基于文献计量的大数据管理决策研究热点分析

传统的模型驱动的决策范式正在演变成大数据驱动的决策新范式，国家自然科学基金委员会于2015年启动了“大数据驱动的管理与决策研究”重大研究计划，以推动我国管理学领域大数据的基础研究.本文以重大研究计划资助的14个项目的文本信息，及2012年~2019年在51种管理类重要国际期刊上发表的近6000篇论文为基础，利用文本挖掘与文献计量方法，从词粒度和主题粒度展开比较分析，并对部分以大数据作为关键词的文献按研究方向进行分类分析.对比分析结果清晰地呈现出大数据驱动的研究在管理学领域的研究态势和创新脉络；剖析国内学者与国际领域主流关注的焦点与异同；揭示出大数据驱动的管理与决策方向上研究热点及其演化趋势，以及未来值得深入研究的一些科学问题.

Status and trends in big-data-driven managerial decision-making on bibliometric

Big data and data science are emerging as a new paradigm and tool in management research. In such contexts, the National Natural Science Foundation of China (NSFC) has launched a major research program since 2015: Big Data driven Management and Decision (BDMD), so as to promote China''s fundamental research on big data. Text mining and bibliometric analysis are applied to studing the textual information of 114 granted projects under the BDMD major research program as well as nearly 6000 articles from 51 leadinginternational journals over the last 8 years. Our comparative analysis is performed at both the keyword-level and topic-level. The paper also attempts to examine those literatures explicitly claiming big data along with the PAGE framework and by classifing them into different categories. Our research highlights the dynamic BDMD research landscape, with its focus constantly moving to new challenges due to new technological developments. Our findings are able to reveal the current research interests and the revolution trends in the field of BDMD. Furthermore, the comparative analysis between NSFC grants data and bibliometric data provides a robust roadmap for future research in the BDMD field.