Trend Analysis of Tourist-arrivals in Nepal Using Auto- Regressive Integrated Moving Average (ARIMA) Model

A comprehensive trend analysis of tourist arrivals in Nepal from 1964 to 2023, using the Auto Regressive Integrated Moving Average (ARIMA) model, reveals that the ARIMA (2, 1, 3) model provides the most accurate forecasts. This finding is significant for Nepal's tourism industry, which includes iconic sites like Lumbini, a UNESCO World Heritage Site and the birthplace of Lord Buddha. The study employed secondary data from the Ministry of Finance, Government of Nepal, and rigorously tested multiple ARIMA models using criteria such as Akaike Information Criterion (AIC) and Mean Absolute Error (MAE). The results underscore the need for flexible and strategic planning to enhance the resilience of Nepal's tourism sector, offering valuable insights for policymakers, industry stakeholders, and researchers.

Khatri, B. B., Poudel, O., Kafle, S. C., Acharya, P., & Simkhada, D. (2024). Trend Analysis of Tourist-arrivals in Nepal Using Auto- Regressive Integrated Moving Average (ARIMA) Model. Journal of Tourism & Adventure, 7(1), 120–143. https://doi.org/10.3126/jota.v7i1.69542