 Digital M&As, knowledge distance, and labor productivity: Technical and organizational perspectivesYiming Zhao, Haitong Li, Zicong Miao and Keyang Li Economic Modelling, 2025, vol. 147, issue C Abstract: This study investigates the impact of digital mergers and acquisitions (M&As) on labor productivity, focusing on the influence of the knowledge distance between merging parties. Using a sample of firms that underwent M&As between 2007 and 2022, we employ the difference-in-differences method to analyze whether digital M&As lead to higher labor productivity than non-digital M&As. Our results show that a longer knowledge distance between merging parties strengthens the positive relationship between digital M&As and labor productivity. Channel tests reveal that digital M&As improve labor productivity through enhanced technological innovation efficiency when knowledge distance is closer and reduce organizational instability when knowledge distance is longer. Moreover, the effects are more pronounced in larger, younger firms and those with higher labor intensity and better talent pools. These findings provide new insights into the outcomes of digital M&As and highlight the critical role of knowledge distance in shaping labor productivity. Keywords: Digital M&A; Labor productivity; Knowledge distance; Innovation efficiency; Organizational instability (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:147:y:2025:i:c:s0264999325000598 DOI: 10.1016/j.econmod.2025.107064 Access Statistics for this article Economic Modelling is currently edited by S. Hall and P. Pauly More articles in Economic Modelling from Elsevier |
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