Navigating the generative AI travel landscape: the influence of ChatGPT on the evolution from new users to loyal adopters

生成语法 旅游 早期采用者 生成模型 营销 款待 业务 社会文化进化 广告 地理 计算机科学 社会学 人工智能 考古 人类学
作者
Yu Li,Soyeun Olivia Lee
出处
期刊:International Journal of Contemporary Hospitality Management [Emerald Publishing Limited]
被引量:15
标识
DOI:10.1108/ijchm-11-2023-1767
摘要

Purpose This study, rooted in affordance-actualization theory and communication theory, aims to critically examine how ChatGPT influences users’ transition from new adopters to loyal advocates within the context of travel decision-making. It incorporates constructs including communication quality, personalization, anthropomorphism, cognitive and emotional trust (ET), loyalty and intention to adopt into a comprehensive model. Design/methodology/approach This study used quantitative methods to analyze data from 477 respondents, collected online through a self-administered questionnaire by Embrain, a leading market research company in South Korea. Lavaan package within R studio was used for evaluating the measurement model through confirmatory factor analysis and using structural equation modeling to examine the proposed hypotheses. Findings The findings reveal a pivotal need for enhancing ChatGPT’s communication quality, particularly in terms of accuracy, currency and understandability. Personalization emerges as a key driver for cognitive trust, while anthropomorphism significantly impacts ET. Interestingly, the study unveils that in the context of travel recommendations, users’ trust in ChatGPT predominantly operates at the cognitive level, significantly impacting loyalty and subsequent adoption intentions. Practical implications The findings of this research provide valuable insights for improving Generative AI (GenAI) technology and management practices in travel recommendations. Originality/value As one of the few empirical research papers in the burgeoning field of GenAI, this study proposes a highly explanatory model for the process from affordance to actualization in the context of using ChatGPT for travel recommendations.
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