Emotional Communication Between Chatbots and Users: An Empirical Study on Online Customer Service System
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
In a digital environment, chatbots act as customer service agents to assist consumers in making decisions. Improving the service efficiency of chatbots has aroused widespread concern in the industry and academia. Based on the computer as a social actor (CASA) and emotional contagion theory, this study explores the influence mechanism of quality assessment in the process of communication between users and human-machine customer service, investigates the relationship between chatbot performance and user perception, and constructs an assessment model for the quality of communication process. It adopts partial least squares (PLS) structural equation modelling (SEM) to evaluate the research model and hypothesis. Based on 163 samples, the results show that, in the process of communication, users’ perception of the robot’s ability, especially the accuracy and effectiveness of the robot, will significantly affect users’ evaluation of the quality of communication. At the same time, the language style of the chatbot has little impact on the evaluation of the quality of communication. The results of this study provide important insights into the rational use of human-computer interaction in e-commerce and lay a foundation for understanding the service mechanism and related theories of online service agents in artificial intelligence.