Skip to main content
SpringerLink
Log in

Efficiency analysis of European Freight Villages: three peers for benchmarking

  • Original Paper
  • Published:
Central European Journal of Operations Research Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Amirteimoori A (2011) An extended transportation problem: a DEA-based approach. Cent Eur J Oper Res 19(4):513–521

    Article  Google Scholar 

  • Andrejić M, Bojović N, Kilibarda M (2013) Benchmarking distribution centres using principal component analysis and data envelopment analysis: a case study of serbia. Expert Syst Appl 40(10):3926–3933

    Article  Google Scholar 

  • Adler N, Liebert V, Yazhemsky E (2013) Benchmarking airports from a managerial perspective. Omega 41(2):442–458

    Article  Google Scholar 

  • Ballis A (2006) Freight villages: warehouse design and rail link aspects. Transp Res Rec 1966(1):27–33

    Article  Google Scholar 

  • Ballis A, Golias J (2002) Comparative evaluation of existing and innovative rail-road freight transport terminals. Transp Res Part A Policy Pract 36(7):593–611

    Article  Google Scholar 

  • Banaszewska A, Cruijssen F, Dullaert W, Gerdessen JC (2012) A framework for measuring efficiency levels—the case of express depots. Int J Prod Econ 139(2):484–495

    Article  Google Scholar 

  • Banker RD, Charnes A, Cooper WW (1984) Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manag Sci 30(9):1078–1092

    Article  Google Scholar 

  • Banker RD, Thrall RM (1992) Estimation of returns to scale using data envelopment analysis. Eur J Oper Res 62(1):74–84

    Article  Google Scholar 

  • Bhanot N, Singh H (2014) Benchmarking the performance indicators of Indian Railway container business using data envelopment analysis. Benchmark Int J 21(1):101–120

    Article  Google Scholar 

  • Cezar-Gabriel C (2010) Performance assessment in operating dry ports. Ann Faculty Econ 1(2):934–938

    Google Scholar 

  • Chakraborty PS, Majumder G, Sarkar B (2011) Performance measurement of distribution center combining data envelopment analysis and analytic hierarchy process. Adv Ind Eng Manag 6(2):117–128

    Google Scholar 

  • Charles V, Kumar M, Irene Kavitha S (2012) Measuring the efficiency of assembled printed circuit boards with undesirable outputs using data envelopment analysis. Int J Prod Econ 136(1):194–206

    Article  Google Scholar 

  • Charnes A, Cooper WW, Rhodes E (1978) Measuring the efficiency of decision making units. Eur J Oper Res 2(6):429–444

    Article  Google Scholar 

  • Chen G, Qian Z (2010) MaxDEA LP manual. http://www.maxdea.cn/. Accessed 14 June 2014

  • Coelli TJ, Rao DSP, O’Donnell CJ, Battese GE (2005) An introduction to efficiency and productivity analysis. Springer, New York

    Google Scholar 

  • Cooper WW, Seiford LM, Tone K (2007) Data envelopment analysis: a comprehensive text with models, applications, references and DEA-solver software. Springer, New York

    Google Scholar 

  • Cooper WW, Seiford LM, Zhu J (2011) Handbook on data envelopment analysis. Springer Science and Business Media, London

    Book  Google Scholar 

  • Cook WD, Tone K, Zhu J (2014) Data envelopment analysis: prior to choosing a model. Omega 44:1–4

    Article  Google Scholar 

  • Cullinane K, Wang TF, Song DW, Ji P (2006) The technical efficiency of container ports: comparing data envelopment analysis and stochastic frontier analysis. Transp Res Part A Policy Pract 40(4):354–374

    Article  Google Scholar 

  • de Carvalho CC, Lima Jr OF (2010) Efficient logistic platform design: the case of Campinas Platform. http://www.abepro.org.br/biblioteca/enegep2010_TI_ST_113_741_17234.pdf. Accessed 20 Feb 2013

  • De Witte K, Marques RC (2010) Designing performance incentives, an international benchmark study in the water sector. Cent Eur J Oper Res 18(2):189–220

    Article  Google Scholar 

  • Dyson RG, Allen R, Camanho AS, Podinovski VV, Sarrico CS, Shale EA (2001) Pitfalls and protocols in DEA. Eur J Oper Res 132(2):245–259

    Article  Google Scholar 

  • Europlatforms EEIG (2004) Logistics centres directions for use, Europlatforms EEIG. http://www.unece.org/fileadmin/DAM/trans/main/eatl/docs/EN-REV-WhatisaFreightVillageFinalcorretto.pdf. Accessed 12 May 2012

  • Farrell MJ et al (1957) The measurement of productive efficiency. J R Stat Soc Ser A (General) 3(120):253–290

    Article  Google Scholar 

  • George SA, Rangaraj N (2008) A performance benchmarking study of Indian railway zones. Benchmark Int J 15(5):599–617

