Quotation YANG, CongCong, Taudes, Alfred, Dong, Guozhi . 2015. Efficiency analysis of European Freight Villages: three peers for benchmarking. Central European Journal of Operations Research S. 1-32.


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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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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Central European Journal of Operations Research
Citation Index SCI
WU-Journal-Rating new STRAT-C
Language English
Title Efficiency analysis of European Freight Villages: three peers for benchmarking
Year 2015
Page from 1
Page to 32
Reviewed? Y
URL http://link.springer.com/article/10.1007/s10100-015-0424-5?wt_mc=internal.event.1.SEM.ArticleAuthorOnlineFirst
DOI http://dx.doi.org/10.1007/s10100-015-0424-5

Associations

People
YANG, CongCong (Former researcher)
Taudes, Alfred (Details)
External
Dong, Guozhi (Computational Science Center, University of Vienna, Austria)
Organization
Produktionsmanagement (Taudes) (Details)
Information Systems and Operations DP (Details)
Research Institute for Supply Chain Management FI (Details)
Research areas (ÖSTAT Classification 'Statistik Austria')
1109 Information and data processing (Details)
1121 Operations research (Details)
1122 Artificial intelligence (Details)
5306 Business data processing (Details)
5310 Manufacturing (Details)
5316 Industrial management (Details)
5333 Business management (Details)
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