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论文编号：	15326
作者编号：	2120223805
上传时间：	2025/6/5 15:46:28
中文题目：	政务智能客服用户满意度研究
英文题目：	Research on user satisfaction of government intelligent customer service
指导老师：	王芳
中文关键字：	政府智能客服；用户满意度；实验研究；情感信任；拟人化风格
英文关键字：	Government Intelligent Customer Service; User Satisfaction; Experimental Research; Government Services; Optimization of Intelligent Customer Service
中文摘要：	在人工智能技术蓬勃发展的背景下，智能客服广泛应用于各领域，政府智能客服也成为提升政务服务效能的关键举措。然而，其用户满意度问题备受关注。本研究聚焦于政府智能客服与人工客服的用户满意度差异，旨在为政府智能客服优化提供科学依据。研究采用实验研究方法，以浙江省政务服务平台和杭州12345政务服务热线为依托，选取36名性别、学历、年龄分布均匀的参与者，分为三组分别体验文字智能客服、语音智能客服和人工客服服务。精心设计10个涵盖不同难度和用户情感状态的问题，通过自制的满意度问卷，从服务响应速度、回答准确性、问题解决程度、沟通友好度等多个维度，采用5分制量化用户满意度，并控制身份、年龄、性别等多种可能影响结果的变量。 研究结果将全面呈现智能客服与人工客服在各关键指标上的表现差异，深入分析不同问题复杂度、用户情绪对满意度的影响。研究发现，智能客服在处理简单问题时效率较高，但在处理复杂问题和应对情绪化用户时存在局限性，人工客服则在复杂问题处理和情感支持方面表现更优。基于此，为政府智能客服优化提出针对性建议。 此外，本研究通过对被试者的访谈中，获取了真实的客服使用体验文本数据，通过案例研究和文本分析，从智能客服、人工客服以及二者类比的角度提出实践对策，为推动政务客服建设提供了新的思路。本研究成果具有广泛的应用价值与深远的社会意义。一方面，政府部门可依据研究结论，有针对性地对智能客服系统进行升级改造，合理分配智能客服与人工客服的工作任务，优化服务流程，从而显著提升政务服务的整体质量与效率，切实增强民众对政务服务的认可度与信赖感。另一方面，研究过程中所采用的科学方法与严谨思路，为其他地区或领域开展类似对比研究提供了可借鉴的范例，有助于推动整个行业在智能客服应用方面的深入探索与良性发展。从长远来看，这不仅有助于提升政府部门的公信力，还能促进政务服务与民众需求之间的精准对接，营造更加和谐、高效的政务服务环境，为构建数字化、智能化的现代社会治理体系贡献关键力量。
英文摘要：	Against the backdrop of the booming development of artificial intelligence technology, intelligent customer service has been widely applied in various fields, and government intelligent customer service has also become a crucial measure to enhance the efficiency of government services. However, the issue of its user satisfaction has received much attention. This research focuses on the differences in user satisfaction between government intelligent customer service and human customer service, aiming to provide a scientific basis for the optimization of government intelligent customer service. The research adopts an experimental research method, relying on the Zhejiang Government Service Platform and the Hangzhou 12345 Government Service Hotline. 36 participants with a uniform distribution of gender, education level, and age were selected and divided into three groups to experience text - based intelligent customer service, voice - based intelligent customer service, and human customer service respectively. Ten questions covering different levels of difficulty and user emotional states were carefully designed. A self - made satisfaction questionnaire was used to measure user satisfaction from multiple dimensions such as service response speed, answer accuracy, problem - solving degree, and communication friendliness, with a 5 - point scale used to quantify user satisfaction. Additionally, various variables that may affect the results, such as identity, age, and gender, were controlled. The research results will comprehensively present the performance differences between intelligent customer service and human customer service in key indicators, and deeply analyze the impact of different problem complexities and user emotions on satisfaction. The study found that intelligent customer service is more efficient in handling simple problems, but has limitations in dealing with complex problems and emotional users. In contrast, human customer service performs better in handling complex problems and providing emotional support. Based on this, targeted suggestions are put forward for the optimization of government intelligent customer service, such as improving natural language processing capabilities, enhancing emotional recognition capabilities, and optimizing complex problem - handling mechanisms. At the same time, it is recommended that government departments strengthen the collaborative work between intelligent customer service and human customer service, allocate resources reasonably, improve the overall satisfaction and credibility of government services, promote the digital transformation of government services, facilitate positive interactions between the government and the public, and contribute to the construction of smart government services. In addition, this research points out the limitations of a small sample size and a relatively single experimental environment, and looks ahead to future research directions such as expanding the sample size, introducing more emotional factors, and exploring the long - term use effects. This research fills the gap in the research field of government intelligent customer service theoretically, deepens the research on user satisfaction, and provides practical guidance for the optimization of government intelligent customer service and the improvement of the quality of government services in practice, thus having important theoretical and practical values.
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