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Performance Assessment Based on the Relative Efficiency of Indian Opencast Coal Mines Using Data Envelopment Analysis and Malmquist Productivity Index

Author

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  • Biswaranjita Mahapatra

    (Department of Management Studies, Indian Institute of Technology (Indian School of Mines), Dhanbad 826004, India)

  • Chandan Bhar

    (Department of Management Studies, Indian Institute of Technology (Indian School of Mines), Dhanbad 826004, India)

  • Sandeep Mondal

    (Department of Management Studies, Indian Institute of Technology (Indian School of Mines), Dhanbad 826004, India)

Abstract

Coal is the primary source of energy in India. Despite being the second-largest coal-producing country, there exists a significant difference in demand and production in India. In this study, the relative efficiency of twenty-eight selected opencast mines from a large public sector undertaking coal company in India for 2018–2019 was assessed and ranked by using data envelopment analysis (DEA). This study used input-oriented DEA with efficiency decomposition to pure technical efficiency, technical efficiency, and scale efficiency. The result showed that 25% and 36% of mines were efficient in technical efficiency and pure technical efficiency, respectively, whereas the eight mines scale efficiency was inefficient with a decreasing return to scale. Further, in this study, theMalmquist Productivity Index (MPI)was employed to measure the efficiency of the selected mines for three consecutive years (2016–2017 to 2018–2019). The result shows that in only three mines the efficiency is continuously improving from 2016–2017 to 2018–2019, whereas in more than 20% of mines the efficiency score is decreasing. Comparing theMPI efficiency and productivity assessment throughout the years, changes in innovation and technology are increasing from 2017–2018 to 2018–2019. Finally, the study concluded with a comprehensive evaluation of each variable with mines performance. The author formulated the strategies, which in turn help coal professionals to improve the efficiency of the mine.

Suggested Citation

  • Biswaranjita Mahapatra & Chandan Bhar & Sandeep Mondal, 2020. "Performance Assessment Based on the Relative Efficiency of Indian Opencast Coal Mines Using Data Envelopment Analysis and Malmquist Productivity Index," Energies, MDPI, vol. 13(18), pages 1-21, September.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:18:p:4902-:d:415822
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    References listed on IDEAS

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    1. Hosseinzadeh, Ahmad & Smyth, Russell & Valadkhani, Abbas & Le, Viet, 2016. "Analyzing the efficiency performance of major Australian mining companies using bootstrap data envelopment analysis," Economic Modelling, Elsevier, vol. 57(C), pages 26-35.
    2. Jamasb, Tooraj & Pollitt, Michael & Triebs, Thomas, 2008. "Productivity and efficiency of US gas transmission companies: A European regulatory perspective," Energy Policy, Elsevier, vol. 36(9), pages 3398-3412, September.
    3. Barros, Carlos Pestana, 2008. "Efficiency analysis of hydroelectric generating plants: A case study for Portugal," Energy Economics, Elsevier, vol. 30(1), pages 59-75, January.
    4. Yang, Hongliang & Pollitt, Michael, 2009. "Incorporating both undesirable outputs and uncontrollable variables into DEA: The performance of Chinese coal-fired power plants," European Journal of Operational Research, Elsevier, vol. 197(3), pages 1095-1105, September.
    5. Vaninsky, Alexander, 2006. "Efficiency of electric power generation in the United States: Analysis and forecast based on data envelopment analysis," Energy Economics, Elsevier, vol. 28(3), pages 326-338, May.
    6. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    7. Chiang Kao, 2017. "Network Data Envelopment Analysis," International Series in Operations Research and Management Science, Springer, number 978-3-319-31718-2, July-Dece.
    8. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
    9. Thompson, Russell G. & Dharmapala, P. S. & Thrall, Robert M., 1995. "Linked-cone DEA profit ratios and technical efficiency with application to Illinois coal mines," International Journal of Production Economics, Elsevier, vol. 39(1-2), pages 99-115, April.
    10. Kulshreshtha, Mudit & Parikh, Jyoti K., 2002. "Study of efficiency and productivity growth in opencast and underground coal mining in India: a DEA analysis," Energy Economics, Elsevier, vol. 24(5), pages 439-453, September.
    11. Fang, Hong & Wu, Junjie & Zeng, Catherine, 2009. "Comparative study on efficiency performance of listed coal mining companies in China and the US," Energy Policy, Elsevier, vol. 37(12), pages 5140-5148, December.
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