Why users continue E-commerce chatbots? Insights from PLS-fsQCA-NCA approach
Behzad Foroughi, Tran Quang Huy, Mohammad Iranmanesh, Morteza Ghobakhloo, Abderahman Rejeb, Davoud Nikbin
Abstract
The study investigates the drivers of intention to continue using chatbots. Data were collected from 476 users and analyzed using the partial least squares (PLS), fuzzy-set qualitative comparative analysis (fsQCA), and necessary condition analysis (NCA) approaches. Based on PLS results, all technology continuance theory (TCT) relationships were verified except for the influence of confirmation and perceived ease of use on perceived usefulness. Information, service, and system quality influence perceptions. Social avoidance and distress positively moderate the impact of attitude on continuance intention. fsQCA revealed five configurations of variables resulting in high continuance intention, and NCA identified perceived ease of use and system quality as necessary conditions. The study extended the literature by identifying the predictors of continuance intention to use chatbots, enriching TCT, demonstrating the moderating influence of social avoidance and distress, and using the PLS-fsQCA-NCA approach. The findings offer practical implications for businesses, enabling them to retain chatbot users.