A bootstrap data envelopment analysis model with stochastic reducible outputs and expandable inputs: an application to power plants
Yükleniyor...
Dosyalar
Tarih
2024
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
EDP Sciences
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Clean production of electricity is not only cost-effective but also effective in reducing pollutants. Toward this end, the use of clean fuels is strongly recommended by environmentalists. Benchmarking techniques, especially data envelopment analysis, are an appropriate tool for measuring the relative efficiency of firms with environmental pollutants. In classic data envelopment analysis models, decision-makers are faced with production processes in which reducible inputs are used to produce expandable outputs. In this contribution, we consider production processes when the input and output data are given in stochastic form and some throughputs are reducible and some others are expandable. A stochastic directional distance function model is proposed to calculate the relative technical efficiency of firms. In order to evaluate firm-specific technical efficiency, we apply bootstrap DEA. We first calculate the technical efficiency scores of firms using the classic DEA model. Then, the double bootstrap DEA model is applied to determine the impact of explanatory variables on firm efficiency. To demonstrate the applicability of the procedure, we present an empirical application wherein we employ power plants. © 2024 The authors. Published by EDP Sciences, ROADEF, SMAI 2024.
Açıklama
Anahtar Kelimeler
Double Bootstrap, Pollutants, Power Plant, Stochastic DEA, Technical Efficiency, Undesirable Outputs
Kaynak
RAIRO - Operations Research
WoS Q Değeri
Q3
Scopus Q Değeri
N/A
Cilt
58
Sayı
4
Künye
Amirteimoori, A., Allahviranloo, T., & Cezar, A. (2024). A bootstrap data envelopment analysis model with stochastic reducible outputs and expandable inputs: an application to power plants. RAIRO-Operations Research, 58(4), 3189-3202.
