Article citationsMore>>

Barnum, D.T., Gleason, J.M., Karlaftis, M.G., Schumock, G.T., Shields, K.L., Tandon, S. and Walton, S.M. (2011) Estimating DEA Confidence Intervals with Statistical Panel Data Analysis. Journal of Applied Statistics, 39, 815-828.
http://dx.doi.org/10.1080/02664763.2011.620948

has been cited by the following article:

• TITLE: DEA Scores’ Confidence Intervals with Past-Present and Past-Present-Future Based Resampling

  AUTHORS: Kaoru Tone, Jamal Ouenniche

  KEYWORDS: Data Variation, Resampling, Confidence Interval, Past-Present-Future DEA, Hospital

  JOURNAL NAME: American Journal of Operations Research, Vol.6 No.2, March 8, 2016

  ABSTRACT: In data envelopment analysis (DEA), input and output values are subject to change for several reasons. Such variations differ in their input/output items and their decision-making units (DMUs). Hence, DEA efficiency scores need to be examined by considering these factors. In this paper, we propose new resampling models based on these variations for gauging the confidence intervals of DEA scores. The first model utilizes past-present data for estimating data variations imposing chronological order weights which are supplied by Lucas series (a variant of Fibonacci series). The second model deals with future prospects. This model aims at forecasting the future efficiency score and its confidence interval for each DMU. We applied our models to a dataset composed of Japanese municipal hospitals.