Performance Evaluation of the Public Bus Transportation in India: An Application of the Malmquist Productivity Index
By using the Data Envelopment Analysis (DEA) Malmquist Productivity Index (MPI), this study measures the efficiency of 33 State Transport Undertakings (STUs) in India, considering the year 2010-16. An output-oriented approach is used with output variables as Effective kilometres and input variables...
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| Published in | Journal of the Eastern Asia Society for Transportation Studies Vol. 15; pp. 553 - 572 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
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Eastern Asia Society for Transportation Studies
2024
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| Online Access | Get full text |
| ISSN | 1881-1124 |
| DOI | 10.11175/easts.15.553 |
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| Abstract | By using the Data Envelopment Analysis (DEA) Malmquist Productivity Index (MPI), this study measures the efficiency of 33 State Transport Undertakings (STUs) in India, considering the year 2010-16. An output-oriented approach is used with output variables as Effective kilometres and input variables as Fleet Size, Total staff, and fuel consumption. The study attempts to provide an overview of the general status of STUs in India regarding their productive efficiencies in terms of years, firm-wise performance, and organisation-wise performance. The research has policy and managerial implications, with the study’s limitations also discussed. |
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| AbstractList | By using the Data Envelopment Analysis (DEA) Malmquist Productivity Index (MPI), this study measures the efficiency of 33 State Transport Undertakings (STUs) in India, considering the year 2010-16. An output-oriented approach is used with output variables as Effective kilometres and input variables as Fleet Size, Total staff, and fuel consumption. The study attempts to provide an overview of the general status of STUs in India regarding their productive efficiencies in terms of years, firm-wise performance, and organisation-wise performance. The research has policy and managerial implications, with the study’s limitations also discussed. |
| Author | VARGHESE, Ann Mary |
| Author_xml | – sequence: 1 fullname: VARGHESE, Ann Mary organization: Vinod Gupta School of Management, Indian Institute of Technology |
| BackLink | https://cir.nii.ac.jp/crid/1390019070462850944$$DView record in CiNii |
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| Copyright | 2024 Eastern Asia Society for Transportation Studies |
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| References | Sheth, C., Triantis, K., Teodorović, D., 2007. Performance evaluation of bus routes: A provider and passenger perspective. Transportation Research Part E: Logistics and Transportation Review 43, 453–478. Jarboui, S., Forget, P., Boujelbene, Y., 2012. Public road transport efficiency: a literature review via the classification scheme. Public Transp 4, 101–128. https://doi.org/10/gm57wk Pal, D., Mitra, S.K., 2016. 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: Policy and Practice 93, 1–12. https://doi.org/10/f857tt Bhattacharyya, A., Kumbhakar, S.C., Bhattacharyya, A., 1995. Ownership structure and cost efficiency: A study of publicly owned passenger-bus transportation companies in India. Journal of Productivity Analysis 6, 47–61. https://doi.org/10.1007/BF01073494 Karlaftis, M.G., 2004. A DEA approach for evaluating the efficiency and effectiveness of urban transit systems. European Journal of Operational Research 152, 354–364. https://doi.org/10.1016/S0377-2217(03)00029-8 Yu, M.-M., Fan, C.