A Novel Data Envelopment Analysis Framework for Performance Evaluation of European Road Transport Systems


  • Mozhgan Mansouri Kaleibar University of Ljubljana, Faculty of Maritime Studies and Transport
  • Evelin Krmac University of Ljubljana, Faculty of Maritime Studies and Transport




data envelopment analysis (DEA), performance efficiency, slacks based measure (SBM), undesirable output (UO), super efficiency, road transport system


The role of transportation is becoming increasingly important in the world economy, and road transport in particular plays a very important role in all types of transportation. For this reason, it is extremely important to monitor its performance regularly. Very often, this is done using Data Envelopment Analysis (DEA) performance evaluation models, and consequently, there are numerous articles in the literature on DEA evaluation of road transport systems. In this study, we first summarise these articles and classify them according to different characteristics (environmental, safety, economic, energy). Finally, we use them as a basis for developing a novel DEA framework, which is used for the evaluation of the efficiency and ranking of road transport systems that also takes into account undesirable outputs, i.e. environmental and safety outputs. As a case study, we evaluate 28 European countries from technical, safety and environmental aspects. The CCR and SBM models are used to evaluate the efficiency of these countries for the last two years of published data. The results show that Denmark ranks first and Cyprus last for both years. It was also found that safety efficiency is generally rated lower than other criteria. Finally, the results and reasons for the efficiency and inefficiency of specific decision-making units, i.e. countries, are discussed.


Eurostat. Road Transport. 2022. https://ec.europa.eu/eurostat/databrowser/explore/all/transp?lang=en&subtheme=road&display=list&sort=category&extractionId=ROAD_GO_CA_D_C.

Statistical pocket book. EU transport in figures. 2021. https://transport.ec.europa.eu/media-corner/publications/statistical-pocketbook-2021_en.

Cooper WW, Swiford L, Tone K. Data envelopment analysis: A comprehensive text with models, applications, references and DEA-solver software. Berlin: Springer Science Business Media; 2007.

Chu X, Fielding GJ, Lamar BW. Measuring transit performance using data envelopment analysis. Transportation Research Part A. 1992;26(3):223-230. DOI: 10.1016/0965-8564(92)90033-4.

Kerstens K. Technical efficiency measurement and explanation of French urban transit companies. Transportation Research Part A. 1996;30(6):431-452. DOI: 10.1016/0965-8564(96)00006-7.

Viton PA. Technical efficiency in multi-mode bus transit: A production frontier analysis. Transportation Research Part B. 1997;31(1):23-39. DOI: 10.1016/S0191-2615(96)00019-7.

Cowie J, Asenova D. Organisation form, scale effects and efficiency in the British bus industry. Transportation. 1999;26:231-248.

Odeck J, Alkadi A. Evaluating efficiency in the Norwegian bus industry using data envelopment analysis. Transportation. 2001;28:211-232.

Pina V, Torres L. Analysis of the efficiency of local government services delivery an application to urban publication transport. Transportation Research Part A. 2001;35:929-944. DOI: 10.1016/S0965-8564(00)00033-1.

Boame AK. The technical efficiency of Canadian urban transit systems. Transportation Research Part E. 2004;40:401-416. DOI: 10.1016/j.tre.2003.09.002.

Karlaftis MG. A DEA approach for evaluating the efficiency and effectiveness of urban transit systems. European Journal of Operational Research. 2004;152:354-364. DOI: 10.1016/S0377-2217(03)00029-8.

Jiang C. A model of evaluating transportation system efficiency based on data envelopment analysis approach. 2009 Second International Symposium on Electronic Commerce and Security. 2009.

Garcia Sanchez IM. Technical and scale efficiency in Spanish urban transport: Estimating with data envelopment analysis. Advances in Operations Research. 2009. DOI: 10.1155/2009/721279.

Rouse P, Chiu T. Towards optimal life cycle management in a road maintenance setting using DEA. European Journal of Operational Research. 2009;196:672-681. DOI: 10.1016/j.ejor.2008.02.041.

Welde M, Odeck J. The efficiency of Norwegian road toll companies. Utilities Policy. 2011;19:162-171. DOI: 10.1016/j.jup.2011.03.001.

Zhenlin W, Peng Z, Shulin A. Efficiency evaluation of Beijing intelligent traffic management system based on super-DEA. Journal of Transportation Systems Engineering and Information Technology. 2012;12(3):19-23. DOI: 10.1016/S1570-6672(11)60200-6.

