Understanding continuance intention toward the use of AI chatbots in customer service among generation Z in Vietnam

As artificial intelligence (AI) becomes integral to digital customer service, AI chatbots increasingly shape user experience and operational efficiency. This research examines the factors influencing Generation Z's continuance intention to use AI chatbot customer services in Vietnam by integrating the Information System Success Model (ISSM) with chatbot marketing effort constructs, including interaction, customization, problem-solving, and perceived enjoyment. Data from 562 valid responses were collected using a non-probability convenience sampling method and analyzed with Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that system quality, information quality, service quality, and perceived enjoyment significantly influence both user attitude and satisfaction, with system quality having the strongest effect. Customization and interaction positively affect only attitude, while problem-solving positively influences only satisfaction. Attitude and satisfaction, in turn, strongly predict continuance intention. These findings suggest that while experiential features primarily influence user attitude, satisfaction is driven by functional performance. This underscores the importance of integrating technical reliability with emotionally engaging, user-centered design to support sustained AI chatbot use. Theoretically, the study advances the ISSM by incorporating affective and behavioral dimensions, offering a richer understanding of post-adoption behavior among digital-native users. Practically, it provides actionable guidance for developers and marketers to enhance chatbot effectiveness through personalization, intuitive usability, and emotionally appealing experiences tailored to Generation Z.