-K., 2009. Measuring the performance of multimode bus transit: A mixed structure network DEA model. Transportation Research Part E: Logistics and Transportation Review 45, 501–515. Boame, A.K., 2004. The technical efficiency of Canadian urban transit systems. Transportation Research Part E: Logistics and Transportation Review 40, 401–416. https://doi.org/10.1016/j.tre.2003.09.002 Pestana Barros, C., Peypoch, N., 2010. Productivity changes in Portuguese bus companies. Transport Policy 17, 295–302. https://doi.org/10.1016/j.tranpol.2010.02.003 Barnum, D.T., Gleason, J.M., 2007. Technical efficiency bias in data envelopment analysis caused by intra-output aggregation. Applied Economics Letters 14, 623–626. Margari, B.B., Erbetta, F., Petraglia, C., Piacenza, M., 2007. Regulatory and environmental effects on public transit efficiency: a mixed DEA-SFA approach. J Regul Econ 32, 131–151. https://doi.org/10.1007/s11149-007-9025-0 Cui, Q., Li, Y., 2014. The evaluation of transportation energy efficiency: An application of three-stage virtual frontier DEA. Transportation Research Part D: Transport and Environment 29, 1–11. https://doi.org/10/f5828n Odeck, J., 2008. The effect of mergers on efficiency and productivity of public transport services. Transportation Research Part A: Policy and Practice 42, 696–708. https://doi.org/10/d33qrv Georgiadis, G., Politis, I., Papaioannou, P., 2014. Measuring and improving the efficiency and effectiveness of bus public transport systems. Research in Transportation Economics 48, 84–91. https://doi.org/10/gm57xd Maier, C., Thatcher, J.B., Grover, V., Dwivedi, Y.K., 2023. Cross-sectional research: A critical perspective, use cases, and recommendations for IS research. International Journal of Information Management 102625. Odeck, J., 2000. Assessing the relative efficiency and productivity growth of vehicle inspection services: An application of DEA and Malmquist indices. European Journal of Operational Research 126, 501–514. Coelli, T.J., Rao, D.S.P., O’Donnell, C.J., Battese, G.E., 2005. An introduction to efficiency and productivity analysis. Springer science & business media. Karlaftis, M.G., 2010. Ownership and competition in European transit: assessing efficiency. Transportmetrica 6, 143–160. https://doi.org/10.1080/18128600903034342 Chen, Y.S., Chen, B.Y., 2011. Applying DEA, MPI, and grey model to explore the operation performance of the Taiwanese wafer fabrication industry. Technological Forecasting and Social Change 78(3), .536-546. https://doi.org/10.1016/j.techfore.2010.04.013 Cooper, W.W., Seiford, L.M., Tone, K., 2007. Data envelopment analysis: A comprehensive text with models, applications, references and DEA-solver software: Second edition, Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software: Second Edition. https://doi.org/10.1007/978-0-387-45283-8 Tretheway, M.W., Waters, W., Fok, A.K., 1997. The total factor productivity of the Canadian railways, 1956-91. Journal of Transport Economics and Policy 93–113. Zhou, P., Ang, B.W., Poh, K.L., 2008. A survey of data envelopment analysis in energy and environmental studies. European Journal of Operational Research 189, 1–18. https://doi.org/10/b5ggpr Hjalmarsson, L., Odeck, J., 1996. Efficiency of trucks in road construction and maintenance: an evaluation with data envelopment analysis. Computers & operations research 23, 393–404. Venkatesh, A., Kushwaha, S., 2017. Measuring technical efficiency of passenger bus companies in India: a non-radial data envelopment analysis approach. OPSEARCH 54, 706–723. https://doi.org/10/gm57vr Odeck, J., 2006. Congestion, ownership, region of operation, and scale: Their impact on bus operator performance in Norway. Socio-Economic Planning Sciences 40, 52–69. https://doi.org/10.1016/j.seps.2004.05.001 Kerstens, K., 1996. Technical efficiency measurement and explanation of French urban transit companies. Transportation Research Part A: Policy and Practice 30, 431–452. https://doi.org/10.1016/0965-8564(96)00006-7 Odeck, J., Alkadi, A., 2001. Evaluating efficiency in the Norwegian bus industry using data envelopment analysis. Transportation 28, 211–232. Viton, P.A., 1997. Technical efficiency in multi-mode bus transit: A production frontier analysis. Transportation Research Part B: Methodological 31, 23–39. https://doi.org/10.1016/S0191-2615(96)00019-7 