Marcos Pereira Estellita Lins

Review of Methods for Increasing Discrimination in Data Envelopment Analysis

We present a review of methods for increasing discrimination between efficient DMUs in Data Envelopment Analysis. These methods were classified into two groups: those that incorporate a priori information and those that do not use or minimize the use of such a priori information. We also compare these methodologies regarding their specific characteristics.

Olympic ranking based on a zero sum gains DEA model

Abstract It is usual to rank the participant countries in the Olympic Games in accordance with the number of medals they have won. An alternative ranking is suggested in this paper. This ranking is based on each country’s ability to win medals in relation to its available resources. This is an efficiency that can be measured with the help of data envelopment analysis (DEA) for which two models exist: the traditional DEA model, that takes into account variable returns to scale, and a DEA model based on the premise that the sum of the gains is zero (constant sum of outputs). It is the latter that is developed in this paper.

Modelling undesirable outputs with zero sum gains data envelopment analysis models

Data envelopment analysis (DEA) literature has proposed alternative models for performance assessment in the presence of undesirable outputs, such as pollutant emissions, where increased outputs imply reduced performance. However, the case where global equilibrium of outputs should be imposed has not yet been considered. We propose that the zero sum gains DEA (ZSG-DEA) models look especially suitable for treating equilibrium models, where the sum of the quantities produced by all decision-making units can be set as the upper admissible bound. This paper uses ZSG-DEA models to evaluate the carbon dioxide emission case study, which can be considered part of the Kyoto Protocol statement.

Contruction of a smoothed DEA frontier

It is known that the DEA multipliers model does not allow a unique solution for the weights. This is due to the absence of unique derivatives in the extreme-efficient points, which is a consequence of the piecewise linear nature of the frontier. In this paper we propose a method to solve this problem, consisting of changing the original DEA frontier for a new one, smooth (with continuous derivatives at every point) and closest to the original frontier. We present the theoretical development for the general case, exemplified with the particular case of the BCC model with one input and one output. The 3-dimensional problem is briefly discussed. Some uses of the model are summarised, and one of them, a new Cross-Evaluation model, is presented.

Integrating Geographical Information Systems and Multi-Criteria Methods: A Case Study

This paper presents an application of the integration between Geographical Information Systems (GIS) and Multi-Criteria Decision Analysis (MCDA) to aid spatial decisions. We present a hypothetical case study to illustrate the GIS–MCDA integration: the selection of the best municipal district of Rio de Janeiro State, Brazil, in relation to the quality of urban life. The best municipal district is the one that presents the closest characteristics to those considered ideal by the decision-maker. The approach adopted is the Multi-Objective Linear Programming (MOLP) and the chosen method is the Pareto Race.

Financing reform and productivity change in Brazilian teaching hospitals: Malmquist approach

This study evaluates the performance and productivity changes for the Brazilian Federal University Hospitals, considering the years of 2003 and 2006, that is, before and after a 2004 financing reform. The analysis is based on the Malmquist index approach. Results indicate that the financing reform provided improvement in the technical efficiency, although the technological frontier has not presented a positive shift. This suggests that increased budgets were a good stimulus for efficiency but the intended enhancement of the technology through the financing reform has not yet taken place.

O uso da Análise Envoltória de Dados (DEA) para avaliação de hospitais universitários brasileiros

In order to demonstrate how DEA modeling can be helpful for hospital performance assessments conducted in compliance with Brazils Teaching Hospital Policy, a case study is presented of 31 general hospitals linked to Federal Universities. It considers data on assistance, teaching and research and the use of the IDEAL (Interactive Data Envelopment Analysis Laboratory) software as a tool for assessing their efficiency. Developed in Brazil, this unique software provides a three-dimensional view of the productivity frontier, for easier exploratory analyses and selection of pertinent variables, with a better understanding of the outputs of the model (multiplier and envelope) for specialists and decision-makers. As an example, a University Hospital benchmark is presented through outputs that take structural and regional input differences into consideration. This modeling also indicates the changes required in the inefficient units (alterations to input and/or /output vectors), setting forth recommendations on public financing based on quality/efficiency.

Integrating the regulatory and utility firm perspectives, when measuring the efficiency of electricity distribution

Abstract Several DEA applications for benchmarking in utility regulation use classical models, which reveal inconsistencies due to Pareto inefficient targets. The natural course of action would be to incorporate weight restrictions, reflecting value judgments and requiring interaction between analyst and decision maker. We show that weight restricted DEA models still present some inconsistencies, since it is not possible to ensure that the target both dominates the observed DMU and lies on the empirical production frontier. Besides the decision maker and analyst interaction, it is necessary to consider a further distinction between the two parties: the regulatory agency and the utility company, which adopt different criteria to determine the efficient target. A model to obtain a preferred target DEA index is formulated, taking advantage of the dual-based DEA graphical analysis. Thus, we propose a two-phase DEA analysis that can integrate both perspectives. A case study about the Brazilian electricity sector is included, which illustrates the above-mentioned issues.

Evaluating the performance of Brazilian university hospitals

In order to demonstrate how DEA modeling can be helpful to aid decision making relative to the Brazilian Teaching Hospital Policy by means of hospital performance assessment, we develop a case study with 30 general hospitals linked to Brazilian Federal Universities. We consider data on medical care (Medical Model—MM), teaching and research (Teaching-Research Model—TRM) and use the software IDEAL (Interactive Data Envelopment Analysis Laboratory) as a tool for the units’ efficiency evaluation. IDEAL, developed in Brazil, is unique in providing a 3-D frontiers visualization, assisting in exploratory analysis and allowing a better understanding of the DEA modeling (envelopment and multiplier). Both models are input-oriented and each hospital is categorized according to its relative efficiency in the MM and TRM. In this phase, it is very important to discuss with the decision-makers the results and patterns of the DEA models. Finally, the modelling indicates the necessary changes for the inefficient units and generates recommendations for teaching ratios and public financing.

Evaluating the Performance of Calculus Classes Using Operational Research Tools

This paper compares the efficiency of calculus classes. Two kinds of classes are evaluated: the traditional ones and others that use computational methods in teaching. This experiment was performed at Fluminense Federal University, Niterói, Brazil, from 1998 to 2000. The emphasis of this paper is on the quantitative evaluation using two operational research tools: multicriteria decision aid methods (mainly using the MACBETH approach) and data envelopment analysis. The evaluating variables are the level at which students enter the university and the performance of the students after studying calculus.