Purpose The purpose of this paper is to provide an outline of the major contributions in the
literature on the determination of the least distance in data envelopment analysis (DEA). The …

Classifying decision-making units into efficient and inefficient classes is a common
procedure in nonparametric data envelopment analysis approach. The inefficient units can …

Nowadays, appraisal of performance, benchmark identification and determining policies for
the survival of the organization is of interest to managers. Data Envelopment Analysis is a …

In for-profit organizations, profit efficiency decomposition is considered important since
estimates on profit drivers are of practical use to managers in their decision making. Profit …

This paper proposes a new method to measure productivity change of decision making units
in the full input-output space. The new approach is based on the calculation of the least …

This paper proposes a new method to measure economic inefficiency of decision making
units based on the calculation of the least distance to the Pareto-efficient frontier in data …

This chapter examines the process of benchmarking in healthcare. In particular, we focus on
hospital performance. We are especially interested in showing that the determination of …

Data envelopment analysis (DEA) is a technique to evaluate the relative performance of a
set of decision-making units (DMUs). Corresponding to each inefficient DMU, an efficient …

Data envelopment analysis (DEA), firstly, checks whether decision making units (DMUs) are
efficient or inefficient and then it introduces a benchmark for inefficient DMUs. This …

تحلیل پوششی داده‎ ها، تکنیکی برای محاسبه کارایی نسبی مجموعه ای از واحدهای تصمیم گیری
(DMUs) است. در این تکنیک ناکارآیی واحدهای تصمیم‎ گیری را می‎ توان با افزایش سطح خروجی‎ ها …‎