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Malmquist productivity index based on common-weights DEA: The case of Taiwan forests after reorganization

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  • Kao, Chiang
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    Abstract

    The performance of a decision making unit (DMU) can be evaluated in either a cross-sectional or a time-series manner, and data envelopment analysis (DEA) is a useful method for both types of evaluation. In order to eliminate the inconsistency caused by using different frontier facets to calculate efficiency, common-weights DEA models have been developed, under which a group of DMUs can be ranked for a specific period. This study proposes a common-weights DEA model for time-series evaluations to calculate the global Malmquist productivity index (MPI) so that the productivity changes of all DMUs have a common basis for comparison. The common-weights global MPI not only has sound properties, but also produces reliable results. The case of Taiwan forests after reorganization shows that the MPIs calculated from the conventional DEA model produce misleading results. The common-weights global MPI approach, on the other hand, correctly identifies districts with unsatisfactory performance before the reorganization and those with unsatisfactory productivity improvement after the reorganization.

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    Bibliographic Info

    Article provided by Elsevier in its journal Omega.

    Volume (Year): 38 (2010)
    Issue (Month): 6 (December)
    Pages: 484-491

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    Handle: RePEc:eee:jomega:v:38:y:2010:i:6:p:484-491

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    Keywords: Data envelopment analysis Efficiency Forestry Malmquist productivity index Common weight;

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    Cited by:
    1. Samoilenko, Sergey & Osei-Bryson, Kweku-Muata, 2013. "Using Data Envelopment Analysis (DEA) for monitoring efficiency-based performance of productivity-driven organizations: Design and implementation of a decision support system," Omega, Elsevier, vol. 41(1), pages 131-142.
    2. Ramón, Nuria & Ruiz, José L. & Sirvent, Inmaculada, 2011. "Reducing differences between profiles of weights: A "peer-restricted" cross-efficiency evaluation," Omega, Elsevier, vol. 39(6), pages 634-641, December.
    3. Wang, Ying-Ming & Chin, Kwai-Sang, 2011. "The use of OWA operator weights for cross-efficiency aggregation," Omega, Elsevier, vol. 39(5), pages 493-503, October.
    4. Kao, Chiang & Hwang, Shiuh-Nan, 2014. "Multi-period efficiency and Malmquist productivity index in two-stage production systems," European Journal of Operational Research, Elsevier, vol. 232(3), pages 512-521.
    5. Hatefi, S.M. & Torabi, S.A., 2010. "A common weight MCDA-DEA approach to construct composite indicators," Ecological Economics, Elsevier, vol. 70(1), pages 114-120, November.
    6. Epure, Mircea & Kerstens, Kristiaan & Prior, Diego, 2011. "Technology-based total factor productivity and benchmarking: New proposals and an application," Omega, Elsevier, vol. 39(6), pages 608-619, December.
    7. Kao, Chiang & Liu, Shiang-Tai, 2014. "Measuring performance improvement of Taiwanese commercial banks under uncertainty," European Journal of Operational Research, Elsevier, vol. 235(3), pages 755-764.
    8. Kao, Chiang & Pao, Hwei-Lan, 2012. "Predicting project approvals: A case of grants from the National Science Council of Taiwan," Omega, Elsevier, vol. 40(1), pages 89-95, January.
    9. Chang, Shyr-Juh & Hsiao, Hsing-Chin & Huang, Li-Hua & Chang, Hsihui, 2011. "Taiwan quality indicator project and hospital productivity growth," Omega, Elsevier, vol. 39(1), pages 14-22, January.

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