Caulfield B, Bailey D, Mullarkey S. Using data envelopment analysis as a public transport project appraisal tool. Transport Policy. 2013;29:74-85. DOI: 10.1016/j.tranpol.2013.04.006.

Fancello G, Uccheddu B, Fadda P. The performance of an urban road system: an innovative approach using D.E.A. (Data Envelopment Analysis). Procedia - Social and Behavioral Sciences. 2013;87:163-176. DOI: 10.1016/j.sbspro.2013.10.601.

Li J, Chen X, Li X, Guo X. Evaluation of public transportation operation based on data envelopment analysis. Procedia - Social and Behavioral Sciences. 2013;96:148-155. DOI: 10.1016/j.sbspro.2013.08.020.

Fu P, Zhan Z, Wu C. Efficiency analysis of Chinese road systems with DEA and order relation analysis method: Externality concerned. Procedia - Social and Behavioral Sciences. 2013;96:1227-1238. DOI: 10.1016/j.sbspro.2013.08.140.

Georgiadis G, Politis L, Papaioanno P. Measuring and improving the efficiency and effectiveness of bus public transport systems. Research in Transportation Economics. 2014;48:84-91. DOI: 10.1016/j.retrec.2014.09.035.

Fancello G, Uccheddu, B, Fadda P. Data Envelopment Analysis (D.E.A.) for urban road system performance assessment. Procedia - Social and Behavioral Sciences. 2014;111:780-789. DOI: 10.1016/j.sbspro.2014.01.112.

Álvarez IC, Blázquez R. The influence of the road network on private productivity measures using Data Envelopment Analysis: A case study from Spain. Transportation Research Part A. 2014;65:33-43. DOI: 10.1016/j.tra.2014.04.002.

Maroto A, Zofío JL. Accessibility gains and road transport infrastructure in Spain: A productivity approach based on the Malmquist index. Journal of Transport Geography. 2016;52:143-152. DOI: 10.1016/j.jtrangeo.2016.03.008.

Li T, Cao X, Yang W. Measuring the efficiency of regional integrated transport in China: A Data Envelopment Analysis. Periodica Polytechnica Transportation Engineering. 2016;44(1):23-34. DOI: 10.3311/PPtr.7529.

Regalado López FJ, Campos Cacheda JM. An approximation to technical efficiency in Spanish toll roads through a DEA approach. Transportation Research Procedia. 2018;33:386-393. DOI: 10.1016/j.trpro.2018.11.005.

Yang T, et al. Efficiency Evaluation of Urban Road Transport and Land Use in Hunan Province of China Based on Hybrid Data Envelopment Analysis (DEA) Models. Sustainability. 2019;11. DOI: 10.3390/su11143826.

Saeedi H, Behdani B, Wiegmans B, Zuidwijk R. Assessing the technical efficiency of intermodal freight transport chains using a modified network DEA approach. Transportation Research Part E. 2019;126:66-86. DOI: 10.1016/j.tre.2019.04.003.

Georgiadis G, Papaioanno P, Politis I. Rail and road public transport: Cooperation or coexistence. Transportation Research Interdisciplinary Perspectives. 2020;5. DOI: 10.1016/j.trip.2020.100122.

Norouzian-Maleki P, et al. An integrated approach to system dynamics and data envelopment analysis for determining efficient policies and forecasting travel demand in an urban transport system. Transportation Letters. 2020. DOI: 10.1080/19427867.2020.1839716.

Gadepalli R, Rayaprolu S. Factors affecting performance of urban bus transport systems in India: A Data Envelopment Analysis (DEA) based approach. Transportation Research Procedia. 2020;48:1789-1804. DOI: 10.1016/j.trpro.2020.08.214.

Neves SA, Marques AC, Moutinho V. Two-stage DEA model to evaluate technical efficiency on deployment of battery electric vehicles in the EU countries. Transportation Research Part D. 2020;86. DOI: 10.1016/j.trd.2020.102489.

Kumar A, Singh G, Vaidya OS. A comparative evaluation of public road transportation systems in India using multicriteria decision-making techniques. Journal of Advanced Transportation. 2020. DOI: 10.1155/2020/8827186.

