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A DEA-based analysis of productivity change and intertemporal managerial performance

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  • E. Grifell-Tatjé
  • C.A.K. Lovell

Abstract

DEA is typically applied to cross-section data to analyze productive efficiency. DEA is infrequently applied to panel data to analyze the variation of productive efficiency over time, but when it is, the technique of choice has been window analysis. Here, we adopt a different approach to the use of DEA with panel data. Following the lead of Färe and others, we use DEA to construct a Malmquist index of productivity change, and we provide a new decomposition of the Malmquist productivity index. Our new decomposition allocates productivity change to change in productive efficiency, the magnitude of technical change, and the bias of technical change. We then propose an evaluation of managerial performance, not on the usual basis of static efficiency, but on the intertemporal basis of change in efficiency and adaptation to the bias of technical change. We illustrate our approach with an examination of the recent productivity change experience in Spanish savings banks. Copyright Kluwer Academic Publishers 1997

Suggested Citation

  • E. Grifell-Tatjé & C.A.K. Lovell, 1997. "A DEA-based analysis of productivity change and intertemporal managerial performance," Annals of Operations Research, Springer, vol. 73(0), pages 177-189, October.
  • Handle: RePEc:spr:annopr:v:73:y:1997:i:0:p:177-189:10.1023/a:1018925127385
    DOI: 10.1023/A:1018925127385
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    Cited by:

    1. Andrew Johnson & John Ruggiero, 2014. "Nonparametric measurement of productivity and efficiency in education," Annals of Operations Research, Springer, vol. 221(1), pages 197-210, October.
    2. Arocena, Pablo & Saal, David S. & Urakami, Takuya & Zschille, Michael, 2020. "Measuring and decomposing productivity change in the presence of mergers," European Journal of Operational Research, Elsevier, vol. 282(1), pages 319-333.
    3. Christos Pantzios & Giannis Karagiannis & Vangelis Tzouvelekas, 2011. "Parametric decomposition of the input-oriented Malmquist productivity index: with an application to Greek aquaculture," Journal of Productivity Analysis, Springer, vol. 36(1), pages 21-31, August.
    4. Po-Chi Chen & Ming-Miin Yu, 2014. "Total factor productivity growth and directions of technical change bias: evidence from 99 OECD and non-OECD countries," Annals of Operations Research, Springer, vol. 214(1), pages 143-165, March.
    5. Michael L. Polemis & Mike G. Tsionas, 2022. "Endogenous productivity: a new Bayesian perspective," Annals of Operations Research, Springer, vol. 318(1), pages 425-451, November.
    6. Wen-Min Lu & Qian Long Kweh & Kang-Fu Chen, 2021. "How do peace dividends bring about human development and productivity?," Annals of Operations Research, Springer, vol. 306(1), pages 435-452, November.
    7. Chia-Yen Lee & Andrew Johnson, 2015. "Effective production: measuring of the sales effect using data envelopment analysis," Annals of Operations Research, Springer, vol. 235(1), pages 453-486, December.
    8. Konstantinos Petridis & Alexander Chatzigeorgiou & Emmanouil Stiakakis, 2016. "A spatiotemporal Data Envelopment Analysis (S-T DEA) approach: the need to assess evolving units," Annals of Operations Research, Springer, vol. 238(1), pages 475-496, March.
    9. Alem Gebremedhin Berhe, 2021. "An Empirical Analysis of Productivity Changes in the Ethiopian Commercial Banks: Using DEA- Based Malmquist Productivity Index Approach," Accounting and Finance Research, Sciedu Press, vol. 10(1), pages 1-48, February.
    10. Yu, Ming-Miin & Chen, Li-Hsueh, 2023. "Productivity change of airlines: A global total factor productivity index with network structure," Journal of Air Transport Management, Elsevier, vol. 109(C).
    11. Abd Hadi Mustaffa & Nur Zahidah Bahrudin & Zahariah Sahudin & Hasni Abdullah & Muhammad Ridzuan Abdul Aziz, 2023. "What have we Learned from Firm Efficiency Research for the Past 35 Years? A Bibliometric Analysis," Information Management and Business Review, AMH International, vol. 15(1), pages 216-227.
    12. Ma, Jinlong & Evans, David G. & Fuller, Robert J. & Stewart, Donald F., 2002. "Technical efficiency and productivity change of China's iron and steel industry," International Journal of Production Economics, Elsevier, vol. 76(3), pages 293-312, April.
    13. Konstantinos Petridis & Alexander Chatzigeorgiou & Emmanouil Stiakakis, 2016. "A spatiotemporal Data Envelopment Analysis (S-T DEA) approach: the need to assess evolving units," Annals of Operations Research, Springer, vol. 238(1), pages 475-496, March.

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