Emrouznejad, A., Yang, G., 2018. A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016. Socio-Economic Planning Sciences 61, 4–8. https://doi.org/10/gfj2tx Odeck, J., 2005. Evaluating target achievements in the public sector: An application of a rare non-parametric DEA and Malmquist indices. Journal of Applied Economics 8, 171–190. Ramanathan, R., 1999. Using data envelopment analysis for assessing the productivity of the state transport undertakings. Indira Gandhi Institute of Development Research. Holvad, T., Hougaard, J.L., Kronborg, D., Kvist, H.K., 2004. Measuring inefficiency in the Norwegian bus industry using multi-directional efficiency analysis. Transportation 31, 349–369. Patankar, P., 1985. Productivity Improvements in Passenger Road Transport Services in Metropolitan Areas. Journal of Transport Management 9, 13–28. Cui, Q., Li, Y., 2015. An empirical study on the influencing factors of transportation carbon efficiency: Evidences from fifteen countries. Applied Energy 141, 209–217. https://doi.org/10.1016/j.apenergy.2014.12.040 Gulati, R., 2022. The accident-adjusted dynamic efficiency of public bus operators in metropolitan cities of India. Benchmarking: An International Journal ahead-of-print. https://doi.org/10.1108/BIJ-03-2021-0154 von Hirschhausen, C., Cullmann, A., 2010. A non-parametric efficiency analysis of German public transport companies. Transportation Research Part E: Logistics and Transportation Review 46, 436–445. https://doi.org/10.1016/j.tre.2009.11.005 Cowie, J., 2002. Acquisition, efficiency and scale economies: An analysis of the British bus industry. Transport Reviews 22, 147–157. https://doi.org/10/cgfwrv Odeck, J., Hjalmarsson, L., 1996. The performance of trucks—an evaluation using data envelopment analysis. Transportation Planning and Technology 20, 49–66. Venkatesh, A., Kushwaha, S., 2018. Short and long-run cost efficiency in Indian public bus companies using Data Envelopment Analysis. Socio-Economic Planning Sciences 61, 29–36. https://doi.org/10/gm57t9 Zhang, C., Juan, Z., Xiao, G., 2015. Do contractual practices affect technical efficiency? Evidence from public transport operators in China. Transportation Research Part E: Logistics and Transportation Review 80, 39–55. https://doi.org/10.1016/j.tre.2015.05.001 Agarwal, S., 2016. Evaluation of efficiency and effectiveness of public transport sector of india using dea approach. Data Envelopment Analysis and its Applications 73. de Borger, B., Kerstens, K., Staat, M., 2008. Transit costs and cost efficiency: Bootstrapping non-parametric frontiers. Research in Transportation Economics 23, 53–64. https://doi.org/10.1016/j.retrec.2008.10.008 Kumar, S., 2011. State road transport undertakings in India: technical efficiency and its determinants. Benchmarking 18, 616–643. https://doi.org/10/dwcmkv Singh, S.K., Venkatesh, A., 2003. Comparing efficiency across state transport undertakings: a production frontier approach. Indian Journal of Transport Management 27, 374–391. Farsi, M., Filippini, M., Kuenzle, M., 2006. Cost efficiency in regional bus companies: An application of alternative stochastic frontier models. Journal of Transport Economics and Policy (JTEP) 40, 95–118. Yan, D., Kong, Y., Ye, B., Shi, Y., Zeng, X., 2019. Spatial variation of energy efficiency based on a Super-Slack-Based Measure: Evidence from 104 resource-based cities. Journal of Cleaner Production 240. https://doi.org/10.1016/j.jclepro.2019.117669 Fitzová, H., Matulová, M., Tomeš, Z., 2018. Determinants of urban public transport efficiency: case study of the Czech Republic. Eur. Transp. Res. Rev. 10, 42. https://doi.org/10/gfbkkr Tone, K., 2001. Slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research 130, 498–509. https://doi.org/10.1016/S0377-2217(99)00407-5 Hsiao, C., 2005. Why panel data? The Singapore Economic Review 50, 143–154. Agarwal, S., Yadav, S.P., Singh, S.P., 2010. DEA based estimation of the technical efficiency of state transport undertakings in India. 