This study aims to explore the role of destination chatbots as innovative tools in travel planning, focusing on their ability to enhance user experiences and influence decision-making processes. Based on the Technology Acceptance Model, Enterprise Content Management, and Information Systems Security models, the study examines the psychological, emotional, and technological factors that drive user satisfaction, continued use, and intention to visit a destination. Understanding these factors is crucial for improving chatbot design and optimizing their implementation in the tourism industry. A total of 312 responses were collected from university students who regularly engage in tourism-related activities. The survey employed a structured questionnaire with items measuring information quality, user satisfaction, perceived enjoyment, usefulness, and behavioral intentions using a 7-point Likert scale. Structural equation modelling [SEM] was used to analyze the relationships between constructs, allowing us to evaluate the validity and reliability of the model. The results reveal that information quality positively enhances user satisfaction, perceived enjoyment, and perceived usefulness. Moreover, perceived enjoyment and usefulness are critical psychological and emotional drivers influencing users' decision to continue utilizing chatbots. Additionally, the analysis highlights the intention to continue using destination chatbots as a strong predictor of tourists' intention to visit the destination. The findings contribute to the theoretical understanding of technology acceptance and user behavior in tourism, while providing practical insights for destination managers and developers to enhance chatbot features and improve traveler engagement.