Journal
ASIAN JOURNAL OF SHIPPING AND LOGISTICS
Volume 38, Issue 2, Pages 99-106Publisher
ELSEVIER
DOI: 10.1016/j.ajsl.2022.03.001
Keywords
Container terminal; Pearl river delta; SBM-DEA model; Undesirable DEA; Efficiency evaluation
Categories
Funding
- 4th Educational Training Program for the Shipping, Port and Logistics from the Ministry of Oceans and Fisheries
Ask authors/readers for more resources
This study evaluates the efficiency of major container terminals in the Pearl River Delta region using data envelopment analysis and undesirable models, and finds that the efficiency of container terminals in Guangzhou is lower than those in Shenzhen and Hong Kong. The results provide a reliable reference for future port investment and regional development policy.
As the three largest central hub cities in the Pearl River Delta (PRD) region, Hong Kong, Guangzhou, and Shenzhen have played critical roles in regional growth. Nevertheless, these ports face many challenges, such as port handling capacity, environmental problems, and the expansion of the complex transportation system owing to the large volume of goods. Therefore, this study used the slacks-based measure-data envelopment analysis (SBM-DEA) and DEA-undesirable models to evaluate the efficiency of the major container terminals in these three cities between 2018 and 2019. Based on the decision-making unit values of the terminals for the past two years, Yantian and Container Terminal 9 (South) were the most efficient, followed by container terminals 6 and 7. Moreover, the efficiency of the major container terminals in Guangzhou was less satisfactory than that of terminals in Shenzhen and Hong Kong. The results provide a reliable reference for future port investment, and regional development policy in the PRD region.(c) 2022 The Authors. Production and hosting by Elsevier B.V. on behalf of The Korean Association of Shipping and Logistics, Inc. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/). CC_BY_NC_ND_4.0
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available