## 4 Results
### Testing Methods for Assessing the Impact of Digital Information Technology  
General view of the system of equations:  
\[ \begin{array}{l}y_{1}^{1}=f(y_{t-j}^{1};y_{1}^{3};y_{1}^{5};X_{1}^{1};X_{2} ^{2};X_{3}^{3};X_{4}^{4};X_{5}^{5};X_{t}^{6})\\ y_{t}^{2}=f(y_{t-j}^{2};y_{1}^{3};y_{1}^{4};y_{1}^{5};X_{1}^{3};X_{1}^{4};X_{1} ^{5};X_{1}^{6};X_{1}^{6})\\ y_{1}^{3}=f(y_{1-j}^{3};y_{1}^{2};y_{1}^{4};y_{1}^{5};y_{1}^{6};X_{1}^{4};X_{1} ^{5};X_{1}^{6})\\ y_{t}^{4}=f(y_{t-j}^{4};y_{1}^{3};y_{1}^{5};X_{1}^{4};X_{1}^{6})\\ y_{t}^{5}=f(y_{t-j}^{5};y_{1}^{2};y_{1}^{3};y_{1}^{4};y_{1}^{6};X_{1}^{3};X_{1} ^{4};X_{1}^{6})\\ y_{t}^{6}=f(y_{t-j}^{6};y_{1}^{5};X_{1}^{2};X_{1}^{5};X_{1}^{6})\\ \end{array}  \tag{1}\]  
Structural form of the model is as follows:  
\[\left\{ \begin{array}{l}Y_{t}^{1}\ =\ c_{1}^{5}*Y_{5}^{5}+c_{1}^{4}*X_{4}^{4}+c_{1}^ {1}*X_{6}^{6}+a_{1}^{1}*Y_{t-1}^{1}\\ Y_{2}^{2}\ =\ d_{2}^{2}*X_{4}^{4}+d_{2}^{2}*X_{6}^{6}+c_{1}^{1}*Y_{t-1}^{1}\\ Y_{t}^{3}\ =\ d_{3}^{3}*X_{2}^{3}+d_{5}^{2}*X_{6}^{6}+a_{3}^{2}*Y_{5}^{5}+b_{3}^{3}*Y_{t -1}^{3}\\ Y_{t}^{4}\ =\ b_{3}^{4}*Y_{5}^{5}+d_{3}^{3}*X_{2}^{5}+b_{4}^{3}*Y_{t-1}^{4}\\ Y_{t}^{5}\ =\ c_{3}^{5}*Y_{3}^{3}+d_{6}^{5}*X_{t}^{6}\\ Y_{t}^{6}\ =\ d_{4}^{6}*X_{t}^{6}\end{array} \right. \tag{2}\]  
\(a_{j}^{i}\), \(b_{j}^{i}\), \(c_{j}^{i}\), \(d_{j}^{i}\)(\(i\ =\ \overline{1.6}\), \(j\ =\ \overline{1.6}\)) are the coefficients of the structural form of the model. To obtain the reduced form from the structural one, we analyze the identification of the system of equations in order to determine the method of least squares, by which we will find the coefficients of the equations. Following this methodology, we obtain the system of reduced equations. All equations are statistically relevant and the regression equations are reliable (for the significance level \(\alpha\) = 0.05). Thus, the system of simultaneous econometric equations, which reflects the influence of digital technologies on the resulting indicators, is as follows:\[\left\{\begin{array}{rl} \begin{array}{rl}Y_{t}^{1}\ =\ 0.248182*X_{t}^{4}+(0.023389)*Y_{t-1}^{5}+ 0.361364*X_{t}^{6}+0.402139*Y_{t-1}^{1}\\ \begin{array}{rl}Y_{t}^{2}\ =\ 0.41659*X_{t}^{4}+0.41559*X_{t}^{6}+(-1.14967)*Y_{t-1}^{ 2}\\ Y_{t}^{3}\ =\ (-0.185153)*X_{t}^{5}+(-0.002232)*X_{t}^{6}+0.504226*Y_{t-1}^{5}+0.686448* Y_{t-1}^{4}\\ Y_{t}^{4}\ =\ 0.975343*Y_{t}^{3}+(-0.028588)*X_{t}^{6}+(-0.001165)*Y_{t-1}^{4}\\ Y_{t}^{5}\ =\ 0.354256*X_{t}^{2}+(-0.300417)*Y_{t-1}^{3}+(-0.139665)*X_{t}^{6}\\ Y_{t}^{6}\ =\ 0.907024*X_{t}^{1}\end{array}\right.\end{array}  \tag{3}\]  
The model obtained reflects the dependence of the resulting performance indicators of the Salesforce company in the global economy environment on the factors influencing it. This model makes it possible to identify the factors that influence the main indicators reflecting the Salesforce activity and the intensity of this influence. This model also allows to forecast the values of indicators over a given time interval. Appendix E explains how the model equations are derived. The equation parameters and test statistics are shown in Tables 10-21: (a) test statistics, which are used in the calculation of the coefficients of the equations of the structural form of the model; (b) the criteria used to justify the selected equations. These are the well-known test statistics that allow us to judge the objective properties of the general population based on the results of our sample. Let us explain the information contained in the tables. Tables 10, 12, 14, 16, 18 and 20 contain estimates of the coefficients of the equations of the structural form of the model, the standard error (SE) of an estimate of a parameter (coefficients), value t-Student's criterion, p-level, confidence limits (lower and upper) of the confidence interval of the deviation of the values of the equation coefficients. The equation is written under each table, to which the information in the table applies.