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Factor-specific Malmquist productivity index based on common weights DEA

Author

Listed:
  • Bojiang Yang

    (PLA University of Science and Technology)

  • Youliang Zhang

    (PLA University of Science and Technology)

  • Hongjun Zhang

    (PLA University of Science and Technology)

  • Rui Zhang

    (PLA University of Science and Technology)

  • Baoyu Xu

    (PLA University of Science and Technology)

Abstract

This paper designs a Malmquist productivity index (MPI) to measure the productivity change of a decision-making unit (DMU) on a specific input/output factor over time. First, factor-specific data envelopment analysis is extended by considering input/output substitution possibilities, where partial correlation is taken as the criterion of substitutability. Factors are clustered and those which are not in the same cluster with the concerned one are excluded when calculating the factor-specific efficiency. Next, the common weights global MPI is employed, in order to simultaneously have the sound properties of consistency, circularity and comparability. Common weights are generated separately for each DMU, since only the productivities of a same DMU at different periods need to be compared in the calculation process of MPI. The case of Taiwan forests after reorganization illustrates that the proposed models can provide new insights into the productivity change of DMUs.

Suggested Citation

  • Bojiang Yang & Youliang Zhang & Hongjun Zhang & Rui Zhang & Baoyu Xu, 2016. "Factor-specific Malmquist productivity index based on common weights DEA," Operational Research, Springer, vol. 16(1), pages 51-70, April.
    • Handle: RePEc:spr:operea:v:16:y:2016:i:1:d:10.1007_s12351-015-0185-x
    DOI: 10.1007/s12351-015-0185-x
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    1. William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), 2011. "Handbook on Data Envelopment Analysis," International Series in Operations Research and Management Science, Springer, number 978-1-4419-6151-8, September.
    2. C B Vaz & A S Camanho, 2012. "Performance comparison of retailing stores using a Malmquist-type index," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 63(5), pages 631-645, May.
    3. Odeck, James, 2006. "Identifying traffic safety best practice: an application of DEA and Malmquist indices," Omega, Elsevier, vol. 34(1), pages 28-40, January.
    4. Adler, Nicole & Yazhemsky, Ekaterina, 2010. "Improving discrimination in data envelopment analysis: PCA-DEA or variable reduction," European Journal of Operational Research, Elsevier, vol. 202(1), pages 273-284, April.
    5. Kao, Chiang, 2010. "Malmquist productivity index based on common-weights DEA: The case of Taiwan forests after reorganization," Omega, Elsevier, vol. 38(6), pages 484-491, December.
    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. Nataraja, Niranjan R. & Johnson, Andrew L., 2011. "Guidelines for using variable selection techniques in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 215(3), pages 662-669, December.
    8. N Adler & B Golany, 2002. "Including principal component weights to improve discrimination in data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(9), pages 985-991, September.
    9. Zhu, Joe, 2000. "Multi-factor performance measure model with an application to Fortune 500 companies," European Journal of Operational Research, Elsevier, vol. 123(1), pages 105-124, May.
    10. Chang, Hsihui & Choy, Hiu Lam & Cooper, William W. & Ruefli, Timothy W., 2009. "Using Malmquist Indexes to measure changes in the productivity and efficiency of US accounting firms before and after the Sarbanes-Oxley Act," Omega, Elsevier, vol. 37(5), pages 951-960, October.
    11. Gong-Bing Bi & Jing-Jing Ding & Yan Luo & Liang Liang, 2011. "A New Malmquist Productivity Index Based On Semi-Discretionary Variables With An Application To Commercial Banks Of China," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 10(04), pages 713-730.
    12. Chen, Yao, 2003. "A non-radial Malmquist productivity index with an illustrative application to Chinese major industries," International Journal of Production Economics, Elsevier, vol. 83(1), pages 27-35, January.
    13. Dyson, R. G. & Allen, R. & Camanho, A. S. & Podinovski, V. V. & Sarrico, C. S. & Shale, E. A., 2001. "Pitfalls and protocols in DEA," European Journal of Operational Research, Elsevier, vol. 132(2), pages 245-259, July.
    14. Rajiv D. Banker & Richard C. Morey, 1986. "Efficiency Analysis for Exogenously Fixed Inputs and Outputs," Operations Research, INFORMS, vol. 34(4), pages 513-521, August.
    15. Pastor, Jesus T. & Lovell, C.A. Knox, 2005. "A global Malmquist productivity index," Economics Letters, Elsevier, vol. 88(2), pages 266-271, August.
    16. Adler, Nicole & Golany, Boaz, 2001. "Evaluation of deregulated airline networks using data envelopment analysis combined with principal component analysis with an application to Western Europe," European Journal of Operational Research, Elsevier, vol. 132(2), pages 260-273, July.
    17. Thanassoulis, E. & Dyson, R. G., 1992. "Estimating preferred target input-output levels using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 56(1), pages 80-97, January.
    18. G D Ferrier & V G Valdmanis, 2004. "Do mergers improve hospital productivity?," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(10), pages 1071-1080, October.
    19. Jenkins, Larry & Anderson, Murray, 2003. "A multivariate statistical approach to reducing the number of variables in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 147(1), pages 51-61, May.
    20. C Kao & H-T Hung, 2005. "Data envelopment analysis with common weights: the compromise solution approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(10), pages 1196-1203, October.
    21. Kao, Chiang & Chi Yang, Yong, 1992. "Reorganization of forest districts via efficiency measurement," European Journal of Operational Research, Elsevier, vol. 58(3), pages 356-362, May.
    22. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
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    Cited by:

    1. Barnabé Walheer, 2018. "Cost Malmquist productivity index: an output-specific approach for group comparison," Journal of Productivity Analysis, Springer, vol. 49(1), pages 79-94, February.
    2. Reza Fallahnejad & Mohammad Reza Mozaffari & Peter Fernandes Wanke & Yong Tan, 2024. "Nash Bargaining Game Enhanced Global Malmquist Productivity Index for Cross-Productivity Index," Games, MDPI, vol. 15(1), pages 1-21, January.
    3. Ali Homayoni & Reza Fallahnejad & Farhad Hosseinzadeh Lotfi, 2022. "Cross Malmquist Productivity Index in Data Envelopment Analysis," 4OR, Springer, vol. 20(4), pages 567-602, December.
    4. Afsharian, Mohsen & Ahn, Heinz & Harms, Sören Guntram, 2021. "A review of DEA approaches applying a common set of weights: The perspective of centralized management," European Journal of Operational Research, Elsevier, vol. 294(1), pages 3-15.
    5. Song, Malin & Wang, Jianlin & Zhao, Jiajia, 2023. "Effects of rising and extreme temperatures on production factor efficiency: Evidence from China's cities," International Journal of Production Economics, Elsevier, vol. 260(C).

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