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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

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  • Pal, Debdatta
  • Mitra, Subrata K.

Abstract

By using the directional distance function (DDF) of data envelopment analysis (DEA), this study measures the technical efficiency of 37 Indian state road transport undertakings (SRTUs) for the year 2012–13. We employ the DDF as a tool for analyzing a joint production function with both desirable and undesirable outputs (i.e., the number of accidents). A comparison between the results with and without accidents shows that several SRTUs have experienced significant changes in their efficiency scores as well as in their rankings after accounting for the undesirable output. This indicates the importance of including the number of accidents – a safety standard – as representative of the undesirable output in computing the efficiency scores of SRTUs. The results of the Tobit model indicate that SRTUs with greater vehicle productivity are more efficient under both conventional DEA and DDF approaches. We also employed zero-truncated negative binomial model to assess the factors influencing the number of road accident experienced by the Indian SRTUs and found that the accident count was significantly influenced by fleet utilization and vehicle productivity.

Suggested Citation

  • Pal, Debdatta & Mitra, Subrata 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, Elsevier, vol. 93(C), pages 1-12.
    • Handle: RePEc:eee:transa:v:93:y:2016:i:c:p:1-12
    DOI: 10.1016/j.tra.2016.08.012
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    Cited by:

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    2. Nikolaou, Paraskevas & Dimitriou, Loukas, 2018. "Evaluation of road safety policies performance across Europe: Results from benchmark analysis for a decade," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 232-246.
    3. Malin Song & Jianlin Wang & Jiajia Zhao & Tomas Baležentis & Zhiyang Shen, 2020. "Production and safety efficiency evaluation in Chinese coal mines: accident deaths as undesirable output," Annals of Operations Research, Springer, vol. 291(1), pages 827-845, August.
    4. Ying Li & Yung‐ho Chiu & Tai‐Yu Lin & Hongyi Cen & Yabin Liu, 2021. "Evaluation of natural disaster treatment efficiency in 27 Chinese provinces," Natural Resources Forum, Blackwell Publishing, vol. 45(3), pages 256-288, August.
    5. Niu, Yanliang & Li, Xin & Zhang, Jiangxue & Deng, Xiaopeng & Chang, Yuan, 2023. "Efficiency of railway transport: A comparative analysis for 16 countries," Transport Policy, Elsevier, vol. 141(C), pages 42-53.
    6. Joohwan Kim & Hwayoung Kim, 2021. "Evaluation of the Efficiency of Maritime Transport Using a Network Slacks-Based Measure (SBM) Approach: A Case Study on the Korean Coastal Ferry Market," Sustainability, MDPI, vol. 13(11), pages 1-17, May.
    7. Chen Chunhua & Liu Haohua & Tang Lijun & Ren Jianwei, 2021. "A Range Adjusted Measure of Super-Efficiency in Integer-Valued Data Envelopment Analysis with Undesirable Outputs," Journal of Systems Science and Information, De Gruyter, vol. 9(4), pages 378-398, August.

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    More about this item

    Keywords

    Technical efficiency; Road transport; Accident; Directional distance function; Tobit; Zero-truncated negative binomial;
    All these keywords.

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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