## 3 Methodology
After describing the novelty of the model, we describe the problem, formulate the prerequisites and axiomatics of building an econometric model [58], justify endogenous variables for evaluating the company's activities and justify the choice of exogenous variables for each endogenous variable. The authors' methodology that is applied to select the indicators for assessing the maturity of a logistic system is based on dividing the indicators into production, financial, and socioeconomic ones. With this approach various areas where a logistic system is operating can be embraced and the capabilities of the logistic system during its development can be pointed out. The literature review shows that in order to assess the stability in development of various systems, quite a big number of various indicators are used [59, 60, 61, 62]. As a rule, the following approaches can be applied: ratio analysis, Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Complex Proportional Assessment (COPRAS), Data Development Analysis (DEA). The advantage of the method used in the suggested methodology to select indicators is the consideration of the interrelation and interdependence of the indicators. This reflects the real life of various socioeconomic systems where all resulting indicators are interdependent and affect each other. The dependent variables used are variables namely Revenues, Marketing costs, Equity, Number of employees, Net income, Market capitalization (Appendix A, Table A1). The independent variable used in this research is R&D Expenses for the development of digital technology. In addition to the main independent variable of R&D Expenses, several control variables are used, namely Share capital, Earnings per share, GDP of the USA, Net national income of the USA, Inflation of the USA (CPI) (Appendix A, Table A2). Table 1 shows the dependent variables for building a model assessing the impact of digital information technologies, Table 2 shows the independent variable. \begin{table}
\begin{tabular}{c c c} \hline \hline  & **Units** & **Variables** \\ \hline \(Y_{t}^{i}\) & & \\ \(Y_{1}^{i}\) & mln \$ & Revenues \\ \(Y_{t}^{2}\) & mln \$ & Marketing costs \\ \(Y_{t}^{3}\) & mln \$ & Equity \\ \(Y_{t}^{4}\) & people & Number of employees \\ \(Y_{t}^{5}\) & mln \$ & Net income \\ \(Y_{t}^{6}\) & mln \$ & Market capitalization \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Dependent variables. Secondly, we use special methods of parameterization due to the violation of the prerequisites of the least-squares method. We present data on the selected indicators in the Tables A1 and A2 for 2000-2016 (Appendices A and B). Then we check the time series of variables for stationarity using the Dickey-Fuller test;  
Next, we make a structural form of the model in the general view. The structural view of the model is based on the following statements:  
1. The process of development of a logistic system is assessed with indicators--a set of endogenous variables (denoted as \(Y_{j}\)), selected according to the procedure proposed by the authors;
2. There is a prehistory of the process of development of the logistic system, i.e., each endogenous variable is affected by the values of the previous periods of the endogenous variable denoted as \((Y_{j-t})\);
3. The endogenous variables mutually influence each other;
4. Each endogenous variable is affected by internalities and externalities, evaluated by the exogenous variables (denoted as \(x_{i}\)). Correlation analysis is conducted (Appendix B). For each equation, we check endogenous and exogenous variables for multicollinearity based on the correlation matrix. Next, we select lags of the endogenous variable that have a strong correlation with the value of the variable at the last stage and check the autocorrelation coefficients using Ljung-Box Q-test. The system of equations in the structural form based on the analysis of variables is to be written (Appendix C). Then, we consider the identifiability of the system of equations (Appendix D).