Potential-based efficiency assessment and target setting

Soltani, Narges; Lozano, Sebastián

doi:10.1016/j.cie.2018.10.013

Cited by 11 publications

(5 citation statements)

References 25 publications

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“…Khoshandam et al, (2014) and Shabani et al, (2015) proposed DEA models by considering non-discretionary factors. Soltani and Lozano, (2018) take into account the undesirable outputs, nondiscretionary variables, and preference structures. Galagedera, (2019) developed a DEA model to assess mutual fund performance in a multi-dimensional framework.…”

Section: Dea and Non-discretionary Factorsmentioning

confidence: 99%

A Modified-Range Directional Measure for Assessing the Sustainability of Suppliers by DEA/UTASTAR

Izadikhah

Saen

Ehsanifar

2022

Journal of Global Information Management

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Sustainability in the supply chain means considering environmental, social, and economic practices. Conventional data envelopment analysis (DEA) models deal with desirable, discretionary, and nonnegative data. However, there might be undesirable outputs, nondiscretionary factors, and negative data. On the other hand, some criteria can be considered as outputs and inputs. These factors are named as the dual-role criteria. The objective of this paper is to develop a non-radial DEA model for dealing with negative data in the presence of undesirable, non-discretionary, and dual-role factors in weight restrictions context. The ordinal regression method, UTASTAR, is performed to define priorities in terms of criteria. The capabilities of the proposed method are compared with other methods. A case study is presented in which the best sustainable suppliers of SAPCO are selected. To check the importance of dual-role variables, two extra cases are considered.

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Section: Dea and Non-discretionary Factorsmentioning

confidence: 99%

A Modified-Range Directional Measure for Assessing the Sustainability of Suppliers by DEA/UTASTAR

Izadikhah

Saen

Ehsanifar

2022

Journal of Global Information Management

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“…As it was discussed above, (17) ( 23) is a relaxed version of the MOLP presented by Hatami-Marbini et al [10] (see models ( 7) or (8) in that paper 260 and how we model the input and output constraints as inequalities). Precisely because the feasibility region of FFDEA is larger than that of Hatami-Marbini et al [10], it is necessary to add constraint (22). These authors did not have to impose that constraint because the lexicographic approach they used for solving their MOLP ensures that✓ p ⌧1.…”

Section: Proposed Ffdea Model and Associated Multiobjective Optimization Problemmentioning

confidence: 99%

“…The DEA methodology uses an optimization model to compute an e ciency 10 score and an e cient target for each DMU. There are di↵erent ways of carrying out the projection onto the e cient frontier and computing the corresponding e ciency scores, such as the radial e ciency approach ([3]), the multidirectional e ciency approach ( [16]) or the potential e ciency approach ( [22]), etc. These crisp DEA approaches require accurate measurement of both the inputs 15 and outputs.…”

Section: Introductionmentioning

confidence: 99%

Efficiencya Assessment and Target Setting Using a Fully Fuzzy DEA Approach

Arana‐Jiménez

Sánchez-Gil

Lozano

2020

Int. J. Fuzzy Syst.

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Data Envelopment Analysis (DEA) is a non-parametric methodology for eciency assessment. This paper proposes a new radial, input-oriented and fully fuzzy DEA approach, based on an LU-fuzzy partial order (L for lower, U for upper), for assessing the relative e ciency of a set of Decision Making Units (DMUs). The proposed approach involves a radial input contraction, Phase I, and an additive slacks maximization, Phase II. Each phase is first formulated as a fully fuzzy linear programming (FFLP), and then it is transformed into a multiobjective optimization problem. The latter is solved using the lexicographic weighted Tchebyche↵ method. The proposed fully fuzzy DEA approach provides, for each unit, a fuzzy e ciency measure and a fuzzy target operating point. A classification of the e ciency status of the units is also presented.Computational experiences and comparison with other fuzzy DEA approaches are reported.

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“…For comparison, the dataset was also solved using different DEA approaches, namely the slacksbased measure of efficiency (SBM) of Tone (2001), the range directional model (RDM) and MEA of Asmild and Pastor (2010), the largest improvement approach of Hampf and Krüger (2015) and the potential-based measure of efficiency (PBM) of Soltani and Lozano (2018). The corresponding targets are shown in Table 8.…”

Section: ==================== Table 7 ===================mentioning

confidence: 99%

A compromise programming approach for target setting in DEA

2019

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This paper presents a new Data Envelopment Analysis (DEA) target setting approach that uses the Compromise Programming (CP) method of multiobjective optimization. This method computes the ideal point associated to each Decision Making Unit (DMU) and determines an ambitious, efficient target that is as close as possible (using an lp metric) to that ideal point. The specific cases p=1, p=2 and p= are separately discussed and analyzed. In particular, for p=1 and p=, a lexicographic optimization approach is proposed in order to guarantee uniqueness of the obtained target. The original CP method is translation invariant and has been adapted so that the proposed CP-DEA is also units invariant. An lp metric-based efficiency score is also defined for each DMU. The proposed CP-DEA approach can also be utilized in the presence of preference information, non-discretionary or integer variables and undesirable outputs. The proposed approach has been extensively compared with other DEA approaches on a dataset from the literature.

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Potential-based efficiency assessment and target setting

Cited by 11 publications

References 25 publications

A Modified-Range Directional Measure for Assessing the Sustainability of Suppliers by DEA/UTASTAR

A Modified-Range Directional Measure for Assessing the Sustainability of Suppliers by DEA/UTASTAR

Efficiencya Assessment and Target Setting Using a Fully Fuzzy DEA Approach

A compromise programming approach for target setting in DEA

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