Optimal Management Decisions Research Articles

Typical mathematical models used in automated systems of organizational management

The article considers typical mathematical models used in automated control systems (ACS), a type of which are automated organizational control systems (ACOC), with the aim of making optimal management decisions. In our time, it is impossible to solve the problems of managing the economy by mechanically increasing the number of the governing apparatus, because the scale of the work requires such a number of people that cannot be directed to the sphere of management. An analysis of the most common types of tasks solved by managers at all levels of management is carried out: inventory management, distribution, mass service, ordering, replacement. An example of solving the problem of inventory management at a warehouse is given. A general description of mathematical models used in deterministic tasks of organizational and economic decision-making in organizational systems is given and the conditions for their application are given.

Model of selecting an optimal management decision for restoration of fixed assets of oil producing enterprises

Subject. The article explores the problem of oil refineries modernization. Objectives. The study aims at analyzing the options for organization of works on restoration of fixed assets of oil producing enterprises and devising an algorithm for cost optimization. Methods. The study employs methods of complex and comparative analysis. Results. We developed an economic and mathematical model enabling to choose the optimal management decision for the restoration of fixed assets of oil producing enterprises, taking into account geographical and technological factors. Conclusions. The findings may be taken into account when devising development programs for strategically important enterprises in conditions of economic uncertainty.

STRATEGIC ASPECTS OF TALENT MANAGEMENT IN A BUSINESS ORGANIZATION

The workforce shortage in the market, combined with the lack of important competencies and the high personnel mobility, are becoming a critical factor in the development of business organizations around the world. The lack of highly qualified personnel for domestic business organizations that operate under conditions of military aggression from Russia is particularly painful. Strategic talent management is a response to the need to increase the efficiency of intellectual resources usage in order to solve a wide range of organizational tasks, in particular, developing innovative products, optimizing management decisions, achieving competitive advantages and creating additional value. Developing a talent management strategy is considered as the starting point in talent management. A talent management strategy aims to improve business efficiency and is a step-by-step program of actions to optimize the performance of high-performing employees through the application of various management tools in the process of attracting, adapting, developing, motivating and retaining talent. The purpose of the article was to establish the principles of construction and a general algorithm for developing a talent management strategy in a business organization. Based on the defined principles, a three-stage scheme for developing a talent management strategy was formed. The initiation stage establishes the key parameters of the strategy development process, taking into account strategic goals and resource constraints. The activation stage determines measures to attract and adapt talents to reach a stable level of productivity. The integration stage refers to measures aimed at ensuring the long-term life cycle of talents, their deep awareness of their role, the achievement of optimal productivity and valuable results for the company. As a practical tool, a template of nine blocks is offered that reflect the specific management actions needed to develop a sound talent management strategy. This allows to provide analysis of the current situation in talent management and develop a reasonable program of actions regarding further measures of effective interaction with them to achieve the organization's strategic business goals.

Artificial Intelligence in Law and Legal Analytics

The author discusses the concept of artificial intelligence and analyses the approaches to its concept and definitions existing in science. In a sketch of emergence of artificial intelligence the author notes artificial intelligence represents a natural stage in the development of technical devices designed to facilitate human intellectual activity. The author offers a classification of devices endowed with artificial intelligence, distinguishing between narrow (weak) AI and general (strong) AI; he outlines the most relevant areas of its development and describes the development stages. Among the spheres of possible application of devices with AI, the author lists the search for and structuring of information; identification of new connections and patterns that humans cannot see; assisting humans in professional activities; relieving humans from time-consuming and unproductive intellectual activities; management automation; assistance in making optimal management decisions. The article places a special focus on the threats and risks associated with the proliferation of AI. The author believes these include: displacement of humans from socially important spheres of activity, and job hijacking; decline in the level of education and qualification of workers leading to degradation of human intellect; corruption of humanity by idle and meaningless existence leading to its physical and cultural degradation; danger of robots making erroneous technical, economic, environmental, medical, etc. decisions; threat of failures in the operation of industrial robots and computerised control systems; particularly dangerous is the deliberate use of robots to cause harm, including the use of military and security systems capable of causing harm to people and property. The article discusses various options for granting AI a legal status. The author assumes a device endowed with artificial intelligence is a complex and autonomously operating tool of human activity, relatively independent of human person. The latter, however, is fully responsible for the consequences of the use of this tool. The author is sure it is counterproductive to artificially extend legal statuses developed for man, who is an individual endowed with consciousness and will, to AI. The article contains results of a “parallel exam” on legal analytics for students and artificial intelligence held at the Department of Law of the National Research University Higher School of Economics in May 2023. Also the author discusses specific areas and examples of the use of AI in law and legal analytics in the spheres of law -making, law enforcement, jurisprudence, and education.

