# Simultaneous Use of Digital Technologies and Industrial Robots in Manufacturing Firms
## 4 Results and Discussion
### Statistical Tests
However, in the case of industrial robots for handling processes, Level 2 was also significant in predicting the usage of this type of robot. Firms that are in Level 2 are 13.1 times more likely to use industrial robots for handling processes The logistic regression results for mobile robots (R3) were inconclusive and could not be included in the Table due to their limited usage in firms. For collaborative robots and autonomous robots, none of the readiness levels showed a statistically significant prediction for the usage of these two types of robots. If the reference category is switched to Level 5, then the odds of using industrial robots can be obtained for firms in Levels 0-4 compared to firms in Level 5 (Table 8). As expected, the results of logistic regression confirm that firms in lower readiness levels have lower odds (or chances) of using industrial robots for manufacturing processes and industrial robots for handling processes. For the other three types of robots, the results were statistically insignificant. The results for firms in Level 0 indicate that the odds of them using industrial robots for manufacturing processes are only 0.002, or 0.2%, in comparison with firms in Level 5. This can also be interpreted as having 99.8% lower odds of using industrial robots for manufacturing processes. Interestingly, the firms in Level 3 have no statistically significant odds of using industrial robots for manufacturing processes than firms in Level 5. In the case of industrial robots for handling processes, the odds of using this type of robot are lower across all levels. For mobile robots, collaborative robots and autonomous robots, no conclusions could be made about the significantly lower odds of using these robots. Our first and second research questions dealt with the inquiry about the correlation and its strength between digital technologies and industrial robots. As results have shown, both types of \"traditional\" industrial robots--for manufacturing and handling processes--are correlated to the majority of selected digital technologies. The only exception is digital visualization (solutions) on the shop floor for the industrial robots for manufacturing processes. In general, these correlations are weak and, on some occasions, medium. Digital technology near-real-time production control systems have the strongest correlation with both \"traditional\" industrial robot types. Our findings indicate that digital technologies and advanced manufacturing technologies, such as industrial robots, are not isolated in their use, regardless of the type of digital technology. Our finding is supported further by our results \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Technology** & **Statistic** & **R1** & **R2** & **R3** & **R4** & **R5** \\ \hline \multirow{2}{*}{Readiness level} & Pearson \(\chi^{2}\) & **0.021** & **\textless{}0.001** & 0.920 & 0.400 & 0.450 \\ \cline{2-7}  & Spearman correlation & **0.283** & **0.437** & 0.096 & 0.198 & 0.141 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Association and correlation results for readiness levels and types of robots. when including Industry 4.0 readiness levels. In our readiness model, these levels depended on the number and specific combination of selected digital technologies. It was shown that the use of \"traditional\" industrial robots is correlated with the number of implemented digital technologies in a manufacturing firm. For industrial robots for handling processes, this correlation is almost strong. This is also the answer to our third research question. The situation with the other three types of robots is a bit different. Although some weak correlation was found between collaborative robots and three digital technologies, in general, these types of robots showed no correlation with the selected digital technologies. There are at least two reasons for this finding. One might be the small number of these robots in our research sample as a result of the total number of included manufacturing firms.