Forecasting Future Tourism Demand to Popular Tourist Attractions to Asses Overtourism: A Machine Learning Modeling Approach

The research was aimed at estimating tourism demand in the medium term to Sri Lanka and the impact of potential high level of tourist arrivals resulting in overtourism and impacting sustainability in tourism to the most popular tourist attractions in Sri Lanka, namely Yala and Sigiriya. Yala is a nature preserve and a popular sight for sighting wild elephants and leopards using safari jeeps. Sigiriya is an ancient rock fortress considered a UNESCO world heritage that is climbed by foot. The two destinations are generally considered ‘must visit’ tourist attractions in a visit to Sri Lanka and could be subject to significant ‘tourist traffic’, particularly during the peak tourist months. Using a machine learning modeling approach, the study forecasts almost doubling of tourist arrivals to Sri Lanka from 2024 to 2027, in a mere 3 years. Based on the future demand, the study then estimated the future visitor demand as a count of daily safari jeeps to Yala and as a count of daily foot traffic to Sigiriya up to 2027, taking into consideration seasonality. The study suggests that the carrying capacity of both these tourist destinations to be significantly strained in the medium term. This is likely to adversely impact these environmentally and archeologically sensitive sites due to overtourism, particularly in peak tourist months, unless appropriate policy measures are taken to limit daily visitations to these sites.