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The objective of this study is to perform a systematic review of the literature on the performance evaluation of countries in Olympic Games, specifically analyzing studies that encompass the non-parametric technique Data Envelopment Analysis (DEA). The scientific articles are dated from 2002 to 2018. It was necessary to organize the evolution of applied mathematical models and analyze the results in the game evaluation process. In addition, it was observed that the variables used and other techniques that helped the authors in the evaluation performed. A trend has been identified in the most recent literature for the use of the DEA model in networks. In general, countries are found to suffer from higher efficiency scores, especially at the administrative level. Therefore, after this type of dissemination of knowledge, it is possible to identify the need to remodel and implement new resource allocation strategies in order to obtain better performance indices in games of this magnitude.

The objective of this paper is to investigate the factors that affect the performance of rail freight and to ascertain the magnitude of the resulting effects. A multiple linear regression model was developed with panel data analysis, considering the fixed effects over time. The data collected correspond to the period from 2011 to 2018 and come from the National Land Transportation Agency (ANTT). The explanatory variables used are: speed, maintenance, accidents and cargo volume (production). After formulating and executing the model, the obtained indices were tested for statistical significance. We attempted to attenuate heteroscedastic errors by calculating robust standard errors and performed a model specification test. It was detected that the volume of cargo transported and speed of the train have a statistically relevant impact on performance. The model developed showed no evidence of poor specification and can assist in the planning of the activities of the observed companies.