文章摘要
杨玲珊,朱亮.基于Kano模型的学术趋势分析工具功能优化研究[J].数字图书馆论坛,2023,(7):63~72
基于Kano模型的学术趋势分析工具功能优化研究
Function Optimization of Academic Trend Analysis Tools Based on Kano Model
投稿时间:2023-04-27  
DOI:10.3772/j.issn.1673-2286.2023.07.007
中文关键词: 学术趋势分析工具;Kano模型;用户满意度;功能优化
英文关键词: Academic Trend Analysis Tool; Kano Model; User Satisfaction; Function Optimization
基金项目:本研究得到中国农业科学院科技创新工程“农业智能知识服务关键技术及产品研发”(编号:CAAS-ASTIP-2023-AII)资助。
作者单位
杨玲珊 中国农业科学院农业信息研究所 
朱亮 中国农业科学院农业信息研究所;国家新闻出版署农业融合出版知识挖掘与知识服务重点实验室;农业农村部农业大数据重点实验室 
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中文摘要:
      科研规模的增长推动着学术趋势分析工具的蓬勃发展,自20世纪90年代起,学术趋势分析工具层出不穷。鉴于用户实际需求与工具功能存在不对等关系,调研学术趋势分析工具功能的属性成为提升其服务质量的重要方式。通过文献调研、问卷调查及Kano模型对学术趋势分析工具的功能进行属性分类,并进行敏感度与优先度分析。将学术趋势分析工具的功能分为基本属性、期望属性、魅力属性和无差异属性,并基于Better-Worse-R矩阵,分析各功能要素对用户满意度的影响水平,进而对学术趋势分析工具的优化方向进行探讨,以期为学术趋势分析工具的开发或改进提供参考。
英文摘要:
      The growth of scientific research scale promotes the vigorous development of academic trend analysis tools, which have emerged in an endless stream since the 1990s. In view of the unequal relationship between users’ actual needs and tool functions, investigating the attributes of academic trend analysis tools’ functions has become an important way to improve their service quality. Based on literature research, questionnaire survey, and Kano model,this paper classifies the functions of academic trend analysis tools, and analyzes their sensitivity and priority. The functions of academic trend analysis tools are divided into must-be type, one-dimensional type, attractive type, and indifferent type. Based on the Better-Worse-R matrix, the influence of each functional element on user satisfaction is analyzed and the optimization direction of academic trend analysis tools is discussed, so as to provide references for the development or improvement of academic trend analysis tools.
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