Airport. But at the same time, it is necessary to note the reconstruction and modernization of those airports that are functioning.Despite the fact that the number of airports in Ukraine was decreasing, the aviation industry was developing, as evidenced by the positive dynamics of the volume of passenger transportation from 2015 to 2019. The corona virus pandemic is a factor that undoubtedly affected the aviation industry not only in Ukraine, but also worldwide. In 2020, the drop in the volume of passenger

A transport system can be defined as a complex system characterized by a random value of transport demand, variable weather and climatic factors, a set of characteristics of transport infrastructure, and a complex system of interconnections. One of the key modes of transport providing freight transport both in domestic and international traffic is road. Its mobility and the ability to deliver cargo from door to door is a unique competitive advantage over other modes of transport. To create an effective logistics infrastructure that meets the demand for domestic freight transport, first of all, information is needed on the needs for transport between regions of the country. Thus, it is necessary to look for mathematical approaches to modeling freight flows, combining their practical implementation using widely used software products (for example, MS Excel). The purpose of the paper is to build effective multifactor regression models of demand for input and output transportation of goods by road for each region of Ukraine according to publicly available statistical data of the State Statistics Service of Ukraine. The modern approach to modeling cargo flows requires fast processing of a large amount of statistical data. In addition, the method should be as universal as possible and capable of quick and simple changes under conditions of a change in statistical data. From this point of view, the most acceptable option can be considered to be the modeling of freight traffic using regression models based on correlation and regression analysis. In general, the task is to find the dependence of the demand for transportation on the factors that influence it. Such factors in the existing models are connected with various macroeconomic indicators, as well as the distance of delivery. The data of regional statistics of the State Statistics Service of Ukraine and data of the “Lardi-Trans” website as the most widely used by freight carriers and shippers were taken as the initial data for modeling. A list of factors has been found that significantly influence the demand for freight transport by road between regions of Ukraine. A rating of influencing factors has been compiled, among which are the gross regional product, regional volumes of foreign trade in goods (imports) and gross regional product per one inhabitant of the region. The absolute values of the correlation coefficients are in the range 0.351-0.974. The lowest correlation coefficient is between the transportation distance and the demand for delivery, which proves a negligible relationship between the volume of regional transportation and the distance of delivery. Multivariate regression models with thirteen, five and two factors of influence on demand are built. Accuracy parameter values are acceptable for all model variants. The normalized R-squared of the obtained models does not fall below 84%, and the average approximation error does not rise above 1.6%, which is an excellent performance of the models.

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