RT Journal Article
T1 A dynamic multi-stage data envelopment analysis model with application to energy consumption in the cotton industry
A1 Khalili-Damghani, Kaveh
A1 Tavana, Madjid
A1 Mohtasham, Sima
A1 Santos Arteaga, Francisco Javier
AB Data envelopment analysis (DEA) is a non-parametric method for evaluating the relative efficiency of homogenous decision making units (DMUs) with multiple inputs and outputs. In this paper, we present a dynamic multi-stage DEA (DMS-DEA) approach to evaluate the efficiency of cotton production energy consumption. In the proposed model, the farms which consume resources (i.e., fertilizers, seeds, and pesticides) to produce cotton are assumed to be the DMUs. Inputs not consumed during a planning period are carried over to the next period in the planning horizon. Initially, a DMS-DEA model is used to determine the overall efficiency of the DMUs with dynamic inputs. Next, the efficiency score of each DMU is calculated for each time period in the planning horizon. We demonstrate the applicability of the proposed method and exhibit the efficacy of the procedures and algorithms with a real-life case study of energy consumption in the cotton industry.
PB Elsevier
SN 0140-9883
YR 2015
FD 2015-09-01
LK https://hdl.handle.net/20.500.14352/126502
UL https://hdl.handle.net/20.500.14352/126502
LA eng
NO Kaveh Khalili-Damghani, Madjid Tavana, Francisco J. Santos-Arteaga, Sima Mohtasham, A dynamic multi-stage data envelopment analysis model with application to energy consumption in the cotton industry, Energy Economics, Volume 51, 2015, Pages 320-328, ISSN 0140-9883, https://doi.org/10.1016/j.eneco.2015.06.020.
DS Docta Complutense
RD 26 mar 2026