• 한국항공운항학회지
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• 제14권3호
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• pp.30-39
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• 2006

The purpose of this study is to analyze how much Air Transportation Industry contribute to national economy by measuring economic spreading effects of Air Transportation Industry on national economy. To achieve the purpose of the study, the study uses an Air Transportation Input-Output Table of year 2000 of korea. The results shows that Air Transportation Industry induce 274,530.8 billion won of national production, import inducement 13,7073.7 billion won, value-added 110,994.9 billion won, especially Air Transportation Industry shows that production inducement coefficient is 1.36803, import inducement coefficient is 0.60581, value-added coefficient is 0.45189, income inducement coefficient is 0.18599 and employment inducement coefficient is 0.00841.

• 한국정보전자통신기술학회논문지
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• 제13권1호
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• pp.72-80
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• 2020

인공지능, IoT 등의 4차 산업의 등장으로 정보화는 가속화됨에 따라 정보보호 산업의 중요성과 시장의 규모가 증가하고 있다. 본 논문에서는 증가하는 정보보호 산업이 국내 경제에 미치는 영향을 산업연관표를 이용하여 분석하였다. 본 논문에서는 산업부문을 정보보호 제품산업과 정보보호 서비스 산업을 분류한 후에, 35개의 산업으로 산업연관표를 재분류하였고, 생산유발계수, 부가가치유발계수, 고용유발계수 등을 산출하였다. 정보보안 제품산업과 정보보안 서비스 산업의 생산유발계수는 각각 1.571, 1.802이고, 부가가치유발계수는 각각 0.632, 0.997이고, 고용유발계수는 각각 2.494, 7.361이다. 정보보호 서비스 산업의 부가가치유발계수만이 전체 산업보다 다소 높고, 나머지 유발계수는 모두 전체 산업보다 낮게 나타났다. 그리고 정보보호 제품산업에는 전·후방연쇄효과가 없고, 정보보호 서비스 산업에는 후방연쇄효과는 없으나 전방연쇄효과는 있는 것으로 나타났다. 정보보호 산업의 경제적 파급효과를 분석한 결과, 생산유발액은 359.9조원, 부가가치유발액은 164.8조원에 달하고, 803천명의 고용을 유발하는 것으로 나타났다.

• 유통과학연구
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• 제19권3호
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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.

• 방송공학회논문지
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• 제26권5호
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• pp.575-582
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• 2021

본 논문에서는 국회 FM라디오의 신규 재정 투입에 따른 경제적 효과 분석을 하고자 한다. 최근 4차 산업혁명과 뉴미디어 패러다임 변화로 모바일, 인터넷, OTT 등 다매체 다채널로 변화하고 있다. 이러한 변화하는 대내외적 여건을 반영하여 국회방송에서도 시청자가 공간과 시간적 제약 없이 공공서비스를 이용할 수 있도록 FM라디오 방송의 도입이 요구된다. 따라서 본 연구는 국회 FM 라디오의 신규 정부 재정 투입 소요 예산을 추계하여 분석을 수행하고자 한다. 주요 분석결과는 생산유발계수는 1.661이며, 부가가치 계수는 1.141, 고용유발계수는 7.1로 도출되었다. 수도권권역기준으로 생산유발효과 69.28억원, 부가가치유발효과 47.58억원, 고용유발효과 28.4명으로 분석되었다. 또한, 전국권역기준으로 생산유발효과는 132.57억원, 부가가치유발효과는 91.06억원 고용유발효과는 49.7명으로 추정되었다.

• 한국산림과학회지
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• 제96권3호
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• pp.338-347
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• 2007

본 논문의 목적은 2000년 대형산불 발생지역인 강원도 내 삼척시, 고성군, 동해시를 대상으로 산업연관분석을 이용하여 산불피해 복구를 위한 정부지원액이 지역경제에 미치는 파급효과를 분석하는데 있다. 생산유발효과는 세 지역 모두 건설업을 제외한 모든 산업에서 직접 생산유발효과가 간접 생산유발효과보다 큰 것으로 나타났다. 소득유발효과는 생산유발효과와 비슷하였고, 고용유발효과는 세 지역의 모든 산업에서 간접 고용유발효과가 직접 고용유발효과보다 크게 나타났다. 동해시에서 전체적으로 삼척시, 고성군보다 생산유발효과 및 소득유발효과가 더 효율적인 것으로 나타났고, 삼척시에서는 고성군, 동해시보다 고용유발효과가 더 효율적으로 사용된 것으로 나타났다.

