TY - JOUR
T1 - Concurrent estimation of efficiency, effectiveness and returns to scale
AU - Khodakarami, Mohsen
AU - Shabani, Amir
AU - Saen, Reza Farzipoor
N1 - Publisher Copyright:
© 2014 Taylor & Francis.
PY - 2016/4/3
Y1 - 2016/4/3
N2 - In recent years, data envelopment analysis (DEA) has been widely used to assess both efficiency and effectiveness. Accurate measurement of overall performance is a product of concurrent consideration of these measures. There are a couple of well-known methods to assess both efficiency and effectiveness. However, some issues can be found in previous methods. The issues include non-linearity problem, paradoxical improvement solutions, efficiency and effectiveness evaluation in two independent environments: dividing an operating unit into two autonomous departments for performance evaluation and problems associated with determining economies of scale. To overcome these issues, this paper aims to develop a series of linear DEA methods to estimate efficiency, effectiveness, and returns to scale of decision-making units (DMUs), simultaneously. This paper considers the departments of a DMU as a united entity to recommend consistent improvements. We first present a model under constant returns to scale (CRS) assumption, and examine its relationship with one of existing network DEA model. We then extend model under variable returns to scale (VRS) condition, and again its relationship with one of existing network DEA models is discussed. Next, we introduce a new integrated two-stage additive model. Finally, an in-depth analysis of returns to scale is provided. A case study demonstrates applicability of the proposed models.
AB - In recent years, data envelopment analysis (DEA) has been widely used to assess both efficiency and effectiveness. Accurate measurement of overall performance is a product of concurrent consideration of these measures. There are a couple of well-known methods to assess both efficiency and effectiveness. However, some issues can be found in previous methods. The issues include non-linearity problem, paradoxical improvement solutions, efficiency and effectiveness evaluation in two independent environments: dividing an operating unit into two autonomous departments for performance evaluation and problems associated with determining economies of scale. To overcome these issues, this paper aims to develop a series of linear DEA methods to estimate efficiency, effectiveness, and returns to scale of decision-making units (DMUs), simultaneously. This paper considers the departments of a DMU as a united entity to recommend consistent improvements. We first present a model under constant returns to scale (CRS) assumption, and examine its relationship with one of existing network DEA model. We then extend model under variable returns to scale (VRS) condition, and again its relationship with one of existing network DEA models is discussed. Next, we introduce a new integrated two-stage additive model. Finally, an in-depth analysis of returns to scale is provided. A case study demonstrates applicability of the proposed models.
KW - integrated two-stage DEA
KW - network data envelopment analysis
KW - returns to scale
KW - service effectiveness
KW - technical effectiveness
KW - technical efficiency
UR - http://www.scopus.com/inward/record.url?scp=84995355521&partnerID=8YFLogxK
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U2 - 10.1080/00207721.2014.919073
DO - 10.1080/00207721.2014.919073
M3 - Article
AN - SCOPUS:84995355521
SN - 0020-7721
VL - 47
SP - 1202
EP - 1220
JO - International Journal of Systems Science
JF - International Journal of Systems Science
IS - 5
ER -