Experience, Trust, eWOM Engagement and Usage Intention of AI Enabled Services in Hospitality and Tourism Industry: Moderating Mediating Analysis

• Published in: Journal of Quality Assurance in Hospitality and Tourism
• Main Author: Alam S.S.; Masukujjaman M.; Mohamed Makhbul Z.K.; Helmi Ali M.; Ahmad I.; Al Mamun A.
• Format: Article
• Language: English
• Published: Routledge 2024
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146982451&doi=10.1080%2f1528008X.2023.2167762&partnerID=40&md5=17a1b0497d96b34ae5767b06da240e47

The study aims to determine the factors affecting the usage intention of AI technology in the hospitality and tourism sector in Malaysia. It also investigates the mediating effect of self-efficacy within some relationships. This is a quantitative study applying a cross-sectional online survey technique. The target population consisted of tourists seeking for services from the tourism and hospitality industry in Malaysia. Data was collected from 250 respondents using a survey questionnaire and analysed by applying a structural equation model using the AMOS 21 version. The results indicate that accuracy experience, insight experience, and interactive experience between trust in AI and eWOM engagements are significant respectively, except for the relationship between interactive experience and eWOM. Likewise, the outcome indicates that trust in AI has a significant positive relationship between usage intention and eWOM, while eWOM significantly and positively influences usage intention. In addition, this study found that word-of-mouth mediates the association between accuracy experience and trust in AI. The results show that self-efficacy moderates the association between accuracy experience and trust in AI. © 2023 Taylor & Francis Group, LLC.