Effects of hinterland accessibility on US container port efficiency

Wan, Yulai; Yuen, Andrew; Zhang, Anming

doi:10.1504/ijstl.2014.062908

Cited by 41 publications

(31 citation statements)

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“…The author use an optimization model to evaluate the impact of different policy instruments such as infrastructure developments and changes in regulatory framework on the total costs and CO 2 emissions of the port-hinterland multimodal transport system in Italy. Another example is Wan et al (2014), where policy questions related to the development of port infrastructure are addressed using regression analysis. Qualitative studies aimed at supporting policy making in port hinterland systems include Dooms et al (2015), Veenstra et al (2012), and Van den Berg and De Langen (2015).…”

Section: A Port-hinterland Logistics Network Model For Policy Analysismentioning

confidence: 99%

A strategic model of port-hinterland freight distribution networks

Halim

Kwakkel

Tavasszy

2016

Transportation Research Part E: Logistics and Transportation Re

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Section: A Port-hinterland Logistics Network Model For Policy Analysismentioning

confidence: 99%

A strategic model of port-hinterland freight distribution networks

Halim

Kwakkel

Tavasszy

2016

Transportation Research Part E: Logistics and Transportation Re

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“…They found that intra-and inter-port competition, and government ownership, enhanced the efficiency of Chinese ports. Wan et al [16] also applied a two-stage DEA and Tobit regression method to analyze the impact of hinterland accessibility, represented by rail facility and road congestion, on US container port productivity. Chang et al [17] analyzed whether the Emission Control Area (ECA) regulation reduced the productivity of 58 European container ports.…”

Section: Dea Application On Port Studymentioning

confidence: 99%

Port Efficiency Incorporating Service Measurement Variables by the BiO-MCDEA: Brazilian Case

Andrade

Lee

et al. 2019

Sustainability

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Data envelopment analysis (DEA) has many advantages for analyzing the efficiency of decision-making units, as well as drawbacks, such as a lack of discrimination power. This study applied bi-objective multiple-criteria data envelopment analysis (BiO-MCDEA), a programming approach used to overcome the limitations of traditional DEA models, to analyze the efficiency of 20 Brazilian ports with a consideration of six input and one output variables from 2010 to 2016. Two time-related variables were included to reflect current problems faced by Brazilian ports experiencing long wait times. The results reveal a significant disparity in port efficiency among Brazilian ports. The top five most efficient ports are those with the highest cargo throughput. A clustering analysis also confirmed a strong correlation between cargo throughput and port efficiency scores. Total time of stay, pier length, and courtyard also had strong correlations with the efficiency scores. The clustering method divided Brazilian ports into three groups: efficient ports, medium efficient ports, and inefficient ports.

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“…First, the container port efficiency was measured by data envelopment analysis (DEA). Then, Tobit regression analysis was undertaken to explore the relationship between DEA scores and ground transportation conditions [36]. Jiang et al introduced the strongly efficient frontier (SEF) and strongly inefficient frontier (SIF) and then proposed several models to calculate various distances between DMUs and both frontiers [37].…”

Section: Literature Reviewmentioning

confidence: 99%

Operational Efficiency Evaluation of Iron Ore Logistics at the Ports of Bohai Bay in China: Based on the PCA-DEA Model

Chen

Wan

Zhang

et al. 2016

Mathematical Problems in Engineering

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Operational efficiency is significant for the comprehensive competitiveness of a port. In this study, we use a principal component analysis-data envelopment analysis (PCA-DEA) integrated model to evaluate the operational efficiency of iron ore logistics at the ports of Bohai Bay, China. The key indicators and systematic framework are established for logistics efficiency research. We consider the PCA-DEA integrated model as a practical tool for evaluating and analyzing the relative efficiency of the iron ore logistics of each port in that area. The proposed method consists of a two-stage research and analysis that begins with PCA. In the first stage, we use PCA to obtain 6 synthetic indicators, including 4 input indicators and 2 output indicators, from 15 original indicators. In the second stage, the standard DEA approach is used with the specific synthetic indicators. The evaluation results of the selected ports from the integrated PCA-DEA model are compared and discussed. The comparison of the evaluation results indicates that the PCA-DEA model provides a practical and powerful tool for the investigation of the port logistics problem. With this integrated model, a comparison analysis and further research into the iron ore logistics efficiency of different ports in the area are presented. Finally, discussions and suggestions are provided.

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Effects of hinterland accessibility on US container port efficiency

Cited by 41 publications

References 0 publications

A strategic model of port-hinterland freight distribution networks

A strategic model of port-hinterland freight distribution networks

Port Efficiency Incorporating Service Measurement Variables by the BiO-MCDEA: Brazilian Case

Operational Efficiency Evaluation of Iron Ore Logistics at the Ports of Bohai Bay in China: Based on the PCA-DEA Model

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