ABSTRACT

Chatbots link companies and users, increase conversions, reduce labor costs, and provide answers based on big data. Since COVID-19, demand for non-face-to-face services has increased. Despite expectations, chatbot use is inconsistent and satisfaction is low. This study identifies factors for improving the sustainability of chatbot services by considering artificial intelligence factors (personalization, anthropomorphism, social presence) and systemic factors (responsiveness, compatibility). The confirmatory factor analysis and structural equation model of the measurement model were analyzed using Smart PLS 3.3. Two hypotheses were rejected because the effect on expectation-confirmation was not statistically significant. This study presents implications for future chatbot research and development.

摘要

聊天机器人连接企业和用户，提高转化率，降低劳动力成本，并根据大数据提供答案。自 COVID-19 以来，对非面对面服务的需求有所增加。尽管有预期，但聊天机器人的使用不一致且满意度较低。本研究通过考虑人工智能因素（个性化、​​拟人化、社会存在）和系统因素（响应性、兼容性），确定了提高聊天机器人服务可持续性的因素。利用Smart PLS 3.3对测量模型进行验证性因子分析和结构方程模型分析。两个假设被拒绝，因为对期望确认的影响在统计上并不显着。这项研究对未来聊天机器人的研究和开发具有重要意义。