AI chatbots and purchase behavior of Gen Z: The role of theoretical intersection

Abstract

AI chatbots create new opportunities for managers to reshape the way consumers make purchasing decisions. Although there have been many studies approaching cognitive and emotional factors in the use of chatbots, the role of content congruence in the process of interacting with them has not been fully explored. Therefore, this study was conducted to test the impact of perceived content congruence on purchasing behavior, based on the integration of social support theory and behavioral reasoning theory. Data were collected from 450 Gen Z consumers who used AI chatbots to make purchasing decisions via online platforms. The Partial Least Squares Structural Equation Modeling (PLS-SEM) analysis process was applied. The findings indicate that perceived content congruence positively influences both relative advantage and satisfaction, which are associated with purchase behavior. The study contributes to theory by being one of the pioneering studies to combine social support theory and behavioral reasoning theory in online commerce. In addition, it provides managerial implications to encourage businesses to increase the personalization of AI chatbot content to enhance the experience and promote the purchase behavior of young customers.