This article analyzes the evolution of management theories' understanding of time as a factor in enterprise competitiveness. From Taylorist timekeeping, which viewed time as a measure of labor operations, through the concepts of "just-in-time" and first-mover strategies, the analysis addresses contemporary challenges: the attention economy, the asynchronous nature of work processes, and the potential of artificial intelligence. The article argues that, in the context of digital transformation and the spread of artificial intelligence, competitive advantages accrue to companies that are able not only to optimize personnel time resources and accelerate processes but also to manage the attention of employees and customers, including through the transition from a "reactive" to a "proactive" IT infrastructure.

The relevance of the study is due to the need to comprehend the processes of qualitative transformation of the labor market under the influence of technological shocks of the fourth industrial revolution (Industry 4.0), characterized by the convergence of artificial intelligence, robotization, and big data. The purpose of the work is to identify the key mechanisms of adaptation of the labor market to automation and digitalization. The methodological framework for this study is based on a synthesis of institutional economics and human capital theory, supplemented by a comparative data analysis. The study identified three aspects of labor market adaptation: technological, institutional, and individual. It was found that countries with a high share of the gig economy demonstrate faster labor reallocation but face increasing precarity and income polarization. A comparative analysis of adaptation models demonstrates that the effectiveness of adaptation depends not on the speed of technology adoption, but on the presence of shock-absorbing institutions, including continuous education systems (Lifelong learning) and the government's active policy on the labor market. The theoretical significance of the study lies in the development of a three-level adaptation model that explains the asynchronous nature of employment transformation.

The article is devoted to the development of mechanism for balanced innovative development of Russian industry through the use of government orders. The relevance of research is determined by the need to ensure the technological sovereignty of the country in context of increasing complexity of production and economic processes. Based on the analysis of statistical data, the problem of the structural imbalance of supply and demand in markets of innovative products due to the limited involvement of enterprises in innovation activities has been identified. The novelty of the research lies in the development of mechanism for interaction between the state, state corporations, vertically integrated companies and other participants in the innovation process when implementing projects to develop and organize the production of complex innovative products, including within the framework of government orders. The mechanism is based on the use of the proposed model for balancing demand, determined by government orders and the needs of vertically integrated companies, and supply, demonstrating the potential of innovation developers. Special attention is paid to the formation of competitive environment in the field of innovation as a factor in improving the efficiency of government procurement. The practical significance of articule lies in the possibility of applying the proposed mechanism and model in the formation of state programs for innovative development and increasing the competitiveness of industry.

The article is devoted to a comprehensive study of the mechanisms of transformation of the internal structure and functioning of design and survey organizations in the context of dynamic market changes. The relevance of the research is due to the need to adapt the design and survey sector to large-scale digitalization and changing economic conditions that require a revision of classical management models. The key factors influencing the maturity of business processes are analyzed in detail, including the impact of the external macroeconomic environment, current technological equipment, accumulated human resources and internal administrative standards. Using the partial least squares method (PLS-SEM), a three-level system of factors (basic, variability management, advanced) is verified and stable statistical dependencies are identified that determine the systemic complexity of production algorithms. This methodological approach has made it possible to accurately assess latent variables affecting the operational efficiency of companies. The article is of practical importance, as it mathematically confirms the priority role of modern management practices and external integration (impact factor β = 0.415) in the long-term development of project companies. The author proves that end-to-end technologies and human resources bring maximum synergetic effect not directly, but indirectly, through their deep integration into the overall system of administrative control and strategic management. Using the materials of the article can help managers, chief project engineers and analysts of large project associations to scientifically optimize the organizational structure and eliminate management gaps. The proposed theoretical conclusions make it possible to correctly allocate scarce investment resources, building clear priorities in the field of introducing advanced digital tools and consolidating strict regulated management standards to significantly improve overall production performance in modern macroeconomic conditions.