Methodological approaches to the assessment of innovation activity

Subject. This article examines the essence and content of such concepts as innovation, innovative activity of an industrial enterprise, its key elements and methodological approaches to their assessment. Objectives. The article aims to develop methodological approaches to the assessment of innovative activity of an enterprise on the basis of a system of indicators that comprehensively characterize innovative activity, innovative potential, as well as the effectiveness and efficiency of innovative activity. Methods. For the study, we used analysis and synthesis, a systems approach, indicative design of the analyzed processes, and the methods of detailing and logical generalization. Results. The article presents the author-developed methodological approaches to the comprehensive assessment of innovation activity on the basis of a system of indicators that can help quantitatively and qualitatively assess the innovation potential, trace its changes, innovative activity of the enterprise, outline the areas for improving innovation activity in order to increase the competitiveness and financial stability of the enterprise. The article also proposes a system of indicators for assessing the innovative activity of the enterprise as a whole, the research and development sector, and it recommends indicators of the impact of the results of innovation activity on the enterprise's economy, and for assessing the effectiveness of innovative projects. Conclusions and Relevance. The proposed methodology for assessing innovation activity based on a system of qualitative and quantitative indicators can help better understand innovation processes and related activities and the results obtained, as well as make optimal management decisions, identify and eliminate bottlenecks, find ways of innovative development and thereby increase the competitiveness of Russian enterprises and domestic products. The results of the study can be used in assessing the innovative activity, innovative potential of enterprises, the effectiveness and efficiency of the innovation process, in making optimal management decisions on strategic planning and making managerial decisions in the field of improving the innovation process, in the selection of the most effective innovative projects.

Mathematical model for managing marine ecosystem risks

The article presents the results of the research aimed at developing and verifying a mathematical model for managing the ecosystem risks of marine areas. The main purpose of the research is to create an effective tool for assessing and managing the risks arising from anthropogenic influence, climate change and other natural factors. The proposed model is based on the existing theory of sea ecosystem risks management and takes into account the relationship between natural and anthropogenic factors, condition of marine ecosystems, their vulnerability and ecosystem services. The model uses mathematical methods, in particular, differential equations, statistical analyses, simulation modeling and network analysis, allowing creation of detailed models that reflect marine ecosystems' dynamics and their response to external influence. Numerous experiments were conducted in order to verify the model. They demonstrate its ability to predict changes in the condition of marine ecosystems under influence of various factors. The results of the research show that the proposed model can be an effective tool for optimizing management strategies, minimizing ecosystem risks and improving sustainability of marine ecosystems. Practical recommendations developed on the basis of the results of the research include strategies for preventing, minimizing and adapting to potential threats, taking into consideration each region's and ecosystem's specifics. The proposed model helps to optimize management decisions, reducing risks and improving the condition of marine ecosystems affected by anthropogenic impact and climate change. It is a reliable tool for ensuring sustainability and preservation of marine ecosystems. This approach allows for evidence-based risk management that increases sustainability of marine ecosystems and their preservation for future generations. The model also considers key factors influencing marine ecosystems, including biological diversity, water quality, industrial fisheries, tourism and recreation, and allows evaluation of effectiveness of various management decisions in the context of such factors. The application of this model in ecosystem management practices allows making more informed decisions regarding protection and preservation of marine resources. It contributes to their sustainable development and provision of ecosystem services having critical importance for society.

