Our article analyses the prospects of coal industry development in the 21st century. It is apparent that the share of coal in the world’s total energy mix is shrinking as it is replaced by natural gas, renewables, and other forms of energy production. In the same time, countries like China, Russia, but also Poland are dependent on coal as the major fuel for generating their electricity. Quite remarkably, China is using more coal to generate electricity for powering its growing fleet of electric vehicles and transport. This cycle needs to be broken in order to ensure the full transition to the renewable energy future and reducing the burden on the climate and global warming. We argue that the shift away from coal to the renewable energy is driven mainly by the growth of green energy policies and supporting actions induced by the political forces. However, it might still remain the major source of power generation in less-developed and developing economies.

Globalization activates qualitative changes in multiple economic entities and requires the development of alternative forms of business organization. At present, one of the most promising development tracks is represented by the implementation of network structures, aimed at achieving common goals and obtaining a win-win outcome via joint effort. Business structures that invite dynamic and consistent transformations on a wide scale prove to be able to successfully compete in the market. In this regard, a project management system at a medical hub serves as a vital tool for implementation of open innovation. Participation in the medical hub allows coordinating intentions and establishing aligned communication between all stakeholders, suppliers and private institutions. In modern sectors of the economy, a developing hub becomes a unique structure, because it unites the contributions of the most important healthcare specialists in a single framework. This research examines the structure of healthcare business process models, and scrutinizes the communication between suppliers, partners and consumers of medical services. It also defines the main directions and outlines strategic goals. Assessment of performance of a project management system at a medical hub proves to be the issue of particular relevance, due to the fact that its tasks should be primarily aimed at increasing the share of successful projects and implementing only those ones that comply with the strategy. Based on the latter, a model for the project management system at a medical hub was designed. As a result, the authors developed an assessment mechanism for innovative projects using SNA methods that align with intra-communication interactions (transactions) between the participants in a medical hub. The conducted research allows concluding that in the current era of cutting-edge technologies, the project management system should be considered the most effective management tool for coordinating the actions of a corporate structure at a medical hub.

The formation of project executives is the most important task facing the project manager and a project leader. Indeed, it is possible to formulate goals correctly, set tasks correctly, choose appropriate management methods and mechanisms, but all this may be in vain if not enough attention is paid to personnel selection. The paper considers the existing approaches to the formation of project teams. The task of forming the team of project executives in the general case is to re-group them by project teams on the basis of the existing set of applicants with many different indicators so that the combined interaction between the members of each team would be as effective as possible. It is worth noting that this problem reduces to the NP-hard problem of combinatorial choice. However, along with the assessment of the professional suitability of employees and roles, it is necessary to consider several indicators: psychological compatibility between team members, the degree of interchangeability in the context of the work performed, etc. All these indicators can be measured in points; however, the values of their indicators can belong to different scales. It is said that such situations are modelled under multicriteria conditions. Our paper presents a methodology for the formation of project teams and builds a model using an interdisciplinary approach based on methods of graph theory, socionics, and operational research.

The article presents a methodology for predicting the success of project initiatives based on an analysis of the structural characteristics of project team communication networks. The study is based on data from task tracking systems (Jira, Trello) that reflect formal interactions between project participants. The research methodology includes a set of analytical tools: correlation analysis using Spearman’s and Pearson’s coefficients, regression modeling based on the Random Forest algorithm, and anomaly detection methods using Isolation Forest. The study revealed statistically significant correlations between key network metrics (betweenness centrality, network density, graph diameter) and project performance indicators (adherence to deadlines, budget, quality of results). A statistically significant negative correlation was found between excessive centralization and adherence to deadlines (ρ = –0.72), as well as a positive correlation between network density and quality of results ( r = 0.68). The developed model based on Random Forest demonstrates the accuracy of forecasting the success of projects at the level of 84%. It was found that excessive centralization of communications reduces the probability of successful project implementation, while the optimal density of the communication network contributes to the achievement of project KPIs. The practical significance of the study lies in the possibility of early detection of project failure risks based on objective metrics of communication activity. The developed methodology, tested on IT company data, allows not only to predict risks, but also to form recommendations for optimizing team interactions. The results of the study are of interest to project managers, HR analysts, and data-driven management specialists.