A Study of Cross-Border Acquisitions by Emerging-Market Multinational Enterprises



Associate Professor

Project Summary

This summer I have had the privilege of working with Professor Zhao of the Management Department on her research of cross-border mergers and acquisitions (M&As). In recent studies, there has been a trend of cross-border acquisitions by emerging-market multinational enterprises (EMNEs), in which the top management team of the acquired company stays intact and integration remains limited. Since this seems to contradict the widely-accepted view that integration is crucial for successful M&As, our aim is to analyze the various motivations behind such deals in the hopes of gaining a better understanding of EMNEs and integration strategies. We started by asking questions such as the incentive of entry, motivation to go overseas or acquire other companies, top management team turnover and its effect on business, and post-merger integration. This was followed by a perusal of Factiva database articles to understand the context surrounding these deals. My role mainly consisted of creating an algorithm for machine learning to classify texts into different merger motivation categories, as well as preparing the texts through tokenization. I also manually verified company names and locations from two databases, the Directory of Corporate Affiliations (DCA) and the SDC Platinum. I combined information from these separate databases in order to find the top management team turnover information of the target and acquirer companies.

I initially became interested in this topic through an M&A project in my WH150 Business Research course and visiting Brazil, one of the world’s largest emerging markets, through the Wharton International Program (WIP) last year. By participating in Professor Zhao’s research, I have been able to expand my knowledge of mergers and their effects on the economy. From reading news reports on the Factiva database, to synthesizing news reports, to writing an algorithm and utilizing a Python tool to classify texts, I have learned to utilize tools and machine learning to facilitate analysis.

In a larger sense, this research opportunity has allowed me to step outside of my comfort zone, into programming and business research. This is my first time shifting away from science research, so this exposure has been very impactful in terms of opening my eyes to the other side of research and possibly my career. Starting from my Business Research class to this, I am very grateful to my mentors along the way who have guided me.