P124 CARDIOVASCULAR RISK RE-CLASSIFICATION BY IMPLEMENTING CAROTID ULTRASONOGRAPHY IN PRIMARY CARE

Background and Objective: The accurate assessment of the total cardiovascular risk (CVR) using risk calculation algorithms in individuals with CVR factors in the primary prevention setting is essential for optimal management decisions, including drug treatment initiation and treatment goals. The aim of this study was to evaluate the contribution of ultrasonographic identification of asymptomatic carotid atherosclerosis in the re-classification of the CVR assessed with the reference SCORE2/2-OP algorithm. Methods: In individuals aged ≥40 years without established cardiovascular disease, the 10-year CVR was calculated using the SCORE2/2-OP algorithm (3 risk categories: low/moderate, high, and very high). Carotid ultrasound study was applied using a portable handheld device (Lumify, Philips) to classify CVR as follows: (i) low/moderate (absence of atherosclerotic plaque), (i) high (atherosclerotic plaque with <50% stenosis), (iii) very high (atherosclerotic plaque with ≥50% stenosis). Results: Data from 332 participants were analysed [age 59±7.5 years, men 41%, current smokers 26%, body mass index 28±5 kg/m2, office blood pressure 125±15/77±10 mmHg (systolic/diastolic), LDL-cholesterol 111±33 mg/dl]. Based on SCORE2/2-OP, 49/46/5% participants were categorised as of low/moderate, high, and very high CVR, respectively. Based on carotid ultrasound, the rates were 39/59/2%, respectively. 44% of individuals categorized as of low/moderate CVR based on SCORE2/2-OP were re-classified into a higher CVR category based on carotid ultrasound. The agreement between the 2 methods (ultrasound versus algorithms) in categorizing low/moderate and high CVR was 67% (kappa 0.35, P<0.001) and 61% (kappa 0.23, P<0.001), respectively. Among 204 participants categorized as of high/very high CVR according to carotid ultrasound, only 15 (7%) had LDL-cholesterol levels <70 mg/dl. Conclusions: These findings suggest that carotid ultrasonography using a portable handheld device may significantly contribute to assess CVR more accurately in primary care, especially in individuals classified as of low/moderate CVR using reference algorithms.

THE ROLE OF DATA ANALYTICS IN MAKING MANAGEMENT DECISIONS BY THE LOGISTICS INTERMEDIARIES

Data analytics plays a crucial role in increasing the effectiveness of management decisions by the logistics of intermediaries. The aim of the article is to identify the extent to which the quality of data analytics affects the effectiveness of decision-making in the logistics intermediaries, in particular, the speed of delivery of the studied companies.The study employed regression and correlation analysis to identify key influencing factors in terms of data analytics on the effectiveness of management decisions of the logistics intermediaries. The significance of investment in the qualification of analysts (with a coefficient of -1.6754), analytical tools (with a coefficient of -1.2575), and integration of analytics in decision-making processes (with a coefficient of -3.2511) directly affect the reduction of delivery time.It is emphasized that each analytical project contributes to the reduction of delivery time by 0.48 hours. Correlation analysis confirmed the relationship between the efficiency of logistics and the level of qualification of analysts (-0.283617), investment in analytical tools (-0.257322), the number of analytical projects (-0.343792), the level of integration of analytics (-0.712058). The strongest correlation was observed for the integration of analytics in management decision-making.It is recommended to focus on the development of analytical competencies, increase of investment in tools, intensification of projects, and integration of analytics in strategic management. Further research is planned on the use of artificial intelligence to optimize management decisions in logistics as part of ensuring the company’s sustainable development.

SENECA study: staging endometrial cancer based on molecular classification

ObjectiveManagement of endometrial cancer is advancing, with accurate staging crucial for guiding treatment decisions. Understanding sentinel lymph node (SLN) involvement rates across molecular subgroups is essential. To evaluate SLN involvement...

Biochemical versus stomatal acclimation of dynamic photosynthetic gas exchange to elevated CO2 in three horticultural species with contrasting stomatal morphology.

