Does AI chatbot really benefit fashion consumption: empirical evidence from various online customer service

Purpose The study aims to explore two issues: What are the differences in consumer trust, satisfaction, perceived quality and purchase intention caused by different types of online customer service; Will AI chatbots in fashion consumption trigger consumer aversion effects? Design/methodology/approach This empirical study primarily utilizes a survey by questionnaire to statistically analyse consumer perceptions of different customer service types in fashion consumption. The study divides the scenarios into pre-sale and post-sale contexts, with three types of customer service (human vs AI chatbot vs hybrid) in it. 346 and 310 valid samples were collected for further empirical analysis. Findings The analysis reveals that, whether in pre-sale or post-sale scenarios, fashion consumers generally exhibit a strong preference for human customer service during online shopping. In addition, fashion consumers also showed greater acceptance of AI chatbots than hybrid models in pre-sale scenarios. However, in post-sale scenarios, hybrid customer service was preferred over AI chatbots. What’s more, the study further found that purchase intention is the most significantly affected variable across two scenarios. Research limitations/implications The empirical evidence based on differences in customer service types not only expands the theoretical findings of fashion marketing and online service quality management but also triggers some management and social implications related to ethics and employment. Originality/value This study enhances the understanding of how AI contributes to customer service workflows and quality while providing recommendations for brands to advance the development of AI-driven customer service.