Siberian Journal of Economic and Business Studies

Background. The relevance of this study is determined by the increasing impact of various external and internal environmental factors destabilizing the higher education system. This, in turn, has a negative impact on its economic security.

Purpose. Development of an original approach that allows for a comprehensive assessment of the economic security of the higher education system.

Methodology. The article used such research methods as GAP analysis, content analysis, analysis and synthesis, statistical methods of analysis, and the Herfindahl-Hirschner index.

Results. А comprehensive approach to analyzing the indicators and criteria for economic security of the higher education system has been developed and tested.

Practical implications. The results obtained can be used by federal government and administrative bodies to improve the efficiency of the higher education system and increase the level of its economic security.

Background. In the context of implementing national priorities in spatial development and ensuring sustainable economic growth of territories, the problem of comprehensive assessment of the state of socio-economic development of single-industry towns is becoming increasingly important. It is shown that for substantiating strategic decisions regarding single-industry towns, a formal status and fragmentary characteristics are insufficient; a holistic understanding of the conditions and obstacles to their development is required.

The proposed approach is based on the use of comparable statistical indicators and is oriented towards the practical task of differentiating the priority directions of strategic development of single-industry towns.

Purpose – identifying the conditions and obstacles to their development and determining the priority areas for the strategic development of single-industry towns by conducting a comprehensive assessment of their socio-economic development based on key statistical indicators.

Method and methodology. Data from official statistics on single-industry municipalities and town-forming enterprises are used. The main method applied is statistical analysis, supplemented by methods of dynamic and structural analysis.

Results. The assessment results confirm that the use of a unified system of indicators, including demographic, labour, economic and investment parameters, makes it possible to link the state of single-industry towns with the tasks of strategic management of their integrated development: the identified relationships make it possible to substantiate the priorities of state support and to determine the set and focus of instruments depending on the current state of a single-industry town.

Practical implications. The approach to comprehensive assessment can be used by public authorities and development institutions as an instrument for differentiating state support measures and setting priorities for the strategic development of single-industry towns, including those having the status of supporting settlements.

Background. Modern government agencies operate in an environment of continuously growing volumes of generated information – from classic statistical reporting to digital behavioral traces arising from citizen interactions in the digital environment. However, prevailing methodological approaches to performance assessment still rely primarily on retrospective analysis and averaged performance indicators, which reduces the flexibility of the public administration system and hinders the development of predictive and analytical models for decision support.

Despite the widespread adoption of digital technologies throughout the country, a key element of the management cycle – the performance assessment system – largely retains characteristics of the industrial management model, where assessment is essentially limited to recording achieved indicator values. This prevents the adequate identification of hidden relationships, predictive factors, and potential risks in the dynamics of the management system. As a result, a gap arises between the technological potential of modern analytical platforms and the existing methodological framework for performance-based management.

Purpose. research and improvement of the architecture of the system for assessing the performance of executive authorities and senior officials of the constituent entities of the Russian Federation.

Materials and methods. The article is based on a set of sources presented by regulatory legal acts, statistical and reference materials.

Results. It was revealed that there are shortcomings in the current architecture of the performance evaluation system for executive bodies and senior officials in the constituent entities of the Russian Federation. A modernization option is proposed that offers several advantages enabling a transition to proactive management and more effective performance, seamlessly integrating with the current architecture.

Background. This article presents the results of an analysis of the bread and bakery market. Both domestic and international scholars have addressed the analysis of food segments and the algorithm for substantiating competitive strategies for economic entities in their research. Based on a review of scientific literature devoted to the analysis of the bread and bakery market and the rationale for adapting to the impact of the competitive environment, it can be concluded that the scientific literature has paid insufficient attention to the relationship between the specific features of this market and the models of the main competitive strategies of bakery enterprises, which determined the choice of research topic.

The objectivepurpose of the study was to identify and analyze trends in the development of the bread and bakery market and to substantiate the competitive strategies of specialized enterprises operating in this market.

Materials and methods. We used research methods such as analysis and synthesis, abstraction, modeling, monographic analysis, and time series analysis. The information base consisted of data from the Federal State Statistics Service for the Omsk Region and the Russian Federation.

Results. Based on statistical data analysis, it was concluded that, on average, over the period 2010-2023, each resident of the country consumed 117 kg of bread and bakery products in their diet annually, which is significantly higher than the recommended norm. The study was conducted in the Omsk Region, where bread consumption exceeds the Russian average; for the period 2010-2023, per capita bread consumption was 127 kg. It was revealed that consumer demand for bread and bakery products is gradually transforming, with a decrease in demand for traditional, mass-produced breads and an increase in demand for bread and bakery products with various additives and reduced-calorie options. A forecast of bread and bakery product consumption was conducted by processing a dynamic series using the least squares method. The calculation results allowed us to conclude that the projected values for bread and bakery product consumption in 2025-2027 will be In the Russian Federation, per capita consumption of bread and bakery products will not exceed 114 kg. In the Omsk Region, the decline in consumption of these products will be more significant, averaging 114.6 kg per capita in 2025-2027.

