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

Pejman Peykani (), Jafar Gheidar-Kheljani (), Reza Farzipoor Saen () and Emran Mohammadi ()
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Pejman Peykani: Iran University of Science and Technology
Jafar Gheidar-Kheljani: Malek Ashtar University of Technology
Reza Farzipoor Saen: Sultan Qaboos University
Emran Mohammadi: Iran University of Science and Technology

Operational Research, 2022, vol. 22, issue 5, No 26, 5529-5567

Abstract: 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.

Keywords: Dynamic efficiency; Data envelopment analysis; Window analysis; Uncertainty; Robust optimization; Panel data; Stock exchange (search for similar items in EconPapers)
JEL-codes: C02 C14 C61 C67 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s12351-022-00729-7

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