Stefaniec A, Hosseini K, Xie J, Li Y. Sustainability assessment of inland transportation in China: A triple bottom line-based network DEA approach. Transportation Research Part D. 2020;80. DOI: 10.1016/j.trd.2020.102258.

Aloulou F, Ghannouchi I. The impact of ownership and contractual practice on the technical efficiency level of the public transport operators: An international comparison. Research in Transportation Business & Management. 2021. DOI: 10.1016/j.rtbm.2021.100707.

Izadikhah M, Azadi M, Toloo M, Hussain FK. Sustainably resilient supply chains evaluation in public transport: A fuzzy chance-constrained two-stage DEA approach. Applied Soft Computing. 2021;113. DOI: 10.1016/j.asoc.2021.107879.

Chen L, et al. A new inverse data envelopment analysis approach to achieve China’s road transportation safety objectives. Safety Science. 2021;142. DOI: 10.1016/j.ssci.2021.105362.

Khanh Van HT, Vinh Ha T, Asada T, Arimura M. Assessing transportation system efficiency in its relationship with urban housing: A data envelopment analysis. Asian Transport Studies. 2022;8. DOI: 10.1016/j.eastsj.2022.100065.

Fitzova H, Matulov M. Comparison of urban public transport systems in the Czech Republic and Slovakia: Factors underpinning efficiency. Research in Transportation Economics. 2022. DOI: 10.1016/j.retrec.2020.100824.

Wu J, et al. Measuring energy and environmental efficiency of transportation systems in China based on a parallel DEA approach. Transportation Research Part D. 2015. DOI: 10.1016/j.trd.2015.08.001.

Liu Z, Qin CX, Zhang YJ. The energy-environment efficiency of road and railway sectors in China: Evidence from the provincial level. Ecological Indicators. 2016;69:559-570. DOI: 10.1016/j.ecolind.2016.05.016.

Ramanatha R. A holistic approach to compare energy efficiencies of different transport modes. Energy Policy. 2000;28:743-747. DOI: 10.1016/S0301-4215(00)00072-0.

Ruzzenenti F, Basosi R. Evaluation of the energy efficiency evolution in the European road freight transport sector. Energy Policy. 2009;37:4079-4085. DOI: 10.1016/j.enpol.2009.04.050.

Cui Q, Li Y. The evaluation of transportation energy efficiency: An application of three-stage virtual frontier DEA. Transportation Research Part D. 2014;29:1-11. DOI: 10.1016/j.trd.2014.03.007.

Song X, Hao Y, Zhu X. Analysis of the environmental efficiency of the Chinese transportation sector using an undesirable output slacks-based measure Data Envelopment Analysis model. Sustainability. 2015;7:9187-9206. DOI: 10.3390/su7079187.

Buzzo Margari B, Erbetta F, Petraglia C, Piacenza M. Regulatory and environmental effects on public transit efficiency a mixed DEA-SFA approach. Journal of Regulatory Economics. 2017;32(2):131-151.

Chang YT, Zhang N, Danao D, Zhang N. Environmental efficiency analysis of transportation system in China: A non-radial DEA approach. Energy Policy. 2013;58:277-283. DOI: 10.1016/j.enpol.2013.03.011.

Pal D, Mitra SK. An application of the directional distance function with the number of accidents as an undesirable output to measure the technical efficiency of state road transport in India. Transportation Research Part A. 2016;93:1-12. DOI: 10.1016/j.tra.2016.08.012.

Li T, Yang W, Zhang H, Cao X. Evaluating the impact of transport investment on the efficiency of regional integrated transport systems in China. Transport Policy. 2016;45:66-76. DOI: 10.1016/j.tranpol.2015.09.005.

Kang CC, Feng CM, Liao BR, Khan HA. Accounting for air pollution emissions and transport policy in the measurement of the efficiency and effectiveness of bus transits. Transportation Letters. 2019. DOI: 10.1080/19427867.2019.1592369.

Stefaniec A, Hosseini K, Xie J, Li Y. Sustainability assessment of inland transportation in China: A triple bottom line-based network DEA approach. Transportation Research Part D. 2020;80. DOI: 10.1016/j.trd.2020.102258.

Liu H, Yang R, Wang Y, Zhu Q. Measuring performance of road transportation industry in China in terms of integrated environmental efficiency in view of Streaming Data. Science of the Total Environment. 2020;727. DOI: 10.1016/j.scitotenv.2020.138675.

