Human–chatbot interaction, social support and public value co-creation: Evidence from users of government chatbots in China

Abstract

Despite the growing significance of government chatbots in the public management domain, limited research has examined government chatbots users’ public value co-creation behavior through the lens of human–chatbots interaction attributes and social support. This study adopts two-stage analytical approach: structural equation modeling (SEM) followed by artificial neural network (ANN) analysis to unearth the key determinants of public value co-creation behavior among government chatbot users. Data were collected from 431 respondents in mainland China via a leading online survey platform. The results reveal that perceived intelligence and informational support positively affect users’ public value co-creation behavior, while perceived privacy concerns have a negative effect. In contrast, perceived social interactivity and emotional support do not show a significant impact. These results add to the theoretical understanding of user behavior in government contexts by highlighting the role of human–chatbot interaction attributes and support mechanisms. They also offer practical implications for government chatbots managers by suggesting strategies such as enhancing chatbot intelligence and improving informational support, to foster active user participation in public value co-creation initiatives.