Transforming society into a more sustainable one relies on green transformation by the private sector. Recently, many industries have seen a surge in “green deals” (BCG, 2022). These mergers and acquisitions (M&As) can promote environmental transformation through green innovation but can also reduce competition and lead to 'killer acquisitions' that stifle future innovation (Cunningham et al., 2021). M&A deals may also be used for 'greenwashing', improving “green image” without genuine environmental transformation.

This project aims to analyze the impact of M&A activity on green innovation and contrast these findings with the effects on “green image” and financial performance. Interest in the impact of mergers on innovation has grown among policymakers, investors, and researchers (Gilbert, 2020). Most research progress has been theoretical, with few studies using real-world data, mainly focusing on the pharmaceutical industry.

This project will focus on green innovation, greenwashing, and firm performance using a large, cross-industry dataset. Novel methods will measure sustainability and green innovation using NLP algorithms. The data will be analyzed using differences-in-differences analysis combined with propensity score matching. The findings will interest policymakers, business leaders, investors, and other stakeholders, contributing to more effective policies and strategies for a sustainable economy.