Managing project activities in organizations of additional professional education based on the example of the Regional Academy of the Federal Tax Service of Russia

The aim of this study is to develop and justify methods for managing project activities in organizations of additional professional education (hereinafter also referred to as DPO) based on advanced artificial intelligence technologies that enable forecasting specific indicators of economic processes and further planning of those. The subject of the research is the organizational relationships arising in the management of project activities within DPO organizations. The analysis of the factors determining the specificity of activities in the DPO segment allowed the authors to develop a project management method and test it using the example of the regional Academy of the Federal Tax Service of Russia. The application of this method will enable DPO organizations to make informed decisions when implementing projects in educational activities aimed at obtaining economic benefits for a specific industry and achieving sustainable growth indicators for such organizations. The scientific novelty of the conducted research lies in the generalization and refinement of the conceptual framework of the studied sphere of activity and the formation of a system of criteria that allows for the assessment of project management effectiveness. In forming the conceptual framework, the criteria determining the effectiveness of project management in DPO organizations were taken into account, such as the presence of managerial competencies among the staff of educational organizations, the alignment of tasks performed by teachers with organizational goals, and the willingness of personnel to participate in projects. The developed management method contributes to the advancement of scientific knowledge regarding the mechanisms of managing project activities in DPO organizations. For the Academy of the Federal Tax Service of Russia, the method consists of simultaneous optimization across all regions of corporate profit tax, personal income tax (PIT), and property taxes based on their corresponding tax base factors, the skill level of employees, and information security in the regions. The optimization is carried out using artificial intelligence technologies including a multi-objective genetic algorithm (MGA), simulated annealing (SA), and pattern search (PS). A conclusion has been made regarding the necessity of implementing new educational programs on corporate profit tax and property taxes, as there is a failure to achieve the projected values for these goals.

continuous education, additional professional education, educational organization, project management, project, artificial intelligence technologies, decision-making, project management methods, professional development, tax collection forecasting