EconPapers    
Economics at your fingertips  
 

A dynamic multi-stage data envelopment analysis model with application to energy consumption in the cotton industry

Kaveh Khalili-Damghani, Madjid Tavana, Francisco J. Santos-Arteaga and Sima Mohtasham

Energy Economics, 2015, vol. 51, issue C, 320-328

Abstract: 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.

Keywords: Data envelopment analysis; Dynamic; Multi-stage; Farm efficiency; Energy planning (search for similar items in EconPapers)
JEL-codes: C02 C44 C61 C67 Q12 Q4 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0140988315002169
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:51:y:2015:i:c:p:320-328

DOI: 10.1016/j.eneco.2015.06.020

Access Statistics for this article

Energy Economics is currently edited by R. S. J. Tol, Beng Ang, Lance Bachmeier, Perry Sadorsky, Ugur Soytas and J. P. Weyant

More articles in Energy Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:eneeco:v:51:y:2015:i:c:p:320-328