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Predicting Tourist Demand Using Big Data

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Analytics in Smart Tourism Design

Part of the book series: Tourism on the Verge ((TV))

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.

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Authors and Affiliations

  1. The Hong Kong Polytechnic University, Hung Hom, Hong Kong

    Haiyan Song

  2. Jilin University, Jilin, People’s Republic of China

    Han Liu

Authors
  1. Haiyan Song
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  2. Han Liu
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Correspondence to Haiyan Song .

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Editors and Affiliations

  1. Department of Hospitality and Tourism Management, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA

    Zheng Xiang

  2. National Laboratory for Tourism & eCommerce Department of Tourism, Recreation and Sport Management, University of Florida, Gainesville, Florida, USA

    Daniel R. Fesenmaier

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Song, H., Liu, H. (2017). Predicting Tourist Demand Using Big Data. In: Xiang, Z., Fesenmaier, D. (eds) Analytics in Smart Tourism Design. Tourism on the Verge. Springer, Cham. https://doi.org/10.1007/978-3-319-44263-1_2

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