人工智能辅助学术期刊同行评议的功能需求分析

Analysis of functional requirements for AI-assisted academic journal peer review

为剖析人工智能(AI)技术在学术期刊同行评议中应用的功能需求层次,借助魅力质量理论和Kano模型分析工具,提出人工智能辅助学术期刊同行评议功能需求的分析方法。采用问卷调查法,通过Better-Worse系数分析将9种AI辅助学术期刊同行评议的功能分为必备属性、一维属性和魅力属性3类,进一步甄别出4种需重点开发或优化的功能,并提出相应建议。研究结果为AI辅助学术期刊同行评议的功能需求分析提供了理论方法和数据支撑。

To analyze the functional requirements for artificial intelligence(AI)technology applied to academic journal peer review,a method of analysis for the functional requirements of AIassisted academic journal peer review is proposed by introducing the attractive quality theory and the analysis tool of Kano model.The questionnaire survey method is used.Nine functions of AI-assisted academic journal peer review are divided into three categories via Better-Worse coefficient analysis,i.e.,the essential attribute,the one-dimensional attribute,and the attractive attribute.Subsequently,four important functions to be developed or optimized with much emphasis are identified,and the corresponding suggestions are made.The research results provided the theoretical method and data support for the functional requirement analysis of AI-assisted academic journal peer review.