[HTML][HTML] A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016
A Emrouznejad, G Yang - Socio-economic planning sciences, 2018 - Elsevier
In recent years there has been an exponential growth in the number of publications related
to theory and applications of Data Envelopment Analysis (DEA). Charnes, Cooper, and …
to theory and applications of Data Envelopment Analysis (DEA). Charnes, Cooper, and …
Green sourcing in the era of industry 4.0: towards green and digitalized competitive advantages
Purpose In the last decade, sustainable sourcing decision has gained tremendous attention
due to the increasing governmental restrictions and public attentiveness. This decision …
due to the increasing governmental restrictions and public attentiveness. This decision …
An integrated model for green supplier selection under fuzzy environment: application of data envelopment analysis and genetic programming approach
Supplier evaluation plays a critical role in a successful supply chain management. Hence,
the evaluation and selection of the right suppliers have become a central decision of …
the evaluation and selection of the right suppliers have become a central decision of …
Modelling environmental energy efficiency in the presence of carbon emissions: Modified oriented efficiency measures under polluting technology of data …
M Taleb - Journal of cleaner production, 2023 - Elsevier
Reductions of carbon dioxide (CO 2) emissions and energy consumption are two vital
methods contributing in improvement of the environmental energy efficiency. Since data …
methods contributing in improvement of the environmental energy efficiency. Since data …
A range adjusted measure of super-efficiency in integer-valued data envelopment analysis with undesirable outputs
C Chen, H Liu, L Tang, J Ren - Journal of Systems Science and …, 2021 - degruyter.com
DEA (data envelopment analysis) models can be divided into two groups: Radial DEA and
non-radial DEA, and the latter has higher discriminatory power than the former. The range …
non-radial DEA, and the latter has higher discriminatory power than the former. The range …
An integrated bi-objective data envelopment analysis model for measuring returns to scale
Classical efficiency studies on data envelopment analysis (DEA) consider all its inputs and
outputs are desirable factors and real valued-data. Additionally, the DEA models only focus …
outputs are desirable factors and real valued-data. Additionally, the DEA models only focus …
A mixed-integer slacks-based measure data envelopment analysis for efficiency measuring of German university hospitals
M Zarrin - Health care management science, 2023 - Springer
Abstract Standard Data Envelopment Analysis (DEA) models consider continuous-valued
and known input and output statuses for measures. This paper proposes an extended …
and known input and output statuses for measures. This paper proposes an extended …
Efficiency measurement of DMUs with undesirable outputs under uncertainty based on the directional distance function: Application on bank industry
N Aghayi, B Maleki - Energy, 2016 - Elsevier
We employ a method that incorporates both direct and indirect approaches based on a
directional distance function. In the proposed model, which is based on constant returns to …
directional distance function. In the proposed model, which is based on constant returns to …
Robust two-stage DEA models under discrete uncertain data
M Esfandiari, A Hafezalkotob… - International Journal …, 2017 - Taylor & Francis
Data envelopment analysis (DEA) is a well-known non-parametric technique for evaluating
the relative efficiency of decision-making units (DMUs). One of the most important issues …
the relative efficiency of decision-making units (DMUs). One of the most important issues …
Robust efficiency measurement with common set of weights under varying degrees of conservatism and data uncertainty
The conventional paradigm in data envelopment analysis (DEA) is to develop an efficiency
measurement model that assumes the input and output data are precise and equal to some …
measurement model that assumes the input and output data are precise and equal to some …