676), water transportation assistant services(1.422), and outport transportation (1.283). Second, value added inducement coefficient of water transportation assistant services was the highest(0.924), followed by load and unload, storage and warehouse(0.902), other transportation services(0.885), harbor facilities(0.832), coast and inland water transportation (0.752), and outport transportation(0.258). Third, import inducement coefficient of outport transportation was the highest(0.742), followed by coast and inland water transportation, harbor facilities, other transportation services, load and unload, storage and warehouse, and water transportation assistance services. Fourth, indexes of the sensitivity of dispersion of other transportation services and load and unload were 1.125 and 0.882 respectively while those of harbor facilities and outport transportation were 0.514. Indexes of power of dispersion of harbor facilities, coast and inland water transportation, load and unload, and other transportation services were the highest, respectively 1.006, 0.954, 0.946, and 0.908 while that of outport transportation was low, 0.659.

• 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 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.

• 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.

• 중국학논총
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• no.69
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• pp.167-186
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• 2021

在本研究中, 爲了分析自加入WTO以来中國金融業的生産誘導效應, 我們使用2007年, 2012年和2017年的中國投入産出表分析了与其他行業交换了哪些政策影響。主要分析結果如下。首先, 影響力系數而言, 在2007年和2012年, 對中國經濟發展産生影響的傳統制造業正逐渐向具備技術的專業裝備制造業轉移。分析表明, 由于出现冲突迹象, 中國金融業的發展已通過實施擴大内需的政策影響了中國的内需相關行業。其次, 感應度系數, 2007年是2006年加入WTO的五年。由于所有部門的全面開放, 對外貿易總额平均每年增長30％。結果, 認爲金融業已經受到金融業的影響, 幷受到其影響, 從而形成了良性循环。在2012年和2017年获得的結果相似, 在全球金融危机之后, 中國政府与基础設施的建設和重建有關, 例如《中國制造2025》和"一带一路", 以及中部地區, 東北振興和西部等區域均衡發展的政策。分析表明該行業已經影響了金融業。

• 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.

• Spatial Information Research
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• v.20 no.6
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• pp.69-76
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• 2012

In this study, we derived the characteristics of the geo-spatial information industry by using input-output analysis. For this analysis, we classified the geo-spatial information industry and reorganized the input-output table. And we derived the production inducement coefficient, index of the power of dispersion and index of the sensitivity of dispersion in the geo-spatial information industry. We confirmed that geo-spatial information industry has a small production inducement coefficient and a great forward linkage effect. Based on these facts, we suggested the strategy direction as follows: 1) building the industrial eco-system, 2) managing both advance and applicability enhancement, 3) Establishing from a long-term point of view.