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Public road transport efficiency: a literature review via the classification scheme. Public Transp 4, 101–128. https://doi.org/10/gm57wk – reference: Kumar, S., 2011. State road transport undertakings in India: technical efficiency and its determinants. Benchmarking 18, 616–643. https://doi.org/10/dwcmkv – reference: Hsiao, C., 2005. Why panel data? The Singapore Economic Review 50, 143–154. – reference: Cowie, J., Asenova, D., 1999. Organisation form, scale effects and efficiency in the British bus industry. Transportation 26, 231–248. https://doi.org/10.1023/A:1005121506841 – reference: Georgiadis, G., Politis, I., Papaioannou, P., 2014. Measuring and improving the efficiency and effectiveness of bus public transport systems. Research in Transportation Economics 48, 84–91. https://doi.org/10/gm57xd – reference: Odeck, J., 2008. The effect of mergers on efficiency and productivity of public transport services. Transportation Research Part A: Policy and Practice 42, 696–708. https://doi.org/10/d33qrv – reference: Farsi, M., Filippini, M., Kuenzle, M., 2006. Cost efficiency in regional bus companies: An application of alternative stochastic frontier models. Journal of Transport Economics and Policy (JTEP) 40, 95–118. – reference: Karlaftis, M.G., 2003. Investigating transit production and performance: a programming approach. Transportation Research Part A: Policy and Practice 37, 225–240. https://doi.org/10.1016/S0965-8564(02)00013-7 – reference: Sheth, C., Triantis, K., Teodorović, D., 2007. Performance evaluation of bus routes: A provider and passenger perspective. Transportation Research Part E: Logistics and Transportation Review 43, 453–478. – reference: Viton, P.A., 1997. Technical efficiency in multi-mode bus transit: A production frontier analysis. Transportation Research Part B: Methodological 31, 23–39. https://doi.org/10.1016/S0191-2615(96)00019-7 – reference: Yu, M.-M., Fan, C.-K., 2006. Measuring the Cost Effectiveness of Multimode Bus Transit in the Presence of Accident Risks. Transportation Planning and Technology 29, 383–407. https://doi.org/10.1080/03081060600917728 – reference: Odeck, J., 2005. Evaluating target achievements in the public sector: An application of a rare non-parametric DEA and Malmquist indices. Journal of Applied Economics 8, 171–190. – reference: Pal, D., Mitra, S.K., 2016. 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: Policy and Practice 93, 1–12. https://doi.org/10/f857tt – reference: Kushwaha, S., Prawesh, S., Venkatesh, A., 2021. Does capacity utilisation influence financial performance? A study of Indian public bus transport companies. Benchmarking: An International Journal 29, 1241–1263. https://doi.org/10.1108/BIJ-01-2021-0039 – reference: Odeck, J., Alkadi, A., 2001. Evaluating efficiency in the Norwegian bus industry using data envelopment analysis. Transportation 28, 211–232. – reference: Tretheway, M.W., Waters, W., Fok, A.K., 1997. The total factor productivity of the Canadian railways, 1956-91. Journal of Transport Economics and Policy 93–113. – reference: Agarwal, S., Yadav, S., Singh, S., 2006. A data envelopment analysis based efficiency assessment of public transport sector of Uttar Pradesh in India. Indian J. Transport Management 30, 5–30. – reference: Emrouznejad, A., Yang, G., 2018. A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016. Socio-Economic Planning Sciences 61, 4–8. https://doi.org/10/gfj2tx – reference: Bhattacharyya, A., Kumbhakar, S.C., Bhattacharyya, A., 1995. Ownership structure and cost efficiency: A study of publicly owned passenger-bus transportation companies in India. Journal of Productivity Analysis 6, 47–61. https://doi.org/10.1007/BF01073494 – reference: Cooper, W.W., Seiford, L.M., Tone, K., 2007. Data envelopment analysis: A comprehensive text with models, applications, references and DEA-solver software: Second edition, Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software: Second Edition. https://doi.org/10.1007/978-0-387-45283-8 – reference: Odeck, J., 2000. Assessing the relative efficiency and productivity growth