Factors Influencing the Acceptance of Industry 4.0 Technologies in Various Sectors: A Systematic Review and Meta-Analysis
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 and meta-analysis based on the Technolog...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/9/4866 |
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| Summary: | 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 and meta-analysis based on the Technology Acceptance Model and its extensions. A total of 47 empirical studies were extracted from five academic databases and included in the meta-analysis. The findings confirmed that perceived usefulness (PU), perceived ease of use (PEOU), and social influence (SI) significantly and positively influenced behavioral intention (BI) toward adopting Industry 4.0 technologies. Among them, PU exhibits the strongest correlation with BI (r = 0.528), followed by PEOU (r = 0.469) and SI (r = 0.487). Subgroup analyses based on geographical region, organization size, and sector showed consistent significance in effect sizes, although moderating effects across subgroups were not statistically significant. The findings of this study contributed to the literature with an in-depth understanding of the acceptance of Industry 4.0 technologies in various sectors and how moderators influence the acceptance. Practically, the findings provided evidence-based guidance for policymakers, technology developers, and business leaders to tailor adoption strategies and foster digital transformation across sectors. |
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| ISSN: | 2076-3417 |