    Article  Google Scholar 

  • Golany B, Roll Y (1989) An application procedure for DEA. Omega 17(3):237–250

    Article  Google Scholar 

  • Grewal D, Levy M, Mehrotra A, Sharma A (1999) Planning merchandising decisions to account for regional and product assortment differences. J Retail 75(3):405–424

    Article  Google Scholar 

  • Hamdan A, Rogers KJ (2008) Evaluating the efficiency of 3PL logistics operations. Int J Prod Econ 113(1):235–244

    Article  Google Scholar 

  • Haralambides H, Gujar G (2012) On balancing supply chain efficiency and environmental impacts: an eco-DEA model applied to the dry port sector of India. Marit Econ Logis 14(1):122–137

    Article  Google Scholar 

  • Ho CT, Zhu DS (2004) Performance measurement of Taiwan’s commercial banks. Int J Prod Perform Manag 53(5):425–434

    Article  Google Scholar 

  • Hung SW, Lu WM (2008) The comparative productivity efficiency of Taiwan’s integrated circuits packaging/testing firms. INFOR Inf Syst Oper Res 46(3):189–198

    Google Scholar 

  • Jacobs R, Smith PC, Street A (2006) Measuring efficiency in health care: analytic techniques and health policy. Cambridge University Press, New York

    Book  Google Scholar 

  • Jha DK, Shrestha R (2006) Measuring efficiency of hydropower plants in Nepal using data envelopment analysis. IEEE Trans Power Syst 21(4):1502–1511

    Article  Google Scholar 

  • Kapros S, Panou K, Tsamboulas D (2005) Multi-criteria approach to the evaluation of intermodal freight villages. Transp Res Rec 1906(1):56–63

    Article  Google Scholar 

  • Koch H, Münch S, Nestler S, Nobel N (2010) Ranking of the European Freight Village locations—benchmarking of the European experience. wvb Wissenschaftlicher Verlag, Berlin

    Google Scholar 

  • Kritikos M, Markellos RN, Prastacos G (2010) Corporate real estate analysis: evaluating telecom branch efficiency in Greece. Appl Econ 42(9):1133–1143

    Article  Google Scholar 

  • Kumar S, Gulati R (2008) Evaluation of technical efficiency and ranking of public sector banks in India: an analysis from cross-sectional perspective. Int J Prod Perform Manag 57(7):540–568

    Article  Google Scholar 

  • Kumar Singh S, Kumar Bajpai V (2013) Estimation of operational efficiency and its determinants using DEA: the case of Indian coal-fired power plants. Int J Energy Sect 7(4):409–429

    Article  Google Scholar 

  • Lau KH (2012) Distribution network rationalization through benchmarking with DEA. Benchmark Int J 19(6):668–689

    Article  Google Scholar 

  • Liang L, Wu J, Cook WD, Zhu J (2008) Alternative secondary goals in DEA cross-efficiency evaluation. Int J Prod Econ 113(2):1025–1030

    Article  Google Scholar 

  • Lin LC, Hong CH (2006) Operational performance evaluation of international major airports: an application of data envelopment analysis. J Air Transp Manag 12(6):342–351

    Article  Google Scholar 

  • Liu CC (2008) Evaluating the operational efficiency of major ports in the Asia-Pacific region using data envelopment analysis. Appl Econ 40(13):1737–1743

    Article  Google Scholar 

  • Liu JH, Dong JQ, Chang Q (2013) Assessing logistics park operational efficiency using dual variables DEA model. Stat Decis 8:60–62

    Google Scholar 

  • Liu J, Zhou Y, Wei X (2010) International studies on logistics parks from 1999 to 2009: a literature review. Logist Technol 29(8):43–45

    Google Scholar 

  • Luo J (2013) Analysis on the operation effects of logistics park based on BP neural network. In: Proceedings of the 19th international conference on industrial engineering and engineering management, pp 1073–1079

  • Malekmohammadi N, Lotfi FH, Jaafar AB (2011) Data envelopment scenario analysis with imprecise data. Cent Eur J Oper Res 19(1):65–79

    Article  Google Scholar 

  • Manfred G, Martin P, Thouraya B (2008) Assessing performance indicators for inland terminals. http://simcont.net/fileadmin/simcont/downloads/Pub_PI.pdf. Accessed 3 May 2010

  • Markovits-Somogyi R, Gecse G, Bokor Z (2011) Basic efficiency measurement of Hungarian logistics centres using data envelopment analysis. Period Polytech Soc Manag Sci 19(2):97–101

    Article  Google Scholar 

  • Meidute I (2005) Comparative analysis of the definitions of logistics centres. Transport 20(3):106–110

    Google Scholar 

  • Merkert R, Mangia L (2014) Efficiency of Italian and Norwegian airports: a matter of management or of the level of competition in remote regions? Transp Res Part A Policy Pract 62:30–38

