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Green M&A deals, value creation and sustainability in post-acquisition performance - PRIN 2022

Progetti nazionali
Programma di ricerca
PRIN 2022
28/09/2023 - 27/09/2025
Antonio Salvi

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Descrizione del progetto


Despite the persistence and recurrence of crises of various origins and nature, the Mergers and Acquisitions activity (M&A) represents a key element of the business strategy of a company for creating value, achieving, and maintaining competitive advantages. These transactions allow companies to expand their product or market extension, to acquire know-how, and, therefore, to increase their competitiveness. Recent years and developments have shown the necessity of more sustainable growth for the economic ecosystem, and companies that recognized this trend as a fundamental constituent of their strategy reached a competitive advantage. However, recent researches confirm that M&A has been still unaffected by this tendency (Caiazza et al., 2021; Tampakoudis & Anagnostopoulou, 2020). Based on the abovementioned consideration, the objective of the research is to investigate the significance of ESG drivers influencing successful M&A transactions. In particular, the analysis aims to understand the evolution of ESG criteria through time, across countries and industries to determine the impact of M&A on the financial and non-financial performance of both the primary parties involved (i.e., target and acquirer) and the broader ecosystem. From a methodological point of view, the research will develop framework to identify attractive M&A targets –companies that, after the occurrence of an M&A transaction, release synergetic value not only to shareholders but to the broader community of stakeholders in a broader sense- using innovative machine learning methods, and test whether these sustainable deals can drive superior performance, in terms of markets, financial and social performance (shared value). On the one hand, will apply econometrics tools to heterogeneous variables, such as traditional financial indicators, macroeconomic variables, novel unconventional indicators, and information extracted from the set of documents that typically follows a deal. On the other hand, state-of-art machine learning (ML) techniques we adopted for uncovering the mapping between the comprehensive and heterogeneous data available and the outcome of the M&A deals. The comprehensive set of retrieved data and indicators will be leveraged for pursuing the final goal of our analysis, namely the characterization of M&A deals as sustainable or unsustainable. Such an analysis will be enabled by the availability of historical information about M&A deals, each associated with the observed outcome. The added value of this multidisciplinary research, to previously studies, is the innovative methodology approach to analyzing the sustainability in M&A deals, correlated post acquisition performance in long-term. Given the complexity of M&A and the challenges of CSR integration into the corporate culture of the acquirer, we aim to analyze the long-term effects to CSR on the ESG scores for companies involved in the deals and the impacts on the social, economic and climate environmental.


Ultimo aggiornamento: 21/03/2024 10:17
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