Integration decision-making in technology-sourcing cross-border M&As: a mathematical model

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Abstract

Post-merger integration plays a key role in the success of mergers and acquisitions, but how to choose the appropriate integration mode to achieve potential synergies in mergers and acquisitions (M&As) still lacks widely accepted theoretical support and practical experience. Therefore, this article establishes a mathematical model considering the similarity and complementarity of resources in an attempt to explore the optimal integration strategy (including the choices of integration degree and autonomy granted to the target) under different conditions of resources similarity and complementarity, thus building a comprehensive framework that considers pre- and post-merger factors together to jointly explain innovation realization in technology-sourcing cross-border M&As. The results show that the higher the resource similarity, the higher the degree of integration and the lower the degree of target autonomy. Conversely, the higher the resource complementarity, the lower the degree of integration and the higher the degree of target autonomy. Resource similarity and resource complementarity have negative interactions for integration and target autonomy. The higher the resource similarity, the faster the convergence of optimal degree of integration, while the higher the resource complementarity, the slower the convergence. The study results add to our knowledge of M&A integration management, and provide some implication for practitioners.

Keywords

M&A Integration Target autonomy Resource similarity Resource complementarity 

Notes

Acknowledgements

This work was supported by Key Projects of Philosophy and Social Sciences Research for the Ministry of Education of China under Grant [16JZD020]; Project of National Natural Science Fund under Grant [71673248]; Key project of the National Social Science Fund under Grant [14AJY007]; Key Projects of Zhejiang Province Natural Science under Grant [LZ14G020002]; and Project of Academy of Financial Research of Zhejiang University under Grant [XK16004].

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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.College of EconomicsZhejiang UniversityHangzhouPeople’s Republic of China
  2. 2.The People’s Bank of ChinaChangshaPeople’s Republic of China

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