Big Data Analytics and Hotel Guest Experience: A Critical Analysis of the Literature

Purpose: Guest experience and satisfaction have been central constructs in the hospitality management literature for decades. In recent years, the use of big data as an increasing trending practice in hospitality research has been characterised as a modern approach which offers valuable insights into understanding and enhancing guest experience and satisfaction. Recognising such potential, both researchers and practitioners need to better understand big data’s application and contribution in the hospitality landscape. This paper critically reviews and synthesizes the literature to shed light on trends and extant patterns in the application of big data in hospitality, particularly in research focusing on hotel guest experience and satisfaction. Design/Methodology/approach: This research is based on a Preferred Reporting Items for Systematic Reviews and Metaanalysis (PRISMA) literature review of academic journal articles in Google Scholar published up to the end of 2020. Findings: By data types, user-generated content, especially online reviews and ratings were at the centre of attention for hospitality-related big data research. By variables, the hospitality-related big data fell into two crucial factor categories: physical environment and guest-to-staff interactions.
Originality/value: This paper shows that big data research can create new insights into attributes that have been extensively researched in the hospitality field. It facilitates a thorough understanding of big data studies and provides valuable insights into future prospects for both researchers and practitioners.