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<p>This study explores how adopting digital technologies helps companies increase their innovation potential by building valuable connections with other firms. These benefits depend on the type of industry and the region where the company operates. Using a hyperlink network as a digital trace of technology use, we examined 10,653 Finnish firms across 9 industries and 19 regions. Linear mixed-effects models show that digital technology adoption strengthens these strategic network positions, with the strongest effects coming from advanced high-technology tools, followed by cloud computing and social media. Knowledge-intensive industries (such as broadcasting and consulting) and digitally advanced regions (such as Ahvenanmaa) benefit the most, while more traditional sectors (like hospitality) and remote regions (like Lappi) face greater limitations. When industry type and regional context align well, the positive effects become even stronger. These findings extend network theory and the concept of dynamic capabilities by showing that digital adoption creates innovation potential through advantageous network positions. By connecting digital technology adoption with network perspectives, the study explains why digital transformation produces different innovation outcomes across sectors and regions.</p>

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Simmelian brokerage in hyperlink networks: How sector–regional contingencies shape innovation potential

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月11日

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  • Peng A. Yang,
  • Juho Pesonen,
  • Rodolfo Baggio

摘要

This study explores how adopting digital technologies helps companies increase their innovation potential by building valuable connections with other firms. These benefits depend on the type of industry and the region where the company operates. Using a hyperlink network as a digital trace of technology use, we examined 10,653 Finnish firms across 9 industries and 19 regions. Linear mixed-effects models show that digital technology adoption strengthens these strategic network positions, with the strongest effects coming from advanced high-technology tools, followed by cloud computing and social media. Knowledge-intensive industries (such as broadcasting and consulting) and digitally advanced regions (such as Ahvenanmaa) benefit the most, while more traditional sectors (like hospitality) and remote regions (like Lappi) face greater limitations. When industry type and regional context align well, the positive effects become even stronger. These findings extend network theory and the concept of dynamic capabilities by showing that digital adoption creates innovation potential through advantageous network positions. By connecting digital technology adoption with network perspectives, the study explains why digital transformation produces different innovation outcomes across sectors and regions.