Generalized robust window data envelopment analysis approach for dynamic performance measurement under uncertain panel data

Pejman Peykani, Jafar Gheidar-Kheljani, Reza Farzipoor Saen*, Emran Mohammadi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This paper proposes a robust window data envelopment analysis (RWDEA) approach for assessing the dynamic performance of decision making units (DMU) in the presence of panel and uncertain data. To present the RWDEA method, generalized data envelopment analysis (GDEA) model, window analysis (WA) method, and robust optimization (RO) approach are taken into account. The proposed RWDEA approach can be used under different returns to scale (RTS) assumptions, including constant returns to scale (CRS), non-increasing returns to scale (NIRS), non-decreasing returns to scale (NDRS), and variable returns to scale (VRS). Notably, the RWDEA model is linear and can fully rank DMUs under deep uncertainty. To solve and show the validity of the proposed approach, the RWDEA model is implemented for evaluating the efficiency of the intellectual capital of 10 automotive and parts manufacturing companies. The results indicate that the RWDEA approach is applicable and useful for the dynamic efficiency assessment of DMUs in the presence of uncertain panel data. The RWDEA approach, by considering the uncertainties in the data and using panel data, provides more reliable results in comparison with the classical DEA models.

Original languageEnglish
Pages (from-to)5529-5567
Number of pages39
JournalOperational Research
Volume22
Issue number5
DOIs
Publication statusPublished - Nov 2022

Keywords

  • Data envelopment analysis
  • Dynamic efficiency
  • Panel data
  • Robust optimization
  • Stock exchange
  • Uncertainty
  • Window analysis

ASJC Scopus subject areas

  • Numerical Analysis
  • Modelling and Simulation
  • Strategy and Management
  • Statistics, Probability and Uncertainty
  • Management Science and Operations Research
  • Computational Theory and Mathematics
  • Management of Technology and Innovation

Cite this