Yang F, Choi Y, Lee H. Life-cycle data envelopment analysis to measure efficiency and cost-effectiveness of environmental regulation in China’s transport sector. Ecological Indicators. 2021;126. DOI: 10.1016/j.ecolind.2021.107717.

Wang CN, et al. Strategic environmental assessment of land transportation: An application of DEA with undesirable output approach. Sustainability. 2022;14. DOI: 10.3390/su14020972.

Zhou G, Chung W, Zhang Y. Measuring energy efficiency performance of China’s transport sector: A data envelopment analysis approach. Expert Systems with Applications. 2014;41:709-722. DOI: 10.1016/j.eswa.2013.07.095.

Wang DD. Assessing road transport sustainability by combining environmental impacts and safety concerns. Transportation Research Part D. 2019;77:212-223. DOI: 10.1016/j.trd.2019.10.022.

Hermans E, Brijs T, Wets G, Vanhoof K. Benchmarking road safety: Lessons to learn from a data envelopment analysis. Accident Analysis and Prevention. 2009;41:174-182. DOI: 10.1016/j.aap.2008.10.010.

Shen Y, et al. A generalized multiple layer data envelopment analysis model for hierarchical structure assessment: A case study in road safety performance evaluation. Expert Systems with Applications. 2011;38:15262-15272. DOI: 10.1016/j.eswa.2011.05.073.

Shen Y, et al. Road safety risk evaluation and target setting using data envelopment analysis and its extensions. Accident Analysis and Prevention. 2012;48:430-441. DOI: 10.1016/j.aap.2012.02.020.

Shen Y, et al. Road safety development in Europe: A decade of changes (2001–2010). Accident Analysis and Prevention. 2013;60:85-94. DOI: 10.1016/j.aap.2013.08.013.

Egilmez G, McAvoy D. Benchmarking road safety of U.S. states: A DEA-based Malmquist productivity index approach. Accident Analysis and Prevention. 2013;53:55-64. DOI: 10.1016/j.aap.2012.12.038.

Shen Y, et al. Serious injuries: An additional indicator to fatalities for road safety benchmarking. Traffic Injury Prevention. 2014;16:246-253. DOI: 10.1080/15389588.2014.930831.

Sadeghi A, Moghaddam AM. Uncertainty-based prioritization of road safety projects: An application of data envelopment analysis. Transport Policy. 2016;52:28-36. DOI: 10.1016/j.tranpol.2016.07.003.

Behnood HR. Best practice analysis of action for road safety in Iran amongst the leading developing countries using an optimized success indicator. Transport Policy. 2017. DOI: 10.1016/j.tranpol.2018.01.017.

Rosic M, et al. Method for selection of optimal road safety composite index with examples from DEA and TOPSIS. Accident Analysis and Prevention. 2017;98:277-286. DOI: 10.1016/j.aap.2016.10.007.

Nikolaou P, Dimitriou L. Evaluation of road safety policies performance across Europe: Results from benchmark analysis for a decade. Transportation Research Part A. 2018;116:232-246.

Ganji SR, Rassafi AA, Ling Xu D. A double frontier DEA cross efficiency method aggregated by evidential reasoning approach for measuring road safety performance. Measurement. 2018. DOI: 10.1016/j.measurement.2018.12.098.

Ganji SS, Rassafi AA. DEA Malmquist productivity index based on a double-frontier-slacks-based model: Iranian road safety assessment. European Transport Research Review. 2019;16. DOI: 10.1186/s12544-018-0339-z.

Omrani H, Amini M, Alizadeh A. An integrated group best-worst method - Data envelopment analysis approach for evaluating road safety: A Case of Iran. Measurement. 2019. DOI: 10.1016/j.measurement.2019.107330.

Ganji SS, Rassafi AA. Road safety evaluation using a novel cross efficiency method based on double frontiers DEA and evidential reasoning approach. KSCE Journal of Civil Engineering. 2019;23:850-865.

Ganji SS, Rassafi AA, Bandari SJ. Application of evidential reasoning approach and OWA operator weights in road safety evaluation considering the best and worst practice frontiers. Socio-Economic Planning Sciences. 2020;69. DOI: 10.1016/j.seps.2019.04.003.

