This paper reviews the literature on the ranking of data envelopment analysis (DEA) in order
to increase the discrimination power of this analytical technique. The methods covered by …

In recent years there has been an exponential growth in the number of publications related
to theory and applications of Data Envelopment Analysis (DEA). Charnes, Cooper, and …

The market trends rapidly changed over the last two decades. The primary reason is the
newly created opportunities and the increased number of competitors competing to grasp …

In today's competitive environment, measuring companies' performance properly has
become a vital subject not only for investors but also for the companies that are working in …

At present, association rules have been widely used in prediction, personalized
recommendation, risk analysis and other fields. However, it has been pointed out that the …

Data envelopment analysis (DEA) is a methodology that uses multiple inputs and outputs for
measuring the efficiencies of a set of decision making units (DMUs). When data are crisp …

Abstract Data Envelopment Analysis (DEA) is a powerful tool for measuring the relative
efficiency for a set of Decision Making Units (DMUs) that transform multiple inputs into …

This paper suggests a novel method to deal with target setting in mergers using goal
programming (GP) and inverse data envelopment analysis (InvDEA). A conventional DEA …

Data envelopment analysis (DEA) has been a very popular method for measuring and
benchmarking relative efficiency of each decision making units (DMUs) with multiple inputs …

Data envelopment analysis seeks a frontier to envelop all data with data acting in a critical
role in the process and in such a way measures the relative efficiency of each decision …