abstract
- This article examines the impact of international tourism in Mexico and introduces a predictive model to estimate the arrivals of international tourists for the period 2023-2025. Using monthly data provided by the Bank of Mexico (BANXICO), the Box-Jenkins method is employed, determining that an ARIMA model optimally fits the data. The results reveal notable demand patterns and emphasize the significant effect of the pandemic on tourist trends. After a marked decline during the most critical phases of the pandemic, a gradual recovery in tourist arrival figures is evident. These findings are essential for the Mexican tourism sector, offering valuable insights for planning and strategic decision-making. The suggested model can be a useful tool for tourism marketing professionals, assisting them in designing more accurate and effective strategies. Additionally, this study contributes, both empirically and methodologically, to the Mexican tourism context and has the potential to be extrapolated and applied in international settings. © 2019 Universidad Nacional Autónoma de México, Facultad de Contaduría y Administración.