Impact of board diversity on Chinese firms’ cross-border M&A performance: An artificial intelligence approach

Shusheng Ding, Min Du, Tianxiang Cui, Yongmin Zhang, Meryem Duygun

Research output: Journal PublicationArticlepeer-review


In this paper, we examine the impact of board demographic characteristics on Chinese firms’ cross-border Mergers and Acquisition (M&A) performance, especially the gender diversity of the board composition. We unveil that female board proportion exhibits a positive and significant effect on cross-border M&A performance. On the other hand, board member age diversity and board member education diversity play a trivial role on cross-border M&A performance. We further introduce an optimization model called Particle Swarm Optimization (PSO), which is an artificial intelligence technical application, to address the optimal board diversity regarding the M&A performance. We demonstrate that a better organized board structure, such as increasing female board presentation tend to improve cross-border M&A performance of Chinese firms. We argue that the enhanced performance from optimized board diversity might be transmitted through the channel of corporate governance. Furthermore, we reveal that the board diversity effect is stronger in private owned companies compared with state owned companies. Our results can thereby deliver implications of corporate governance.

Original languageEnglish
Pages (from-to)1321-1335
Number of pages15
JournalInternational Review of Economics and Finance
Publication statusPublished - Apr 2024


  • Corporate governance
  • Cross-border mergers and acquisitions
  • Gender diversity
  • Particle swarm optimization
  • Strategic management

ASJC Scopus subject areas

  • Finance
  • Economics and Econometrics


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