Sensitivity and Stability Analysis in DEA: Some Recent Developments
R. Thrall and
Journal of Productivity Analysis, 2001, vol. 15, issue 3, 217-246
This papersurveys recently developed analytical methods for studying thesensitivity of DEA results to variations in the data. The focusis on the stability of classification of DMUs (Decision MakingUnits) into efficient and inefficient performers. Early workon this topic concentrated on developing solution methods andalgorithms for conducting such analyses after it was noted thatstandard approaches for conducting sensitivity analyses in linearprogramming could not be used in DEA. However, some of the recentwork we cover has bypassed the need for such algorithms. Evolvingfrom early work that was confined to studying data variationsin only one input or output for only one DMU at a time, the newermethods described in this paper make it possible to determineranges within which all data may be varied for any DMU beforea reclassification from efficient to inefficient status (or vice versa) occurs. Other coverage involves recent extensionswhich include methods for determining ranges of data variationthat can be allowed when all data are varied simultaneously for all DMUs. An initial section delimits the topics to be covered.A final section suggests topics for further research. Copyright Kluwer Academic Publishers 2001
Keywords: Efficiency; Data Variations; Sensitivity; Stability (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations View citations in EconPapers (44) Track citations by RSS feed
Downloads: (external link)
Access to full text is restricted to subscribers.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:kap:jproda:v:15:y:2001:i:3:p:217-246
Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/11123/PS2
Access Statistics for this article
Journal of Productivity Analysis is currently edited by William Greene, Chris O'Donnell and Victor Podinovski
More articles in Journal of Productivity Analysis from Springer
Series data maintained by Sonal Shukla ().