Abstract
This study examines how the PU of AI language models (AILM) during the pre-trip, during-trip, and post-trip phases, along with perceived risk (PR), operationalised through perceived drawbacks (PD) and ethical issues (EI), affects tourists’ emotional responses (EMO) and ultimately their intention to adopt (IntA) AILM. Integrating the Technology Acceptance Model (TAM) with the Stimulus-Organism-Response (SOR) framework, a survey of 1,175 respondents was analysed using structural equation modelling. Findings reveal that PU dimensions related to travel planning (BT) and experience (AT) significantly enhance positive EMO and IntA, while PD negatively influences EMO, thereby reducing adoption intention. Notably, these relationships are consistent across both tech-savvy and traditional travellers. The results offer valuable theoretical insights and practical implications for refining e-marketing strategies and technology design in the evolving tourism landscape.
Presenters
Kai Xin TaySenior Lecturer, Faculty of Business, Economics, and Accountancy, Universiti Malaysia Sabah, Malaysia
Details
Presentation Type
Paper Presentation in a Themed Session
Theme
Critical Issues in Tourism and Leisure Studies
KEYWORDS
AI LANGUAGE MODELS, PERCEIVED USEFULNESS, PERCEIVED RISK, EMOTIONAL RESPONSES, INTENTION
