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Analysing Olympic Games through dominance networks

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  • Calzada-Infante, Laura
  • Lozano, Sebastián

Abstract

The aim of this paper is to assess the results/performance of countries in the Olympic Games, taking into account their size and resources. A complex network analysis approach is proposed. The first step is to build the dominance network, which is a weighted directed graph in which nodes represent the participating nations and the arc length between any two nations measures the weighted difference in the number of medals won by both countries. An arc from a country to another b exists only if the latter has won more medals than the former and, in addition, it is smaller in population and in terms of GDP. In other words, an arc between two nodes exists if the origin nation performs worse than the destination when, given the population and GDP of both countries, it should have performed better (or at least equally). This dominance network has transitive links and a layered structure and, apart from being visualized, it can be characterized using different complex network measures. The results of the Beijing 2008 Olympic Games are used to illustrate the proposed approach.

Suggested Citation

  • Calzada-Infante, Laura & Lozano, Sebastián, 2016. "Analysing Olympic Games through dominance networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1215-1230.
    • Handle: RePEc:eee:phsmap:v:462:y:2016:i:c:p:1215-1230
    DOI: 10.1016/j.physa.2016.07.001
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    Cited by:

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    2. Alexandre de Cássio Rodrigues & Carlos Alberto Gonçalves & Tiago Silveira Gontijo, 2019. "A two-stage DEA model to evaluate the efficiency of countries at the Rio 2016 Olympic Games," Economics Bulletin, AccessEcon, vol. 39(2), pages 1538-1545.
    3. Sebastián Lozano & Gabriel Villa, 2023. "Multiobjective centralized DEA approach to Tokyo 2020 Olympic Games," Annals of Operations Research, Springer, vol. 322(2), pages 879-919, March.
    4. Laura Calzada-Infante & Sebastián Lozano, 2022. "Computing multiperiod efficiency using dominance networks," Annals of Operations Research, Springer, vol. 309(1), pages 37-57, February.

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