The study of value co-creation for managing customer relationships: AI Chatbot interaction in managing customer complaints on food delivery platform

Abstract

In the highly competitive food delivery platform business, AI-integrated chatbots for complaint management have become essential tools for co-creating value with customers. This research examines and compares the effects of chatbot interactions in emotional-based (Chatbot A), task-based (Chatbot B), and non-customized (Chatbot C) formats on complainants' emotions, perceptions, and satisfaction through within-subjects experiments. It was found that Chatbot A significantly outperforms Chatbots B and C in terms of Perceived Empathy, Perceived Humanness, and Response Satisfaction. Chatbot B significantly outperforms Chatbots A and C in terms of Offer Satisfaction. For Brand Trust, Future Usage Intention, and Overall Satisfaction, there were no significant differences between Chatbots A and B. This indicates that Chatbot A is suitable for co-production processes, helping complainants become more willing to share information through complaints, while Chatbot B excels in Reliability and Assurance dimensions. The appropriate interaction pattern at each stage of value co-creation according to the IEPAR model (Interaction/ Engagement/ Proposal/ Act/ Realized) begins with emotional-based communication showing empathy to establish interaction and engagement, followed by task-based communication emphasizing efficiency and clear proposals alongside emotion-focused communication to lead to acceptance of solutions (Proposal/Act), which will result in positive experiences, trust, and long-term brand loyalty (Realized).