Showcasing Leximancer in tourism and hospitality research: a review of Leximancer-based research published in tourism and hospitality journals during 2014–2020

Abstract

ABSTRACT This study showcases how the Leximancer program can be used to review Leximancer-based research published in tourism and hospitality journals during 2014-2020. Along with a Leximancer-generated concept map, a new tags' association visual analysis was also performed. This innovative method of analysis is a key contribution, as past Leximancer studies in hospitality and tourism have predominantly relied on thematic analysis only. An Insight Dashboard report that is based on Bayesian algebra algorithm in calculating Prominence Scores (PS) for key concepts and compound concepts emergent from the data, supplemented the visual analyses. Thirty-three (33) tourism and three (3) hospitality papers were analysed. The most common tourism context was China and Chinese tourism, and the most prominent phenomena were tourists' experiences, shopping experiences, tourists' evaluations and perceptions. Data for these research studies were predominantly obtained from online reviews, user-generated content (UGC), social media and news media. In the hospitality context, research studies used Leximancer to analyse sentiment, risk factors, and attitudes of frontline hotel employees. Tourism Management and Current Issues in Tourism, had the most papers which used Leximancer. Australian researchers were identified as the leaders in tourism research using Leximancer, followed by lead researchers from Portugal and China.