## 3 Results
### Weighting with the CRITIC Method  
The 2018 performance criteria weights calculated using 13 different variables and the CRITIC method, an MCDM technique, are shown in Table 2. As seen in Table 2, the weighting coefficients of electricity from wind, electricity from hydro sources, consumer price index, and per capita energy use are higher for the first cluster, while the weighting coefficients of employment-to-population ratio, purchasing power parities and exchange rates, CO\({}_{2}\) emissions, and carbon intensity of electricity are higher for the second cluster. The weighting coefficients of electricity from solar sources, other renewables including bioenergy, population, labor force, and GDP indicators are higher for the third cluster compared to other clusters. There are significant differences between the criteria weights of all three clusters. The 2019 performance criteria weights are shown in Table 3. The weighting coefficients of population, labor force, GDP, and consumer price index are higher for the first cluster, while the weighting coefficients of electricity from wind, other renewables including bioenergy, employment-to-population ratio, purchasing power parities and exchange rates, and per capita energy use are higher for the second cluster. The weighting coefficients of electricity from solar sources, CO\({}_{2}\) emissions, and carbon intensity of electricity indicators are higher for the third cluster compared to other clusters. There are significant differences between the criteria weights of all three clusters. Table 4 shows the performance criteria weights for 2020. The weighting coefficients of electricity from wind, labor force, GDP, purchasing power parities and exchange rates, and consumer price index are higher for the first cluster, while the weighting coefficients of employment-to-population ratio, population, and per capita energy use are higher for the second cluster. The weighting coefficients of electricity from hydro sources, electricity from solar sources, other renewables including bioenergy, CO\({}_{2}\) emissions, and carbon intensity of electricity indicators are higher for the third cluster compared to other clusters. There are significant differences between the criteria weights of all three clusters. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & \multicolumn{3}{c}{**Cluster**} \\ \cline{2-4}
**Variables** & **1** & **2** & **3** \\ \hline Electricity from wind—TWh & 0.0739 & 0.0582 & 0.0601 \\ \hline Electricity from hydro sources—TWh & 0.0787 & 0.0666 & 0.0774 \\ \hline Electricity from solar sources—TWh & 0.0584 & 0.0679 & 0.0723 \\ \hline Other renewables including bioenergy—TWh & 0.0567 & 0.0624 & 0.0690 \\ \hline Employment-to-population ratio, 15+, total (\%) & 0.0362 & 0.0721 & 0.0605 \\ \hline Population & 0.1448 & 0.1455 & 0.1463 \\ \hline Labor force, total & 0.0704 & 0.0881 & 0.0930 \\ \hline GDP & 0.0768 & 0.0641 & 0.0796 \\ \hline Purchasing power parities and exchange rates & 0.0756 & 0.0785 & 0.0616 \\ \hline Consumer price index & 0.1089 & 0.0495 & 0.0752 \\ \hline CO\({}_{2}\) emissions & 0.0702 & 0.0843 & 0.0605 \\ \hline Carbon intensity of electricity—gCO\({}_{2}\)/kWh & 0.0436 & 0.0761 & 0.0623 \\ \hline Per capita energy use & 0.1059 & 0.0867 & 0.0824 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: “CRITIC” weight coefficients of the criteria for 2018. The performance criterion weights for 2021 are shown in Table 5. While the weighting coefficients of electricity from hydro sources, electricity from solar sources, employment, population, and consumer price index indicators are higher for the first cluster, the weighting coefficients of the labor force, purchasing power parities and exchange rates, and per capita energy use indicators are higher for the second cluster. The weighting coefficients of electricity from wind, other renewables including bioenergy, GDP, CO\({}_{2}\) emissions, and carbon intensity of electricity indicators are higher for the third cluster compared to the other clusters.