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ABSTRACT 12
제1장 서론 16
제1절 연구의 목적 16
제2절 연구의 방법 및 논문의 구성 17
제3절 기존연구에 대한 검토 19
1. 국내연구 19
2. 국외연구 20
제2장 중국 주요항만의 역사, 현황, 정책 및 전략 23
제1절 중국 주요항만의 역사 및 현황 23
1. 중국항만의 역사 및 일반현황 23
2. 중국 10개 주요항만의 역사 및 현황 25
3. 중국항만의 물동량 현황 54
4. 중국항만 기항현황 62
제2절 중국 주요항만의 항만정책 66
1. 중국의 항만정책의 변화 66
2. 중국정부의 항만전략 70
제3장 중국 주요항만의 효율성분석 73
제1절 효율성의 개념 및 측정방법 73
제2절 DEA기법을 활용한 경쟁력 분석 76
1. DEA의 정의 76
2. DEA의 특징 77
3. DEA의 한계 78
4. DEA 모형의 효율성 측정방법 79
제3절 변수선정 88
제4절 실증분석과 해석 90
1. CCR과 BCC분석 91
2. Malmquist 분석 94
제4장 SWOT분석을 통한 중국 주요항만의 특성분석 105
제1절 SWOT분석의 이론적 고찰 105
제2절 SWOT분석을 통한 항만별 특성분석 105
1. 다롄항 106
2. 톈진 109
3. 칭다오 112
4. 상하이 117
5. 닝보 120
6. 카오슝 121
7. 홍콩 123
8. 심천 124
9. 광저우 126
10. 샤먼 127
제3절 SWOT분석을 통한 지역별 특성분석 128
1. 동북·화북지역 129
2. 화동 및 대만지역 131
3. 화남지역 132
제4절 SWOT분석을 통한 종합적인 특성분석 134
1. 거시적 부분 135
2. 미시적 부분 137
제5장 중국 주요항만의 경쟁력 강화방안 146
제1절 항만별 경쟁력 강화방안 146
1. 다롄항 146
2. 톈진항 149
3. 칭다오항 150
4. 상하이항 151
5. 닝보 152
6. 카오슝 153
7. 홍콩항 155
8. 심천항 156
9. 광저우항 158
10. 샤먼 159
제2절 지역별 항만의 경쟁력 강화방안 160
1. 동북·화북지역 160
2. 화동 및 대만지역 161
3. 화남지역 162
제3절 중국주요항만의 종합적인 경쟁력 강화방안 164
1. 해운정책 강화 및 법률의 실시 관리와 감독 166
2. 정보 기술의 발전방안 168
3. 해운회사의 연합 및 합병전략 170
4. 선박구조의 개선 174
5. 개별항만 자체의 효율성 증진을 통한 경쟁력 강화방안 176
제6장 결론 및 정책적 함의와 향후연구방향 176
제1절 결론 177
제2절 정책적 함의 178
제3절 향후 연구의 방향 179
부록 180
참고문헌 186
감사의 글 193
[그림 1] 중국연해항만 분포도 22
[그림 2] 톈진항 컨테이너 처리실적 추이 29
[그림 3] 상하이항 연간 컨테이너 물동량 상황 35
[그림 4] 항만규모(2006년 기준) 59
[그림 5] 중국의 GDP증가율과 컨테이너물동량의 탄성치 59
[그림 6] 중국 중심의 컨테이너 해상항로의 변화 62
[그림 7] 중국항만 기항수 증가추이 63
[그림 8] 맴퀴스트분석에 의한 항만별 효율성 지수의 변화 98
[그림 9] 1999-2006년까지의 중국 10개 주요항만의 Malmquist(Maimquist)분석에 의한 5개 효율성수치의 변화 101
[그림 10] 화남지역 경제발전구 163
[그림 11] 중국 컨테이너항만의 지속적인 발전 가능성 165
[그림 12] 중국 컨테이너항만의 발전가능성 순위 165
The purpose of this paper is to investigate the efficiency of 10 major Chinese ports using DEA(data envelopment anlaysis) and to find the special characteristics using SWOT(Strength, Weakness, Opportunities, and Threats) method, and according to that empirical results, to suggest the strengthening plan for enhancing the competition power.
Logistics hub-ports are playing more and more important role in global economy. Like other countries. China has also been doing constructions on logistic hub ports since 1984 by opening its shipping market and improving the infrastructures.
