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Digital M&As, knowledge distance, and labor productivity: Technical and organizational perspectives

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  • Zhao, Yiming
  • Li, Haitong
  • Miao, Zicong
  • Li, Keyang

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.

Suggested Citation

  • Zhao, Yiming & Li, Haitong & Miao, Zicong & Li, Keyang, 2025. "Digital M&As, knowledge distance, and labor productivity: Technical and organizational perspectives," Economic Modelling, Elsevier, vol. 147(C).
    • Handle: RePEc:eee:ecmode:v:147:y:2025:i:c:s0264999325000598
    DOI: 10.1016/j.econmod.2025.107064
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    Keywords

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    JEL classification:

    • G34 - Financial Economics - - Corporate Finance and Governance - - - Mergers; Acquisitions; Restructuring; Corporate Governance
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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