Data Envelopment Analysis (DEA) is the most commonly used approach for evaluating healthcare efficiency (Hollingsworth, 2008), but a long-standing concern is that DEA assumes that data are measured without error. This is quite unlikely, and DEA and other efficiency analysis techniques may yield biased efficiency estimates if it is not realized (Gajewski, Lee, Bott, Piamjariyakul and Taunton, 20...

measuring the performance of a production system has been an important task in management for purposes of control, planning, etc. lord kelvin said :“when you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meager and unsatisfactory kind.” hence, manageme...

‎the purpose of this paper is to offer the equitable method for ranking decision making units(dmus) based on the dynamic data envelopment analysis (ddea) concept, where quasi-fixed inputs or intermediate products are the source of inter-temporal dependence between consecutive periods. in fact, this paper originally makes the use of an approach extending the ranking of dmus in dea by khodabakhsh...

This paper provides an application of Data Envelopment Analysis (DEA) to the measurement of the relative efficiency of highway maintenance operations within eight counties across the state of Virginia over the fiscal years 2003 to 2007. Selection of controllable and uncontrollable factors that are appropriate for the evaluation of efficiency performance is discussed. Regression Analysis, Analyt...

this paper processes a combined method, based on vikor and data envelopment analysis (dea) to select the units with most efficiency. we utilize the vikor as compromise solution method. this research is a two-stage model designed to fully rank the alternatives, where each alternative has multiple inputs and outputs. the problem involves belief parameters in the solution procedure. first, the alt...

the ahp/dea methodology is an integration of analytical hierarchical process (ahp) and data envelopment analysis. this method uses the capabilities of both ahp and dea. however, it has some problems: it illogically compares two decision-making units in a data envelopment analysis (dea) model, it is not compatible with dea ranking in the case of multiple inputs/multiple outputs, and it leads to ...

This paper is drawn from the use of Data Envelopment Analysis (DEA) in helping a Portuguese bank to manage the performance of its branches. The bank wanted to set targets for the branches on such variables as growth in number of clients, growth in funds deposited and so on. Such variables can take positive and negative values but traditional DEA models, with some specialised exceptions, have hi...

Literature of productive efficiency analysis is currently divided between two main paradigms: the parametric Stochastic Frontier Analysis (SFA) and the deterministic, nonparametric Data Envelopment Analysis (DEA). This paper develops a new encompassing framework that melds the SFA-style stochastic composite error term to the DEA-type nonparametric frontier that satisfies monotonicity and concav...

In the evaluation of non-efficient units by Data Envelopment Analysis (DEA) referenced Decision Making Units (DMU’s) have an important role. Unfortunately DMU’s with extra ordinary output can lead to a monopoly in a reference set, the fact called abnormality due to the outliers' data. In this paper, we introduce a DEA model for evaluating DMU’s under this circumstance. The layer model can resul...

The study was carried out to provide empirical evidence on technical efficiency of maize production in Nigeria using parametric and non-parametric approaches. The study employed annual secondary data on maize production in Nigeria from 1971 to 2010.Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA) were used to estimate the technical efficiency of maize production. The resul...