## 2 Methods
### Launching an Expert Survey
The remaining three were rejected due to the acceptable loss of information (the total influence of which did not exceed 5%). Consistency of expert opinions was evaluated using the concordance coefficient:  
\[\mathrm{W}=\frac{12\sum_{i=1}^{n}\left(\sum_{j=1}^{m}a_{ij}-\frac{1}{2}m(n+1) \right)^{2}}{m^{2}(n^{3}-n)}=0.887, \tag{2}\]  
where n is the number of factors (11),  
m is the number of experts (113),  
a is the matrix of experts' opinions. Further, according to the findings of the expert questionnaire, the most significant eight parameters, having the greatest influence on the quality of a construction facility, were identified:  
* Specifications for construction facilities (\(P_{1}\));
* Reliable and sufficient materials, including engineering surveys (\(P_{2}\));
* Compliance with administrative and engineering solutions (\(P_{5}\));
* Compliance with the sequence of work procedures (\(P_{6}\));
* Geotechnical monitoring (\(P_{7}\));
* Availability of hoisting machinery (\(P_{8}\));
* Use of industrial formwork systems (\(P_{10}\));
* Use of advanced engineering machinery (\(P_{11}\)). The presence of eight factors, changing at three levels, entails the following factor-based experiment:  
\[\mathrm{N}=3^{k}=3^{8}=6561 \tag{3}\]  
where 3 is the number of levels of variability,  
k is the number of factors. \begin{table}
\begin{tabular}{c c c} \hline \hline \(\mathrm{\boldsymbol{N}}\) & **Factors** & **Expert’s Score** \\ \hline
1. & Specifications for construction facilities \\ \hline
2. & Reliable and sufficient materials, including all sections on engineering surveys (reports on engineering-geodesic, engineering-geological, engineering-ecological, engineering-hydrological surveys) \\ \hline
3. & Compliance of design solutions with requirements of Construction Regulations, State Standards, and other regulatory and engineering documents in force at the moment of examination \\ \hline
4. & Full compliance of supplied materials and equipment with the requirements of regulatory and design documentation \\ \hline
5. & Compliance with administrative and engineering solutions \\ \hline
6. & Compliance with the sequence of work procedures \\ \hline
7. & Geotechnical monitoring \\ \hline
8. & Availability of hoisting machinery \\ \hline
9. & Number of employees, including specialists with sufficient work experience and appropriate qualifications \\ \hline
10. & Use of industrial formwork systems \\ \hline
11. & Use of advanced engineering machinery \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The questionnaire to be completed by the experts (the template). According to the results of the analysis of the intercorrelation matrix, we can identify four groups of interrelated variables (\(z_{1}\), \(z_{2}\), \(z_{3}\) and \(z_{4}\)):  
* First group \(z_{1}\): facility specifications (\(P_{1}\)) and work sequence compliance (\(P_{6}\));
* Second group \(z_{2}\): reliable and sufficient materials, including all sections on engineering surveys (\(P_{2}\)) and geotechnical monitoring (\(P_{7}\));
* Third group \(z_{3}\): compliance with the requirements of administrative and engineering solutions (\(P_{5}\)) and availability of hoisting machinery (\(P_{8}\));
* Fourth group \(z_{4}\): use of industrial formwork systems (\(P_{10}\)) and advanced engineering machinery (\(P_{11}\)). The significance of all groups of factors was determined using the dispersion index of factor loading and factors. To calculate the value of group \(z_{i}\), we need to find the total sum of squares of loading of each of \(x_{1}\) factors in all columns of the factor matrix. Their importance characteristics indicate how much dispersion the particular group \(z_{i}\) takes up in the intercorrelation matrix.