Conclusion. The decline in demand for bread and bakery products will be accompanied by a further reduction in production volumes of these products by regional enterprises and increased competition in the bread and bakery market. When substantiating competitive strategies, it is recommended to consider market development characteristics, enterprise resources and capabilities, technological development, seasonality of demand, and consumer preferences. Basic competitive strategies are proposed that bakeries can use to adapt to changes in the competitive environment of the bread and bakery market.

Background. The article is devoted to the analysis of the prospects for the formation of a tourist brand in the city of Verkhoyansk (Republic of Sakha (Yakutia)), a settlement with an officially registered absolute minimum temperature in the Northern Hemisphere (-67.8°C). Based on a comparative analysis of successful international urban branding cases (Rovaniemi (Finland), Oslo (Norway), Irkutsk (Russia), Veliky Ustyug (Russia)), the authors have developed a multi-level positioning strategy that includes phases of identification, productive development and promotion.

Purpose. The aim is to develop scientifically based and practical recommendations for creating an attractive international tourism brand for the city of Verkhoyansk based on the adaptation of successful practices of international urban branding.

Materials and methods. The methodological basis of the research is a synthesis of qualitative approaches, including a comparative analysis of successful international cases, an assessment of Verkhoyansk’s internal potential and external conditions using SWOT analysis, as well as strategic modeling based on the theoretical framework of Simon Anholt’s place branding (the “Hexagon of Nations” model) and Philip Kotler’s place marketing.

Results. Special attention is paid to the balance between the commercialization of extreme climate and the preservation of the authentic cultural environment of the indigenous peoples of the North. The result of the research is a roadmap that provides for the creation of a cluster model and a set of communication solutions for target audiences.

Background. In a highly competitive world in the tobacco market, companies face the need to optimize their data analysis and decision-making processes. The main problem is the processing of ever-growing volumes of sales data that were previously stored and analyzed in Excel, which led to slower analysis processes, calculation errors, and reduced effectiveness of marketing strategies. To solve this problem, the company’s management decided to switch to using modern technologies.

The relevance of the study is due to high competition in the tobacco market and the need to optimize data analysis and decision-making processes. Previously, sales data was stored and analyzed in Excel, which slowed down analysis, led to calculation errors, and reduced the effectiveness of marketing strategies.

Purpose: to develop and implement a machine learning-based data analysis and sales forecasting system to improve the effectiveness of trade marketing

Methodology. The work uses machine learning methods, automation of analytical reporting, as well as tools for working with data (PostgreSQL, Power BI, Python). Airflow is used to manage the execution of data processing scripts and model training, monitor the updating of analytical reports, and integrate the system with CRM.

Results. A data processing and analysis system has been developed; data has been transferred from Excel to PostgreSQL to solve encoding problems; automatic data loading and conversion mechanisms have been implemented; high-quality data preparation for analysis has been carried out.

Practical implications. The results of the study can be applied in companies working with large volumes of data; in the field of business analytics and working with big data; in industries with fierce competition and complex market conditions.

Background. Fluctuations in economic activity remain a key focus of macroeconomic analysis, as the phases of the business cycle reflect the economy’s response to external and internal shocks. For Russia, this topic is particularly relevant due to repeated crisis episodes over the past two decades and the need for reliable tools to diagnose phases of growth and recession. A comparison of time-series filtering methods makes it possible to identify which of them provide the most accurate assessment of cyclical fluctuations in GDP.

Purpose – is to conduct a comparative analysis of the cyclical components of Russia’s real GDP extracted using the Hodrick-Prescott (HP), Baxter-King (BK), and Christiano-Fitzgerald (CF) filters.

Materials and methods. Quarterly Russian GDP data for 2003 - 3rd quarter 2025 (at 2021 prices, seasonally adjusted) were obtained from Rosstat. The study employed econometric and statistical methods of time-series analysis: the HP, BK, and CF filters implemented in the Statsmodels package (Python).

Results. The analysis showed that all three methods consistently capture the main recessions in the modern Russian economy – 2009, 2015-2016, and 2020. The BK and CF filters produce nearly identical cyclical trajectories, with a correlation coefficient of about 0.97, indicating their statistical equivalence in business-cycle estimation.

The HP filter generates a higher-frequency, noisier component and smooths the negative phases at the series ends due to the endpoint problem. This results in lower accuracy when identifying short-term downturns (about 75% of crisis quarters compared to 100% for BK and CF).

The extracted cycles reproduce the well-known recessionary periods: the sharp GDP decline in 2009, the contraction in 2015–2016, and the 2020 downturn are captured by all three methods. Band-pass filters (BK and CF) provide a more realistic dynamic that reflects the duration and depth of crisis phases, while HP smooths amplitudes and accelerates the transition to recovery. The novelty of the study lies in the comparative evaluation of three classical filters using a modern Russian dataset, including the most recent observations, and in the quantitative assessment of their ability to accurately detect crisis episodes.

Practical implications. The results can be used for business cycle analysis, assessment of deviations of actual GDP from potential levels, macroeconomic forecasting, and the development of anti-crisis economic policy measures.