PURPOSE. The paper studies the influence of urbanization on the social and economic aspects of regional transport and tourism industries. METHODS. The tourism transport infrastructure is characterized by non-linear processes. Nonlinearity allows to create and test the models of the system with realistic dynamic characteristics and develop the models of various processes. Simulation modeling is the most promising method for building simplified descriptions of real processes in order to study their behavior in different possible situations. RESULTS AND THEIR DISCUSSION. Simulation modeling is a theory that describes the structure and internal interactions in the system. The structure of the model can be based on the principles of dynamic behavior of a system with a feedback. Alternatively, the model can present a description of some observed fragments of the system. Describing process dynamics, the model can change the rates and levels for system’s behavior transformation in time, and according to the tasks for which it was developed. CONCLUSIONS. It is found that modeling of regional tourism transport infrastructure aims at finding its optimum states which would correspond to the growing transport and tourist flows. It would also offer the alternatives of transport system development and redistribution of transport flows in the region in order to reduce the load on the territory and environment, propose the ways to increase customer satisfaction with the complex of tourist and transport services as well as present the methods to transform transit passengers and visitors into the tourists of the region.
The paper deals with the engineering training problems in the field of information and communication technologies (ICT). It analyzes the content and relationship of ICT educational and professional standards, formulates a number of engineering education problems under a two-level system of personnel training and proposes their solutions.
The article describes a new PRIM index for evaluating the innovative potential of the region. It briefly reviews the concept of building the PRIM index. Three sub-indices that constitute the PRIM index are characterized: an IRLA index (index of innovative regulatory legal acts), an OII index (index of objects of innovation infrastructure) and an ISM index (index of innovation support mechanisms) are characterized. The formula for calculating sub-indices is given. Three groups of respondents (representatives of business structures, innovation organizers and senior students) are characterized. The results of using the PRIM index in the Irkutsk region are presented. Graphs are given and the interpretation of the obtained results is provided.