Understanding photosynthetic acclimation to elevated CO2 (eCO2) is important for predicting plant physiology and optimizing management decisions under global climate change, but is underexplored in important horticultural crops. We grew three crops differing in stomatal density-namely chrysanthemum, tomato, and cucumber-at near-ambient CO2 (450 μmol mol-1) and eCO2 (900 μmol mol-1) for 6 weeks. Steady-state and dynamic photosynthetic and stomatal conductance (gs) responses were quantified by gas exchange measurements. Opening and closure of individual stomata were imaged in situ, using a novel custom-made microscope. The three crop species acclimated to eCO2 with very different strategies: Cucumber (with the highest stomatal density) acclimated to eCO2 mostly via dynamic gs responses, whereas chrysanthemum (with the lowest stomatal density) acclimated to eCO2 mostly via photosynthetic biochemistry. Tomato exhibited acclimation in both photosynthesis and gs kinetics. eCO2 acclimation in individual stomatal pore movement increased rates of pore aperture changes in chrysanthemum, but such acclimation responses resulted in no changes in gs responses. Although eCO2 acclimation occurred in all three crops, photosynthesis under fluctuating irradiance was hardly affected. Our study stresses the importance of quantifying eCO2 acclimatory responses at different integration levels to understand photosynthetic performance under future eCO2 environments.

Hereditary Syndromes Associated with Pancreatic and Lung Neuroendocrine Tumors.

Pancreatic neuroendocrine tumors (PanNETs) and lung NETs (LNETs) represent a rare but clinically significant subgroup of neoplasms. While the majority is sporadic, approximately 17% of PanNETs and a subset of LNETs develop in the context of monogenic familial tumor syndromes, especially multiple endocrine neoplasia type 1 (MEN1) syndrome. Other inherited syndromes associated with PanNETs include MEN4, von Hippel-Lindau (VHL) syndrome, neurofibromatosis type 1 (NF1), and tuberous sclerosis complex (TSC). These syndromes are highly penetrant and their clinical manifestations may vary even among members of the same family. They are attributed to genetic mutations involving key molecular pathways regulating cell growth, differentiation, and angiogenesis. Pancreatic NETs in hereditary syndromes are often multiple, develop at a younger age compared to sporadic tumors, and are associated with endocrine and nonendocrine tumors derived from multiple organs. Lung NETs are not as common as PanNETs and are mostly encountered in MEN1 syndrome and include typical and atypical lung carcinoids. Early detection of PanNETs and LNETs related to inherited syndromes is crucial, and specific follow-up protocols need to be employed to optimize diagnosis and management. Genetic screening is recommended in childhood, and diagnostic screening starts often in adolescence, even in asymptomatic mutation carriers. Optimal management and therapeutic decisions should be made in the context of a multidisciplinary team in specialized centers, whereas specific biomarkers aiming to identify patients denoted to follow a more aggressive course need to be developed.

Making decisions under demographic, management, and monitoring uncertainty with value of information

AbstractLearning and resolving uncertainty should be important components of management decisions, but not every type of uncertainty is equally important to resolve. For rare, threatened, and endangered species, information may be limited and there is often great urgency to halt potential population declines. Therefore, the most important uncertainties are those that would lead to different decisions intended to improve outcomes for species of interest. The New England cottontail (Sylvilagus transitionalis) is an endemic species to the northeastern United States and is listed as a species of special concern, threatened, or endangered in all states in its current range. States within the historical New England cottontail range have made substantial investments in habitat management, captive breeding, and research, but considerable demographic, management, and monitoring uncertainties remain. Connecticut is the geographic core of the current range of the species and therefore has been the focus of many management efforts, including improving habitat, creating new habitat patches, removing eastern cottontails (Sylvilagus floridanus), and releasing captive‐bred New England cottontails. We used a value of information analysis to identify the optimal management decision given current uncertainty and to evaluate how sources of uncertainty might lead to changes in management decisions. Given the current understanding of the New England cottontail in Connecticut, we identified the optimal management decision as improving existing habitat patches without monitoring for the species and managers could expect a 3.4% increase in populations if decision‐making uncertainty could be fully resolved. Multiple sources of uncertainty influenced results, but variation in New England cottontail density and the response of the species to the removal of eastern cottontails were most likely to result in changes to management decisions. At lower New England cottontail densities, releasing captive‐bred individuals competed with improving habitat as the optimal management action. Accounting for the value of information benefits New England cottontail management by guiding research efforts toward information that is most beneficial for decision‐makers and providing insights into parameter thresholds that would lead to changes in management decisions.

