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...

banks are one of the most important financial sectors in order to the economic development of each country. certainly, efficiency scores and ranks of banks are significant and effective aspects towards future planning. sometimes the performance of banks must be measured in the presence of undesirable and vague factors. for these reasons in the current paper a procedure based on data envelopment...

In this article, I propose a hybrid data envelopment analysis (DEA) system that utilizes a methodology combining the tier analysis with the neural clustering method. I aim to show that the hybrid system can be used to evaluate the inter-organizational efficiency in the life insurance companies. The application is unfolded in two phases. In the first phase, DEA is repetitively used to evaluate t...

Data envelopment analysis (DEA) has been utilized worldwide for measuring efficiencies of banks, telecommunications, electric utilities and so forth. Yet, the existing models have some well known shortcomings that limit their usefulness. In DEA we have two fundamental approaches to measuring efficiency with very different characteristics; radial and non-radial. We demonstrate a method for linki...

Article history: Received 5 January 2014 Received in revised format 8 March 2014 Accepted 11 March 2014 Available online 12 March 2014 Measuring the relative efficiency of banking industry has been a popular subject among both practitioners and academicians. Data envelopment analysis (DEA) has been widely applied for different purposes. This paper presents an empirical investigation to measure ...

The existing data envelopment analysis (DEA) models for measuring the relative efficiencies of a set of decision making units (DMUs) using various inputs to produce various outputs are limited to crisp data. The notion of fuzziness has been introduced to deal with imprecise data. Fuzzy DEA models are made more powerful for applications. This paper develops the measure of efficiencies in input o...

Data envelopment analysis (DEA) is a method frequently used to evaluate relative firm performance. However, high values in a few indicators can lead to a company being regarded as ‘efficient’, despite valuing poorly in other essential indicators. The Inefficiency Countervailed DEA (IC-DEA) method is thus developed. The method first defines an inefficient frontier using the proposed Reverse DEA ...

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...

Data Envelopment Analysis (DEA) is one of the most widely used methods in the measurement efficiency and productivity of Decision Making Units (DMUs). DEA for a large dataset with many inputs/outputs would require huge computer resources in terms of memory and CPU time. This paper introduces a neural network backpropagation Data Envelopment Analysis. Neural network requirements of computer memo...