基于 NK 模型的并购目标、分拆与组织关系网络仿真研究

    Simulation Research on M&A Targets, Spin-offs and Interfirms Networks Based on NK Model

    • 摘要: 为研究企业在探索式和利用式并购目标下采取不同整合行为的效果,基于网络视角将企业并购整合中的分拆行为划分为“加法”和“减法”分拆,结合复杂适应系统理论构建“并购目标−整合行为−并购结果”分析框架,建立NK仿真模型,对比分析两种目标下采取不同分拆方式的绩效及组织关系网络变化。研究发现:加法分拆提高了中介中心性,降低了约束度、全局聚类系数和网络全局效率,使自我网络更开放,有利于探索式目标的实现;减法分拆提高了约束度和中介中心性,降低全局聚类系数和网络全局效率,使自我网络更封闭,有利于利用式目标的实现。相比不分拆行为,决策复杂度的增加使得分拆行为对并购绩效的正向影响更明显。

       

      Abstract: To examine the impact of different integration undertaken by firms during M&A integration, we categorize the spin-offs strategic into “additive” and “subtractive” based on network theory. Integrating complex adaptive system theory, we develop an analytical framework that links M&A objectives, integration behaviors, and outcomes. Additionally, we employ an NK model to compare the performance and evolution of interfirms networks for different spin-offs under exploratory and exploitative goals. This study finds that: additive spin-offs increases between centrality, reduces the constraint of the ego network, the average clustering coefficient, and the efficiency of the global network, which renders the ego network more open for explorative goals. Whereas the subtractive spin-offs improves the constraint degree and between centrality of the ego-network, declines the average clustering coefficient and efficiency of the global network, and assembles the ego-network more closed, which is conducive to the realization of the exploitative goal. The higher internal decision complexity makes the advantage of spin-offs behavior more pronounced than that of non-split behavior.

       

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