Imaging of Neuroendocrine Neoplasms; Principles of Treatment Strategies. What Referring Clinicians Want to Know.

Neuroendocrine neoplasms (NENs) are a diverse group of tumors that express neuroendocrine markers and primarily affect the lungs and digestive system. The incidence of NENs has increased over time due to advancements in imaging and diagnostic techniques. Effective management of NENs requires a multidisciplinary approach, considering factors such as tumor location, grade, stage, symptoms, and imaging findings. Treatment strategies vary depending on the specific subtype of NEN. In this review, we will focus on treatment strategies and therapies including the information relevant to clinicians in order to undertake optimal management and treatment decisions, the implications of different therapies on imaging, and how to ascertain their possible complications and treatment effects.

Estimating carbon sequestration potential and optimizing management strategies for Moso bamboo (Phyllostachys pubescens) forests using machine learning

Estimating the carbon sequestration potential of Moso bamboo (Phyllostachys pubescens) forests and optimizing management strategies play pivotal roles in enhancing quality and promoting sustainable development. However, there is a lack of methods to simulate changes in carbon sequestration capacity in Moso bamboo forests and to screen and optimize the best management measures based on long-term time series data from fixed-sample fine surveys. Therefore, this study utilized continuous survey data and climate data from fixed sample plots in Zhejiang Province spanning from 2004 to 2019. By comparing four different algorithms, namely random forest, support vector machine, XGBoost, and BP neural network, to construct aboveground carbon stock models for Moso bamboo forests. The ultimate goal was to identify the optimal algorithmic model. Additionally, the key driving parameters for future carbon stocks were considered and future aboveground carbon stocks were predicted in Moso bamboo forests. Then formulated an optimal management strategy based on these predictions. The results indicated that the carbon stock model constructed using the XGBoost algorithm, with an R2 of 0.9895 and root mean square error of 0.1059, achieved the best performance and was considered the optimal algorithmic model. The most influential driving parameters for vegetation carbon stocks in Moso bamboo forests were found to be mean age, mean diameter at breast height, and mean culm density. Under optimal management measures, which involve no harvesting of 1–3 du bamboo, 30% harvesting of 4 du bamboo, and 80% harvesting of bamboo aged 5 du and above. Our predictions show that aboveground carbon stocks in Moso bamboo forests in Zhejiang Province will peak at 36.25 ± 8.47 Tg C in 2046 and remain stable from 2046 to 2060. Conversely, degradation is detrimental to the long-term maintenance of carbon sequestration capacity in Moso bamboo forests, resulting in a peak aboveground carbon stock of 29.50 ± 7.49 Tg C in 2033, followed by a continuous decline. This study underscores the significant influence of estimating carbon sequestration potential and optimizing management decisions on enhancing and sustaining the carbon sequestration capacity of Moso bamboo forests.

ALGORITHM FOR CALCULATING THE COEFFICIENT OF LABOR PARTICIPATION OF OPERATORS OF LINES, MACHINES AND PLANTS USING THE 1C:ENTERPRISE SYSTEM

