A Seasonal Autoregressive Integrated Moving Average (SARIMA) Model to Forecasting Tourist Arrival in the Philippines: A Case Study in Moalboal, Cebu (Philippines)

  • Severina P. Velos Cebu Technological University - Moalboal Campus
  • Marivel B. Go Cebu Technological University
  • Glynne P. Bate Cebu Technological University
  • Elvira B. Joyohoy Cebu Technological University
Keywords: Tourism demand forecasting, time series forecasting, SARIMA, stochastic processes, seasonal time series

Abstract

Forecasting plays a critical part in implementing effective tourism management strategies. However, the role of tourism forecasting is not extensively studied in the Philippines, which is a key tourism destination in Southeast Asia. To address such gap, this paper explores the dynamics of tourist demand in the Philippines through a case study. It illustrates the tourist arrival using a SARIMA model. Results show that the adopted methodology was able to capture the dynamics of the tourist demand in the Philippines. By providing lenses to the Philippine tourism case, this paper would help shed light to the gaps in the literature’s current understanding of tourism in the Philippines. Moreover, these findings would be beneficial for stakeholders in shaping policies, strategies, and other tourism initiatives.

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Published
2020-06-30
How to Cite
VelosS., GoM., BateG., & JoyohoyE. (2020). A Seasonal Autoregressive Integrated Moving Average (SARIMA) Model to Forecasting Tourist Arrival in the Philippines: A Case Study in Moalboal, Cebu (Philippines). Recoletos Multidisciplinary Research Journal, 8(1), 67-78. https://doi.org/10.32871/rmrj2008.01.05
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