Data envelopment analysis (DEA) is a non-parametric mathematical programming methodology used to not only evaluate the relative efficiencies of comparable decision making units (DMUs) with multiple inputs and outputs, but also provide efficiency targets for the DMUs. For a visualization of this method, see Figure 1. Since the incept of Charnes, Cooper and Rhodes (1978), DEA has gained increasin...

Applications of data envelopment analysis often incorporate inputs and outputs stated as proportions or percentages, which are typically used to represent socio-economic quality characteristics the production process. As is well known, use such ratio measures inconsistent with assumption convexity required by conventional variable constant returns-to-scale (VRS CRS) technologies, additional sca...

In this paper, a method is proposed to calculate a comprehensive index that calculates the ecological efficiency of a city by combining together the measurements provided by some Data Envelopment Analysis (DEA) cross-efficiency models using the Shannon’s entropy index. The DEA models include non-discretionary uncontrollable inputs, desirable and undesirable outputs. The method is implemented to...

The effects of government R&D subsidies can vary across recipient firms, depending on the various characteristics a firm, potentially including firm's accounting information quality (AIQ). It has been well recognized that high AIQ helps to reduce asymmetry between investors and firms and, consequently, improves investment efficiency. However, there is lack clear understanding about specific rol...

This paper proposes an alternative approach for efficiency analysis when a set of DMUs uses interval scale variables in the productive process. To test the influence of these variables, we present a general approach of deriving DEA models to deal with the variables. We investigate a number of performance measures with unrestricted-in-sign interval and/or interval scale variables.

In traditional data envelopment analysis (DEA) the uncertainty of inputs and outputs is not considered when evaluating the performance of a unit. In other words, effects of uncertainty on optimality and feasibility of models are ignored. This paper introduces a new model for measuring the efficiency of decision making units (DMUs) having interval inputs and outputs. The proposed model is based ...