Factors Influencing the Acceptance of Industry 4.0 Technologies in Various Sectors: A Systematic Review and Meta-Analysis DOI Creative Commons
Wenjun Zou, Siu Shing Man, Wenbo Hu

et al.

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(9), P. 4866 - 4866

Published: April 27, 2025

Adopting Industry 4.0 technologies across sectors is critical for enhancing operational efficiency and competitiveness. However, empirical studies on the determinants of such adoption have yielded inconsistent results. This study conducted a systematic review meta-analysis based Technology Acceptance Model its extensions. A total 47 were extracted from five academic databases included in meta-analysis. The findings confirmed that perceived usefulness (PU), ease use (PEOU), social influence (SI) significantly positively influenced behavioral intention (BI) toward adopting technologies. Among them, PU exhibits strongest correlation with BI (r = 0.528), followed by PEOU 0.469) SI 0.487). Subgroup analyses geographical region, organization size, sector showed consistent significance effect sizes, although moderating effects subgroups not statistically significant. this contributed to literature an in-depth understanding acceptance various how moderators acceptance. Practically, provided evidence-based guidance policymakers, technology developers, business leaders tailor strategies foster digital transformation sectors.

Language: Английский

Factors Influencing the Acceptance of Industry 4.0 Technologies in Various Sectors: A Systematic Review and Meta-Analysis DOI Creative Commons
Wenjun Zou, Siu Shing Man, Wenbo Hu

et al.

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(9), P. 4866 - 4866

Published: April 27, 2025

Adopting Industry 4.0 technologies across sectors is critical for enhancing operational efficiency and competitiveness. However, empirical studies on the determinants of such adoption have yielded inconsistent results. This study conducted a systematic review meta-analysis based Technology Acceptance Model its extensions. A total 47 were extracted from five academic databases included in meta-analysis. The findings confirmed that perceived usefulness (PU), ease use (PEOU), social influence (SI) significantly positively influenced behavioral intention (BI) toward adopting technologies. Among them, PU exhibits strongest correlation with BI (r = 0.528), followed by PEOU 0.469) SI 0.487). Subgroup analyses geographical region, organization size, sector showed consistent significance effect sizes, although moderating effects subgroups not statistically significant. this contributed to literature an in-depth understanding acceptance various how moderators acceptance. Practically, provided evidence-based guidance policymakers, technology developers, business leaders tailor strategies foster digital transformation sectors.

Language: Английский

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