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      • KCI등재

        DEA와 Malmquist 지수를 활용한 한·중·일 해운기업의 효율성 및 생산성 분석

        가이어동 ( Gai Yu-tong ),구종순 ( Koo Jong-soon ) 한국해운물류학회(구 한국해운학회) 2017 해운물류연구 Vol.33 No.특별호

        본 논문은 DEA와 Malmquist 지수를 활용하여 한·중·일 해운기업의 효율성 및 생산성을 평가하였다. 2009년부터 2015년까지 자료수집이 가능한 13개 중국 해운기업, 9개 한국 해운기업, 5개 일본 해운기업을 대상으로 DEA를 활용하여 각 연도별 효율성을 평가한다. CCR 모형과 BCC 모형에 의한 정태적 효율성 분석 결과, 대체로 일본 해운기업이 한·중 해운기업보다 효율성이 높게 나타났다. Malmquist 지수에 의한 생산성 변화의 측정 결과, 2009년~2015년간 7개 중국 해운기업의 평균생산성 변화는 1.064로 매년 6.4%씩 생산성이 상승하는 것으로 나타났고, 4개 한국 해운기업의 평균생산성 변화는 1.075로 매년 7.5%씩 생산성이 상승하는 것으로 나타났고, 4개 일본 해운기업의 평균생산성 변화는 1.066로 매년 6.6%씩 생산성이 상승하는 것으로 나타났다. This paper aimed at evaluating the efficiency and productivity of shipping companies from Korea, China, and Japan using the DEA method and Malmquist index. The DEA method was first employed to assess the annual efficiency of 13 Chinese, nine Korean, and five Japanese shipping companies based on the data collected from 2009 to 2015. As a result of the statistical efficiency analysis through the DEA-CCR and DEA-BCC models, the Japanese shipping companies showed higher efficiencies than the Korean and Chinese shipping companies. Furthermore, the measurement of productivity change through the Malmquist model demonstrated the following outcomes: the average productivity change of the seven Chinese shipping companies during the period 2009 to 2015 was 1.064, which represented an annual productivity increase of 6.4%; the average productivity change of the four Korean shipping companies was 1.075, increasing at 7.5% annually; and the average productivity change of the four Japanese shipping companies was 1.066, increasing at 6.6% annually.

      • KCI등재

        중국 해운기업을 대상으로 한 DEA-AR/AHP 모형의 타당성 분석

        구종순 ( Jong Soon Koo ),가이어동 ( Yu Tong Gai ) 한국해운물류학회(구 한국해운학회) 2016 해운물류연구 Vol.32 No.2

        2008년 글로벌 금융위기 이후 전세계 해상 물동량 감소 및 해운산업의 침체는 해운기업 간의 치열한 경쟁을 야기하고 있으며 또한 해운기업들 간의 전략적 제휴의 확대를 가져왔다. 전략적 제휴를 통해 규모의 경제를 달성한 거대 해운동맹들과의 경쟁에서 살아남기 위한 경쟁력 제고를 위해 중국 해운기업들의 효율성을 진단하고, 본 연구의 결과인 해운기업 간 효율성 측정치의 우선순위결정은 중국 정부의 해운기업 육성정책 또는 해운기업의 운영평가의 순위를 결정하는데 있어서 객관적이고 합리적인 평가기준을 제시하는 기초자료로 사용될 것이다. 이에 본 연구는 중국 해운기업들을 대상으로 DEA-AR/AHP 분석방법을 사용하여 상대적 효율성을 평가하고 DEA-AR/AHP 결합모형이 기존의 DEA모형에 비해 효과적인 방법임을 제시한다. The study attempts to analyze the efficiency of Chinese shipping companies using DEA-AR/AHP and to verify that this methodology is the most effective to analyze the efficiency of shipping companies compared to DEA(Data Envelopment Analysis), which is used for efficiency analysis in general. DEA has two models: CCR (Charnes, Cooper, and Rhodes, 1978) and BCC (Banker, Charnes, and Cooper, 1984). This study compares the results both between CCR and CCR DEA-AR and between BCC and BCC DEA-AR. According to the empirical analysis, DEA-AR/AHP is very effective to analyze the efficiency compared to previous DEA methodology because it is possible to show the order of priority among shipping companies. Some results of the empirical analysis and the implication are as follows. First, the study verified the order of priority of 13 Chinese shipping companies through DEA-AR analysis. According to CCR-AR, only one company was effective throughout entire period (2009-2014) of analysis and other companies were not effective at all. Additionally, the difference in effectiveness between effective and ineffective shipping companies is too big. The results of BCC-AR also show that the effective number of shipping companies are 3, 3, 2, 2, 3, and 2 in 2009, 2010, 2011, 2012, 2013, and 2014 respectively. The number of effective shipping companies based on CCR-AR is smaller than the number of effective shipping companies based on BCC-AR, considering variable RTS (returns to scale). Second, according to the empirical results between DEA and DEA-AR/AHP, the number of effective shipping companies under BCC-AR is reduced twice or three times as much as it is in BCC. In the same way, the number of effective shipping companies in CCR-AR is reduced three or four times as much as it is in CCR. Based on this result, DEA-AR/AHP is more effective than previous DEA for the effective analysis of shipping companies. Moreover, according to empirical analysis, some Chinese shipping companies still maintain high efficiency under what has become a challenging environment. The contribution of this study has been to provide objective evidence of Chinese shipping companies` competitiveness to policy-makers and thus encourage them to consider practical ways for the sustainable development of shipping companies. Moreover, the academic research in relation to Chinese shipping companies using DEA-AR/AHP methodology is still insufficient. It is absolutely necessary that academic research analyzes the situation and environment of shipping companies, and suggests strategies and policy to increase shipping companies` competitiveness. This study has some limitations with regard to the empirical analysis. This study uses general data and financial data to analyze efficiency due to the absence of data. However, it is better to consider other data such as capacity of operation, satisfaction, policies by shipping institutes or authority in order to verify the efficiency of shipping companies. Moreover, this study conducted the empirical analysis with smaller samples even though DEA analysis requires large DMUs for relative efficiency analysis; it also did not consider Chinese small-sized shipping companies. Therefore, in the future, we will attempt to conduct research related to the efficiency of small-sized shipping companies.

