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題名 Chatbot applications in government frontline services: leveraging artificial intelligence and data governance to reduce problems and increase effectiveness
作者 陳敦源
Chen, Don-Yun;Wang, Chian-Wen;Hsu, Bo-Ya
貢獻者 公行系
關鍵詞 Chatbots; artificial intelligence; data governance; human-robot collaboration; digital transformation
日期 2024-09
上傳時間 9-May-2025 11:04:08 (UTC+8)
摘要 Taiwan has been developing digital technology for many years. Whether it is industry or government, Taiwan’s digitalisation level is among the highest in the world. This research aims to show how the application of chatbots and AI technology affects Taiwan’s local governments, what problems have arisen from its operations so far, and what key factors provide a better understanding of the effectiveness of chatbots. Contributions to the transformation of existing digital governments can be used to strengthen governance and political participation. This article adopts a case study approach. The research findings are based on the evaluation model constructed by literature review and in-depth interviews; this ideal model examined the operational effectiveness of existing local government chatbots. Through in-depth interviews, we discovered that human-robot collaboration would be the most beneficial model for using artificial intelligence in the future. In order to maximise the benefits of human-robot collaboration, government agencies must enhance organisational members’ understanding of artificial intelligence through education and training to help cross-domain communication and coordination activities with entrusted units and through education and training to build an organisational culture that supports the organisation’s digital transformation.
關聯 Asia Pacific Journal of Public Administration, Vol.46, No.4, pp.488-511
資料類型 article
DOI https://doi.org/10.1080/23276665.2024.2397677
dc.contributor 公行系
dc.creator (作者) 陳敦源
dc.creator (作者) Chen, Don-Yun;Wang, Chian-Wen;Hsu, Bo-Ya
dc.date (日期) 2024-09
dc.date.accessioned 9-May-2025 11:04:08 (UTC+8)-
dc.date.available 9-May-2025 11:04:08 (UTC+8)-
dc.date.issued (上傳時間) 9-May-2025 11:04:08 (UTC+8)-
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/156865-
dc.description.abstract (摘要) Taiwan has been developing digital technology for many years. Whether it is industry or government, Taiwan’s digitalisation level is among the highest in the world. This research aims to show how the application of chatbots and AI technology affects Taiwan’s local governments, what problems have arisen from its operations so far, and what key factors provide a better understanding of the effectiveness of chatbots. Contributions to the transformation of existing digital governments can be used to strengthen governance and political participation. This article adopts a case study approach. The research findings are based on the evaluation model constructed by literature review and in-depth interviews; this ideal model examined the operational effectiveness of existing local government chatbots. Through in-depth interviews, we discovered that human-robot collaboration would be the most beneficial model for using artificial intelligence in the future. In order to maximise the benefits of human-robot collaboration, government agencies must enhance organisational members’ understanding of artificial intelligence through education and training to help cross-domain communication and coordination activities with entrusted units and through education and training to build an organisational culture that supports the organisation’s digital transformation.
dc.format.extent 109 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) Asia Pacific Journal of Public Administration, Vol.46, No.4, pp.488-511
dc.subject (關鍵詞) Chatbots; artificial intelligence; data governance; human-robot collaboration; digital transformation
dc.title (題名) Chatbot applications in government frontline services: leveraging artificial intelligence and data governance to reduce problems and increase effectiveness
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.1080/23276665.2024.2397677
dc.doi.uri (DOI) https://doi.org/10.1080/23276665.2024.2397677