중국 해운기업을 대상으로 한 DEA-AR/AHP 모형의 타당성 분석
Feasibility Study of DEA-AR/AHP Model for Chinese Shipping Companies
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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.
Abstract
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.
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