Forecasting of Visitors Arrived in Taiwan for Tourism Supply Chain Demand using Big Data

Abstract

The fast development of Information and Communication Technology, generate, collect and operate a large amount of data, which is termed big data. The search queries in web search engines can be retrieved by visitors to obtain useful infor-mation for the selected next visiting destinations. Google Trends on Google search engine can evaluate and compare how many times users are searching for specific terms or topics. Otherwise, economic factors, covering income, the rela-tive prices, and relative exchange rate usually influence the international tourist demand. However, there are different conclusions in different settings. Accord-ingly, this work presents the ARIMAX model for modelling and forecasting numbers of international tourists visiting Taiwan from Japan for different pur-poses and provides an analysis of the effects of big data and economic factors. The results can contribute to the decision makers of the tourism industry in Taiwan