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

Author:

Mariani Marcello,Baggio Rodolfo,Fuchs Matthias,Höepken Wolfram

Abstract

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.

Publisher

Emerald

Subject

Tourism, Leisure and Hospitality Management

Reference161 articles.

1. Sentiment analysis in tourism: capitalizing on big data;Journal of Travel Research,2017

2. Competitive analysis of online reviews using exploratory text mining;Tourism and Hospitality Management,2016

3. The end of theory: the data deluge makes the scientific method obsolete;Wired Magazine,2008

4. Web usage and content mining to extract knowledge for modelling the users of the bidasoa turismo website;Expert Systems with Applications,2013

5. Logit models for forecasting nationwide intercity travel demand in the United States;Transportation Research Record: Journal of the Transportation Research Board,2007

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