As artificially intelligent conversational agents (ICAs) become a popular customer service solution for businesses, understanding the drivers of user acceptance of ICAs is critical to ensure its successful implementation. To provide a comprehensive review of factors affecting consumers' adoption and use of ICAs, this study performs a systematic literature review of extant empirical research on this topic. Based on a literature search performed in July 2019 followed by a snowballing approach, 18 relevant articles were analyzed. Factors found to influence human-machine cognitive engagement were categorized into usage-related, agent-related, user-related, attitude and evaluation, and other factors. This study proposed a collective model of users' acceptance and use of ICAs, whereby user acceptance is driven mainly by usage benefits, which are influenced by agent and user characteristics. The study emphasizes the proposed model's context-dependency, as relevant factors depend on usage settings, and provides several strategic business implications, including service design, personalization, and customer relationship management.

中文翻译：

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影响用户采用和使用会话代理的因素：系统评价

随着人工智能会话代理 (ICA) 成为企业流行的客户服务解决方案，了解用户接受 ICA 的驱动因素对于确保其成功实施至关重要。为了全面回顾影响消费者采用和使用 ICA 的因素，本研究对该主题的现有实证研究进行了系统的文献回顾。基于 2019 年 7 月进行的文献检索，然后采用滚雪球方法，分析了 18 篇相关文章。发现的影响人机认知参与的因素分为使用相关、代理相关、用户相关、态度和评估以及其他因素。本研究提出了用户接受和使用 ICA 的集体模型，其中用户接受主要由使用利益驱动，受代理和用户特征的影响。该研究强调了所提议模型的上下文相关性，因为相关因素取决于使用设置，并提供了若干战略业务影响，包括服务设计、个性化和客户关系管理。