From self-service to AI-assisted service: A mixed-method study of IT support service provision using search tools and chatbots

IF 20.1 1区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE
Antino Kim , Agrim Sachdeva , Alan R. Dennis
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引用次数: 0

Abstract

Organizations are increasingly adopting chatbots for self-service IT support alongside traditional search tools to supplement human-staffed IT support desks. This raises the question of whether investing in chatbots is warranted, given the presence of well-established traditional search tools serving a similar function. We investigate how chatbots compare to self-service search tools from the user’s perspective. We conducted three experiments and a transcript analysis study in the context of self-service IT support using a chatbot versus a search tool, both running on the same large IT support knowledge base. All three experiments found higher user satisfaction with the chatbot than with the search tool. The main study investigated two potential theoretical mechanisms underlying these effects: (i) perceived assistance and (ii) co-creating questions with the chatbot to find an answer. Both significantly contributed to users’ satisfaction and willingness to use, with perceived assistance fully mediating the effect of the chatbot. The transcript analysis study showed that 57 % of user questions were quickly answered (1–2 conversation turns), and another 22 % quickly abandoned without an answer. Co-creation was important in successfully answering the remaining 21 % of questions that took longer than two conversation turns. We conclude that organizations can enhance their self-service IT support by integrating chatbots alongside existing traditional search tools. This transformation effectively shifts the self-service experience into an AI-assisted service experience for users.
从自助服务到人工智能辅助服务:使用搜索工具和聊天机器人提供IT支持服务的混合方法研究
组织越来越多地采用聊天机器人进行自助IT支持,以及传统的搜索工具,以补充人工IT支持台。这就提出了一个问题:考虑到现有的传统搜索工具具有类似的功能,投资聊天机器人是否有必要。我们从用户的角度研究了聊天机器人与自助搜索工具的比较。我们在使用聊天机器人和搜索工具的自助IT支持上下文中进行了三个实验和一个记录分析研究,两者都运行在相同的大型IT支持知识库上。所有三个实验都发现,用户对聊天机器人的满意度高于搜索工具。主要研究调查了这些影响背后的两种潜在理论机制:(i)感知帮助和(ii)与聊天机器人共同创造问题以找到答案。两者都对用户的满意度和使用意愿有显著贡献,感知帮助完全调解了聊天机器人的效果。成绩单分析研究表明,57 %的用户问题得到了快速回答(1-2次对话回合),另有22 %的用户在没有答案的情况下迅速放弃。共同创造对于成功回答其余21% %耗时超过两次对话的问题很重要。我们的结论是,组织可以通过将聊天机器人与现有的传统搜索工具集成在一起来增强他们的自助IT支持。这种转变有效地将自助服务体验转变为人工智能辅助的用户服务体验。
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来源期刊
International Journal of Information Management
International Journal of Information Management INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
53.10
自引率
6.20%
发文量
111
审稿时长
24 days
期刊介绍: The International Journal of Information Management (IJIM) is a distinguished, international, and peer-reviewed journal dedicated to providing its readers with top-notch analysis and discussions within the evolving field of information management. Key features of the journal include: Comprehensive Coverage: IJIM keeps readers informed with major papers, reports, and reviews. Topical Relevance: The journal remains current and relevant through Viewpoint articles and regular features like Research Notes, Case Studies, and a Reviews section, ensuring readers are updated on contemporary issues. Focus on Quality: IJIM prioritizes high-quality papers that address contemporary issues in information management.
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