Xu, Faye, Nash, Nicolas and Whitmarsh, Lorraine (2019) Big data or small data, a methodological review of sustainable tourism. Journal of Sustainable Tourism, 28 (2). pp. 144-163. ISSN 0966-9582

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Abstract

Research in the field of sustainable tourism is increasingly important due to significant growth in tourism industries and the unsustainable impacts incurred. Innovation in sustainable tourism studies is required to meet a number of challenges including socio-ecological impacts; the critical turn in tourism research; and the growth of ICTs, mobile technologies and big data analytics. These shifts in particular are transforming the field and creating new research opportunities. This paper seeks to identify potential new methodological areas of application to sustainable tourism studies for both quantitative and qualitative methods. A range of methods are reviewed, focusing on big data (e.g., mobile device signaling, GPS, social media and search engine data) that elucidates wider patterns of tourist movement, as applied to forecasting travel demands and sustainable management of a destination. Three novel ‘small data’ methods are also discussed, comprising visual methods, autoethnography, and qualitative GIS, that provide deeper, contextual insights into the drivers, dynamics and impacts of sustainable tourism. We consider how expansive qualitative methodologies might yield potentially important insights concealed by existing methodologies. Furthermore, we argue that combined big data and small data approaches can address methodological imbalance and generate mutually reinforcing insights at a number of levels.

Item Type:	Article
Identifier:	10.1080/09669582.2019.1631318
Additional Information:	his is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Sustainable Tourism on 12/07/19, available online: https://www.tandfonline.com/10.1080/09669582.2019.1631318.
Keywords:	Big data, small data, sustainable tourism, mobility, research methods
Subjects:	Hospitality and tourism > Tourism
Related URLs:	Publisher
Depositing User:	Faye Xu
Date Deposited:	05 Jun 2020 15:38
Last Modified:	06 Feb 2024 16:03
URI:	https://repository.uwl.ac.uk/id/eprint/7012

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