MODELS FOR PORT COMPETITIVE ANALYSIS
4. Conclusion and Discussion
Port competition has grown more intense with the growth of international trade and global economies. Asia is the pre-eminent region in the world
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container throughput and the competition among Asian container ports is even more intense than in other regions of the world, highlighting the need for effective benchmarking methodologies. This paper focused on benchmarking major ports in the Asia-Pacific region from three aspects:
port efficiency, port connectivity and impacts of factors on individual ports.
Using DEA models, it was found that Singapore, Hong Kong and Shanghai rank as the most efficient. When considering a network framework to evaluate connectivity in terms of throughput capacity and waiting time, Singapore ranks as the most well connected, followed by Busan, Yokohama, Qingdao and Shanghai. Lastly, the sensitivity of ports towards the impact of various factors can be measured and benchmarked using a network flow model, which revealed the importance of Shanghai-Ningbo as major competitors to Singapore and Busan.
Some facts should be mentioned as follows:
• Most of the data used in the paper are collected from CI-online and some other resources. However, some of the data could not be found and they had to be estimated which will lead to inaccuracy of data. In addition, some data used may be outdated or inaccurate as there is no reliable universal source. So, further study may be required.
• Only nine ports and three liner shipping companies are included in this study for port efficiency and impact of factors on individual ports. The small number of ports and liner companies may not be representative of the whole maritime transportation network of Asia-Pacific region and this could likely lead to some inaccurate conclusions. More ports and liner shipping companies should be involved in future studies.
• Port connectivity in this paper is still a preliminary study and as mentioned earlier it is closely related to some other factors such as waiting time, responsiveness and cost. Thus, it will be more meaningful if we integrate these factors together in our connectivity analysis.
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