Accelerated digital transformation and the growing use of artificial intelligence technologies in Russian businesses in a competitive environment have exacerbated the lack of holistic management approaches to integrating machine learning models into business process management. The purpose of this study is to analyze the current state of such integration in a competitive environment, identify key barriers, and propose a methodology for synchronizing the BPM and ML lifecycles. In accordance with this goal, the following tasks are addressed: synchronizing the stages of the enterprise's business process lifecycle with the stages of the machine learning model lifecycle, identifying business problems and analyzing the situation, developing a machine learning model, aligning the goals and scope of ML application between business strategy and BPM objectives, and comparing approaches to integrating ML into BPM internationally and in Russia. The study developed a proprietary model for synchronizing the BPM and ML lifecycles, introduced metrics for evaluating integration effectiveness (forecast accuracy, productivity gains, implementation speed, etc.), conducted a systematic comparative analysis of international and Russian approaches (presented in a table), and proposed a structured step-by-step roadmap for implementing AI in business processes, specifying stages, participants, deadlines, and resources. This study confirmed that ML integration can increase productivity, reduce costs, and improve the customer experience of enterprises in a competitive environment. However, its adoption is hampered by a number of barriers (poor data quality, skills shortages, resistance to change, security risks, etc.).

The article systematizes scientific views on the content of the concept of "competitiveness of the region". Four approaches to its understanding are identified – socio-economic, techno-technological, institutional, marketing, their advantages and disadvantages are identified. The necessity of adapting the region's competitiveness management to the meaningful characteristics of the category is substantiated. The basic foundations of the managerial stage are formulated within the boundaries of the marketing vision. An algorithm for managing the competitiveness of the region has been developed, the starting point of which is the formation of a conceptual framework for positioning the territory, which makes it possible to identify significant consumer groups for it, and the result is to achieve a balanced consumer structure and increase the competitiveness of the region both as a whole and in the context of targeted groups – the population, enterprises and tourists, due to compliance with the principle of target orientation in the allocation of regional resources. A set of indicators of the ratio of regional resources and consumer flows has been proposed to identify "missing", "sufficient", and "redundant" groups, and management models have been developed to restore the balance of consumer flows, taking into account the strategic priorities of the region. The methods of comparison, content analysis, modeling, statistical and balance method contributed to obtaining significant conclusions. The theoretical and methodological developments proposed by the author streamline the system of views on the content and management of the competitiveness of the region from the standpoint of a marketing approach, and provide the basis for further theoretical research in this field of knowledge. The conclusions and suggestions obtained can be useful in the practical activities of government authorities in the process of developing strategic planning documents, achieving strategic priorities and developing effective management decisions aimed at increasing the competitiveness of the region, and in the future adapted to different levels of the spatial system.

The article analyzes the problems of increasing the effectiveness of strategic planning mechanisms in the regional construction sector. The system-forming role of the construction complex in the regional economy, the need to fulfill target indicators of national projects and the decrease in the effectiveness of existing planning procedures in conditions of macroeconomic instability – these three factors determine the high relevance of the topic. The scientific novelty of the work lies in the fact that the authors do not limit themselves to stating the dynamics of industry indicators, but identify institutional gaps between strategic guidelines and actual trajectories of development of construction production. Based on empirical material from the Oryol region for 2023–2025. For the first time, it has been shown that the systematic overfulfillment of planned indicators in 2024 – by 19.5% is a consequence not so much of management efficiency as of a strategy of lowering planned targets, which creates the illusion of stability, but when the situation worsens, it results in the failure of plans in 2025 – a decrease in input by 5.6%. The methodological basis of the study included a comparative analysis of foreign and domestic strategizing models, statistical analysis of the dynamics and structure of housing construction, assessment of the efficiency of use of fixed assets, as well as methods of program-target and scenario planning. The information basis was provided by data from Orelstat, the Unified Resource of Developers, reports from the Government of the Oryol Region and the Ministry of Construction of the Russian Federation. The theoretical significance of the work lies in the substantiation of the criterion of adaptability as a key indicator of the effectiveness of strategic planning – as opposed to the traditional focus on the formal implementation of quantitative plans. The practical significance lies in the development of proposals for adjusting the monitoring system and mechanisms of state support for the construction sector, taking into account the identified imbalances: underestimation of planning targets, high market concentration and a structural shift towards individual housing construction.