    Article  Google Scholar 

  • Mostafa M (2007) Benchmarking top Arab banks’ efficiency through efficient frontier analysis. Ind Manage Data Syst 107(6):802–823

    Article  Google Scholar 

  • Nataraja NR, Johnson AL (2011) Guidelines for using variable selection techniques in data envelopment analysis. Eur J Oper Res 215(3):662–669

    Article  Google Scholar 

  • Nyhan RC, Martin LL (1999) Comparative performance measurement: a primer on data envelopment analysis. Public Perform Manag Rev 22(3):348–364

    Google Scholar 

  • Ondrich J, Ruggiero J (2002) Outlier detection in data envelopment analysis: an analysis of jackknifing. J Oper Res Soc 53(3):342–346

    Google Scholar 

  • Pahwa A, Feng X, Lubkeman D (2003) Performance evaluation of electric distribution utilities based on data envelopment analysis. Power Syst IEEE Trans 18(1):400–405

    Article  Google Scholar 

  • Peng Wong W, Yew Wong K (2007) Supply chain performance measurement system using DEA modelling. Ind Manage Data Syst 107(3):361–81

    Article  Google Scholar 

  • Podinovski VV, Thanassoulis E (2007) Improving discrimination in data envelopment analysis: some practical suggestions. J Prod Anal 28(1–2):117–126

    Article  Google Scholar 

  • Ramanathan R (2003) An introduction to data envelopment analysis: a tool for performance measurement. Sage Publ, India

    Google Scholar 

  • Ross AD, Droge C (2004) An analysis of operations efficiency in large-scale distribution systems. J Oper Manag 21(6):673–688

    Article  Google Scholar 

  • Sarkis J, Talluri S (2004) Performance based clustering for benchmarking of US airports. Transp Res Part A Policy Pract 38(5):329–346

    Article  Google Scholar 

  • Smith P, Mayston D (1987) Measuring efficiency in the public sector. Omega 15(3):181–189

    Article  Google Scholar 

  • Sufian F (2007) Trends in the efficiency of Singapore’s commercial banking groups: a non-stochastic frontier DEA window analysis approach. Int J Prod perform Manag 56(2):99–136

    Article  Google Scholar 

  • Tongzon J (2001) Efficiency measurement of selected Australian and other international ports using data envelopment analysis. Transp Res Part A Policy Pract 35(2):107–122

    Article  Google Scholar 

  • Vrochidis B (2013) Logistics centres as economic drivers of their regions. Department of Erasmus School of Economics: Erasmus University of Rotterdam, Rotterdam. http://thesis.eur.nl/pub/14748

  • Wang DZ, Chen JJ (2009) Analysis on logistics park performance appraisal based on fuzzy synthetic evaluation method. Logist Sci Tech 10(32):79–82

    Google Scholar 

  • Winkler H, Seebacher G (2011) Management of freight villages: findings from an exploratory study in Germany. Int J Logist Res App 14(4):271–283

    Article  Google Scholar 

  • Wu J, Haasis HD (2013) Converting knowledge into sustainability performance of freight villages. Logist Res 6(2–3):63–88

    Article  Google Scholar 

  • Yadav VK, Padhy NP, Gupta HO (2010) A micro level study of an Indian electric utility for efficiency enhancement. Energy 35(10):4053–4063

    Article  Google Scholar 

  • Yadav VK, Padhy NP, Gupta HO (2011) Performance evaluation and improvement directions for an Indian electric utility. Energy Policy 39(11):7112–7120

    Article  Google Scholar 

  • Yu MM, Chen PC (2011) Measuring air routes performance using a fractional network data envelopment analysis model. Cent Eur J Oper Res 19(1):81–98

    Article  Google Scholar 

  • Zhou G, Min H, Xu C, Cao Z (2008) Evaluating the comparative efficiency of Chinese third-party logistics providers using data envelopment analysis. Int J Phys Distrib Log 38(4):262–279

    Article  Google Scholar 

  • Zhu J (2000) Multi-factor performance measure model with an application to Fortune 500 companies. Eur J Oper Res 123(1):105–124

    Article  Google Scholar 

  • Zhu J, Shen ZH (1995) A discussion of testing DMUs’ returns to scale. Eur J Oper Res 81(3):590–596

    Article  Google Scholar 

Download references

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.

Author information

Authors and Affiliations

  1. Institute for Production Management, Vienna University of Economics and Business, Welthandelsplatz 1, Building D2, 1020, Vienna, Austria

    Congcong Yang & Alfred Taudes

  2. Computational Science Center, University of Vienna, Oskar-Morgenstern-Platz 1, 1090, Vienna, Austria

    Guozhi Dong

Authors
  1. Congcong Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alfred Taudes
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Guozhi Dong
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alfred Taudes.

Ethics declarations

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).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

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

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10100-015-0424-5

Keywords

Search

Navigation