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Applying EBM Model and Grey Forecasting to Assess Efficiency of Third-Party Logistics Providers

机译:应用EBM模型和灰色预测来评估第三方物流提供商的效率

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摘要

A third-party logistics (TLP) provider's outsourcing mode is developed to support the economic activities for various industries. The aim of this research is to assess the efficiency of 10 large TPL providers from past to future by integrating the GM (1,1) model in grey forecasting and an epsilon-based measure model (EBM) in data envelopment analysis (DEA). The GM (1,1) model is utilized to formulate a forecast data in the future over period from 2018 to 2022. Then, via EBM model, past-current-future data are used for computing efficiency of these providers. The empirical values show that 115 cases comprise 79 efficiency cases and 36 inefficiency cases. CHRW, ECHO, and UPS get strong efficiency and keep a stable efficiency score in whole term. EXPD and KRRYF do not achieve efficiency during the period from 2013 to 2022. Excluding CHRW, ECHO, and UPS, seven TPL providers demonstrate upward trend and downward trends in every term. The increasing and decreasing variation index of 10 third-party logistics providers will help customers to select the best TPL providers.
机译:开发了第三方物流(TLP)提供商的外包模式,以支持各个行业的经济活动。这项研究的目的是通过将灰色预测中的GM(1,1)模型与数据包络分析(DEA)中的基于ε的度量模型(EBM)集成在一起,评估过去10年来大型TPL供应商的效率。 GM(1,1)模型用于制定2018年至2022年期间未来的预测数据。然后,通过EBM模型,将过去的当前数据用于这些提供商的计算效率。经验值表明,115个案例包括79个效率案例和36​​个效率低下案例。 CHRW,ECHO和UPS获得了强大的效率,并在整个学期内保持稳定的效率得分。 EXPD和KRRYF在2013年至2022年期间未达到效率。除CHRW,ECHO和UPS外,七个TPL供应商在每个学期均表现出上升趋势和下降趋势。 10家第三方物流提供商的变化指数的增减将帮助客户选择最佳的第三方物流提供商。

著录项

  • 来源
    《Journal of Advanced Transportation》 |2018年第7期|1212873.1-1212873.14|共14页
  • 作者单位

    Natl Kaohsiung Univ Sci & Technol Dept Ind Engn & Management Kaohsiung 80778 Taiwan|Fortune Inst Technol Dept Ind Engn & Management Kaohsiung 83160 Taiwan;

    Natl Kaohsiung Univ Sci & Technol Dept Ind Engn & Management Kaohsiung 80778 Taiwan;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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