This paper uses both the non-parametric method of Data Envelopment Analysis (DEA) and the econometric method of Stochastic Frontier Analysis (SFA) to study the production technology and cost efficiency of the U.S. dental care industry using practice level data. The American Dental Association (ADA) 2006 survey data for a number of general dental practices in Colorado are used for the empirical ...

Airport efficiency is an area of increasing interest to academics, policy makers and practitioners. This has resulted in a body of literature applying various econometric techniques to compare efficiency between different samples of airports. This paper uses the multi-criteria decision making method Analytic Hierarchy Process (AHP) to incorporate the weightings of input and output variables int...

Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision-making units (DMUs) that use multiple inputs to produce multiple outputs. The standard DEA models assume that all inputs and outputs are crisp and can be changed at the discretion of management. While crisp input and output data are fundamentally indispensable in the standard DEA evalua...

Airport efficiency is an area of increasing interest to academics, policy makers and practitioners. This has resulted in a body of literature applying various econometric techniques to compare efficiency between different samples of airports. This paper uses the multi-criteria decision making method Analytic Hierarchy Process (AHP) to incorporate the weightings of input and output variables int...

In this paper, we have developed a heuristic that uses Data Envelopment Analysis (DEA) to rank Decision Making Units (DMUs) with fuzzy input and output values in the order of their probable efficiency. The heuristic is designed to be used with the raw samples of the fuzzy data, and does not require knowledge of the fuzzy data’s probability distribution. It is meant to be a simple method of diff...

Some indexes are necessary for performance evaluation of a management system. Balanced scorecard (BSC) is used in order to extraction of these indexes for evaluating the necessary performances in the evaluation process. Utilization of BSC causes to prevent in increasing information and data. Furthermore, all of the important indexes are considered in evaluation performance.Data envelopment anal...

Supplier evaluation and selection, an important element in supplier-based manufacturing and supply chain management has been gaining attention in both academic literature and industrial practice. In this paper, we presented a modified data envelopment analysis (DEA) method for supplier selection which can operate under conditions of imprecise information. A brief description of the importance o...

There are some specific features of the non-radial DEA (data envelopment analysis) models which cause some problems under the returns to scale measurement. In the scientific literature on DEA, some methods were suggested to deal with the returns to scale measurement in the non-radial DEA models. These methods are based on using Strong Complementary Slackness Conditions in the optimization theor...

one of the difficulties of data envelopment analysis(dea) is the problem of deciency discriminationamong efficient decision making units(dmus) and hence, yielding large number of dmus as efficientones. the main purpose of this paper is to overcome this inability. one of the methods for rankingefficient dmus is minimizing the coefficient of variation (cv) for inputs-outputs weights. in this pap...

in the use of peer group data to assess individual, typical or best practice performance, the effective detection of outliers is critical for achieving useful results. in these ‘‘deterministic’’ frontier models, statistical theory is now mostly available. this paper deals with the statistical pared sample method and its capability of detecting outliers in data envelopment analysis. in the prese...