## 5 Results and Discussion
In the final stage of the evaluation, within the PROMETHEE II model, each of the 22 technologies (L11-L64) was assigned an appropriate type and class of preference func  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Modern Technology Notation** & **U1–U2** & **U1–U3** & **U2–U1** & **U2–U3** & **U3–U1** & **U3–U2** \\ \hline L11 & 1.000 & 0.334 & \(-\)1.000 & \(-\)0.666 & \(-\)0.334 & 0.666 \\ L12 & 0.  
tion. Depending on the characteristics of the technology, either quantitative functions (e.g., based on measurable units) or qualitative functions (based on expert assessments) were applied. For the quantitative functions, parameters and reference units were also defined to facilitate managerial interpretation and practical implementation. All assignments are presented in Table 8. Additionally, each technology was assigned a dominant transformation perspective (U1-U3), in which its implementation is particularly impactful. This categorization was based on the results of the previous ranking analysis and validated through expert consultation. In the literature, several classes of preference functions are distinguished [86]. The most commonly used ones include the following: class 1--a function without a discrimination threshold; class 2--a function with a fixed threshold value; class 3--a linear preference function. The selection of the appropriate type of preference function--qualitative or quantitative--determines the assignment of a specific parameter to each function (Table 9). This parameter can take one of three values: 0, 1, or 2. The value 2 indicates a strong association between the given technology and a specific perspective, while the value 0 signals a low likelihood that the given perspective is relevant for the assessed technology. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Modern Technology** & **Modern Technology** & **Type of Preference** & **Class of Preference** & **Parameter** & **Unit of Preference** & **Perspective for Assessment of Industrial** \\  & **Notation** & **Function** & **Function** & **Value** & **Function** & **In Industrial** \\ \hline Internet of Things & & & & & & & \\ (IoT) & L11 & Quantitative & 1 & 0 & Number of beacons & U3 \\  & & & & & & Number of security \\ Cybersecurity & L12 & Quantitative & 3 & 1 & & & \\  & & & & & software, and & \\  & & & & & & processes & \\ Wireless & & & & & & & Percentage of \\ Communication/5G & L13 & Quantitative & 3 & 2 & & communication & U3 \\ \hline Artificial Intelligence & & & & & & & share \\ (AI) and Machine & & L21 & Qualitative & 2 & 1 & - & U2 \\ Learning (ML) & & & & & & & \\ Big Data and Data & & L22 & Qualitative & 2 & 1 & - & U2 \\ Analytics & & & & & & Number of IT & U3 \\ IT Support Systems & L23 & Quantitative & 1 & 0 & & systems & \\ \hline Cloud Computing & L31 & Qualitative & 2 & 1 & - & U1 \\
3D Printing (Additive & & & & & Share in total & U1 \\ Manufacturing) & & & & & & production & U1 \\ Robotics and Automation/Autonomous & & & & & & Share in total & U1 \\ Production Systems & & & & & & production & U1 \\ Augmented and & & & & & & & \\ Virtual Reality & & & & & & & U2 \\ (AR/VR) & & & & & & & \\ \hline Human-Centered & & & & & & & \\ Robotics & & & & & & & \\ (New-Generation & & & & & & \\ Cobots) & & & & & & & \\ Hyper-Personalized & & & & & & & \\ Production & & & & & & \\ Neuromorphic & & & & & & & \\ Computers and & & & & & & & \\ Brain–Machine & & & & & & & \\ Interfaces & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Industry 4.0 and 5.0 technologies and perspectives for industrial transformation assessment. Considering the values from Table 9 and the weighting coefficients from Table 4, the final form of the differences (Table 10) between the evaluation perspectives for each technology is determined based on Equation (7).