AI电商客服与人工客服服务质量的比较研究——基于SERVQUAL模型的分析

A Comparative Study of Service Quality in AI-Powered and Human-Provided E-Commerce Customer Service—An Analysis Based on the SERVQUAL Model

摘要: 随着人工智能技术的快速发展，智能客服在电商平台中得到广泛应用。然而，AI客服与人工客服在服务质量方面存在差异，如何优化客服体系成为电商平台面临的重要课题。本研究借助SERVQUAL模型所包含的五个评价维度——即有形性、可靠性、响应性、保证性及同理心，对AI客服与人工客服在服务质量上的异同展开系统比较，并区分传统IVR、关键词匹配机器人与生成式AI客服的服务特征。研究发现：AI客服在响应性方面具有相对优势，适合处理标准化、重复性问题；人工客服在同理心和保证性方面表现更为稳健，在处理复杂问题和建立情感连接方面具有一定优势；生成式AI客服相较早期规则型客服，在连续对话、解释生成与情绪安抚方面表现出一定改进潜力。基于此，本文提出构建基于问题复杂度、客户情绪指数和客户价值的动态路由模型，提升AI客服智能化水平，加强情感交互能力，优化客服服务流程，为电商平台提升服务质量提供参考。

Abstract: With the rapid advancement of artificial intelligence, AI-powered customer service has become widely adopted on e-commerce platforms. However, differences remain between AI and human customer service in terms of service quality. Drawing on the SERVQUAL model, this study systematically compares their performance across five dimensions and distinguishes traditional IVR, keyword-matching chatbots, and generative AI customer service. The findings show that AI customer service has a relative advantage in responsiveness and is well suited to handling standardized and repetitive inquiries, while human customer service remains more robust in empathy and assurance and still holds certain advantages in handling complex issues and building emotional connections. Compared with earlier rule-based systems, generative AI customer service shows improvement potential in continuous dialogue, explanation generation, and emotional soothing. Based on these findings, this paper proposes a dynamic routing model based on issue complexity, customer emotion index, and customer value, providing practical references for e-commerce platforms to optimize service quality.