Measuring the Role of Trust and Information Quality on Intention to Use AI Chatbots in Mobile Shopping: A Structured Equation Modeling Approach

The integration of artificial intelligence (AI) chatbots in online shopping platforms has gained traction, offering personalized assistance and enhancing the customer experience. However, ensuring consumer acceptance and adoption of these conversational agents remains a challenge. The present research examines the elements shaping consumer perspectives and objectives regarding the utilization of AI chatbots in mobile shopping applications by proposing an extended Technology Acceptance Model (TAM) framework. Drawing from prior literature, the model incorporates constructs such as trust, information quality to the traditional TAM. 309 usable responses were collected through online survey and analyzed through Structural equation modeling (SEM). The findings reveal that usefulness, attitude, trust, and information quality significantly influence consumers' intentions to use AI chatbots for mobile shopping. Additionally, perceived ease of use emerged as a significant predictor of perceived usefulness, while perceived usefulness positively affected attitude toward using. This research enriches the current understanding by furnishing empirical data on the factors driving the adoption of AI chatbots within the realm of mobile shopping. Discussions delve into theoretical and practical implications, underscoring the significance of designing chatbots that are valuable, user-friendly, trustworthy, and informative to cultivate consumer acceptance. Limitations and future research directions are also outlined.