      • KCI등재

        DEA-AR/AHP 모형을 이용한 한 · 중 해운기업의 효율성 분석

        구종순(Jong-Soon Koo),가이어동(Yu-Tong Gai) 한국무역연구원 2017 무역연구 Vol.13 No.2

        As global sourcing increases worldwide and the separation of production and consumption markets continue to grow, the maritime industry is becoming increasingly important as world commodity trade expands. This study compares the efficiencies of Korean and Chinese maritime companies by using the DEA-AR/AHP model, which can largely improve the evaluation quality for efficiency discrimination and also search for more efficient benchmarked shipping companies. In order to combine the DEA-AR model with the AHP method, we conducted a survey on 23 maritime companies in Korea and China using a questionnaire. After evaluating the efficiencies of these 23 Korea-China shipping companies by using the DEA-CCR-AR/AHP result obtained through the DEA-AR/AHP model, it was found that Korea’s Sinokor Merchant Marine Co., Ltd. was the most efficient shipping company from the year 2010 to 2015, whereas the other shipping companies exhibited less efficiency.

      • KCI등재

        우리나라 조선산업에서 특허가 국제경쟁력에 미치는 영향에 관한 분석

        구종순 ( Jong Soon Koo ),황정현 ( Jung Hyun Hwang ),가이어동 ( Yu Tong Gai ) 한국해운물류학회(구 한국해운학회) 2013 해운물류연구 Vol.29 No.3

        본 연구의 목적은 우리나라 조선산업의 현황을 파악하고, 지속적인 비교우위를 유지할 수 있는 방안을 제시하기 위한 것이다. 이러한 연구목적을 달성하기 위해 조선 산업의 무역특화지수, 불변시장점유율 분석, 수출경합도 등의 다양한 지수들을 이용하여 국제경쟁력을 측정하였다. 그리고 Malmquist지수를 이용하여 조선산업 주요국의 생산성변화를 분석한 결과 한국, 중국, 일본 모두 2000년대 중반이후 생산성이 하락하는 추세를 보이고 있는데, 생산성은 기술혁신과 밀접한 관련이 있으므로 이러한 생산성 하락은 보다 강한 기술혁신이 필요한 시점이라고 할 수 있다. 또한 기술혁신을 대표하는 특허변수를 고정효과모형에 이용하여 주요 산업의 국제경쟁력 결정요인을 분석한 결과 IT, 신재생에너지, 조선산업 모두에 (+)영향을 미치는 변수였으며, 특히 조선산업에서 영향력이 가장 크게 나타났다. Globalization has been discussed as an important market environment in various territories. Maritime industry is also closely associated with globalization. Together with globalization, faster, more reliable, and cheaper maritime transport services have facilitated the expansion of global trade. With the development of emerging economies, the maritime industry had increased dramatically. The rise of China as the world manufacturing center was a key driver of this growth. Since 2008, however, there have been some declines because of the global financial crisis. It is not easy for container ports to have a sufficient container cargo volumes including transshipment. Therefore, container ports in individual countries require effective strategies for generating sufficient container traffic. Through a country-level analysis, this paper is designed to empirically investigate the influences of globalization on individual container ports` internal capabilities and transshipment traffic volumes.

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