## 5 Results and Discussion
Therefore, the higher ranking of L12 and L11 does not diminish the relevance of Industry 5.0 solutions but rather highlights the staged nature of transformation--where enabling technologies are implemented first to create the conditions for downstream innovations. Figure 2 provides a graphical representation of cause-and-effect relationships for Industry 4.0/5.0 areas. The causality indicator \(\left(D_{i}-R_{i}\right)\) enables the determination of the direction of interactions within the analysed system. A positive value of the indicator means that a given parameter exerts an influence on other elements of the network, while a negative value indicates a receiving role. In the analysis of transformation areas, the highest positive causality values were recorded for K1 (Automation and Connectivity), K5 (Sustainability), and K4 (Human-Centricity), suggesting that these areas act as primary drivers within the interaction structure. On the contrary, K2 (Data-Driven Optimization), K3 (Agility and Flexibility), and K6 (Resilience) exhibited negative values, which suggests their dependence on other elements of the system. These findings reflect the typical progression of transformation: connectivity, automation, and data infrastructure (K1) serve as foundational enablers, paving the way for the development of more adaptive and resilient systems (K6). Strategically, K1 underpins the functioning of all other areas, particularly those characteristic of Industry 5.0. In Figure 2, K1--due to its dominant centrality and causality values--is additionally highlighted using bold formatting to emphasize its systemic importance. The position of individual technologies from these areas is visible in Figure 3, which presents the system of connections in relation to both indicators. Figures 2 and 3 employ bold formatting to draw attention to the most influential technologies. Notably, L12 has the highest centrality index, and L53 has the highest causality index within the DEMATEL-based structure. In the set of Industry 4.0 technologies, the most pronounced influencing components are the positive values \(\left(D_{i}-R_{i}\right)\) for L21 (Artificial Intelligence (AI) and Machine Learning (ML)), L13 (Wireless Communication/5G), and L34 (Augmented and Virtual Reality-AR/VR). Figure 2: Cause–effect diagram for Industry 4.0 and Industry 5.0 areas. For Industry 5.0, strong potential impact is observed in the cases of L53 (Autonomous Vehicles and Drones), L62 (Quantum Computing), and L41 (Human-Centered Robotics, New-Generation Cobots). Simultaneously, it is important to highlight technologies that function primarily as 'influence receivers'--these include L64 (Digital Twin), L22 (Big Data and Data Analytics), and L23 (IT Support Systems). These technologies, although characterized by lower causality values, may serve as critical support components, reacting to changes initiated by other, more influential components. Using the centrality index \((D_{i}+R_{i})\) and (6), a ranking of Industry 4.0 and 5.0 areas (Table 4) and technologies (Table 5) was developed. This distinction enables a separate assessment of the strategic significance of individual technologies and the domains in which they are implemented, offering a more comprehensive perspective on their transformational potential. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Modern Technology Notation** & \(W_{i}\) & **Ranking** \\ \hline L12 & 59.444 & 1 \\ L11 & 55.080 & 2 \\ L23 & 53.263 & 3 \\ L22 & 53.175 & 4 \\ L42 & 52.717 & 5 \\ L63 & 52.266 & 6 \\ L52 & 51.044 & 7 \\ L64 & 50.402 & 8 \\ L61 & 49.644 & 9 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Industry 4.0/5.0 technology ranking. Figure 3: Cause–effect diagram for Industry 4.0 and Industry 5.0 technologies. The ranking analysis shows that the highest-rated technology, based on the global preference flow, is L12, ahead of L11, L23, and L22. Technologies characteristic of Industry 5.0, including L42 and L63, also ranked high, confirming their growing role in the directions of transformation.