Fancello G, Carta M, Serra P. Data envelopment analysis for road safety analysis in urban road network: A comparative study using CCR and BCC models. Case Studies on Transport Policy. 2020. DOI: 10.1016/j.cstp.2020.07.007.

Antić B, Grdinić M, Pešić D, Pajković V. Benchmarking of the road safety performance among the regions by using DEA. Transportation Research Procedia. 2020;45:78-86. DOI: 10.1016/j.trpro.2020.02.065.

Fancello G, Carta M, Serra P. Data Envelopment Analysis for the assessment of road safety in urban road networks: A comparative study using CCR and BCC models. Case Studies on Transport Policy. 2020;8(3):736-744. DOI: 10.1016/j.cstp.2020.07.007.

Shen Y, et al. Towards better road safety management: Lessons learned from inter-national benchmarking. Accident Analysis and Prevention. 2020;138. DOI: 10.1016/j.aap.2020.105484.

Zhu JH, Chen J, Li GF, Shuai B. Using cross efficiency method integrating regret theory and WASPAS to evaluate road safety performance of Chinese provinces. Accident Analysis and Prevention. 2021;162. DOI: 10.1016/j.aap.2021.106395.

Pajkovic V, Rakonjac MJ. Evaluation of road safety performance based on self-reported behavior data set. Sustainability. 2021;13. DOI: 10.3390/su132413837.

Kang L, Wu C. Measuring the development of Chinese provincial road safety over the period 2007–2016. Measurement. 2021;175. DOI: 10.1016/j.measurement.2021.109133.

Nikolaou P, Folla K, Dimitriou L, Yannis G. European countries’ road safety evaluation by τaking ιnto αccount multiple classes of fatalities. Transportation Research Procedia. 2021;52:284-291. DOI: 10.1016/j.trpro.2021.01.033.

Raheel Shah SA, et al. Relationship between road traffic features and accidents: An application 2 of two-stage decision making approach for transportation engineers. Journal of Safety Research. 2021. DOI: 10.1016/j.jsr.2019.01.001.

Kang L, Wu C. Evaluating the performance of Chinese provincial road safety based on the output-input ratio. Transportation Letters. 2022;14(2):114-123. DOI: 10.1080/19427867.2020.1819077.

Tian N, Tang S, Che A, Wu P. Measuring regional transport sustainability using super-efficiency SBM-DEA with weighting preference. Journal of Cleaner Production. 2020;242. DOI: 10.1016/j.jclepro.2019.11847.

Hahn JS, Kho SY, Choi K, Kim DK. Sustainability evaluation of rapid routes for buses with a network DEA model. International Journal of Sustainable Transportation. 2017. DOI: 10.1080/15568318.2017.1302022.

Hussain Z, Xia Z, Li Y. Estimating sustainable transport efficiency and socioeconomic factors: Application of non-parametric approach. Transportation Letters. 2023;15(7):685-697. DOI: 10.1080/19427867.2022.2082004.

Korhonen PJ, Luptacik M. Eco-efficiency analysis of power plants: An extension of data envelopment analysis. European Journal of Operational Research. 2004;154:437-446. DOI: 10.1016/S0377-2217(03)00180-2.

Charnes A, Cooper WW. Programming with linear fractional functional. Naval Research Logistics Quarterly. 1962;9:181-186.

Tone K. A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research. 2001;130(3):498-509. DOI: 10.1016/S0377-2217(99)00407-5.

Tone K. Toronto: Presentation at NAPW III. In: Dealing with undesirable outputs in DEA: A Slacks-Based Measure (SBM) approach. Tokyo, Japan: National Graduate Institute for Policy Studies; 2004.

Statistical pocket book. EU transport in figures. 2020. https://op.europa.eu/en/publication-detail/-/publication/f0f3e1b7-ee2b-11e9-a32c-01aa75ed71a1.

The official portal of the European data. https://data.europa.eu/en.

European road safety observatory. Annul statistical report on road safety in EU. 2021.

Environmental noise in Europe. European Environmental Agency; 2020. https://www.eea.europa.eu/publications/environmental-noise-in-europe




How to Cite

Mansouri Kaleibar, M., & Krmac, E. (2024). A Novel Data Envelopment Analysis Framework for Performance Evaluation of European Road Transport Systems. Promet - Traffic&Transportation, 36(1), 24–41. https://doi.org/10.7307/ptt.v36i1.321