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系列并购对企业全要素生产率的影响:数字化转型的中介作用。

The impact of serial mergers and acquisitions on enterprises' total factor productivity: The mediating role of digital transformation.

机构信息

School of Business Administration, University of Science and Technology Liaoning, Anshan, Chinae.

出版信息

PLoS One. 2024 Nov 20;19(11):e0311045. doi: 10.1371/journal.pone.0311045. eCollection 2024.

Abstract

RESEARCH BACKGROUND

M&A (Mergers and acquisitions) is a strategic measure for enterprises to expand their scale, enhance their competitiveness and improve productivity in the market competition. As a new factor of production, data is changing the factor input model and value creation path of enterprises.

RESEARCH OBJECTIVES

From the perspective of serial M&A, this study explores the impact of serial M&A on enterprises' TFP (total factor productivity) and the mechanism of digital transformation between them.

RESEARCH METHODS

Take the serial M&A transactions of China's A-share listed companies from 2010 to 2019 as samples, using the theory of organizational learning to analyze the relationship among serial M&A, enterprises' TFP and the degree of digital transformation. Three-step regression is used to construct a model that serial M&A indirectly affects enterprises' TFP through intermediary variable digital transformation.

RESEARCH FINDING

There is a significant inverse U-shaped relationship between serial M&A and enterprises' TFP, and digital transformation plays a mediating role in this relationship. The impact of serial M&A on enterprises' TFP shows an upward trend at first and then a downward trend and this relationship is indirectly realized through digital transformation. The results are still valid after considering the change-explained variables, lag test, Sobel-Goodman test, and Bootstrap test. Heterogeneity analysis shows that for enterprises with non-state-owned property rights, smaller enterprise scale, and higher business environment index, serial M&A has a more obvious effect on TFP indirectly through the degree of digital transformation.

RESEARCH VALUE

It further enriches the existing literature on the decision-making of M&A from the perspective of serial M&A and profoundly reveals the mechanism of the degree of digital transformation in the relationship between serial M&A and enterprises' TFP. The research provides theoretical support and empirical evidence for enterprises to achieve high-quality development.

摘要

研究背景

并购(Mergers and acquisitions)是企业在市场竞争中扩大规模、提高竞争力、提高生产力的战略措施。作为一种新的生产要素,数据正在改变企业的要素投入模式和价值创造路径。

研究目的

从连续并购的角度出发,本研究探讨了连续并购对企业全要素生产率(total factor productivity,TFP)的影响及其与数字化转型之间的机制。

研究方法

以 2010 年至 2019 年中国 A 股上市公司的连续并购交易为样本,运用组织学习理论分析连续并购、企业 TFP 与数字化转型程度之间的关系。采用三步回归构建了一个模型,即连续并购通过中介变量数字化转型间接影响企业的 TFP。

研究发现

连续并购与企业 TFP 之间存在显著的倒 U 型关系,数字化转型在这一关系中起着中介作用。连续并购对企业 TFP 的影响呈现出先上升后下降的趋势,这种关系通过数字化转型间接实现。在考虑了变化解释变量、滞后检验、Sobel-Goodman 检验和 Bootstrap 检验后,结果仍然有效。异质性分析表明,对于非国有产权、企业规模较小、商业环境指数较高的企业,连续并购通过数字化转型程度对 TFP 的间接影响更为明显。

研究价值

它从连续并购的角度进一步丰富了现有关于并购决策的文献,并深刻揭示了数字化转型程度在连续并购与企业 TFP 关系中的作用机制。该研究为企业实现高质量发展提供了理论支持和经验证据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb72/11578476/d402b2ff5194/pone.0311045.g001.jpg

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