Key points are not available for this paper at this time.
Purpose This study explores how predictor variables (value congruence and customer–AI-assisted exchanges) lead tourism businesses to meet customer needs through contactless technology and enhance their willingness to pay more. Design/methodology/approach The research model was designed from the perspective of consumer-brand relationships and acceptance of AI device use. This study collected and analyzed 647 valid questionnaires using the structural equation modeling (SEM) approach. Findings The findings indicate that value congruence and customer-AI-assisted exchanges (CAIX) affect intimacy. Intimacy affects satisfaction and the willingness to pay more for contactless technological services. Moreover, brand trust and sensory brand experience play a role in moderating contactless technological services. Originality/value Effective interactions between customers and AI-assisted services significantly contribute to overall satisfaction. When AI systems can understand and respond appropriately to customer queries, needs, and preferences, they enhance customer experience and satisfaction levels, increasing overall customer satisfaction with AI services.
Edward C.S. Ku (Mon,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: