The issues of managing complex engineering projects for product development in conditions of high technical risks and uncertainty have been studied. The disadvantages of traditional management accounting systems have been considered, and ways to overcome them through implementing formalized decision-making algorithms have been proposed. The methodological contradictions between static accounting systems and the dynamic nature of innovative projects have been analyzed. An adaptive approach has been substantiated, which provides for a flexible combination of calculation methods and accounting of project life cycles, the central element of which is a system of quantitative threshold criteria formalizing key management procedures.

The algorithm of transition between the development stages, changes in calculation methods, cost capitalization, and reserves replenishment has been given. The developed system of algorithms for managing research and development works serves as the foundation for managing complex engineering projects in terms of forming models of the interrelationships of technical and economic parameters and developing classifiers of typical management situations with identifying features. The efficiency assessment demonstrates a reduction in calculation errors and operational risks.

The integration of the proposed system of formalized algorithms into digital end-to-end controlling platforms and E-Management class systems for automating managerial decision-making makes it possible to move from solving specific management automation problems to creating a holistic management theory for complex engineering projects in the context of digital transformation. The study results prove an increase in the accuracy of financial planning and a reduction in operational risks when using the proposed algorithms.

In the context of the development of Industry 4.0, the nuclear industry is faced with the need to rethink the employment structure and update the professional competencies of specialists. The relevance of the research topic is due to the fact that digital transformation of the nuclear industry is not only a technological, but also a socio-economic process that has a direct impact on the employment structure, the labor content, and employees’ professional identity. The purpose of the study is to scientifically substantiate conceptual approaches to managing employment transformation and formation of new competencies of nuclear industry specialists in the context of digital modernization. To achieve it, the following tasks have been solved.

The current trends in digital development of the nuclear industry and their impact on the employment structure and staff labor content have been analyzed. Changes in professional roles and qualification requirements for nuclear industry specialists in the context of digitalization have been identified. A set of key professional competencies has been identified that ensure the economic and managerial effectiveness of employees in a digital production environment.

A conceptual model of transformation of employment and competencies of nuclear specialists has been developed, reflecting new forms of labor organization and trajectories of professional development of personnel. Practical recommendations have been formulated to improve the personnel policy, the professional education system, and the mechanisms of continuous training at nuclear industry enterprises. Based on systemic and institutional approaches, a conceptual model for the transformation of nuclear specialists’ employment has been developed, reflecting new forms of labor organization, requirements for digital and managerial competencies, as well as the trajectories of personnel’s professional development.

It has been proved that digital transformation contributes to improving the quality of employment and strengthening the role of competencies related to analytics, project management, and security. The practical significance of the research lies in the possibility of using the results obtained when forming human resource management strategies and developing professional education programs and continuous training systems at nuclear industry enterprises.

The innovative activities management in tourism companies in the context of accelerated digital transformation has been studied. The purpose of the study is to develop and empirically validate a strategic management decision support model based on a hybrid architecture of artificial neural networks. The model is designed to predict the effectiveness of innovation initiatives and make recommendations on choosing the optimal type of innovation (product, process, or marketing).

The hypothesis of the study is that a joint analysis of the external environment through the processing of unstructured text data and an assessment of a company’s internal innovation potential will improve the accuracy and adaptability of strategic management in tourism.

The methodological base of the study includes the collection and pre-processing of multi-source data such as financial and operational indicators of travel companies, user reviews, as well as digital maturity indices. A pre-trained BERT language model, bidirectional LSTM networks, and a multilayer perceptron have been used to build the model. Training and quality assessment have been conducted using k-fold cross-validation and the SHAP method for interpreting the results. The experiment has shown the accuracy of predicting the success of innovation at the level of 86.4%. During the pilot implementation, ROI from innovative projects increased by 12–27% in 10 companies.

The scientific novelty of the research lies in creating an integrated neural network model that combines predictive and prescriptive functions in the context of strategic innovation management in tourism.

The study results confirm that the use of neural network technologies increases the validity and flexibility of forming an innovation strategy. The model can be implemented in the practice of strategic planning of hotels, tour operators, online aggregators, as well as used by government agencies in the development of industry innovation policy.

A comprehensive analysis of the public finance management system transformation in the context of active digitalization has been carried out. The key principles and content of this process have been systematized, among which transparency, data integration, automation, and citizen engagement are of priority importance. The author studies in detail the role of modern technologies such as artificial intelligence, blockchain, big data, and digital platforms in improving efficiency, accountability, and sustainability of the budget system.

The main study result is the conclusion about forming a new, synergetic management model, where a combination of technologies allows moving from retrospective control to predictive risk analysis and proactive planning. Using the example of Russian practice, in particular the Electronic Budget State Information System, its system-forming role in ensuring end-to-end transparency of the entire budget cycle, minimizing transaction costs, and creating technological barriers to corruption has been proved.

Of particular practical importance is the revealed systemic contradiction: despite the high technological potential, its implementation is hindered by organizational barriers such as departmental fragmentation, lack of digital competencies, and resistance to change. The necessity of parallel deep institutional reforms has been substantiated in order to fully realize the advantages of digital transformation in public finance.

The possibilities and limitations of using digital analytics in the management system of spatial development of regions in the context of the regional economy transformation have been studied. The relevance of the research topic is due to the increasing territorial differentiation of the socio-economic development of regions and the need to increase the validity of management decisions based on the spatial data analysis. Digital analytics has been considered as a tool for identifying patterns of economic activity, factors of agglomeration development, and mechanisms for forming sustainable regional economic structures.

The purpose of the study is to analyze the potential of digital analytics for managing the spatial development of regions and identify key limitations of its application in regional practice. The analysis of theoretical approaches to spatial development and industrial agglomeration has been carried out, and the results of using spatial analysis and econometrics tools in assessing regional processes have been summarized.

It has been shown that the use of digital analytics makes it possible to increase the efficiency of identifying agglomeration effects and assessing the interrelationships between the production facilities location, infrastructural deve­ lopment, and the human resources potential of regions. At the same time, it has been found that the effectiveness of digital tools is limited by institutional, information, and personnel factors, including fragmented data and insufficient integration of analytical results into the regional management system.

The practical significance of the study lies in the possibility of using the findings when designing strategies for the spatial development of regions, forming regional industrial policy, and improving management support mechanisms for agglomeration processes.

The purpose of the study is to develop and empirically validate a data-driven managerial model for assessing the intellectual maturity of industrial ecosystems using the modified Analytic Hierarchy Process. The research hypothesis assumes that the intellectual maturity of industrial ecosystems is formed as a synergistic outcome of the interaction among strategic, process, organizational, data-related, architectural, and operational-innovation dimensions, rather than as the sum of their isolated characteristics.

The research methodological framework integrates the classical Saaty procedure with entropy-based weight objectification and an inter-dimensional interaction matrix, which makes it possible to account for nonlinear relationships and to reduce the subjectivity of expert judgments through the analysis of data variability.

The empirical validation has been conducted on an expert sample representing enterprises from the mechanical engineering, chemical-technological, pharmaceutical, and IT sectors. The average integrated level of intellectual maturity amounted to 3.6 on a 0–5 scale, corresponding to a transition from the Managed to the Established level. The highest levels of intellectual maturity have been observed in the strategic and architectural dimensions (3.9 and 3.8, respectively), forming the core of ecosystem maturity, while the process dimension has also demonstrated values close to the established level (3.7). At the same time, the organizational, data-related, and operational-innovation dimensions have exhibited lower maturity levels (3.4, 3.2, and 3.3, respectively).

The obtained study results confirm the applicability of the mo­ dified Analytic Hierarchy Process for the quantitative assessment and forecasting of the intellectual development of industrial ecosystems. The practical value of the study lies in the possibility of using the proposed model to design maturity-enhancement roadmaps, define priorities for digital and AI transformation, and support the transition from fragmented digitalization to sustai­ nable data-driven governance.

The impact of changes in the dynamics of the markets of additive technologies (3D printing) and the aerospace industry on the growth of the titanium market and its alloys has been studied, considering the scenario approach in conditions of economic instability. The data for 10 years of global demand for titanium and its alloys have been analyzed. Possible applications of titanium alloys in various industries have been considered. The analysis of the industry’s impact on achieving sustainable development goals in the context of stricter environmental regulations has been carried out. A step-by-step modeling plan has been presented for estimating the growth rate of the titanium market depending on the aerospace and additive technologies industries development.

