## 5 Results
### Overall Effect Sizes  
The meta-analysis results were derived from the random effects models due to the significant variations in the effect sizes across these primary studies. Table 4 summarizes the estimated overall effect size of the size-weighted zero-order correlations of PU-BI (0.528, 95% CI 0.420-0.621), PEOU-BI (0.469, 95% CI 0.402-0.531), and SI-BI (0.487, 95% CI 0.363-0.594). The results reveal that all three correlations were positively associated with the adoption of Industry 4.0 technologies in various sectors at a 0.01 significance level. The results suggest that when organizations know the intrinsic benefits of Industry 4.0 technologies and think these technologies are user-friendly, the organizations' workforce is more likely to experience a higher propensity to engage with and adopt these technologies. Also, when organizations have supportive environments where peer and managerial endorsement is evident, they tend to accept these technologies. Ultimately, by leveraging these insights, organizations can make informed strategic decisions that minimize resistance, optimize resource allocation, and accelerate the integration of cutting-edge technologies, thereby enhancing productivity and competitive advantage in an increasingly digital marketplace. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**Random Effects Model**} & \multicolumn{3}{c}{**Fixed Effects Model**} \\ \hline Direct effects & PU–BI & PEOU–BI & SI–BI & PU–BI & PEOU–BI & SI–BI \\ No. of studies & 43 & 43 & 12 & 43 & 43 & 12 \\ Total of & & & & & & \\ sample & 9753 & 9845 & 4810 & 9753 & 9845 & 4810 \\ studies & & & & & & \\ Effect size & 0.528 *** & 0.469 *** & 0.487 *** & 0.475 *** & 0.444 *** & 0.467 *** \\
95\% CI & (0.420, 0.621) & (0.402, 0.531) & (0.363, 0.594) & (0.460, 0.490) & (0.429, 0.461) & (0.445, 0.489) \\ Z-value & 8.256 & 12.049 & 6.851 & 51.323 & 47.133 & 34.982 \\ Direct effects & PU–BI & PEOU–BI & SI–BI & PU–BI & PEOU–BI & SI–BI \\ \hline \hline \end{tabular} Note: *** represents the significance at the 1% level.  
\end{table} 
Table 4: Results of random effects and fixed effects models. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multicolumn{1}{c}{**Characteristics**} & **Statistical Results** & **Characteristics** & **Statistical Results** \\ \hline M/all participants \textgreater{} 0.5 & 17 & NA & 22 \\ M/all participants \textless{} 0.5 & 9 & Organization sector & \\ NA & 21 & Agriculture & 1 \\ Geographical region & & Industry & 13 \\ Asia & 32 & Service & 18 \\ Europe & 6 & Multisector & 8 \\ South America & 1 & NA & 7 \\ North America & 2 & & \\ Africa & 3 & & \\ NA & **4** & & \\ \hline \hline \end{tabular}  
NA: Data not available from the source study.  
\end{table} 
Table 2: _Cont._  
\end{table}
Table 3: Pairwise correlations in primary studies. The quantitative results have demonstrated the effects of the three factors on Industry 4.0 technology adoption, eliminating the controversial results in the previous studies. The positive correlation between PU and BI (H1) was supported, indicating that the acceptance of Industry 4.0 technologies was based on the users' perceptions of how useful these technologies are in improving their working efficiency and the organization's productivity. In addition, the positive association between PEOU and BI (H2) was confirmed, suggesting that the acceptance of Industry 4.0 technologies heavily relied on PEOU. Finally, the results revealed that SI should be paid attention to when adopting Industry 4.0 technologies in various sectors (H3). Interestingly, the effect sizes in these three pairwise relationships varied significantly. The effect size of PU-BI was the highest, whereas the effect size of SI-BI was the lowest. A possible reason is that most organizations are economy-oriented; thus, they pay much attention to determining a cost-effective way to improve their productivity and increase their profits. Accordingly, PU can generate a direct impetus for technology adoption, which is the most critical factor to be considered.