Satisfaction with AI chatbots in crowdsourcing services: anthropomorphic and fairness perspectives
Le Yi Koh, Yek Guo Cheh, Kum Fai Yuen, Xueqin Wang · Behaviour and Information Technology · 2025
The creation of human-like AI chatbots for service interactions has raised controversies about whether such technologies can truly generate a personal touch while improving fairness perception and overall customer experience. Pivoting on computer as social actors and perceived justice theories, this research examines and updates the factors influencing customers’ satisfaction with AI chatbots in the modern era. An online questionnaire was conducted in Singapore and 450 valid responses were collated. Structural equation modelling was utilised to investigate the model and the gathered data. The outcomes of this study have shown that perceived anthropomorphic characteristics and perceived empathy have significant and positive impacts on customers’ perceptions of interactional justice, distributive justice, and procedural justice. These justice perceptions then create trust in the AI chatbots and consequently influence customer satisfaction. The findings have substantiated the use of AI chatbots from anthropomorphic and fairness contexts. They also provide theoretical and managerial contributions for existing and future service providers that adopt AI chatbots.