Periodic efficiency measurement for achieving correct efficiency among several terms of evaluation

Lotfı, Farhad Hosseinzadeh; Jahanshahloo, G. R.; Vaez-Ghasemi, Mohsen; Moghaddas, Zohreh

doi:10.1504/ijor.2013.055530

Cited by 5 publications

(3 citation statements)

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“…DMU 2 fluctuates at first but increases gradually. DMU 9 changes in interval [1,6]. DMU 6 progress is higher than DMU 5 and less than DMU 1 and DMU 4 .…”

Section: Applicationmentioning

confidence: 93%

“…In the modern managements, several applied scientific methods have been developed to improve the quality of systems. Data Envelopment Analysis (DEA) is one of the most suitable and applicable methods to evaluate and compare several units or a unit in various times [1][2][3]. By using this scientific technique, the system manager is in the position to find and apply the best decision for improving that system [4,5].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Progress and Regress of Time Dependent Data and Application in Bank Branch

Lotfı

Taeb

Abbasbandy

2014

Journal of Applied Mathematics

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To evaluate each decision making unit having time dependent inputs and outputs data, a new method has been developed and reported here. This method uses the Malmquist productivity index, and is a very simple function based on Cubic Spline function to determine the progress and regress of that unit. To show the capability of this developed method, the data of 9 branches of a commercial bank has been used, evaluated, and reported.

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“…DMU 2 fluctuates at first but increases gradually. DMU 9 changes in interval [1,6]. DMU 6 progress is higher than DMU 5 and less than DMU 1 and DMU 4 .…”

Section: Applicationmentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Progress and Regress of Time Dependent Data and Application in Bank Branch

Lotfı

Taeb

Abbasbandy

2014

Journal of Applied Mathematics

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“…To answer these questions, Hosseinzadeh et al [14] introduced the periodic efficiency (PE) model, which considers the data of different periods simultaneously for the evaluation. Building on the PE model, this paper aims to bring more plausible answers to the aforementioned questions through a global multi-period approach.…”

Section: Global Multi-period Dea Modelmentioning

confidence: 99%

Global multi-period performance evaluation – New model and productivity index

2022

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In this paper, we develop a new mathematical model for the multi-period data envelopment analysis (MDEA) problem that attempts to circumvent the limitations of the existing MDEA models through a global approach. The proposed global MDEA model is based on modifications of some DEA axioms, enabling a decision making unit (DMU), defined with inputs and outputs of period $t,$ to be evaluated within the production possibility set (PPS) of another period $l,~t\neq l.$ Building on the properties of the global MDEA model, we also introduce the Global Progress and Regress index (GPRI) to evaluate the extent of progress or regress of a DMU over multi-period time horizons under variable returns to scale (VRS) assumption, as opposed to known productivity indices that are restricted to two successive periods and constant returns to scale (CRS) production technologies. The most salient features of the new MDEA model as well as the GPRI are highlighted using an application that involves a real-life sample of 25 bank branches considered over 4 years.

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