In data envelopment analyze (DEA) the scale efficiency in the input-oriented CCR model is less than or equal to the scale efficiency in DEA based on the fractional analysis (DEA-R). Also, the scale efficiency in case of multiple inputs and one output and vice versa the scale efficiencies are equal in DEA and DEA-R. In this paper, first, DEA-R model with weight restrictions when there is relativ...

Data envelopment analysis (DEA) is a well-Known method in efficiency evaluation of a set of decision making units (DMUs) such as organizations and banks. An advantage of DEA technique is selection of weights at random. Weight selection is of crucial importance in efficiency evaluation. In this regard, it is important to employ models that have more freedom in selecting weights. One such model i...

In many organizations and financial institutions, we don't always have acsses to inputs and outputs to evaluate the decision-making units (DMUs), but rather only a ratio of inputs to outputs ( or reverse) might be available. In DEA, cost efficiency determines input standards based on input costs. In multi-stage network DEA processes, in addition to input standards, cost efficiency would determi...

This study analyzes the efficiency of small and medium-sized enterprises (SMEs) of a national technology innovation research and development (R&D) program. In particular, an empirical analysis is presented that aims to answer the following question: "Is there a difference in the efficiency between R&D collaboration types and between government R&D subsidy sizes?" Methodologically, the efficienc...

Data envelopment analysis (DEA) is a representative method to estimate efficient frontiers and derive efficiency. However, in a situation with weight restrictions on individual input–output pairs, its suitability has been questioned. Therefore, the main purpose of this paper is to develop a mathematical method, which we call the input-oriented ratio-based comparative efficiency model, DEA-R-I, ...

Data envelopment analysis (DEA), based on mathematical programming techniques, is a popular method for assessing the relative efficiency of various decision-making units (DMUs). Efficient DEA computations need to circumvent intensive time-consuming calculations. This paper indicates that the “corner points” in single input and single output scatter plot has extreme efficiency with regard to the...

The computer industry plays an important role in promoting the development of national economy and national comprehensive power of China. As an important evaluation indicator, the R&D efficiency of computer industry becomes one of the most important research fields currently. According to the shortages of traditional C2R model of DEA, this paper constructs an improved DEA model for measuring th...

Because of the unreasonable and unnecessary weight restriction assumption, a barely noticeable deficiency in pseudo-inefficiency occurs at times when applying a CCR model. The CCR was the first model designed for Data Envelopment Analysis (DEA); it remains its most popular model. To detect this type of unobvious deficiency, this study compared the following: the efficiency score and optimal wei...

Halme, Joro, Korhonen, Salo and Wallenius [1998] present an approach for using preference information in Data Envelopment Analysis (DEA). In their paper, they develop value efficiency, an extension of the concept of efficiency in DEA. In this paper, we develop some related concepts, and present two refinements: 1. Some bounds on the value efficiency scores that may be obtained without any decis...

The conventional data envelopment analysis (DEA) measures the relative efficiencies of a set of decision making units (DMUs) with exact value of inputs and outputs. For imprecise data, i.e., mixtures of interval data and ordinal data, some methods have been developed to calculate the interval of the efficiency scores. This paper constructs a procedure to measure the efficiencies of DMUs with mi...