The purpose of the study was to improve the remuneration system for operators of automatic lines, machines and plants by using the labor participation rate, which will allow making optimal management decisions on accounting for payroll settlements with staff and the achieving of strategic goals of the organization. The article suggests the ways to solve the problem using the example of improving the system of awarding bonuses to the staff of a manufacturing enterprise, it is recommended to use formulas that allow evaluating the productivity of an individual employee. Software implementation in the 1C:Enterprise system is performed. The developed software solution allows you to automate the process of calculating bonuses for operators of lines, machines and plants, taking into account the amount of work each employee does. The proposed algorithm for calculating the labor participation coefficient is supposed to be developed in further studies to more accurately assess the contribution of an employee's labor, for example, by taking into account defects and evaluating the quality of manufactured products. Purpose. Development of an algorithm for calculating the coefficient of labor participation of operators of lines, machines and plants using the 1C:Enterprise system. Methodology: in article methods for formalizing and specifying formulas used in calculating the labor participation rate, and also development methods on the 1C:Enterprise platform were used. Results. The software implementation of calculating the premiums of operators of lines, machines and plants taking into account the labor participation coefficient is performed. Practical implications it is expedient to apply the received results the manufacturing enterprises staffed by operators of automatic or semi-automatic lines, machines and plants.

Выбор критерия оптимальности при принятии управленческих решений в сложных технических системах

Criteria for the optimality of a management decision make it possible to predict possible options for solving a problem, analyze the influence of various factors and optimize the operation of the system. An effective management decision implies the choice of an option for solving a given problem that corresponds to the best achievement of the goal, in terms of initial information about the problem. Automating the search for multiple valid management decisions can significantly speed up the design process and provide more effective interaction between humans and systems. The use of a rational optimality criterion, taking into account the various stages of the system’s operation, will help to select optimal management decisions and achieve the goals of the project. Thus, the correct choice of optimality criterion ensures an effective search for solutions and helps to determine the set of optimal solutions for the designed technical system. This in turn allows you to increase the efficiency and quality of the organization. The purpose of this work is to substantiate the choice of optimality criterion for a management decision when designing a complex system - a logging highway. An analysis of existing criteria was carried out. An optimality criterion has been proposed and justified, denoting the effect of the construction of a logging road, calculated over the period from the beginning of its construction to the start of the first major repair. A system for automated search for management decisions is described.

TECHNICAL AND ECONOMIC ANALYSIS AND ITS ROLE IN IMPROVING THE EFFICIENCY OF THE ENTERPRISE

The essence of the technical and economic analysis aimed at improving the economic activity of enterprises and making optimal management decisions depending on the obtained results is revealed. It is pointed out the need to carry out a complex and systematic technical and economic analysis of the production and economic activity of the enterprise in order to objectively evaluate its results, which will contribute to increasing the efficiency of production. Systematicity consists in the study of the object as part of a higher-level system, and complexity - in the comprehensive and interdependent assessment of elements, the analysis of many characteristics of the enterprise's activity, which are reflected in the system of analytical and evaluation indicators. At the same time, the methods of comprehensive assessment of the enterprise's activity and the directions of its implementation are given, based on general indicators of production efficiency, financial condition and competitiveness. The most important tasks of the technical and economic analysis of the enterprise's activity are highlighted in order to ensure the scientific and economic validity of the enterprise's activity plans and the implementation of control over their implementation. It is emphasized that one of the important directions of the technical and economic analysis of the production and economic activity of the enterprise is not only its assessment, but also diagnostics, determination of factors affecting the analyzed indicators, and identification of reserves for improving work efficiency. Technical and economic analysis is basically intra-informative analysis. In the process of such an analysis, the activity of all structural subdivisions of the enterprise, services, shops, districts, teams and individual workplaces is investigated. The source of information for such an analysis is planning and normative data, operational and accounting materials, off-account data. Technical and economic analysis is carried out daily, for a decade, a month, a quarter, a year before drawing up the final report. Important management decisions are made based on the results of the analysis. Depending on the results of the diagnosis of the main indicators and the factors affecting them, it is proposed to make economic-mathematical and simulation models, the reliability of the analysis results will depend on their correct construction. For a more complete study of the activities of enterprises, it is recommended to use factor and correlation analyses based on mathematical, statistical and economic methods.

