Business intelligence and big data in hospitality and tourism: a systematic literature review
By Marcello M. Mariani, Rodolfo Baggio, Matthias Fuchs, Wolfram Hoepken. International Journal of Contemporary Hospitality Management, 2018
314 citations recorded by the source corpus.
Purpose This paper aims to examine the extent to which Business Intelligence and Big Data feature within academic research in hospitality and tourism published until 2016, by identifying research gaps and future developments and designing an agenda for future research. Design/methodology/approach The study consists of a systematic quantitative literature review of academic articles indexed on the Scopus and Web of Science databases. The articles were reviewed based on the following features: research topic; conceptual and theoretical characterization; sources of data; type of data and size; data collection methods; data analysis techniques; and data reporting and visualization. Findings Findings indicate an increase in hospitality and tourism management literature applying analytical techniques to large quantities of data. However, this research field is fairly fragmented in scope and limited in methodologies and displays several gaps. A conceptual framework that helps to identify critical business problems and links the domains of business intelligence and big data to tourism and hospitality management and development is missing. Moreover, epistemological dilemmas and consequences for theory development of big data-driven knowledge are still a terra incognita. Last, despite calls for more integration of management and data science, cross-disciplinary collaborations with computer and data scientists are rather episodic and related to specific types of work and research. Research limitations/implications This work is based on academic articles published before 2017; hence, scientific outputs published after the moment of writing have not been included. A rich research agenda is designed. Originality/value This study contributes to explore in depth and systematically to what extent hospitality and tourism scholars are aware of and working intendedly on business intelligence and big data. To the best of the authors’ knowledge, it is the first systematic literature review within hospitality and tourism research dealing with business intelligence and big data.
Subfields: Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/d345778be736495187b4fd71205fd8125cd32370
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In Sociology and Political Science
Citations in the corpus
- Destination Image Analytics through Traveller-Generated Content (2019, background): “In a systematic review of literature from the Web of Science and Scopus published between 2000 and 2016, the authors selected 96 articles on big data and tourism, only 17 of which appeared in journals addressing hospitality or tourism [42].”