信息资源管理学报 ›› 2023, Vol. 13 ›› Issue (3): 61-78.doi: 10.13365/j.jirm.2023.03.061

• 计量经济模型 • 上一篇    下一篇

国内基于二手数据计量经济模型的信息管理与信息系统研究综述:研究方法、前沿热点与理论运用

陈丽萍 任菲   

  1. 北京大学光华管理学院,北京,100871
  • 出版日期:2023-05-26 发布日期:2023-06-09
  • 作者简介:陈丽萍,博士生,研究方向为信息系统管理、数字化转型等;任菲(通讯作者),博士,教授,研究方向为电子商务、用户在线行为、社交媒体、数字化转型等,Email:fren@gsm.pku.edu.cn。

A Review of Secondary Analysis in Information Management and Information Systems Research in China: Research Methods,Topics, and Theory Applications

Chen Liping Ren Fei   

  1. Guanghua School of Management, Peking University, Beijing, 100871
  • Online:2023-05-26 Published:2023-06-09

摘要: 基于国内信息管理与信息系统(IM&IS)领域2012—2022年发表的282篇基于二手数据的计量经济模型研究论文,深入分析国内该领域研究方法、前沿热点与理论运用的分布情况和发展趋势。研究发现,基于二手数据的计量经济模型研究方法在数据获取和因果检验方面的优势愈发突出,体现在数据来源逐渐多元,因果实证检验愈发严谨,机制分析更加丰富,且混合方法研究开始涌现。四个研究热点分别为宏观数字化发展、企业数字化转型、企业与市场信息交互,以及用户在线行为。然而,现有文献在构建本领域理论和运用中国本土理论思想方面有待进一步加强。本研究创新性地采用文献计量分析与机器学习(LDA、DTM主题模型)相结合的方法,从多维度揭示我国IM&IS领域的二手数据计量经济模型研究的发展概况与趋势,并提出研究展望。研究结论为加强研究规范、把握领域研究热点以及构建与运用理论提供了证据和指引,也为学科发展和科研战略规划提供了建议。

关键词: 信息管理与信息系统, 二手数据计量经济模型, 研究方法, 因果实证检验, 混合方法研究

Abstract: This study conducts a content analysis of 282 Chinese research papers published from 2012 to 2022 that use secondary analysis in the area of information management and information systems (IM&IS), aiming to reveal the distribution and trend of research methods, topics, and theory applications. The results show that the advantages of secondary analysis in data acquisition and causality identification are increasingly prominent, as reflected in the gradual diversity of data sources, rigorous empirical analysis on causality testing, richer mechanism analyses, and the emergence of mixed-method research. Four research topic trends have been identified, including macro digital development, enterprise digital transformation, information interaction between enterprise and market, and user online behavior. However, IM&IS theory development and the application of Chinese theories require further improvement. This study is novel in that it combines bibliometric analysis with machine learning methods (LDA and DTM) to reveal a multi-dimensional overview of the secondary analysis in IM&IS in China. The findings provide evidence and guidelines for further strengthening research norms, grasping research topic trends, developing and applying theories, as well as suggestions for disciplinary development and strategic research planning.

Key words: Information management and information systems, Secondary analysis, Research method, Causality testing, Mixed-method research

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