Problem statement: Data Envelopment Analysis (DEA) is a non-parametric technique for measuring the relative efficiency of a set of production systems or Decision Making Units (DMU) that have multiple inputs and outputs. Sometimes, DMUs have a parallel structure, in which systems composed of parallel units work individually; the sum of their own inputs/outputs is the input/output of the system. ...

In this research we employ data envelopment analysis (DEA) to measure the Malmquist productivity of semiconductor packaging and testing firms in Taiwan from 2000 to 2003. Malmquist productivity has three components: the measurement of technical change, the measurement of the frontier forward shift, and the measurement of the frontier backward shift of a company over two consecutive periods. Thi...

In this paper, a Network DEA approach to assess the efficiency of NBA teams is proposed and compared with a black-box (i.e. single-process) DEA approach. Both approaches use a Slack-Based Measure of efficiency (SBM) to evaluate the potential reduction of inputs consumed (team budget) and outputs produced (games won by the team). The study considers the distribution of the budget between first-t...

An original data envelopment analysis (DEA) model is to evaluate each decision-making unit (DMU) with a set of most favorable weights of performance indices. The efficient DMUs obtained from the original DEA construct an efficient (bestpractice) frontier. The original DEA can be considered to identify good (efficient) performers in the most favorable scenario. For the purpose of identifying bad...

Data envelopment analysis (DEA) is a non-parametric method for measuring the efficiency of a set of decision making units (DMUs), such as companies or public sector agencies. The main DEA models are only used for positive data. In recent years, some models have been presented to deal with negative data in DEA models. However, these models do not discriminate between efficient DMUs and only eval...

Recently, in Data Envelopment Analysis (DEA) methodology, there are two type of efficiency measurement; radial and non-radial measure represented by the CharnesCooper-Rhodes (CCR) and the slack-based measure (SBM) model respectively. There are two characteristics to the target in oriented CCR model; the input minimization (output maximization) plus any further reduction (expansion) indicated by...

In this paper, a new three-stage virtual frontier SBM-DEA (Slacks-Based Measure of Efficiency in Data Envelopment Analysis) model is proposed to evaluate the sustainable efficiency construction industry. The relevant industry data 30 Chinese PARs (provincial administrative regions) from 2011 2016 are brought into calculate each region and verify rationality model. order solve problem that value...

A new approach or model to the dynamic DEA, referred to as the adjusted dynamic DEA, is proposed in this study. Adjusted dynamic DEA optimizes the production activity of DMUs by introducing adjustment variables to modify the interconnecting activities between consecutive terms, solving conflicts that arise between terms and between management and shareholders. The non-oriented SBM model is used...

In this paper a model for fuzzy SBM of efficiency in DEA is presented based on a-cuts of the fuzzy number parameters to convert fuzzy linear programming problem to an interval programming problem. Then, by introducing a variable in each of the obtained intervals and applying suitable substitutions, a linear programming problem would be achieved. To demonstrate the concept, numerical examples ar...