This study aims to investigate how chatbots’ warmth and competence affect customer behavioural expectation (i.e. purchase, recommendation) through perceived humanness and perceived persuasiveness. Moreover, prior knowledge of chatbot is considered the boundary condition of the effects of chatbots’ warmth and competence.
A lab-in-field experiment with 213 participants and a scenario-based experiment of 186 participants were used to test the model using partial least squares structural equation modelling via SmartPLS 4.
Chatbot warmth positively affects customer behavioural expectation through perceived humanness while chatbot competence positively affects customer behavioural expectation through perceived persuasiveness. Prior knowledge of chatbot positively moderates the effect of chatbot warmth on perceived humanness.
This study provides nuanced insights into the effects of chatbots’ warmth and competence on customer behavioural expectation. Future studies could extend the model by exploring additional boundary conditions of the effects of chatbots’ warmth and competence in different generations.
This study offers insightful suggestions for marketing managers on how to impress and convert online customers through designing verbal scripts in customer−chatbot conversations that encourage the customers to anthropomorphise the chatbots.
This study probes into the effects of chatbots’ warmth and competence on customer behavioural expectation by proposing and examining a novel research model that incorporates perceived humanness and perceived persuasiveness as the explanatory mechanisms and prior knowledge of chatbot as the boundary condition.
