%0 Journal Article %A Xiaodong HUANG %A Debin DU %A Chengliang LIU %T The evolution process and growth mechanism of global cross-border M&A network %D 2021 %R 10.11821/dlxb202110014 %J Acta Geographica Sinica %P 2536-2550 %V 76 %N 10 %X

Cross-border M&A (mergers and acquisitions) is an important way for enterprises to carry out overseas strategic layout, which has a significant impact on the pattern evolution of world economic geography. Based on record data of global cross-border M&A transactions from 2001 to 2017, a national-based network for the global scales is established to explore the evolution process and growth mechanism of global cross-border M&A network via the complex network analysis, the GIS method, and the spatial gravity model. Several conclusions can be drawn as follows. (1) The scale, density, and scope of the global cross-border M&A network have increased slightly, while there exists a trend of decentralization. (2) There is a sign that the center of gravity has been shifting from Western Europe and North America to the Asia-Pacific region for global cross-border M&A network, which is mainly driven by China. However, Chinese import and export of cross-border M&A largely rely on Hong Kong, British Virgin Islands, Cayman Islands and so on. (3) There is a process of division and integration for condensing subgroup of global cross-border M&A network. Among them, the scope of condensing subgroup led by the UK and the US has been narrowed, while that led by China has been expanded, and the European condensing subgroup has been further integrated. (4) The evolution of global cross-border M&A network to varying degrees was influenced by the indicator attributes for each country (region), which was in turn related to the science and technology level, offshore financial center, as well as proximity indicators, which were related to geographical conditions, language and history. However, natural resource endowment and economic market size for cross-border M&A linkages only have one-way (receiving or output) effect, and economic proximity index is not significant in 2009 to 2017.

%U https://www.geog.com.cn/EN/10.11821/dlxb202110014