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Efficiency analysis of European Freight Villages: three peers for benchmarking

Abstract

Measuring the efficiency of Freight Villages (FVs) has important implications for logistics companies and other related companies as well as governments. In this paper we apply data envelopment analysis (DEA) to measure the efficiency of European FVs in a purely data-driven way, incorporating the nature of FVs as complex operations that use multiple inputs and produce several outputs. We employ several DEA models and perform a complete sensitivity analysis of the appropriateness of the chosen input and output variables, and an assessment of the robustness of the efficiency score. It turns out that about half of the 20 FVs analyzed are inefficient, with utilization of the intermodal area, warehouse capacity and level of goods handling being the most important areas of improvement. While we find no significant differences in efficiency between FVs of different sizes and in different countries, it turns out that the FVs Eurocentre Toulouse, Interporto Quadrante Europa and GVZ Nürnberg constitute more than 90 % of the benchmark share.

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Acknowledgments

The authors would like to thank Dr. Claudio di Ciccio for the questionnaire translation and all of the participants who kindly provided useful information for our survey. The authors are grateful to two anonymous referees for their very constructive suggestions for improving the paper.

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Correspondence to Alfred Taudes.

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We express our appreciation for the State Scholarship Fund of China Scholarship Council (Grant No. 2011613013). We herewith state that there are no potential conflicts of interest (financial or non-financial) and that the submission complies with the Ethical Rules of the Central European Journal of Operations Research (CJOR).

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Yang, C., Taudes, A. & Dong, G. Efficiency analysis of European Freight Villages: three peers for benchmarking. Cent Eur J Oper Res 25, 91–122 (2017). https://doi.org/10.1007/s10100-015-0424-5

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Keywords

  • Freight Village
  • Benchmarking
  • Efficiency measurement
  • Data envelopment analysis (DEA)