中国管理科学领域热点主题识别与趋势预测  

Identifying Hot Topics and Trend Prediction of Management Science in China

作　　者：余辉 梁镇涛 张羽帆 Yu Hui;Liang Zhentao;Zhang Yufan(Center for Studies of Information Resources,Wuhan University,Wuhan 430072,China)

机构地区：[1]武汉大学信息资源研究中心,湖北武汉430072

出　　处：《中国科技论坛》2021年第8期145-156,共12页Forum on Science and Technology in China

基　　金：教育部人文社会科学研究一般项目“基于引文内容分析的交叉学科知识生长路径和融合模式研究”(19YJC870018)。

摘　　要：识别和预见管理科学领域内的研究热点及其发展趋势,对相关学者和科研管理机构把握研究方向、有效分配科研经费具有重要意义。本研究借鉴引文分析中“睡美人”文献识别方法,以国家自然科学基金委员会(NSFC)指定管理科学的重要期刊近20年所刊载文献为分析数据源,对其进行关键词语义聚类识别出研究主题,依据主题沉睡时长特征和主题热度综合把主题类划分为睡美人特征热点、成熟热点、潜力热点和其他共4类,并用美丽系数来识别睡美人特征主题浮现点,结合热点浮现点对主题类进行研究热度预测,采用累计增长数曲线对比验证其合理性。结果表明,创新能力、关系网络、行为意向和资源环保4个主题属于睡美人热点主题;创业人才、国际贸易、工业汽车和行为心理属于潜力热点主题,它们主题浮现点较晚,近年来增长速度较快,很可能成为新兴热点主题。It is important for scholars and research administrators to grasp the direction of research and allocate research funds effectively,which can identify and anticipate research hotspots and their trends in management science.In this study,the literature published in important management science journals designated by National Natural Science Foundation of China(NSFC)in recent 20 years was used as the analysis data source,and the“Sleeping Beauty”literature identification method in citation analysis was used for keyword semantic clustering to identify the research topic.Based on the characteristics of theme dormancy and hotness,the theme class is divided into four categories:sleeping beauty feature hotspots,mature hotspots,potential hotspots and others.The beauty coefficient was used to identify the emergence points of sleeping beauty themes,combined hotspot emergence points to predict the research hotness of the theme categories,and the cumulative growth curve was used to verify its reasonableness.The results show that the four themes of innovation capability,relationship network,behavioral intention and resources and environmental protection belong to the sleeping beauty hot topics.Entrepreneurial talent,international trade,industrial automobiles and behavioral psychology are potential hot topics,which are late to emerge,have grown faster in recent years and are likely to become emerging hot topics.

关 键 词：关键词聚类 主题划分 研究热点 趋势预测 

分 类 号：G353.1[文化科学—情报学]