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

机译:基于PCA-DEA模型的中国渤海湾港口铁矿石物流运营效率评估

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摘要

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.
机译:运营效率对于港口的综合竞争力至关重要。在这项研究中,我们使用主成分分析-数据包络分析(PCA-DEA)集成模型来评估中国渤海湾港口铁矿石物流的运营效率。建立了物流效率研究的关键指标和系统框架。我们认为PCA-DEA集成模型是评估和分析该地区每个港口铁矿石物流的相对效率的实用工具。所提出的方法包括从PCA开始的两阶段研究和分析。在第一阶段,我们使用PCA从15个原始指标中获得6个综合指标,包括4个输入指标和2个输出指标。在第二阶段,将标准DEA方法与特定的综合指标一起使用。比较并讨论了从集成PCA-DEA模型中选择的端口的评估结果。评估结果的比较表明,PCA-DEA模型为调查港口物流问题提供了一种实用而强大的工具。利用该集成模型,对该地区不同港口的铁矿石物流效率进行了比较分析和进一步研究。最后,提供了讨论和建议。

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  • 来源
    《Mathematical Problems in Engineering》 |2016年第1期|9604819.1-9604819.13|共13页
  • 作者单位

    College of Transport and Communications Shanghai Maritime University Shanghai 201306 China Shanghai International Shipping Institute Shanghai 200082 China;

    College of Transport and Communications Shanghai Maritime University Shanghai 201306 China Institute of Transportation Studies University of California Davis Davis CA 95616 USA;

    College of Transport and Communications Shanghai Maritime University Shanghai 201306 China;

    School of Port Logistics Tong Myong University Busan 608711 Republic of Korea;

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