[논문]중국 수리조선산업의 효율성 분석에 관한 연구

양윤옥; 왕고봉

doi:10.38121/kpea.2017.12.33.4.117

중국 수리조선산업의 효율성 분석에 관한 연구
Analysis of the Efficiency of Chinese Repair Shipbuilding Industry 원문보기

한국항만경제학회지 = Journal of Korea Port Economic Association, v.33 no.4, 2017년, pp.117 - 134

양윤옥 (한국해운거래정보센터) , 왕고봉 (한국해양대학교 물류시스템공학과)

초록
AI-Helper

본 연구는 12개 중국 수리조선 업체를 대상으로 DEA모형을 활용해 중국 수리조선산업의 효율성을 분석하고자 하였다. 기존 연구들과 달리 본 연구에서는 연구대상 뿐만 아니라 선정된 투입과 산출변수도 차별성을 지닌다. 연구대상은 수리조선시장에서 경쟁우위를 보이고 있는 중국의 업체를 대상으로 진행하였다. 효율성 분석을 위한 투입변수는 시설 외에 기술자 수를 고려하였으며, 산출변수는 매출액 외에도 수리선 척수 및 서비스 범위를 사용하여 관련 변수들을 다양화하였다. 분석에는 DEA모형에 의하여 시설만 투입변수로 한 경우 및 시설과 기술자 수를 투입변수로 하여 차이점을 분석하였다. 비효율적인 DMU의 경우, 효율적인 DMU가 될 수 있도록 참조집합을 통해 비효율성의 원인을 찾아 장단점을 분석하였다. 또한 국영기업과 민영기업을 구분해서 개선방안을 도출하였다.

Abstract ▼ AI-Helper

The purpose of this research is to analyze the efficiency of the Chinese repair shipbuilding industry using a DEA model with 12 Chinese repair shipbuilding companies. Unlike preceding studies, this study has different research subjects as well as selected input and output variables. The research was conducted with competitive Chinese companies in the market. For the efficiency analysis, input variables included the number of technicians as well as facilities, and output variables were diversified with relevant factors using the number of repaired ships and service ranges as well as sales. The differences were analyzed by including only facilities as an input variable for the DEA model, and then both facilities and technicians. For inefficient DMUs, the strengths and weaknesses were analyzed by finding the causes through a reference group, which was developed into an efficient DMU. Moreover, public and private companies were separated to develop improvement measures.

주제어

AI 본문요약
AI-Helper

* AI 자동 식별 결과로 적합하지 않은 문장이 있을 수 있으니, 이용에 유의하시기 바랍니다.

문제 정의

Regarding the strengthened competitiveness of the Chinese industry, it identified decision-making units of the companies and analyzed efficiency levels. Based on the results, this research aims to provide officials from the Korean government and those who are involved in Korean repair shipbuilding companies with various implications for competitiveness and development of the Korean industry.
As such, this research utilized the DEA model to analyze the efficiency of 12 companies with top sales records in the Chinese repair shipbuilding industry in 2015. It aims to provide not only Chinese but also Korean repair shipbuilding workers with implications.
This research identified the input and output factors of inefficient DMU, and developed measures to improve efficiency based on improvement levels of inefficient companies. In particular, public companies among inefficient DMUs have relatively bigger liabilities and higher financial risks, causing additional financial expenses.

제안 방법

Based on existing research, this research selected total length and area of dock, total weight of dock and floating dock and number of technicians, which are factors that have the most direct influence on company efficiency, as input variables; and number of repaired ships, national and local scope that used repair shipbuilding service as well as 2015 sales as output variables. This research employed the DEA model and used the DEAP2.
Ecorys Research and Consulting(2009) analyzed the characteristics and development process of the shipbuilding industry in Europe. It also identified the current competitive status and competitors, and developed a strategy to develop the European shipbuilding industry by using the SWOT analysis technique.
The inefficient DMU was divided according to eh characteristics and further investigation was conducted on the DMU. As seen in Table 9, the pros and cons of inefficient DMUs were analyzed according to the characteristics of DMUs (public and private) and improvement measures were suggested.
The limitation of this research is that a non-parametric method including the DEA model was employed for analysis; it is necessary to further study using various methods including a parametric method. As there were a small number of repair shipbuilding companies that can be compared, and there were difficulties in investigating corporate internal financial conditions and collecting various evaluation data aside from service levels, it was difficult to conduct a comprehensive efficiency evaluation.

