Forecasting Foreign Visitors Arrivals Using Hybrid Model and Monte Carlo Simulation (original) (raw)

International Journal of Information Technology & Decision Making

Abstract

The tourism industry is one of the important revenue sectors in today’s world. Millions of visits are made monthly to different countries across the planet. Some countries host more tourists than others, depending on the availability of factors that would fascinate visitors. Tourism demand can be affected by different factors, which may include government policies, insecurity, political motive, etc. Being an important sector, policymakers/governments are keen on models that would provide an insight into the inherent dynamics of tourism in their country. Especially in forecasting future tourist arrivals, as it will greatly assist in decision making. Several tourism demand models have been presented in the literature. The best practice is to have a model that would account for uncertainty in estimations. In this paper, an ANN-Polynomial-Fourier series model is implemented to capture and forecast tourist data for Turkey, Japan, Malaysia, and Singapore. The proposed model is a combinati...

Asaf Varol hasn't uploaded this paper.

Let Asaf know you want this paper to be uploaded.

Ask for this paper to be uploaded.