Understanding AI-based customer service resistance: A perspective of defective AI features and tri-dimensional distrusting beliefs

Communicating with customers through AI-based chatbots in customer service (AISC) has become increasingly popular for many companies. However, in actual service encounters, AISC seems defective and is not always accepted by customers. Occasionally it is even resisted. This study aims to investigate such customer resistance. In addition to two cognition-centered AI features (i.e., irrelevant and biased information) discussed in prior studies, this study proposes that lack of empathy is another key feature of defective AI (i.e., in its emotional dimension) and investigates the underlying mechanism of empathy. Specifically, this study proposes three pathways in which empathy functions are lacking. A survey was conducted to test our hypotheses, and the results suggest that lack of empathy has three effects on customer resistance: direct, indirect, and moderating. Finally, theoretical contributions and practical implications are discussed.