of vehicle inspection services: An application of DEA and Malmquist indices. European Journal of Operational Research 126, 501–514. – reference: Odeck, J., 2006. Congestion, ownership, region of operation, and scale: Their impact on bus operator performance in Norway. Socio-Economic Planning Sciences 40, 52–69. https://doi.org/10.1016/j.seps.2004.05.001 – reference: Patankar, P., 1985. Productivity Improvements in Passenger Road Transport Services in Metropolitan Areas. Journal of Transport Management 9, 13–28. – reference: Tone, K., 2001. Slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research 130, 498–509. https://doi.org/10.1016/S0377-2217(99)00407-5 – reference: Venkatesh, A., Kushwaha, S., 2017. Measuring technical efficiency of passenger bus companies in India: a non-radial data envelopment analysis approach. OPSEARCH 54, 706–723. https://doi.org/10/gm57vr – reference: Ramanathan, R., 1999. Using data envelopment analysis for assessing the productivity of the state transport undertakings. Indira Gandhi Institute of Development Research. – reference: Holvad, T., Hougaard, J.L., Kronborg, D., Kvist, H.K., 2004. Measuring inefficiency in the Norwegian bus industry using multi-directional efficiency analysis. Transportation 31, 349–369. – reference: Cui, Q., Li, Y., 2015. An empirical study on the influencing factors of transportation carbon efficiency: Evidences from fifteen countries. Applied Energy 141, 209–217. https://doi.org/10.1016/j.apenergy.2014.12.040 – reference: Hensher, D.A., 1992. Total factor productivity growth and endogenous demand: Establishing a benchmark index for the selection of operational performance measures in public bus firms. Transportation Research Part B: Methodological 26, 435–448. https://doi.org/10.1016/0191-2615(92)90009-L – reference: Barnum, D.T., Gleason, J.M., 2007. Technical efficiency bias in data envelopment analysis caused by intra-output aggregation. Applied Economics Letters 14, 623–626. – reference: Pestana Barros, C., Peypoch, N., 2010. Productivity changes in Portuguese bus companies. Transport Policy 17, 295–302. https://doi.org/10.1016/j.tranpol.2010.02.003 – reference: Karlaftis, M.G., 2004. A DEA approach for evaluating the efficiency and effectiveness of urban transit systems. European Journal of Operational Research 152, 354–364. https://doi.org/10.1016/S0377-2217(03)00029-8 – reference: Cui, Q., Li, Y., 2014. The evaluation of transportation energy efficiency: An application of three-stage virtual frontier DEA. Transportation Research Part D: Transport and Environment 29, 1–11. https://doi.org/10/f5828n – reference: Boame, A.K., 2004. The technical efficiency of Canadian urban transit systems. Transportation Research Part E: Logistics and Transportation Review 40, 401–416. https://doi.org/10.1016/j.tre.2003.09.002 – reference: Fitzová, H., Matulová, M., Tomeš, Z., 2018. Determinants of urban public transport efficiency: case study of the Czech Republic. Eur. Transp. Res. Rev. 10, 42. https://doi.org/10/gfbkkr – reference: Zhang, C., Juan, Z., Xiao, G., 2015. Do contractual practices affect technical efficiency? Evidence from public transport operators in China. Transportation Research Part E: Logistics and Transportation Review 80, 39–55. https://doi.org/10.1016/j.tre.2015.05.001 – reference: Margari, B.B., Erbetta, F., Petraglia, C., Piacenza, M., 2007. Regulatory and environmental effects on public transit efficiency: a mixed DEA-SFA approach. J Regul Econ 32, 131–151. https://doi.org/10.1007/s11149-007-9025-0 |
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| SubjectTerms | Analysis Malmquist Productivity Index Data Envelopment Efficiency Measurement India Public Bus Transportation |
| Title | Performance Evaluation of the Public Bus Transportation in India: An Application of the Malmquist Productivity Index |
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| ispartofPNX | Journal of the Eastern Asia Society for Transportation Studies, 2024, Vol.15, pp.553-572 |
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