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- W3120659129 abstract "In research, public, and policy debate, there is increasing interest in data intensive firms like Google, Facebook, and Amazon. As business models of data firms are often characterized by high scale economies and network externalities, they are expected to have a particularly large incentive to grow, among others through mergers and acqui- sitions (M&A). Adding to the up to now mainly theoretical or anecdotal discussion on data intensive firms, this study empirically analyzes the relationship between firms’ data intensity and M&A activity. Using text-based measures to identify data inten- sive firms, I find that data generators are more likely to become acquirers, whereas data analysis and storage companies are more likely to become targets. Transactions by data firms, on average, do not create value as abnormal announcement returns are zero. There is evidence for pre-emptive merger activity, i.e., data intensive firms acquiring particularly often rather small, non-public companies that are not (yet) on the radar of competition authorities." @default.
- W3120659129 created "2021-01-18" @default.
- W3120659129 creator A5063662217 @default.
- W3120659129 date "2020-01-01" @default.
- W3120659129 modified "2023-09-23" @default.
- W3120659129 title "Mergers and Acquisitions in the Data Economy" @default.
- W3120659129 doi "https://doi.org/10.2139/ssrn.3686247" @default.
- W3120659129 hasPublicationYear "2020" @default.
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