科学学与科学技术管理 ›› 2024, Vol. 45 ›› Issue (03): 57-73.

• 创新战略与管理 • 上一篇    下一篇

技术并购、内部研发网络重构与企业探索式创新

  

  1. 南京理工大学 经济管理学院,南京 210094
  • 收稿日期:2022-07-11 出版日期:2024-04-10 发布日期:2024-04-12
  • 通讯作者: 周小虎,925537218@qq.com
  • 作者简介:张桂阳(1991— ),男,汉族,江苏泰州人,南京理工大学经济管理学院副教授,博士,研究方向:技术创新管理、创新 战略、研发网络;李新新(1997— ),女,汉族,安徽阜阳人,南京理工大学经济管理学院硕士研究生,研究方向:创新管理;周小 虎(1962— ),男,汉族,江苏南京人,南京理工大学经济管理学院教授,博士,研究方向:战略变革、企业创新管理。
  • 基金资助:
    国家社会科学基金项目(21CGL004

Technological Mergers and Acquisitions, Internal R&D Network Reconstruction, and Firm Exploratory Innovation. #br#

  1. School of Economics & Management, Nanjing University of Science and Technology, Nanjing 210094, China
  • Received:2022-07-11 Online:2024-04-10 Published:2024-04-12

摘要: 要想通过技术并购提升探索式创新绩效,需要同时满足以下两个条件:(1) 并购双方的技术之间存在新颖的重组 机会;(2) 并购企业可以有效整合目标企业的技术。技术匹配特征是影响并购后双方技术重组新颖度和整合难度的关 键因素。技术邻近在强调双方技术基础在宽泛的领域中相关的同时又允许它们在细分的技术领域中存在差异,因而可 在提升技术重组新颖度的同时降低技术整合难度。基于中国高端装备制造业在 20132017 年完成的 253 起技术并购 事件进行的实证研究结果发现:并购双方的技术邻近特征通过促进并购企业的内部研发网络重构正向影响其并购后的 探索式创新绩效;程度中心势负向调节技术邻近与内部研发网络重构之间的关系;网络聚集系数则增强了程度中心势 的负向调节效应。异质性分析显示:内部研发网络重构的中介效应在国有企业主导的技术并购中不显著;程度中心势 和网络聚集系数的调节效应在成熟企业主导的技术并购中更强。与利用式创新的辨析表明:内部研发网络重构是技术 并购双方技术邻近影响并购企业探索式创新的独特机制。

关键词: font-family:FZKTK--GBK1-0, font-size:8.93pt, ">技术并购;技术邻近;内部研发网络重构;探索式创新;程度中心势;网络聚集系数

Abstract: Accelerating the innovative development of high-end equipment manufacturing industry is crucial for speeding up the construction of a modern economic system and supporting high-quality economic development, among other things. Currently, China's high-end equipment manufacturing industry is still in the middle and lower reaches of the global industrial chain, lacking corresponding dominance, and facing "bottleneck" technical predicaments in key areas, which urgently need to improve exploratory innovation. Due to the cognitive lock-in of R&D personnel, it is difficult forfirms to continuously explore technology based on internal knowledge, and the efficient acquisition of external technology is key to improving the performance of exploratory innovation. Technological mergers and acquisitions, as an important cooperative innovation strategy and external technology acquisition strategy, have received widespread attention from both industry and academia. Whether technological mergers and acquisitions can lead to exploratory innovation depends on two points: first, there are novel recombination opportunities between the technologies of the merging parties; second, the merged firm can effectively integrate the technology of the target firm. Current research on technological mergers and acquisitions is limited to the quantity and quality of technology acquisition, neglecting the dynamic process of post-merger internal and external technology recombination. According to the recombination innovation theory, the matching characteristics of technology are key factors affecting the novelty and integration difficulty of post-merger technology recombination between the two parties. Technological proximity emphasizes that while the technological foundations of both parties are relevant in a broad field, they also allow for differences in specific technical fields, thus potentially enhancing the novelty of technology recombination while reducing the difficulty of technology integration. The reconstruction of the internal R&D network may be one of the important mechanisms by which technological mergers and acquisitions impact exploratory innovation, but how it is quantified and empirically validated as a mediation mechanism is still not clear. Moreover, the dynamic reconstruction of cooperation networks has distinct path dependence and self-reinforcing features, and different structural features of previous networks may affect the degree of reconstruction of internal cooperation networks. This study aims to construct a moderated mediation effect model to empirically test the process mechanism of how technological proximity between the merging parties affects the exploratory innovation of the merged firm. Based on multiple matching data such as technological mergers and acquisitions, invention patents, and financial information of 253 high-end equipment manufacturing industries from 2013 to 2017, the negative binomial regression model is used for empirical testing. The study found that: (1) The technological proximity of the merging parties positively influences the exploratory innovation performance after the merger by promoting the reconstruction of the internal R&D network of the merged firm; (2) Degree centrality negatively moderates the relationship between technological proximity and the reconstruction of the internal R&D network; (3) Network clustering coefficient strengthens the negative moderating effect of degree centrality. Heterogeneity analysis shows that: (1) Technological proximity does not significantly impact post-merger exploratory innovation in firms with strong profitability and adequate R&D investment; (2) The mediating effect of the reconstruction of the internal R&D network is not significant in technology mergers and acquisitions led by state-owned enterprises; (3) The moderating effects of degree centrality and network clustering coefficient are stronger in technology mergers and acquisitions led by mature firms. A comparison with exploitation innovation reveals that the reconstruction of the internal R&D network is a unique mechanism through which the technological proximity of the merging parties impacts the exploratory innovation of the merged firm. In response to this, this article further discusses possible reasons from perspectives such as resource constraints, network inertia, and ambidextrous learning. The theoretical contribution of this article can be summarized from two aspects: First, the measurement index based on patent variables improves the precision of statistical analysis of technological matching characteristics between the merging parties. Second, through the introduction of a dynamic network perspective and an internal corporate viewpoint, it is revealed how technological mergers and acquisitions influence the process mechanism of exploratory innovation within a firm. Based on the research findings, it is recommended that high-end equipment manufacturing firms in China should: First, select targets for technological mergers and acquisitions that have similar technological strategies and foundations; Second, dynamically allocate internal R&D teams and strengthen communication and cooperation between new and old employees; Third, adopt decentralization and eliminate "clique" culture, promoting cross-team collaborative innovation.

Key words: technological mergers and acquisitions, technological proximity, internal R&D network reconstruction; exploratory innovation, degree centrality, network clustering coefficient

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