A resource allocation model (RAM) for not-for-profit organization in the framework of Data Envelopment Analysis (DEA) was introduced by Zhang and Cui ([1]). The model is an inverse formulation to the DEA model , as pointed in paper [2], and can be transformed into a parametric linear programming problem. Also a multi-objective programming problem was introduced in [2] to solve RAM when the effi...

In data mining applications, it is important to develop evaluation methods for selecting quality and profitable rules. This paper utilizes a non-parametric approach, Data Envelopment Analysis (DEA), to estimate and rank the efficiency of association rules with multiple criteria. The interestingness of association rules is conventionally measured based on support and confidence. For specific app...

the portfolio is a perfect combination of stock or assets, which an investor buys them. the objective of the portfolio is to divide the investment risk among several shares. using non-parametric dea and dea-r methods can be of great significance in estimating portfolio. in the present paper, the efficient portfolio is estimated by using non-radial dea and dea-r models. by proposing non-radial m...

As the efficiency measuring and analyzing is a crucial problem in modern enterprise management, this paper focuses on the problem of small and medium enterprise financing efficiency analyzing, and we proposed an improved DEA model based on stepwise regression to tackle this problem. Data envelopment analysis technology can calculate the efficiency of each decision making unit relative. Hence, D...

Data Envelopment Analysis (DEA) is a technique used to compare efficiency in various sectors such as hospitals, chain stores, and dealerships. It represents a set of linear programming techniques and uses deter-ministic data (inputs and outputs), in stable conditions. The DEA technique cannot be used when there is data with indeterministic nature, or when there is an environment with dynamic co...

Evaluation of efficiency of each of the DMUs (Decision Making Units) in a company is a very important task. Thus, the studies of evaluation of efficiency are being actively carried out, based on production function. Until quite recently, the loglinear production function (the Cobb-Douglas function) has been used for evaluation purposes. The loglinear model evaluates the DMUs by measuring the av...

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...

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...

This paper examines the Data Envelopment Analysis (DEA) methodology from a cognitive perspective. Specifically, it analyzes (a) the role of DEA scores as an overall efficiency measure and (b) to what extent the presence of DEA scores for a non-financial performance appraisal influences a posterior financial performance assessment. The study confirms that the efficiency score acts as a strong pe...

Data envelopment analysis (DEA) is a powerful tool for measuring the relative efficiencies of a set of decision making units (DMUs) such as schools and bank branches that transform multiple inputs to multiple outputs. In centralized decision-making systems, management normally imposes common resource constraints such as fixed capital, budgets for operating capital and staff count. In consequenc...