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Mergers and Acquisitions

The Innovation Impact

Edited by Bruno Cassiman and Massimo G. Colombo

This book examines the issue of mergers and acquisitions (M & As) in the context of technological development, and in particular the impact of M & As on the innovation process. In so doing, the book integrates two bodies of literature, on M & As, and on innovation studies, a nexus which the editors contend represents an important step in the advancement of our understanding of both with clear implications for competitive advantage and growth of firms. Drawing on perspectives from both management and economics, the book offers a cohesive blend of theory, methodology, and a wealth of empirical material.
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Chapter 8: The Impact of M & A on Innovation: Empirical Results

Massimo G. Colombo and Paola Garrone


8. The impact of M&A on innovation: empirical results Massimo G. Colombo and Paola Garrone 8.1 INTRODUCTION This chapter analyses the effects of mergers and acquisitions (M&A) on the research and development (R&D) process. We pay special attention to the role played by technology and market relatedness of the combining firms, but we are interested in exploring the role of other M&A characteristics as well. Before reporting the key findings of our analysis, we briefly illustrate the empirical methodology. The difference in the value of R&D indicators across different M&A classes (e.g. rival versus non-rival firms) is tested through univariate statistics. The variables submitted to statistical tests include both traditional R&D indicators and new R&D constructs; the latter are drawn from a dataset that codifies the interviewees’ responses on the innovation process in the merging firms. First, we will consider a limited selection of traditional indicators. They capture changes in merging firms’ R&D inputs and performance that are, according to the interviewed managers, directly attributable to the completion of the deal. Answers in the questionnaire concerning such aspects were codified as ordered categorical variables and so they can be used in statistical analyses. Use of such traditional indicators makes it easier to compare our results with those of previous studies. Secondly, as was mentioned in previous chapters, the questionnaire comprises a large number of specific questions relating to changes in R&D inputs, outputs,...

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