대상 데이터

This research analyzed 12 companies efficiency out of the top 14 Chinese repair shipbuilding companies in sales as of 2015, whose data were available. The data were collected from the 2016 China Shipbuilding Industry Yearbook, the China Association of the national Shipbuilding Industry Repair Branch, the companies’ official sites, phone calls and e-mails with persons in charge of operations, and ‘Report on the demand and supply and investment prospect and analysis on the Chinese repair shipbuilding industry’ by Forward Business Information Co.

이론/모형

Despite the studies and evaluations on the efficiency of the shipbuilding industry, further research on the repair shipbuilding industry is required. Accordingly, this research analyzed the efficiency of the top 12 Chinese repair shipbuilding companies in sales in 2015 using the DEA model. Regarding the strengthened competitiveness of the Chinese industry, it identified decision-making units of the companies and analyzed efficiency levels.
Although preceding research evaluated the efficiency of the shipbuilding industry and the Korean repair shipbuilding industry, none has conducted a study on the efficiency of the Chinese repair shipbuilding industry. As such, this research utilized the DEA model to analyze the efficiency of 12 companies with top sales records in the Chinese repair shipbuilding industry in 2015. It aims to provide not only Chinese but also Korean repair shipbuilding workers with implications.
Although the Chinese repair shipbuilding market is getting bigger, it is necessary to evaluate the industry at this point. In order to understand repair shipbuilding companies in China, this research analyzed the efficiency of 12 Chinese companies using the DEA model.

성능/효과

For the corporate characteristics, public enterprises and private enterprises, the average efficiency of inefficient DMU was compared by inputting facility and number of facilities and technicians, and private enterprises showed higher average efficiency. In general, unlike corporate characteristics, inputting both facility and number of technicians had higher average efficiency than inputting only facility.
While most of existing literature considered variables for facility, this research conducted efficiency analysis considering number of technicians; this means a difference in the existing efficiency score. The analysis results revealed six efficient companies including DMU 1, 5, 6, 8, 10 and 11 and the other six inefficient companies including DMU 2. When number of technicians was used as an input variable, DMU8, a non-efficiency company, was converted into an efficient one.
Dev and Saha(2015) estimated multiple regression models by the least squares method so as to develop a model on ship repair time with 600 cargo ships dealt with at a single yard. The analysis results showed that ship type, age of vessel, loadage, and major hull repair tasks including coating, piping, structural steel and tank coating had effects on repair shipbuilding time.

참고문헌 (25)

Charnes, A., Cooper, W. W. and Rhodes, E. (1978), Measuring the efficiency of decision making units, European Journal of Operational Research, 2(6), 429-444.

상세보기
Chen, Z. Q., and He, Z. Q.(2015), Efficiency analysis of shipbuilding industry in China based on PCA-DEA model, Manager' Journal, 2015(9Z), 171-172.
China Association of the National Shipbuilding Industry : http://www.cansi.org.cn.
China Industry Information Network(2016), Analysis of the Development of Shipbuilding Industry in China, http://www.chyxx.com/industry.
China Ship Network(2007), Present Situation Analysis and Countermeasures of Ship Repair Market, http://www.cnshipnet.com.
Dev, A. K., and Saha, M.(2015), Modeling and Analysis of Ship Repairing Time, Journal of Ship Production and Design, 31(2), 129-136.

상세보기
Ecorys research and consulting(2009), Study on Competitiveness of the European Shipbuilding Industry. Within the Framework Contract of Sectoral Competitiveness Studies -ENTR/06/054, Final report.
Forward Business Information Co.,Ltd (2017), Report of Prospects and Investment Forecast on China Ship Repairing Industry (2017-2022).
Jiang, L. P., and Bastiansen, E., Strandenes, S. P.(2013), The International Competitiveness of China's Shipbuilding Industry, Transportation Research Part E, 60, 39-48.

상세보기
Kim, Y. J., and Park, E. Y. (2016),Measuring the Efficiency and Productivity in Ship Repair Industry using DEA and MPI, Journal of Korean National Economy, 34(2), 95-119.
Kim, Y. M.(2017), An Analysis of Multidimensional Productivity for the Shipbuilding Performance, Korean Management Science Review, 34(2), 57-66.
Kim, M. Z.(2010), An Empirical Study on the Management Efficiency of the Domestic Shipbuilding Industry Using DEA Model, The Journal of Shipping and Logistics, 26(3), 651-673.
Koo, J. S., Lee, J. S. and Jia, Y. W.(2014), A Study on the Efficiency and Productivity Analysis of Chinese Major Shipyards, Journal of International Trade&Commerce, 10(3), 469-488.
Korea International Trade Association(2016), Current Status and Characteristics of Chinese Shipbuilding Industry.
Lee, J. P., and Jang, Y. S.(2012), Measuring Relative Efficiency of Marine Engine Repair Company Using DEA -Specially located in Yeong-Do Gu, Busan-, The Journal of Fisheries Business Administration, 43(2), 51-66.

