How configuration theory explains performance growth and decline after Chinese firms cross-border M&A: using the fsQCA approach

ABSTRACT

Mergers and acquisitions are important mechanisms for the growth of corporations, but up to now the evidence and explanations for good deals and bad deals are mixed. This study attempts to apply configuration theory to perceive and evaluate M&As holistically – that is, as a complex configuration of Timing, Environment, and People, an ideology that stems from ancient Chinese philosophers and has been spread in China for thousands of years. Overlooking the interdependent nature of the factors of Timing, Environment, and People in influencing M&As has limited our understanding of acquisition performance. Through examining the 80 largest cross-border M&A cases in Chinese listed companies by deal value between 2015 and 2018, relying on fuzzy-set methodology by using fsQCA, we investigate different configurations that lead to performance change; the result reveals two different configurations that equifinally result in post-merger performance growth, and three that decline. By constructing a typology of ‘good’ and ‘bad’ deals, we develop a mid-range theory of M&A performance change. Thus, the central contribution of this study is to help with the formation of a comprehensive understanding of M&As, and to offer novel managerial implications for practitioners.

KEYWORDS:

• Acquisition
• configuration
• cross-border
• fsQCA
• M&A
• performance
• China

Disclosure statement

We declare that we have no financial and personal relationships with any people or organizations that could inappropriately influence our work, and that there is no professional or other personal interest of any nature or kind in any product, service, and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled, ‘How Configuration Theory explains Performance Growth and Decline after Chinese firms cross-border M&A: Using the fsQCA approach’.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China under Grant 71772164; 72032008; and the Natural Science Foundation of Zhejiang Province under Grant LR19G020001.

Notes on contributors

Cong Cheng

Dr. Cong Cheng is Professor in the School of SMEs at Zhejiang University of Technology. His research interests include big data analysis, international business, business ecosystem, and SMEs innovation. His publications have appeared in Journal of Business Research, International Journal of Entrepreneurial Behavior and Research, Sustainability and other Chinese academic journals.

Ze Yang

Ze Yang is currently pursuing his master’s degree at the School of Management, Zhejiang University of Technology. His research interests include business intelligence, international business and SMEs innovation.

Yining He

Yining He is currently pursuing his PhD degree at the School of Management, Zhejiang University of Technology. His research interests include leadership, international business and SMEs innovation. His publications have appeared in Sustainability and other Chinese academic journals.

Lulu Yan

Lulu Yan is pursuing her PhD degree at the School of Management, Zhejiang University of Technology. Her research interests include digital innovation, big data analysis and international business. Her publications have appeared in several Chinese journals.