Unlocking the Data Advantage

Daniela S. Schoch ()
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Daniela S. Schoch: EM - EMLyon Business School

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Abstract: This paper examines M&A activity of firms in the data economy. I develop text-based measures for data intensive companies, i.e., firms that are rich in data resources and capabilities, and relate them to M&A likelihood and performance. Results indicate that data intensity relates to a higher likelihood to become acquirer or target. The largest share of increased acquirer likelihood can be attributed to conglomerate deals. Targets of data intensive acquirers are more often small, foreign, and non-public. While investors do not expect superior performance at deal announcement, data intensive acquirers demonstrate superior long-term stock returns in the years after deal announcement. This study contributes to existing literature by proposing new measures for identifying data intensive companies and investigating these firms' M&A activity and performance.

Keywords: Deal Performance; Deal Likelihood; Natural Language Processing; Mergers & Acquisitions; Data Economy (search for similar items in EconPapers)
Date: 2024-08-30
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Published in European Association for Research in Industrial Economics (EARIE) Annual Conference 51st, Aug 2024, Amsterdam, Netherlands. 61 p

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05606719

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