## 1 Introduction
Fifteen experts in the area of well-being, macroeconomics, construction, human development and quality of life assigned the same significance (equal to 1) to all 30 well-being, macroeconomic, construction, human development and values-based decision factors, which means the significances of the 30 criteria add up to a total of 30. The units of the criteria were determined, and their values and significances were calculated. When the criteria values and significances are available, and multiple criteria decision methods applied, the success and utility degree of the construction industry is rather easy to determine and the industry's priority (efficiency) easy to establish. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Data** & **Unit** & **Source** \\ \hline \(X_{1}\): Average GDP growth (annual \%) from 1990 to 2019 1 & Percentage & [73; 74; 75; 76] \\ \(X_{2}\): GDP per capita in USD, 2018 & USD & [77; 78; 79; 80; 81; 82; 83; 84; 85; 86; 87; 88; 89; 90; 91; 92; 93; 94; 95; 96; 97; 98; 99; 100; 101; 102; 103; 104; 1  
Stages 1-5 of the INVAR technique [57] were applied to perform multiple criteria assessment of the sustainable construction industries in the EU member states (see Figure 1). Stage 1. Calculate the weighted normalised decision table, D. Applied equations:  
\[d_{ij}=\frac{x_{ij}\cdot q_{i}}{\sum_{j=1}^{n}x_{ij}},i=\overline{1,\ m},j= \overline{1,\ n} \tag{1}\]  
\[\sum_{j=1}^{n}d_{ij}=q_{i} \tag{2}\]  
Calculations:  
\[d_{11}=1*4.53/(4.53+2.19+1.96+3.03+8.4+1.64+5.83+4.22+4.14+2.92+4.2+3.88\] \[+2.57+4.15+3.67+4.16+4.31+3.76+3.15+4.38+2.02+1.71+4.98+2.82+4.62\] \[+3.27+4.4)=1*4.53/100.91=0.0449;\]  
\[d_{61}=1*1.5/(1.5+1.2+1.8+1.3+2.3+1.7+1.2+2.3+2.5+3+1.5+2.5+0.6+1.5\]  
\[+2.4+0.9+4.2+1.8+2.6+0.7+2.6+1.2+3.4+1+1.7+0.7+2.5)=1*1.5/50.6=0.0296\]  
Stage 2. Calculate the sums of advantageous attributes (\(S_{+j}\)) and non-advantageous attributes (\(S_{-j}\)). Applied equations:  
\[S_{+j}=\sum_{i=1}^{m}d_{+ij},\ S_{-j}=\sum_{i=1}^{m}d_{-ij},\ i=\overline{1,\ m},\ j=\overline{1,\ n} \tag{3}\] \begin{table}
\begin{tabular}{c c c c} \hline
**Compared Countries** & **Success of a Country** & **County’s Priority Rank** & **County’s Utility** \\ **(\(a_{j}\))** & **(\(Q_{j}\))** & **(\(P_{j}\))** & **Degree (\(U_{j}\)), \%** \\ \hline Germany & 1.3039 & 4 & 86.93\% \\ France & 1.0668 & 15 & 71.12\% \\ United Kingdom & 1.2027 & 9 & 80.18\% \\ Denmark & 1.4228 & 2 & 94.86\% \\ Norway & 1.5 & 1 & 100\% \\ Sweden & 1.2803 & 6 & 85.36\% \\ Finland & 1.2552 & 7 & 83.68\% \\ Lithuania & 1.0863 & 13 & 72.42\% \\ Estonia & 1.1553 & 11 & 77.02\% \\ Latvia & 1.0034 & 19 & 66.90\% \\ Belgium & 1.1107 & 12 & 74.05\% \\ Bulgaria & 0.7662 & 27 & 51.08\% \\ Greece & 0.891 & 25 & 59.40\% \\ Austria & 1.1899 & 10 & 79.33\% \\ Poland & 0.9892 & 20 & 65.95\% \\ Portugal & 1.0111 & 18 & 67.41\% \\ Romania & 0.8416 & 26 & 56.11\% \\ Slovenia & 1.0549 & 17 & 70.33\% \\ Slovakia & 0.9692 & 22 & 64.62\% \\ Cyprus & 1.085 & 14 & 72.34\% \\ Czech Republic & 1.0556 & 16 & 70.38\% \\ Ireland & 1.301 & 5 & 86.74\% \\ Hungary & 0.9824 & 21 & 65.50\% \\ Croatia & 0.9035 & 24 & 60.24\% \\ Luxembourg & 1.3771 & 3 & 91.81\% \\ Italy & 0.9682 & 23 & 64.55\% \\ Netherlands & 1.2261 & 8 & 81.75\% \\ \hline \end{tabular}
\end{table} 
Table 2: Outcomes of the multiple criteria evaluation of the construction industries of 25 EU countries, the UK and Norway. \[S_{+} = \sum\
olimits_{j=1}^{n}S_{+j}=\sum\
olimits_{i=1}^{m}\sum\
olimits_{j=1 }^{n}d_{+ij},=\overline{1,\ m},\ j=\overline{1,\ n} \tag{4}\] \[S_{-} = \sum\
olimits_{j=1}^{n}S_{-j}=\sum\
olimits_{i=1}^{m}\sum\
olimits_ {j=1}^{n}d_{-ij},=\overline{1,\ m},\ j=\overline{1,\ n} \tag{5}\]  
Calculations:  
\[S_{-1}=0.0301+0.0073+0.0103+0.0202+0.0083+0.0344+0.0296+0.0447+0.0171=0.202\]  
\[S_{+1}=0.0449+0.0432+0.0392+0.047+0.0444+0.0402+0.0391+0.0453+0.0376\]  
\[+0.0375+0.0312+0.0286+0.0338+0.0355+0.039+0.0409+0.0404+0.0398+0.0357\]  
\[+0.0389+0.0404=0.8226\]  
Stage 3. Determine the relative significances or priorities of the alternatives based on positive and negative alternative features.