运筹与管理 ›› 2025, Vol. 34 ›› Issue (5): 135-141.DOI: 10.12005/orms.2025.0154

• 应用研究 • 上一篇    下一篇

并购相似性抑制了企业研发投资?——基于并购参与企业双方经营特征的文本分析

刘井建, 田楠, 张冬妮   

  1. 大连理工大学 经济管理学院,辽宁 大连 116024
  • 收稿日期:2023-04-26 发布日期:2025-08-26
  • 通讯作者: 刘井建(1981-),男,江苏铜山人,博士副教授,研究方向:公司金融。
  • 基金资助:
    国家社会科学基金一般项目(21BGL080)

Does M&A Similarity Inhibit R&D Investment?Text Analysis Based on the Operating Characteristics of Both Parties Involved in M&A

LIU Jingjian, TIAN Nan, ZHANG Dongni   

  1. School of Economics and Management, Dalian University of Technology, Dalian 116024, China
  • Received:2023-04-26 Published:2025-08-26

摘要: 本文揭示了并购参与双方的相似性对主并方企业研发投资的影响机理,以重大重组并购事件为样本,运用文本分析方法量化并购相似性程度,结果发现:并购相似性程度每提高1个标准差,企业并购后研发投资两年均值降低8.55%;路径分析发现,并购相似性程度越高,研发人员比例增长越低,资本报酬率水平越高,支持了资源整合和利润追逐假说;对专利成果的检验说明,相比利润追逐导致创新惰性,并购相似性更能促进研发资源的精简与整合而提高创新效率,而相似性达到一定程度后净效应才会由资源整合效应转为利润追逐效应所主导。进一步讨论发现,企业创新知识积累越多,或并购前专利知识创造越少,并购相似性对研发投资的抑制效应越大。本文为并购目标选择、资源整合以及提升知识溢出而推动持续创新提供了借鉴。

关键词: 并购相似性, 技术创新, 研发投资, 专利, 文本分析

Abstract: China’s economy has begun a new stage of high-quality development, and the requirements of enterprises for technological innovation are becoming more and more urgent. With the acceleration of technological progress and the continuous introduction of new products, in addition to independent research and development or collaborative research and development to improve the innovation capacity of enterprises, mergers and acquisitions (M&A) have become one of the shortcuts to quickly capture innovation opportunities. It is worthwhile to pay attention to whether and by what characteristics of M&A activities the technological innovation of enterprises is affected, and the existing literature mainly focuses on the value effect and innovation results of M&A. However, due to the complexity of the M&A process and the limited data disclosure, there is little empirical research on the mechanism and effect of the influence of the characteristics of M&A on R&D investment. Revealing this “black box” is of great significance for selecting M&A targets, improving resources integration and realizing synergies.
This paper selects the domestic major restructuring M&A events that were implemented and completed from 2008 to 2020, and the bidders are A-share listed companies as samples. It applies Python to analyze the business scope and product features in the financial statements of the two parties to the merger and acquisition, and uses the related textual expressions such as business operation and technical products as the corpus source of the similarity estimation of the merger and acquisition, so as to measure the degree of similarity of the enterprises of both parties involved in the merger and acquisition based on the cosine similarity theorem. Using the Tobit model, we empirically test the effect of M&A similarity on the R&D investment of the main merging firms; we use the mediation effect model to test the path effect of resource integration and profit chasing, and further analyze the innovation efficiency in order to identify the critical paths; we use the instrumental variable method and dynamics test to alleviate the endogeneity problem and construct a moderating effect model to test the effect of innovation knowledge accumulation and creation on the relationship between M&A similarity and R&D investment.
The results show that: overall, M&A similarity significantly reduces enterprises’ R&D investment, and for every one standard deviation increase in the degree of M&A similarity, the two-year average of enterprises’ R&D investment after M&A decreases by 8.55%; the path analysis reveals that the higher the degree of M&A similarity is, the lower the growth of R&D personnel ratio is, and the higher the level of return on capital, which supports the hypotheses of resource integration and profit chasing; the tests on patent results indicate that M&A similarity is more effective in streamlining and integrating R&D resources to improve innovation efficiency than profit chasing that leads to innovation inertia, and that the net effect is dominated by the resource integration effect to the profit chasing effect only after similarity reaches a certain level. Further discussion reveals that the more innovation knowledge a firm accumulates, or the less pre-merger proprietary knowledge it creates, the greater the inhibitory effect of M&A similarity on R&D investments. The insights of this paper are as follows: First, similarity is an important feature of M&A target selection, and the advantages of M&A similarity on innovation result in reducing the inertia that inhibits R&D investment. Second, enterprises should pay more attention to the efficiency of resources integration while chasing profits, with an effective integration of inter-firm resources and optimization of R&D staffing. Third, we should tap into the resources base advantage, improve the knowledge spillover effect of enterprises and maintain the innovation motivation and incentive mechanism. Future research can further focus on the impact of MNEs’ overseas M&A similarity on R&D investment decisions.

Key words: M&A similarity, technological innovation, R&D investment, patents, textual analysis

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