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| 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 |
| 投稿时间：2021-06-24 修订日期：2021-09-07 |
| DOI： |
| 中文关键词: 同行评议 学术期刊 用户需求 人工智能 Kano模型 魅力质量理论 |
| 英文关键词: peer review academic journals customer requirement artificial intelligence Kano model theory of attractive quality |
| 基金项目:中国科技期刊卓越行动计划选育高水平办刊人才子项目—青年人才支持项目（2020ZZ111042）；中国高校科技期刊研究会“一流高校科技期刊建设”专项基金（CUJS2021-007） |
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| 摘要点击次数: 217 |
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| 中文摘要: |
| 为剖析人工智能（artificial intelligence, 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功能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。 |
| 英文摘要: |
| 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 AI-assisted 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 provide the theoretical method and data support for the functional requirement analysis of AI-assisted academic journal peer review. |
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