After Chinese access to WTO, the competition situation has become grimmer. As for the port logistics enterprise of our country, which have just begun to develop, with the all-round openness of the port to the outside world, facing the old brand post logistics enterprise of the developed countries in the world, relying on advanced logistics equipments and installations, logistics management, they are aiming at the huge port logistics market-china, eager to have a try. In these circumstances, we must make thorough study of the port logistics enterprise.
Especially this investment is intensively being made in the economic special area which is authorized by Chinese government. As the economy grows rapidly, three economic special areas-Bohai(渤海) Bay Area in northern region, Changjiang(長江) Delta Area in the eastern region, Zhuijiang(珠江) Delta Area in the southern region-is being developed into the agglomeration are which attracts all kings of production factor including labor, capital and technology connected to manufacturing industry, financial market and R&D center etc., which leads to the creation of increasing returns to scale. So it is never accidental that the ports is well constructed and operated in this 3 areas.
This study tries to apply the Data Envelopment Analysis(DEA) model to the competitive power of 10 major ports in China for 8 years from 1999 to 2006 through DEA-CCR, DEA-BCC, Malmquist model and scale efficiency. DEA is an efficiency evaluation model based on mathematical programming theory. DEA offers an alternative to classical in extracting information form sample observation. DEA optimizes each individual observation with the objective of calculating a discrete piece-wise frontier determined ty the set of Pareto efficient decision making units(DMUs). DEA analysis can involve multiple inputs as well as multiple outputs in its efficiency valuation. This makes DEA analysis more suitable for port efficiency measurement because ports produce a number of different outputs. Furthermore, DEA provides the user with information about the efficient and inefficient units, as the efficiency scores and reference sets for inefficient units.
This paper also analyzed the current status of the competitive power of 10 major ports in China using efficiency and SWOT analysis and sought the solutions that will be helpful in making further strategy for the future development of these 10 ports. Through the analysis, this paper could investigate the efficiency of 10 major Chinese ports and figure out the trend of the efficiency during the recent 8 years from 1999 to 2006. To carry out a SWOT analysis, this paper focused on problems and improvement plan in terms of geographical location, hinterland city, hinterland industrial complex, location of main route, port facility, and port policy. That is aimed to suggest the proper measures for developing Chinese part into the logistics hub port in the Asia - Pacific region.
The main empirical results are as follows:
First, empirical study by using CCR and BCC models show that the ports of Ningbo, Hong Kong, Kaohsiung and Shenzhen were found to be at high efficient level. The ports of Ningbo, Hong Kong, Xiamen and Shenzhen show the high efficient levels under the BCC model. The ports of Hong Kong, Xiamen and Shenzhen show the constant or increasing returns to scale.
Second, the trends of efficiency change for 8 years by using Malmquist model show that all other period except 2002/2003 and 2004/2005 which were decreasing in efficiency were upward tendency in terms of averaged Malmquist index. The averaged Malmquist efficiency of the ports of Ningbo and Xiamen has rapidly upwarded. The averaged technical efficiency change has shown the upward trends except the periods of 1999/2000, 2002/2003 and 2004/2005 which have been declined. However, overall efficiency was decreasing.
The policy implications of this thesis are as follows:
First, the CCR-BCC, Economies of Scale and Malmquist models have the merits of providing an alternative method to traditional DEA models for measuring the efficiency of seaports. Malmquist model showed the usefulness for measuring the trends of efficiency change dynamically for 8 years.
Second, when port authorities want to measure the international competitive strength of seaports and enhance their efficiency, they should consider both the traditional method as well as the introduction of the Malmquist models including CCR-BCC model. Chinese ports should be more wisely opened to foreign companies, not only for getting more investment and advanced technology but also for getting the experience about port operation.
Third, the planner of seaport policy should adopt and enforce the efficiency evaluation indicators for enhancing the competition power with the efficiency of individual seaport. Chinese ports have to figure out a good way to set a balanced relationship with eht middle and small sized ports around it to keep them from malignant competition an make a just competitive atmosphere for the shipping market.
Fourth, policy planner of seaport should introduce the port management by private enterprises for the scientific and systematic port management efficiently. Improve the information system by uniting the different information systems in all the sections of the port and establishing the database and EDI system.
Fifth, Chinese parts have to build multi functional logistics park by improving the function of the International logistic center, the High Tech Park and the traffic network of the hinterland.*표시는 필수 입력사항입니다.
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