Inefficiency Evaluation With an Additive Dea Model Under Imprecise Data, an Application on Iauk Departments

Matin, Reza Kazemi; Jahanshahloo, G. R.; Hadi-Vencheh, A.

doi:10.15807/jorsj.50.163

Cited by 4 publications

(4 citation statements)

References 17 publications

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“…The RADD model (16) can be compared to the imprecise additive models developed in Lee et al (2002) and Matin et al (2007). Consider the numerical example given in Cooper et al (1999) and presented in Table 3.…”

Section: Extension To the Additive Dea Model And Imprecise Datamentioning

confidence: 99%

“…The result of the retrieved exact data is given in Table 4. From this data, we compare the result of the RADD model with the two-stage imprecise additive model of Lee et al (2002) and the onestage imprecise additive model of Matin et al (2007). Table 5 presents the inefficiency of DMUs proposed by the different methods.…”

Section: Extension To the Additive Dea Model And Imprecise Datamentioning

confidence: 99%

“…The scheme allows DMUs to be classified into fully robust efficient, partially robust efficient and robust inefficient. We further extend our robust approach to the non-radial additive model where a newly proposed robust additive model is compared with peer imprecise additive models proposed in Lee et al (2002) and Matin et al (2007).…”

Section: Introductionmentioning

confidence: 99%

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Robust data envelopment analysis via ellipsoidal uncertainty sets with application to the Italian banking industry

Mensah

2020

Decisions Econ Finan

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This paper extends the conventional DEA models to a robust DEA (RDEA) framework by proposing new models for evaluating the efficiency of a set of homogeneous decision-making units (DMUs) under ellipsoidal uncertainty sets. Four main contributions are made: (1) we propose new RDEA models based on two uncertainty sets: an ellipsoidal set that models unbounded and correlated uncertainties and an interval-based ellipsoidal uncertainty set that models bounded and correlated uncertainties, and study the relationship between the RDEA models of these two sets, (2) we provide a robust classification scheme where DMUs can be classified into fully robust efficient, partially robust efficient and robust inefficient, (3) the proposed models are extended to the additive DEA model and its efficacy is analyzed with two imprecise additive DEA models in the literature, and finally, (4) we apply the proposed models to study the performance of banks in the Italian banking industry. We show that few banks which were resilient in their performance can be robustly classified as partially efficient or fully efficient in an uncertain environment.

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Section: Extension To the Additive Dea Model And Imprecise Datamentioning

confidence: 99%

Section: Extension To the Additive Dea Model And Imprecise Datamentioning

confidence: 99%

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Robust data envelopment analysis via ellipsoidal uncertainty sets with application to the Italian banking industry

Mensah

2020

Decisions Econ Finan

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“…Park (2007) shows two distinct strategies to arrive at an upper and lower bound of efficiency that the evaluated DMU can have within the given imprecise data. Matin et al (2007) employ an additive DEA model to evaluate the technical inefficiency of DMUs under imprecise data. The non-linear DEA model is transformed into an equivalent linear one, then the translation invariant property is used and a one-stage approach is introduced in this inefficiency evaluation.…”

Section: Imprecise Datamentioning

confidence: 99%

Media selection in the presence of flexible factors and imprecise data

Saen

2011

Journal of the Operational Research Society

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A combination of QFD and imprecise DEA with enhanced Russell graph measure: A case study in healthcare

Azadi

Saen

2013

Socio-Economic Planning Sciences

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Inefficiency Evaluation With an Additive Dea Model Under Imprecise Data, an Application on Iauk Departments

Cited by 4 publications

References 17 publications

Robust data envelopment analysis via ellipsoidal uncertainty sets with application to the Italian banking industry

Robust data envelopment analysis via ellipsoidal uncertainty sets with application to the Italian banking industry

Media selection in the presence of flexible factors and imprecise data

A combination of QFD and imprecise DEA with enhanced Russell graph measure: A case study in healthcare

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