Theoretical principles of the study of agglomeration factors of the investment attractiveness of communities

Understanding the specifics of agglomeration factors is not just an academic exercise, but a crucial step towards forming an attractive investment climate in communities. In the face of globalization and intensified interregional competition, this understanding is paramount. Theoretical comprehension of these processes is not a mere intellectual pursuit, but a necessary tool to identify and analyze the mechanisms through which agglomeration influences investment activity and the economic efficiency of communities. This, in turn, will provide practical recommendations for optimizing management decisions at the local and regional levels of government. The importance of this research is further underscored by the need for local communities to adapt to changing external conditions, identify potential growth points, and form development strategies based on internal innovative resources and agglomeration advantages. The aim of this article is to analyze the theoretical foundations of studying the agglomeration factors of the investment attractiveness of territorial communities, with a clear focus on its practical implications. The article analyzes the theoretical aspects of the interaction between agglomeration phenomena and investment activity, considering the impact of scale, level of concentration, and specialization of production processes on regional economic development. Theoretical approaches to analyzing agglomeration factors are proposed, investigating their impact on economic development and the ability to mobilize investment resources within a specific territorial unit. The development of infrastructure capabilities, initiation of innovative clusters, and support for entrepreneurial activities serve as the main directions for enhancing the investment attractiveness of agglomerations. However, it's important to note that the process of creating urban agglomerations is not a simple task. It's a long-term endeavor that provokes debates and represents a significant level of complexity. It is determined that thanks to the agglomeration effect, regional development becomes more logical, focusing on a variety of economic activities in territories optimal for their implementation. Analyzing the level of development of urban agglomerations allows for a more targeted approach to planning their further development strategies, but it's a task that requires a deep understanding of the complex dynamics at play. Keywords: investment attractiveness, socio-economic development, agglomerations, agglomeration factors, territorial communities.

Models for building an enterprise data Warehouse

We live in an era of big data where data is generated continuously and at an exponential rate, so we need a place to collect, store and process it. Data can be generated by devices and sensors either remotely or in real time. The place where data can be collected, stored and processed is called a data warehouse. The term «data warehouse» was coined in the 1980s to describe a technology that allows companies to integrate data from many different sources into a single model. Data integration was seen as the most promising means of supporting deep insights into operational processes and identifying the latest opportunities to improve efficiency and profitability at the organizational level. An equally important role of data warehouses was seen as structural optimization by eliminating redundant decision support systems, most of which relied in one way or another on organizational performance data from the same centralized source. In contrast, the concept of a single data warehouse promised to eliminate redundancy and ensure data consistency, making it more suitable for optimizing management decisions at the enterprise level. This article discusses the concept of data warehouse, identifies its main advantages, reviews and compares enterprise data warehouse models and data platform on the example of Sberbank.

ЗАБЕЗПЕЧЕННЯ ЕКОНОМІЧНОЇ БЕЗПЕКИ ПІДПРИЄМСТВА НА ЗАСАДАХ ЗАДАЧ ДВОРІВНЕВОЇ ОПТИМІЗАЦІЇ

The article considers approaches to economic security management based on two-level optimization problems. Two-level optimization allows you to take into account the complex hierarchical structure of decision-making in large organizations, where strategic decisions of the upper level affect tactical and operational decisions of the lower level. This approach ensures consistency and efficiency of management processes, contributing to the achievement of economic stability and security of the enterprise. The article analyzes modern methods and models used to optimize management decisions in order to increase economic security. Mathematical models of two-level optimization that allow solving the problems of optimal allocation of resources, risk management, cost minimization and profit maximization are considered. Special attention is paid to the algorithms for solving such problems, in particular to the methods of sequential iteration and decomposition. The authors study the practical aspects of the application of two-level optimization problems in the management of enterprises of various industries. Examples of successful use of such approaches in real conditions are given, demonstrating their effectiveness in ensuring economic security. The analysis shows that enterprises that implement two-level optimization are able to respond more flexibly to changes in the external environment, use resources more efficiently, and reduce risks associated with financial instability, competition, and other threats. Thus, two-level optimization problems are a powerful tool for increasing the economic security of an enterprise. They enable the integration of strategic and tactical aspects of management, ensuring the integrity and consistency of decisions at all levels of the organization. The article makes a significant contribution to the development of the theoretical and practical foundations of ensuring the economic security of enterprises, offering new approaches and solutions that can be used in modern business conditions. Developed issues of ensuring the economic security of the enterprise in conditions of market turbulence.