This article utilizes data envelopment analysis (DEA) to estimate the productivity of the English and Welsh police forces and to determine whether there are categorical scale effects in policing using multiple discriminant analysis (MDA). The article demonstrates that by using DEA efficiency results it is possible to make inferences about the optimal size and structure of the English and Welsh ...

The field of productive efficiency analysis is currently divided between two main paradigms: the deterministic, nonparametric Data Envelopment Analysis (DEA) and the parametric Stochastic Frontier Analysis (SFA). This paper examines an encompassing semiparametric frontier model that combines the DEA-type nonparametric frontier, which satisfies monotonicity and concavity, with the SFA-style stoc...

In order to evaluate the multistage supply chain efficiency, an appropriate performance evaluation system is importantly required. A representative multistage supply chain has three members composing a supplier-manufacturer-retailer structure, and has intermediate measures connecting these supply chain members. Existing data envelopment analysis (DEA) models have difficulties in measuring these...

Model misspecification has significant impacts on Data Envelopment Analysis (DEA) efficiency estimates. This paper discusses the four most widely-used approaches to guide variable specification in DEA. We analyze Efficiency Contribution Measure (ECM), Principal Component Analysis (PCA-DEA), a regression-based test, and bootstrapping for variable selection via Monte Carlo simulations to determin...

Abstract—Data Envelopment Analysis is a kind of important analyzing tool and research method in evaluation. As a method, introducing secondary relative evaluation method, the Data Envelopment Analysis (DEA) is applied to evaluate road traffic safety in different areas based on optimizing evaluation index system. This paper mostly discusses the relatively safety of different areas. Keywords—road...

This study uses a sample of 30 banks (4 public, 18 local private and 8 foreign banks) and two stage Data Envelopment Analysis (DEA) to provide evidence on the impact of macroeconomic and bank specific factors on banks’ efficiency. We first use DEA to estimate technical and scale efficiency and then Tobit regression approach to find out the impact of several bank-specific and macroeconomic facto...

This paper provides a sketch of some of the major research thrusts in data envelopment analysis (DEA) over the three decades since the appearance of the seminal work of Charnes et al. (1978) [Charnes, A., Cooper, W.W., Rhodes, E.L., 1978. Measuring the efficiency of decision making units. European Journal of Operational Research 2, 429–444]. The focus herein is primarily on methodological devel...

Supplier selection has a strategic importance for every company. Hybrid integer data is one of the models in data envelopment analysis (DEA). In many real world applications, data are often stochastic. A successful approach to address uncertainty in data is to replace deterministic data via random variables, leading to chance-constrained DEA. In this paper, a chance-constrained hybrid integer d...

Data envelopment analysis (DEA) is a technique for performance evaluation of peer decision making units (DMUs). The network DEA models study the internal structures of DMUs. Using two-stage network structures as an example, the current paper examines additive efficiency decomposition where the overall efficiency is defined as a weighted average of stage efficiencies and the weights are used to ...