A DEA model with a non discritionary variable for Olympic evaluation

Abstract

In recent years, a lot of work has been done dealing with alternative performance rankings for the Olympic Games. Almost all of these works use Data Envelopment Analysis (DEA). Generally speaking, those works can be divided into two categories: Pure rankings with unitary input models and relative rankings with classical DEA models; both output oriented. In this paper we introduce an approach taking into account the number of athletes as a proxy to the country investment in sports. This number is an input for a DEA model, and the other input is the population of the country. We have three outputs, the number of gold, silver and bronze medals earned by each country. Contrary to the usual approach in the literature, our model is not output oriented. It is a non-radial DEA model oriented to the "number of athletes" input, as our goal is not a countries' ranking. We intend to analyse whether the number of athletes competing for each country accords with the number of won medals. For this analysis, we compare each country with its benchmarks. The Decision Making Units (DMU) are all the countries participating in the Beijing Olympic Games, including those that did not earn a single medal. We use a BCC model and we compare each DMU's target with the number of athletes who have won, at least one medal. © 2012 Brazilian Operations Research Society.