Using a scenario approach, the dynamics of key consumer industries of titanium and its alloys has been analyzed, and the demand for the metal for each scenario has been calculated. The study results have shown that by 2050, the accelerated implementation of additive technologies and the growth of the aerospace sector will have a significant impact on the titanium market, while traditional sectors (chemical industry, energy) will maintain stable demand.

The increased use of titanium ­ creates opportunities for exporting countries, including Russia, to increase supplies and develop deep processing of raw materials. The prerequisites for further development of the proposed toolkit using alternative and sophisticated models to assess the growth rate of the titanium market have been given.

In the context of the global transition to sustainable economy, green financing mechanisms development and support for environmentally oriented businesses are of particular importance. Modern economic systems face the need to combine economic growth with environmental sustainability, which enhances the role of financial instruments aimed at supporting environmental projects and initiatives. The purpose of the study is to analyze the features of the development of green business and the green financing system in Kazakhstan and Russia, as well as to identify key trends and issues in sustainable financial mechanisms formation in the context of environmental transformation of the economies.

The theoretical foundations of green financing have been considered, and national sustainable development strategies have been analyzed, as well as tools for supporting environmental projects, including green bonds, government incentive programs, and financial mechanisms for sustainable investment. Special attention has been paid to the comparative analysis of the institutional conditions for developing green financing in Kazakhstan and Russia, the role of government institutions, the banking sector, and international organizations.

The methodological basis of the research includes comparative, systematic, and statistical analysis, as well as a generalization of scientific approaches to green economy development. The key directions of green financing development in the countries under consideration have been identified, as well as the main barriers preventing the more active implementation of environmentally oriented financial instruments.

The obtained research results allow us to conclude that the further development of green business and the green financing tools expansion are important conditions for forming sustainable economy and improving the environmental efficiency of economic development.

The practical significance of the research lies in the possibility of using its results when developing state policy in the directions of sustainable development and environmentally oriented financial mechanisms.

The purpose of the study is a comprehensive analysis of the key factors determining the dynamics of global demand for palladium, as well as the creation of forecast scenarios for its development until 2040, considering structural changes in the automotive industry. The market’s dependence on stricter environmental emission standards has been revealed, which stimulated the use of palladium in catalytic converters of gasoline engines.

Special attention has been paid to the structural shifts in the automotive industry caused by the transition to electric transport. The analysis has demonstrated that the rapid growth in sales of palladium-free battery electric vehicles is creating a long-term negative trend for demand. At the same time, it has been established that the segment of hybrid vehicles equipped with internal combustion engines remains a significant consumer of metal and acts as a key stabilizing factor in the market. Based on the scenario approach, three possible trajectories of the palladium market development have been constructed. Calculations has shown that aggregate demand will be determined by the balance between the growing production of hybrid vehicles and the continued production of traditional vehicles with internal combustion engines.

The conclusion about a possible reduction in the palladium market’s dependence on the automotive sector in the long term has been substantiated. The critical importance of demand diversification through developing new uses for the metal in hydrogen energy, electronics, and chemical synthesis has been emphasized.

Active development of artificial intelligence technologies creates opportunities and poses new challenges for social and economic modernization, and much depends on the willingness to use these technologies in specific economic systems. This paper is a review of a recently published book examining the role of artificial intelligence in digital transformation in the Global South. It contains 8 chapters, each of which is an independent scientific analysis of a specific aspect of the above-mentioned issues. The book is informative, and the number of noteworthy ideas is large. These include perceptions of infrastructural, legal, and other barriers to the mass use of artificial intelligence, dependence on dynamically changing investment volumes and competition for their flows, and emergence of fundamentally new issues of institutionalization of intellectual property and environmental sustainability in the context of rapid digitalization.

The monograph contains many examples of the successful use of artificial intelligence tools in the economies of the Global South countries and demonstrates a wealth of factual material. In general, the book allows to get a general impression of the economic activity specifics related to artificial intelligence in these countries. There are no country reviews in the book, and linking a number of arguments to the historical and cultural context could be stronger. Less than necessary attention has been paid to the situations in national education systems. Compositionally and stylistically, the publication is of high quality, and the extensive references lists in each chapter are interesting in themselves.

The reviewed monograph is a rare consolidated work of this kind; therefore, it may be of interest to Russian readers.