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Forecasting Tourist Indicators in Greece: A Comparative Evaluation of Statistical and Deep Learning Models

Author

Listed:
  • Nikolina Christou

    (University of Patras, Department of Tourism Management)

  • Vassiliki Karioti

    (University of Patras, Department of Tourism Management)

Abstract

Accurate forecasting of tourism demand is an essential tool for sustainable development and strategic planning of the tourism sector. This study investigates the performance of SARIMA statistical models and LSTM and GRU deep learning models in forecasting two critical indicators: international air arrivals and bed occupancy rates in Greece. In the case of SARIMA models, two scenarios were applied: one includes the COVID-19 pandemic period, while the other excludes it. The results show that SARIMA models are suitable in stable seasonal conditions, while LSTM and GRU neural networks achieve superior performance in complex and nonlinear periods, such as crisis periods. The study highlights the importance of selecting an appropriate forecasting model depending on the nature of the data and suggests future directions for improving the accuracy of tourism forecasting.

Suggested Citation

  • Nikolina Christou & Vassiliki Karioti, 2026. "Forecasting Tourist Indicators in Greece: A Comparative Evaluation of Statistical and Deep Learning Models," Springer Proceedings in Business and Economics,, Springer.
    • Handle: RePEc:spr:prbchp:978-3-032-17545-8_22
    DOI: 10.1007/978-3-032-17545-8_22
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    Keywords

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • Z32 - Other Special Topics - - Tourism Economics - - - Tourism and Development

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