A new approach to evaluate railways efficiency considering safety measures


Ali Noroozzadeh and Seyed Jafar Sadjadi


Safety is one of the main reasons for choosing railway to other transportation modes and improvement of transportation safety has attracted many researchers in recent years. In this paper, we aim to investigate the influence of safety measures on railways performance evaluation, empirically. The proposed model of this paper uses data envelopment analysis (DEA) to estimate the railways efficiency scores in the presence of safety measure. According to three proposed factors, the most appropriate model is selected to compare its result with output-oriented DEA model. The results of the survey are surprising since inefficient railroads become efficient through adding undesirable outputs in evaluation model.


DOI: j.dsl.2013.02.003

Keywords: Data envelopment analysis ,Railroad industry ,Efficiency

How to cite this paper:

Noroozzadeh, A & Sadjadi, S. J. (2013). A new approach to evaluate railways efficiency considering safety measures.Decision Science Letters, 2(2), 71-80.


References

ADDIN EN.REFLIST Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management science, 30(9), 1078-1092.Chiu, Y., Huang, C., & Ma, C. M. (2011). Assessment of China transit and economic efficiencies in a modified value-chains DEA model. European Journal of Operational Research, 209(2), 95-103.Cowie, J. (1999). The technical efficiency of public and private ownership in the rail industry: the case of Swiss private railways. Journal of Transport Economics and Policy, 241-251.Färe, R., & Grosskopf, S. (2004). Modeling undesirable factors in efficiency evaluation: comment. European Journal of Operational Research, 157(1), 242-245.Färe, R., Grosskopf, S., Lovell, C. A. K., & Pasurka, C. (1989). Multilateral productivity comparisons when some outputs are undesirable: a nonparametric approach. The review of economics and statistics, 90-98.Fielding, G. J., Babitsky, T. T., & Brenner, M. E. (1985). Performance evaluation for bus transit. Transportation Research Part A: General, 19(1), 73-82.Hua, Z., & Bian, Y. (2007). DEA with undesirable factors. Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis, 103-121.International union of railways synopsis, 2008. from http://www.uic.org/spip.php?article1347Jain, P., Cullinane, S., & Cullinane, K. (2008). The impact of governance development models on urban rail efficiency. Transportation Research Part A: Policy and Practice, 42(9), 1238-1250.Karlaftis, M. G. (2004). A DEA approach for evaluating the efficiency and effectiveness of urban transit systems. European Journal of Operational Research, 152(2), 354-364.Lawrence, W., & Erwin, T. (2003). Technical efficiency and service effectiveness for railways industry: DEA approaches. Journal of the Eastern Asia Society for Transportation Studies, 5.Oum, T. H., & Yu, C. (1994). Economic efficiency of railways and implications for public policy: a comparative study of the OECD countries' railways. Journal of Transport Economics and Policy, 121-138.Railway Safety Performance in the European Union 2010. from http://www.era.europa.eu/Document-Register/Pages/railway-safety-performance-in-european-union-2010.aspxSeiford, L. M., & Zhu, J. (2002). Modeling undesirable factors in efficiency evaluation. European Journal of Operational Research, 142(1), 16-20.Smith, P. (1990). Data envelopment analysis applied to financial statements. Omega, 18(2), 131-138.Yu, M. M., & Lin, E. T. J. (2008). Efficiency and effectiveness in railway performance using a multi-activity network DEA model. Omega, 36(6), 1005-1017.Zofı́o, J. L., & Prieto, A. M. (2001). Environmental efficiency and regulatory standards: the case of CO2 emissions from OECD industries. Resource and Energy Economics, 23(1), 63-83.