The purpose of this study was to emphasize that the Data Envelopment Analysis (DEA) method is an important benchmarking tool which provides necessary information for improving business performance. To fulfil abovementioned goal, we used a sample 48 Slovak companies involved in field heat supply. As their position economic and social environment country essential, considerable attention should b...

One of the primary concerns on target setting the electricity distribution companies is the uncertainty on input/output data. In this paper, an interactive robust data envelopment analysis (IRDEA) model is proposed to determine the input and output target values of electricity distribution companies with considering the existence perturbation in data. Target setting is implemented with the unce...

In the course of improving various abilities of data envelopment analysis (DEA) models, many investigations have been carried out for ranking decision-making units (DMUs). This is an important issue both in theory and practice. There exist a variety of papers which apply different ranking methods to a real data set. Here the ranking methods are divided into seven groups. As each of the existing...

A typical use and interpretation of data envelopment analysis (DEA) targets is to identify performance goals that if achieved will project an inefficient decision making unit onto the efficiency frontier. This will occur, however, only if all other units maintain their same input and output levels, which is rarely the case over time. This paper investigates alternate approaches for interpreting...

Previous work from our lab, and elsewhere, has demonstrated that remembered target locations are stored and updated in an eye-fixed reference frame. That is, reach errors systematically vary as a function of gaze direction relative to a remembered target location, not only when the target is viewed in the periphery (Bock, 1986, known as the retinal magnification effect), but also when the targe...

Keywords: Data envelopment analysis Target unit Undesirable output Multiple objective linear programming Minimax method a b s t r a c t Data Envelopment Analysis (DEA) is a mathematical programming technique for identifying efficient Decision Making Units (DMUs) with multiple inputs and multiple outputs. DEA provides a technical efficiency score for each DMU, a technical efficiency reference se...

A widely publicized series of mergers has characterized the banking industry in recent years. Shareholder returns from these mergers have often been disappointing. This study finds delays in implementing potential operating savings and realizing benefits of scale economies may be one reason bank mergers have disappointing returns. We analyze a 200 branch network formed in a merger of four banks...

It is well established that multiple reference sets may occur for a decision making unit (DMU) in the non-radial DEA (data envelopment analysis) setting. As our first contribution, we differentiate between three types of reference set. First, we introduce the notion of unary reference set (URS) corresponding to a given projection of an evaluated DMU. The URS includes efficient DMUs that are act...

Learning from high performance projects is crucial for software process improvement. Therefore, we need to identify outstanding projects that may serve as role models. It is common to measure productivity as an indicator of performance. It is vital that productivity measurements deal correctly with variable returns to scale and multivariate data. Software projects generally exhibit variable ret...