Forecasting of Indian and foreign tourist arrivals to Himachal Pradesh using Decomposition, Box–Jenkins, and Holt–Winters exponential smoothing methods

Keerti Manisha () and Inderpal Singh ()
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Keerti Manisha: National Institute of Technology Hamirpur
Inderpal Singh: National Institute of Technology Hamirpur

Asia-Pacific Journal of Regional Science, 2024, vol. 8, issue 3, No 5, 879-909

Abstract: Abstract Himachal Pradesh offers many tourist experiences to Indian and foreign visitors. The mountainous state experiences a high degree of tourism seasonality, interrupting the efficient operation of the tourism infrastructure. Fundamental requirements for tourism planning are accurate projections of tourist demands. However, estimating future demands becomes challenging because of the high degree of seasonality. The compound and annual growth rate methods are used in state-level tourism research to forecast future growth. Since these models cannot manage seasonality and trends in data series, they inaccurately predict future demand. In this context, forecasting models such as the Decomposition, Box–Jenkins, and Holt–Winters exponential smoothing methods were used to forecast the seasonal tourism demands in the study area. The dataset utilized for the analysis was the monthly Indian and foreign tourist arrivals from 2008 to 2018. Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and Theil’s U1 coefficients validated that the forecast models produced accurate results. The Box–Jenkins model accurately forecasted the tourist arrivals (2019 to 2031) as reflected by the lowest error metrics (Indian: RMSE 36833.8, MAPE 3.0, Theil's U1 0.023; Foreign: RMSE 6907.59, MAPE 15.51, Theil's U1 0.10). This approach outperformed the traditional seasonal data series forecasting techniques and contributed to the literature on univariate tourist demand forecasting for hilly areas experiencing a high degree of seasonality. Estimating maximum tourist arrivals is crucial in long-term strategic planning for tourism expansion to withstand maximum loads and ensure efficient business flow, higher investment, enhanced economic growth, and environmental protection in the state. This study is a pioneer in examining tourism demands for stakeholders, tourism operators, and planners to plan the fluctuating tourism in Himachal Pradesh while adhering to sustainability principles. Furthermore, it provides inputs for effective planning and policy formulations specific to the tourism industry based on future demand assessments.

Keywords: Demand; Forecasting; Seasonality; Tourism; Tourist arrivals (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s41685-024-00344-8

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