Research on Prediction and Evaluation Methods for Olympics Host Countries and Cities


  • Yilin Wang
  • Haotian Chu
  • Heng Wu



Multiple linear regression; Markov prediction; VAR model; BP neural network; Olympic Games.


Aiming at problem: By reviewing the literature and the application criteria for the right to host the Olympic Games, we selected GDP and total national reserves as economic indicators, value added of services as service level indicators, national population and national prime age labor force ratio as social indicators, national land ratio as land use indicators, and birth mortality rate as medical level indicators to establish evaluation criteria for hosting the Olympic Games, and through linear regression to The influence factor analysis of each indicator was conducted, and the significant degree of influence of each indicator was obtained, among which the influence of labor force, GDP and total reserves was more significant. By judging the influence factors, we selected GDP, total national reserves, value added of service industry, national population, proportion of prime labor force, and birth mortality rate as the indicators to continue evaluating the hosting of the Olympic Games, and selected the minimum value of each indicator as the conditional threshold through quantitative analysis to establish the threshold coefficient matrix. According to the conditions of Olympic Games submission bid, the data of each indicator in the future 2022-2029 are predicted by VAR model, and then the country or city hosting the Olympic Games is predicted whether it can be held normally by BP neural network and the conditional threshold coefficient matrix. If there is no country or city that meets the conditions for holding the Olympic Games, we choose the United States as the fixed host city and use the data from 2012-2020 to predict the index data for the next 8 years by Markov for example. Therefore, textual solution has certain feasibility.


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How to Cite

Wang, Y., Chu, H., & Wu, H. (2023). Research on Prediction and Evaluation Methods for Olympics Host Countries and Cities. BCP Business & Management, 50, 127-131.