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Estimating energy consumption of transport modes in India using DEA and application to energy and environmental policy

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  • R Ramanathan

    (Sultan Qaboos University)

Abstract

Energy is consumed both by passenger and freight traffic, and it is generally not possible to apportion energy consumption exclusively to either of the traffic without making restrictive assumptions on the energy consumption norms of vehicles. The use of data envelopment analysis (DEA) has been suggested earlier in the literature for comparing energy efficiencies without requiring any such restrictive assumptions. In this paper, the applicability of DEA is further extended to estimate energy consumption of rail and/or road transport that would result in a pre-specified DEA efficiency. Using this new approach, effects of capturing some modal split in favour of rail transport on future energy consumption and emissions of carbon dioxide are presented in the paper via a scenario analysis. It is shown that if rail could capture 50% modal share in the years 2005–2006 and 2020–2021, it would save nearly 35% energy consumption and emissions compared to the situation when existing patterns of modal split are allowed to continue without policy intervention.

Suggested Citation

  • R Ramanathan, 2005. "Estimating energy consumption of transport modes in India using DEA and application to energy and environmental policy," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(6), pages 732-737, June.
    • Handle: RePEc:pal:jorsoc:v:56:y:2005:i:6:d:10.1057_palgrave.jors.2601866
    DOI: 10.1057/palgrave.jors.2601866
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    9. Georgia Makridou, Kostas Andriosopoulos, Michael Doumpos, and Constantin Zopounidis, 2015. "A Two-stage approach for energy efficiency analysis in European Union countries," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
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    11. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
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    13. Chiu, Yung-Ho & Lee, Jen-Hui & Lu, Ching-Cheng & Shyu, Ming-Kuang & Luo, Zhengying, 2012. "The technology gap and efficiency measure in WEC countries: Application of the hybrid meta frontier model," Energy Policy, Elsevier, vol. 51(C), pages 349-357.
    14. Guo, Xiaoying & Lu, Ching-Cheng & Lee, Jen-Hui & Chiu, Yung-Ho, 2017. "Applying the dynamic DEA model to evaluate the energy efficiency of OECD countries and China," Energy, Elsevier, vol. 134(C), pages 392-399.
    15. Ching-Cheng Lu & Liang-Chun Lu, 2019. "Evaluating the energy efficiency of European Union countries: The dynamic data envelopment analysis," Energy & Environment, , vol. 30(1), pages 27-43, February.
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    17. A Paucar-Caceres & A Espinosa, 2011. "Management science methodologies in environmental management and sustainability: discourses and applications," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(9), pages 1601-1620, September.
    18. Thiago Victorino & Carlos Rosano Peña, 2023. "The Development of Efficiency Analysis in Transportation Systems: A Bibliometric and Systematic Review," Sustainability, MDPI, vol. 15(13), pages 1-32, June.
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    21. Boban Djordjević & Evelin Krmac, 2019. "Evaluation of Energy-Environment Efficiency of European Transport Sectors: Non-Radial DEA and TOPSIS Approach," Energies, MDPI, vol. 12(15), pages 1-27, July.
    22. Yuan, Qianqian & Fang Chin Cheng, Charles & Wang, Jiayu & Zhu, Tian-Tian & Wang, Ke, 2020. "Inclusive and sustainable industrial development in China: An efficiency-based analysis for current status and improving potentials," Applied Energy, Elsevier, vol. 268(C).
    23. Lu, Ching-Cheng & Chiu, Yung-Ho & Shyu, Ming-Kuang & Lee, Jen-Hui, 2013. "Measuring CO2 emission efficiency in OECD countries: Application of the Hybrid Efficiency model," Economic Modelling, Elsevier, vol. 32(C), pages 130-135.
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