Measuring the efficiency of decision making units

The performances of decision-making units (DMUs) can be measured from two different points of view: optimistic or pessimistic, which leads to two different efficiencies for each DMU: the best relative efficiency and the worst relative efficiency.…

This paper is concerned with the comparison of two popular non-parametric methodologies-data envelopment analysis and artificial neural networks-as tools for assessing performance. Data envelopment analysis has been established since 1978 as a…

Generally, data mining is the process of analyzing data from different viewpoint and summarizing it into valuable information. This area presents new theories and methods for processing large volumes of data and has obtained noteworthy consideration…

Data Envelopment Analysis (DEA) is a nonparametric method for measuring the efficiency of a set of decision making units such as firms or public sector agencies, first introduced into the operational research and management science literature by…

In contrast to parametric approaches which try to optimize a single regression function through the observed data set, DEA optimizes on each individual observation with a objective of calculating a discrete piece-wise linear frontier. In the…

This paper discusses the problem of evaluating the efficiency of a set of interdependent Decision Making Sub-units (DMSUs) that make up a large Decision Making Unit (DMU). The DMSUs are interdependent in the sense that some outputs produced by each…

We employ Data Envelopment Analysis to compute the technical efficiency of Italian and English higher education institutions. Our results show that, in relation to the country-specific frontier, institutions in both countries are typically very…

In models of data envelopment analysis (DEA), an optimal set of input and output weights is generally assumed to represent the assessed decision making unit (DMU) in the best light in comparison to all the other DMUs. The paper shows that this may…

The concept of a "production function" as means to measuring efficiency began in 1928 with the seminal paper by Cobb and Douglas (1928). However, until the 1950s, production functions were largely used as a tool for studying the functional…

In this paper, we introduce a generalized Data Envelopment Analysis (DEA) model which unifies and extends most of the well-known DEA models developed over the past fifteen years and points the way to new models. By setting three binary parameters of…