Business intelligence and big data in hospitality and tourism: a systematic literature review

Abstract

Purpose-This study examines 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; 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 datadriven 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 our knowledge, it is the first systematic literature review within hospitality and tourism research dealing with Business Intelligence and Big Data.

Destination Image Analytics through Traveller-Generated Content

“…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]. In a similar review of literature from the Web of Science, ScienceDirect, SAGE Journals Online, Emerald Insight, Wiley Online Library and Springer published between 2007 and 2016, the authors examined 144 journal papers and 21 conference papers [41].…”

“…gave rise to the link between their analysis and that of big data [34][35][36]. Therefore, much research has been devoted to social media analytics in general [37][38][39] and tourism analytics in particular [40][41][42].…”

Geo-Tagged Photo Metadata Processing Method for Beijing Inbound Tourism Flow

“…In the tourism industry, the widespread availability of big data opportunities has changed the traditional research approach substantially. The enormous amount of available data has made the information extraction phase more complex, such that it now requires advanced analytics techniques to perform [18,19].…”

A systematic assessment of gaps between academic research and industry participation in hospitality management discipline

“…Differences were also found in the methodology and interpretation of research data. Mariani et al (2018) analyzing large data found that the academic research was fragmented in scope with limited methodologies and several gaps. A conceptual framework related to business domain and identification of critical business intelligence using big data was found to be missing in hospitality management research.…”