What question did this study set out to answer?

The research aims to identify the most accurate forecasting methods for passenger traffic at Thai airports.

January 22, 2026Modelling—International Open Access Journal of Modelling in Engineering Science0 citationsOpen Access

Comparative Evaluation of Event-Based Forecasting Models for Thai Airport Passenger Traffic

TCThanrada ChaikajonwatKing Mongkut's Institute of Technology Ladkrabang AAAutcha AraveepornKing Mongkut's Institute of Technology Ladkrabang

Key Points

The research aims to identify the most accurate forecasting methods for passenger traffic at Thai airports.
Forecasting passenger traffic at four airports using data from 2017 to 2024.
Divided data into training (2017-2023) and testing (2024) sets.
Compared six forecasting methods: Single Exponential Smoothing, Holt’s, Holt’s with Events Adjustment, Holt–Winters Multiplicative, TBATS, and Box–Jenkins.
Evaluated forecast performance using Mean Absolute Percentage Error (MAPE) and Mean Absolute Error (MAE).
Holt’s Method with Events Adjustment produced the most accurate forecasts for BKK and DMK.
Holt–Winters Multiplicative method performed best for CNX and HKT, indicating strong seasonal patterns.
Optimal forecasting method varies based on airport characteristics and external events like COVID-19.

Abstract

Accurate passenger traffic forecasting is vital for strategic planning in Thailand’s aviation industry. This study forecasts the monthly total number of passengers at Suvarnabhumi (BKK), Don Mueang (DMK), Chiang Mai (CNX), and Phuket (HKT) airports using data from 2017 to 2024. The dataset was partitioned into training (January 2017–December 2023) and testing (January–December 2024) sets. Six methods were compared: Single Exponential Smoothing, Holt’s, Holt’s with Events Adjustment, Holt–Winters Multiplicative, TBATS model, and Box–Jenkins. Performance was evaluated using Mean Absolute Percentage Error (MAPE) and Mean Absolute Error (MAE). The results indicate that the optimal forecasting method varies by airport characteristics. Holt’s Method with Events Adjustment, which incorporates major disruptions such as the COVID-19 pandemic, produced the most accurate forecasts for BKK and DMK by effectively capturing external shocks. In contrast, the Holt–Winters Multiplicative method performed best for CNX and HKT, reflecting strong seasonal patterns typically driven by tourism activities in these destinations.

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