Abstract

Artificial intelligence (AI) chatbots are pervasive in the travel industry and have significantly alleviated solo travelers' concerns in trip planning and booking. However, many existing AI chatbots have yet to meet the expectations of solo travelers, especially when they demand more personalized information to assist in travel decision-making. Based on complexity theory, this research examines the factors that stimulate solo travelers' purchase intentions when using AI chatbots, particularly covering the three main aspects of marketing efforts, communication quality, and affective characteristics. Drawing from a sample of 281 solo travelers, partial least squares-structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) are used to examine the proposed relationships. The PLS-SEM results illustrate that interaction, entertainment, trendiness, communication competence, and satisfaction have significant direct effects on purchase intentions. The fsQCA results further revealed four solutions exhibiting high purchase intentions among solo travelers. Different core, peripheral, and necessary causal conditions in each configuration path were identified. The findings enrich the AI chatbot literature by examining the underlying reasons why solo travelers react differently to this emerging technology and produce practical recommendations for designing AI chatbot systems.

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