원문보기 상세보기
Lee, J. S., Kim, Y. K. and Noh, H. S.(2015), The Emergence of Competitiveness in Korea-China Ship Distribution Industry, Journal of Distribution Science, 13(7), 11-18.

원문보기 상세보기
Oh, J. S., Sin, Y. Jon. and Lee, S. D.(2007), Plan for Vitalization of Busan New Port by Activating Ship-Repair Industry, Journal of the Korean Society of Marine Engineering, 31(6), 810-817.

원문보기 상세보기
Park, H. H., Kim, C. and Du, J. I.(2003), Status and Development Plan of Repair Shipbuilding Industry in Pusan Area, Regional Economic Research Data.
Park, M. H.(2008), Efficiency and Productivity Analysis, Korean Academic Information.
Park, S. H.(2010), Efficiency and Productivity of Seven Large-sized Shipbuilding Firms in Korea, Journal of Korea Port Economic Association, 6(4), 88-206.
Park, S, H., and Kim, H, N.(2012), The Change of Productivity and Efficiency of Korean Shipbuilding Industry and Its Determinant, Journal of Korea Port Economic Association, 28(2), 155-177.
Sina Finance(2017), A Quarter of Shiprepair Dock Utilization Rate of 95% Industry Consensus:Cautious Optimism, http://finance.sina.com.cn.
Song, H. C., Seo, M. C. and Yum, J. S.(2010), Analysis on the International Competitiveness of Ship Repair Industry in Korea, Journal of Korean Navigation and Port Research, 34(10), 799-805.

원문보기 상세보기
Zhang, L., Xu, Z. C. and Liu, Y. Q.(2011), Efficiency Evaluation of Production Process Optimization for Small and Medium Sized Shipbuilding Enterprises Based on DEA Method, Ship&Ocean Engineering, 40(3), 73-76.
Zhang, H., and Xu, X. G.(2010), Analysis and Evaluation on Management Efficiency of Shipbuilding Enterprises Based on the Dea, Journal of Systems & Management, 19(1), 49-55.

저자의 다른 논문 :

표제어: PCR

동의어: Packet Collision Rate

용어 설명 출처 목록 (6)

용어 설명: PCR은 세균 특이성이 있는 primer를 이용하여 적은 수의 세균이 있을지라도 쉽게 검출할 수 있는 유용한 방법이며, 이를 이용하여 구강 내 치면세균막이나 타액에서 직접 세균을 검출할 수 있게 되었다[8].

내보내기 구분	파일저장 인쇄 메일전송
구성항목	기본정보 상세정보 관리번호, 논문명, 저널/프로시딩명, 저자 , 발행년, 권, 호, 시작페이지, 끝페이지, 발행기관 관리번호, 논문명, 대등논문명, 저자 , 저널/프로시딩명, 발행기관, 발행년, 발행언어, 권, 호, 시작페이지, 끝페이지, ISBN, ISSN, 주제분야, 키워드, 초록(한글), 초록(영문), 저자(소속기관)
저장형식	Text(ASCII format) Excel format RefWorks Direct Export RIS format (for Reference Manager, ProCite, EndNote), Scholar's Aids, Mendeley
메일정보	받는사람 (필수) @ 보내는사람 (선택) @ 제목 내용 KISTI 검색결과 이메일 서비스
안내	총 건의 자료가 검색되었습니다. 다운받으실 자료의 인덱스를 입력하세요. (1-10,000) 검색결과의 순서대로 최대 10,000건 까지 다운로드가 가능합니다. 데이타가 많을 경우 속도가 느려질 수 있습니다.(최대 2~3분 소요) 다운로드 파일은 UTF-8 형태로 저장됩니다. 파일의 내용이 제대로 보이지 않을실 때는 웹브라우저 상단의 보기 -> 인코딩 -> 자동선택 여부를 확인하십시오. ~ Text(ASCII format) Excel format

연합인증