MODELING THE EFFECTS OF CHATBOT RESPONSIVESS, USEFULNESS, AND PERCEIVED RISK ON E-COMMERCE USER SATISFACTION AND BEHAVIORAL INTENTION

As e-commerce grows quickly in Indonesia, more businesses are using AI chatbots to make their services more efficient and available. These chatbots are meant to provide quick, useful answers that can improve the customer experience and encourage people to keep using the service. Still, many users worry about how reliable chatbots are, whether their data is safe, and if the responses are accurate. These concerns can make people feel there is a high risk, which may lower their satisfaction and make them less likely to keep using the service. Although past studies have looked at these issues one at a time, there is research that examines them together. This study aims to analyze the influence of chatbot responsiveness, usability, and risk perception on user satisfaction and behavioral intentions, and to examine the mediating role of satisfaction in these relationships. This study used a quantitative approach with 403 active e-commerce users from Shopee, Tokopedia, Lazada, and Blibli. Data analysis was carried out using the Partial Least Squares Structural Equation Modeling (PLS-SEM) method with SmartPLS 4. To add depth to the findings, qualitative guerrilla interviews were also conducted to capture real user experiences. This result found that when chatbots are responsive and easy to use, customers are more satisfied and more likely to act positively. However, if customers feel there is risk, their satisfaction drops. Customer satisfaction partly explains how these factors affect what people do, but it does not account for everything. The study showed that when chatbots are responsive and helpful, users are more satisfied and more likely to use them again. However, if users feel there is a high risk, their satisfaction drops. These results help explain how people in emerging markets adopt AI chatbots and offer useful guidance for e-commerce companies looking to design more trustworthy, reliable chatbots.