@inbook{c1235a3f5fea4a479d8f96a5deb1c553,
title = "Predicting Tourist Demand Using Big Data",
abstract = "Big data is one of the most important new tools that have impacted the world travel industry. It also plays an important role in determining the ways in which tourism businesses and non-governmental organizations formulate their strategies and policies. However, very limited academic research has been conducted into tourism forecasting using big data due to the difficulties in capturing, collecting, handling, and modeling this type of data, which is normally characterized by its privacy and potential commercial value. In this chapter, we define big data in the context of tourism forecasting and summarize the changes it has brought about in tourism business decision-making. A framework of tourism forecasting using big data is then presented.",
keywords = "Big data, Forecasting, Mixed frequency, Tourist demand",
author = "Haiyan Song and Han Liu",
note = "Publisher Copyright: {\textcopyright} 2017, Springer International Publishing Switzerland.",
year = "2017",
doi = "10.1007/978-3-319-44263-1_2",
language = "English",
series = "Tourism on the Verge",
publisher = "Springer Nature",
pages = "13--29",
editor = "Ulrike Gretzel",
booktitle = "Tourism on the Verge",
address = "United States",
}