An Empirical Analysis on the Determinants of Cross-Border Mergers and Acquisitions of Chinese Enterprises
- DOI
- 10.2991/978-94-6463-256-9_153How to use a DOI?
- Keywords
- Cross-border M&A; Enterprise scale; Enterprise R&D investment; Enterprise nature
- Abstract
On the basis of sorting out and analyzing the background of China’s cross-border Mergers and Acquisitions (M&A) and combing relevant literature and theoretical knowledge, this paper selects 47 cross-border M&A data of listed companies on the Shanghai and Shenzhen Stock Exchanges from January 1st, 2019 to December 31st, 2017 and constructs binary Logit model. Eviews software were used to conduct empirical analysis of the factors affecting the success of Chinese companies’ cross-border M&A. The result shows that the enterprise scale and R&D investment are positively related to the possibility of successful cross-border M&A. The nature of enterprise has a significant impact on the possibility of successful cross-border M&A. The three factors of enterprise growth capacity, international M&A experience and share ownership of M&A have not been tested.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Tingting Zhang PY - 2023 DA - 2023/10/09 TI - An Empirical Analysis on the Determinants of Cross-Border Mergers and Acquisitions of Chinese Enterprises BT - Proceedings of the 2023 4th International Conference on Management Science and Engineering Management (ICMSEM 2023) PB - Atlantis Press SP - 1516 EP - 1521 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-256-9_153 DO - 10.2991/978-94-6463-256-9_153 ID - Zhang2023 ER -