This book helps to solve the problem of substantial waste and inefficiency in port production by analyzing operational efficiency at more than 30 Chinese and Korean leading container ports using three types of DEA model. In addition it offers a returns-to-scale analysis， which is particularly useful for port managers or policy makers deciding on the scale of production. The results provide port managers and relevant scholars with insights into resource allocation and operating performance optimization. This book was supported by the National Fund for Academic Publication in Science and Technology.

　As the competition among the world container terminals has become increasingly fierce， every terminalis striving to increase its investments constantly and lower its operational costs in order to maintain the competitive edge and provide satisfactory services to terminal users. The unreasoning behaviour， however， has induced that substantial waste and inefficiency exists in container terminal production.Therefore， it is of great importance for the manager to know whether it has fully used its existing infrastructures and that output has been maximized given the input.
　　From this perspective， data envelopment analysis (DEA) provides a more appropriate benchmark for the container terminal. This study analyzes the relevance of data envelopment analysis (DEA) to the estimation of productive efficiency in the container terminal industry. Following an exposition of the DEA methodology，the many previous applications of the technique to the terminal industry are reviewed and assessed. The DEA technique is illustrated through a detailed application of data relating to the Chinese and Korean major container terminals.This study applies three models of DEA to acquire a variety of analytical results about the operational efficiency of container terminals. By applying with the DEA models based on input orientation and output orientation， the study first establishes the causes of inefficiency on the basis of efficiency value analysis. Slack variable analysis is then used to identify potential areas of improvement for inefficient terminals and giving the projection results. This is followed by the utilization of retum to scale analysis to assess whether each terminal is in a state of increasing，decreasing， or constant return to scale.
　　Overall， the results reveal that substantial waste exists in container terminal production. It is also found that the Chinese and Korean major terminals exhibit a mix of decreasing， increasing and constant returns to scale. The study concludes that the optimum efficiency levels indicated by DEA results might not be achievable in reality， because each individual terminal has its own specific and unique context.Moreover， the results of this study can provide terminal managers with insights into resource allocation and optimization of the operating performance.
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Preface
1 Introduction
1．1 Background of Research
1．2 Purpose and Method of Research


2 DEA Conceptual Exposition and Literature Review
2．1 Data Envelopment Analysis Conceptual Exposition
2．2 Economic Meanings of DEA Efficiency
2．3 Literature Review of DEA to Container Terminals


3 Evaluation Modeling for Container Terminal
3．1 Approach of Definition Variables
3．2 Implementation of Definition Variables
3．3 Definition of Output Variable
3．4 Definition of Input Variables
3．5 Standardization of Output and Input Variables
3．6 Flow Process of DEA Analyses
3．7 Research Procedure


4 Data Collection and Analysis
4．1 Outline of Chinese Container Ports
4．1．1 Description of Shanghai Port
4．1．2 Description of Hong Kong Port
4．1．3 Description of Shenzhen Port
4．1．4 Description of Qingdao Port
4．1．5 Description of Ningbo Port
4．1．6 Description of Guangzhou Port
4．1．7 Description of Tianjin Port
4．2 Outline of Korean Container Ports
4．2．1 Description of Busan Port
4．2．2 Description of Gwangyang Port
4．2．3 Description of Incheon Port
4．2．4 Description of Ulsan Port
4．2．5 Description of Masan Port
4．2．6 Description of Gunsan Port
4．2．7 Description of Pyeongtaek Port
4．3 Collected Data Analysis


5 Efficiency Analysis and Implication
5．1 Efficiency Analysis of Container Terminals
5．2 Implication of Efficiency Analysis
5．2．1 Implication by Throughput
5．2．2 Implication by China and Korea
5．2．3 Implication by Input-Orientation and Output-Orientation
5．2．4 Suggestion by Research Results


6 Conclusion
Appendix A
Appendix B
Appendix C
References
The Index
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