This paper uses the DEA-CCR and the DEA-BCC models to evaluate the performance of Greek life insurance companies in the period 1994 to 2003, combining operational and financial variables. These models identify adequately the inefficient companies, but are weak in discriminating among those found to be efficient. To improve the results, we employ the Cross-Efficiency and the SuperEfficiency mode...

selection of an appropriate set of information system (is) projects is a critical business activity which is very helpful to all organizations. in this paper, after describing real is project selection problem of iran ministry of commerce (moc), we introduce two data envelopment analysis (dea) models. then, we show applicability of introduced models for identifying most efficient is project fro...

This chapter discusses returns to scale (RTS) in data envelopment analysis (DEA). The BCC and CCR models are treated in input oriented forms while the multiplicative model is treated in output oriented form. (This distinction is not pertinent for the additive model which simultaneously maximizes outputs and minimizes inputs in the sense of a vector optimization.) Quantitative estimates in the f...

China has long been stuck in applying traditional data envelopment analysis (DEA) models to measure technical efficiency of public hospitals without bias correction of efficiency scores. In this article, we have introduced the Bootstrap-DEA approach from the international literature to analyze the technical efficiency of public hospitals in Tianjin (China) and tried to improve the application o...

This paper describes an intelligent decision support system for evaluating state-owned enterprises (SOEs) using DEA models. This decision support system converts numerical data into information that can be used to evaluate state-owned enterprises (SOEs). In this paper, we use DEA models, including CCR, BCC and FDH, to shed new light on the operational efficiency and determinants of stateowned e...

Data envelopment analysis (DEA) is a widely used mathematical programming approach for comparing the input and output of a set of comparable decision-making units (DMUs) by evaluating their relative efficiency. The traditional DEA methods require accurate measurement of both the inputs and outputs. However, the real evaluation of the DMUs is often characterized by imprecision and uncertainty in...

In the history of DEA, there are two fundamental “Radial” and “Non-radial” approaches for the efficiency measurement. Each approach has its own advantageous and shortcomings. Avkiran et al. (2008) provided a unified framework, named Connected-SBM, for linking these approaches. In the present paper, first, based on the directional distance function we develop the Directional Slack-Based Measures...

Traditional super-efficiency data envelopment analysis (DEA) models rank efficient units under the assumption of constant returns to scale (CRS). However, infeasibility may occur in super-efficiency models under variable returns to scale (VRS). This paper proposes a modified VRS super-efficiency DEA model to deal with infeasibility by relaxing the convexity constraint 1, 0 1 n j j j λ = ≠ = ∑ t...

Selection of an appropriate set of Information System (IS) projects is a critical business activity which is very helpful to all organizations. In this paper, after describing real IS project selection problem of Iran Ministry of Commerce (MOC), we introduce two Data Envelopment Analysis (DEA) models. Then, we show applicability of introduced models for identifying most efficient IS project fro...

Data Envelopment Analysis (DEA) cannot provide adequate discrimination among efficient decision making units (DMUs). To discriminate these efficient DMUs is an interesting research subject. The purpose of this paper is to develop the mix integer linear model which was proposed by Foroughi (Foroughi A.A. A new mixed integer linear model for selecting the best decision making units in data envelo...