Classifying and Predicting Efficiencies Using Interval DEA Grid Setting

Main Author: Yiannis G. Smirlis
Format: Article
Bahasa: eng
Terbitan: , 2018
Subjects:
Online Access: https://zenodo.org/record/1317188
Daftar Isi:
  • The classification and the prediction of efficiencies in Data Envelopment Analysis (DEA) is an important issue, especially in large scale problems or when new units frequently enter the under-assessment set. In this paper, we contribute to the subject by proposing a grid structure based on interval segmentations of the range of values for the inputs and outputs. Such intervals combined, define hyper-rectangles that partition the space of the problem. This structure, exploited by Interval DEA models and a dominance relation, acts as a DEA pre-processor, enabling the classification and prediction of efficiency scores, without applying any DEA models.