Share This Article:

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

Full-Text HTML XML Download Download as PDF (Size:560KB) PP. 121-135
DOI: 10.4236/ajor.2016.62015    2,737 Downloads   3,291 Views Citations
Author(s)

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.

Cite this paper

Tone, K. and Ouenniche, J. (2016) DEA Scores’ Confidence Intervals with Past-Present and Past-Present-Future Based Resampling. American Journal of Operations Research, 6, 121-135. doi: 10.4236/ajor.2016.62015.

Copyright © 2020 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.