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Cited by 1,068

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

Big data in tourism research: A literature review

Li, Jingjing, Xu, Lizhi, Tang, Ling, Wang, Shouyang, Li, Ling·2018·Tourism Management
DOI 10.1016/j.tourman.2018.03.009
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Abstract

Abstract Even at an early stage, diverse big data have been applied to tourism research and made an amazing improvement. This paper might be the first attempt to present a comprehensive literature review on different types of big data in tourism research. By data sources, the tourism-related big data fall into three primary categories: UGC data (generated by users), including online textual data and online photo data; device data (by devices), including GPS data, mobile roaming data, Bluetooth data, etc.; transaction data (by operations), including web search data, webpage visiting data, online booking data, etc. Carrying different information, different data types address different tourism issues. For each type, a systematical analysis is conducted from the perspectives of research focuses, data characteristics, analytic techniques, major challenges and further directions. This survey facilitates a thorough understanding of this sunrise research and offers valuable insights into its future prospects.

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Metadata

Authors
Li, J., Xu, L., Tang, L., Wang, S., & Li, L.
Venue
Tourism Management
Publisher
Elsevier BV
Published
2018-10
Volume
68
Pages
301-323
ISSN
0261-5177 (ISSN-L)
DOI
10.1016/j.tourman.2018.03.009
OpenAlex
W2798990976
Cited by
1,068
References
7
FWCI
208.45
Type
journal article
Language
en
Open access
closed

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.