• 산업경영시스템학회지
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• 제38권4호
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• pp.39-44
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• 2015

The VHTR (Very High Temperature gas-cooled nuclear Reactor) has been considered as a major heat source and the most safe generation IV type reactor for mass hydrogen production to prepare for the hydrogen economy era. The VHTR satisfies goals for the GIF (Generation IV International Forum) policy such as sustainablility, economics, reliability and proliferation resistance and physical protection, and safety. As a part of a VHTR economic analysis, we have studied the VHTR construction cost and operation and maintenance cost. However, it is somewhat difficult to expect the ripple effect on the whole industry due to the lack of information about Inter-industries relationship. In many case, the ripple effect are based on experts' knowledge or uncertain qualitative assumptions. As a result, we propose quantitative analysis techniques for ripple effects such as the production inducement effect, added value inducement effect, and employment inducement effect for VHTR 600MWt${\times}$4 modules construction and operation ripple effect based on NOAK (Nth Of A Kind). Because inducement effect values have been published annually, we predict inducement effect's relation function and estimated values including production inducement effect value, added value inducement effect value, and employment inducement effect value using time series and estimated values are verified with published inducement effects' value. This paper presents a new method for the ripple effect and preliminary ripple effect consequence using a time series analysis and inter-industry table. This ripple effect analysis techniques can be applied to effect expectation analysis as well as other type reactor's ripple effect analysis including VHTR for process heat.

• 한국콘텐츠학회논문지
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• 제13권1호
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• pp.147-155
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• 2013

본 연구의 목적은 공연산업의 경제적 파급 효과를 분석하는데 있다. 연구분석을 위해 한국은행의 2009년 산업연관표를 이용하여 연극, 음악 및 기타 예술(390 부문)만을 공연산업으로 한정하고 새로이 공연 산업연관표를 작성하여 공연산업의 경제적 파급효과를 분석하였다. 연구 결과, 공연산업의 총생산유발액은 391.6조원, 소득유발액은 65.1조원, 생산세유발액은 총 16.3조원으로 나타났다. 특히 공연산업의 생산유발계수는 1,387, 감응도 계수 0.020, 영향력계수 0.025, 부가가치유발계수 0.662, 소득유발계수 0.455, 생산세유발계수 0.046 그리고 노동유발계수 0.010 등으로 나타났다.

• 한국정보통신학회논문지
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• 제18권4호
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• pp.771-778
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• 2014

본 연구에서는 우리나라의 지식서비스 산업에 대한 생산유발, 부가가치유발, 고용유발 효과 및 전 후방연쇄효과를 추정하였다. 지식서비스 산업은 부가가치 및 고용 증대에는 크게 기여하고 있지만, 생산유발이나 전 후방연쇄효과는 매우 취약한 것으로 나타났다. 최근 정부는 지식서비스 산업으로부터 새로운 성장 동력을 찾고 있는데, 그 방향성은 지식서비스 산업의 생산성 향상이 되어야 한다는 사실이 본 연구를 통하여 입증되었다.

• 산경연구논집
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• 제10권5호
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• pp.27-36
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• 2019

Purpose - Naver has emerged as a new leader in the open market. While existing open markets such as Gmarket, 11th Street, and so on are suffering from profitability deterioration, Naver is attracting sellers based on low commission and powerful search engine. We would like to analyze the impact of Naver shopping on the national economy, especially on employment, in a situation where the market reaction to Naver's strength as a leader in online shopping is mixed. Research Design, Data, and Methodology - Through the demand inducing inter-industry analysis, we estimate the employment inducement effect by Naver shopping from its shopping transaction. In turn, through the supply inducing inter-industry analysis, we estimate the employment inducement effect by Naver shopping from its low commission and powerful search engine. For the purpose of inter-industry analysis, as of 2018, the most recently announced 2014 inter-industry table (extension table) from the Bank of Korea is used. Results - The results of this study are as follows. First, Naver Shopping is expected to generate 7.8 trillion won's trade in 2018, resulting in 244,225 of job inducement, and 158,598 of employment inducement. In addition, Naver Shopping is estimated to benefit KRW 213 billion to its sellers due to low commission and powerful search function, resulting in 8,667 of job inducement, and 5,655 of employment inducement. Second, in terms of job inducement and employment inducement due to Naver Shopping's trade, transportation, business support service, information and communication, broadcasting, restaurants and lodging were ranked. Third, in terms of job inducement and employment inducement due to Naver Shopping's low commission and powerful search function, restaurants and hospitality, f/b and cigarette manufacturing, construction, and transportation equipment manufacturing were ranked. Conclusions - The number of job inducement resulting from low commission and powerful search engine of Naver shopping in 2018 was 8,667 (3.7% of 244,225, which was caused by transaction in Naver shopping in 2018), and employment inducement was 5,655 (3.7% of 158,598, which was caused by transaction in Naver shopping in 2018), which can be considered as additional employment impacts of Naver Shopping compared to the other online shopping operators.

• 한국IT서비스학회지
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• 제13권3호
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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.