摘要
以2007~2021年A股上市公司并购事件为样本,通过年报文本分析法构建并购方“大数据”应用程度的指标,检验并购方大数据应用对并购绩效的影响,研究发现:相对于没有应用大数据的并购方,应用大数据的并购方总体上获得了更高的并购绩效;信息获取是大数据提高并购方并购绩效的主要机制;大数据对并购绩效的提升作用仅限于目标公司为公众公司,当目标公司为非公众公司时,大数据难以显著提高并购方的并购绩效,说明大数据分析只能根据目标公司的公开资料提供有限信息;并购方与目标公司存在董事联结,能够强化大数据对并购绩效的提升作用,尤其强化了目标公司为公众公司时(与目标公司为非公众公司相比)的并购绩效,说明机器的有限“硬信息”与人的“软信息”相结合更能够显著提高并购绩效。因此,“人机协同”或许是数字时代提高并购绩效的有效策略。
This paper,by using merger and acquisition(M&A)events of A-share listed companies in China from 2007 to 2021 as a sample,and constructing indicators of the degree of“big data”application by M&A parties through text analysis of annual reports,tests the impact of big data application by M&A parties on M&A performance.It is found that M&A parties that apply big data obtain a higher overall M&A performance compared to those that do not apply big data.In addition,information access is the main mechanism by which big data improves the M&A performance of M&A parties.Moreover,the enhancement effect of big data on M&A performance is limited to the target company being a public company.When the target company is a non-public company,it is difficult for big data to significantly improve the M&A performance of the M&A party,indicating that big data analysis can only provide limited information based on the public information of the target company.Furthermore,the effect of big data on M&A performance is enhanced when there is a link between the M&A party and the directors of the target company, especially when the target company is a public company (compared with a non-public company), indicating that the combination of limited “hard information” of machines and “soft information” of people can significantly improve the M&A performance. Therefore, “human-computer cooperation” may be an effective strategy to improve the M&A performance in the digital age.
作者
武琼
柳扬
谢雁翔
刘孟晖
WU Qiong;LIU Yang;XIE Yanxiang;LIU Menghui(School of Management,Lanzhou University,Lanzhou 730000,China;Business School,Nankai University,Tianjin 300071,China;Business School,Zhengzhou University,Zhengzhou 450001,China)
出处
《系统管理学报》
CSCD
北大核心
2024年第3期824-839,共16页
Journal of Systems & Management
基金
国家自然科学基金青年科学基金资助项目(72202088)
甘肃省基础研究计划——软科学专项资助项目(22JR4ZA039)
中央高校基本科研业务费专项资金资助项目(22lzujbkydx028)。
关键词
大数据
有限信息
董事联结
并购绩效
big data
limited information
director linkage
merger and acquisition(M&A)performance