Regional Development Strategies Research Articles

Weaving a foundational narrative – place-making and change in an old-industrial town in East Germany

ABSTRACT In light of economic, social and discursive changes, old-industrial towns and regions increasingly apply entrepreneurial strategies to actively shape discourses as part of place-making processes. Foundational narratives play an important role in this regard. They are used by agents to foster cohesion in a local community, to legitimize and anchor their actions and goals and to make sense of complex development processes. Applying the methodology of Critical Narrative Analysis, the present study zooms in such processes of narrative building in Lauchhammer (Germany). Despite having experienced the decline of the most important parts of its industry, local actors still mobilize the industrial past in order to strengthen local identity and attract new businesses and manufacturers. Yet, the paper shows that different agents foreground different aspects of the industrial past and narratives may be contested. At the same time, local, regional and national development strategies are closely interlinked offering ‘opportunity spaces’ for local actors but raising also questions about a potential (de)legitimization of local narratives.

Assessment of the Dynamics of Structural Changes in the Socio-Economic Environment and Their Typology in the Context of a Statistical Approach

The purpose of the study is to substantiate the documentation for assessing the dynamics of structural changes in the socio-economic environment and their typology. The relevance of the study is related to the problems of reflecting the socio-economic environment, which affect the efficiency of economic activity. To address these issues, many regions of the country have adopted regional development strategies for the period up to 2030, which correspond to the national development goals of the Russian Federation. Various approaches of scientists to determining the essence and significance of the socio-economic environment, which is defined as a set of conditions and factors that influence all sectors of the economy, are studied.Methods: structural, index, comparative estimates and methodology of the system of national accounts.Results: the article uses a digital meter as a reproduction of the population and gross regional product (GRP), which objectively reflect the structural changes and typologies of the regions. GRP is calculated by types of economic activity, at the stages of: production, income generation and final consumption of households 2012-2021. Typologies of the Ural regions have been developed according to the following criteria: specialization of the economy, the position of the region in production, by types of primary income and final consumption of households per capita.Conclusion: the advantage of the statistical approach of studying the assessment of the dynamics of structural changes in the socio-economic environment and their typology allows us to get a more objective idea of the prevailing trends and the state of the regional economy. The results obtained made it possible to formulate a methodological basis for future scientific research in the field of structural changes in the meso-environment and socio-economic behavior of the population. They can also be used as a methodological basis for the development of public policy measures and strategies for sustainable development of territories in the future.

Study on Spatialization and Spatial Pattern of Population Based on Multi-Source Data—A Case Study of the Urban Agglomeration on the North Slope of Tianshan Mountain in Xinjiang, China

The urban agglomeration on the north slope of the Tianshan Mountains is a pivotal place in Western China; it is essential for the economic growth of Xinjiang and acts as a critical bridge between China’s interior and the Asia–Europe continent. Due to unique natural conditions, the local population distribution exhibits distinct regional characteristics. This study employs the spatial lag model (SLM) from conventional spatial analysis and the random forest model (RFM) from contemporary machine learning techniques. It integrates traditional geographic data, including land cover data and nighttime light data, with geographical big data, such as POI (points of interest) and OSM (OpenStreetMap), to build a comprehensive indicator database. Subsequently, it simulates the spatial population distribution within the urban agglomeration on the northern slopes of the Tianshan Mountains in 2020. The accuracy of the results is then compared and assessed against the accuracy of other available population raster datasets, and the spatial distribution pattern in 2020 is analyzed. The findings reveal the following: (1) The result of SLM, combined with multi-source data, predicts the population distribution as a relatively uniform and nearly circular structure, with minimal spatial differentiation. (2) The result of RFM, employing multi-source data, better captures the spatial population distribution, resulting in irregular boundaries that are indicative of strong spatial heterogeneity. (3) Both models demonstrate superior accuracy in simulating population distribution. The spatial lag model’s accuracy surpasses that of the GHS and GPW datasets, albeit still trailing behind WorldPop and LandScan. Meanwhile, the random forest model significantly outperforms the four aforementioned population raster datasets. (4) The population spatial pattern in the urban agglomeration on the north slope of the Tianshan Mountains predominantly consists of four distinct circles, illustrating a “one axis, one center, and multiple focal points” distribution characteristic. Combining the random forest model with geographic big data for spatialized population simulation offers robust scientific validity and practicality. It holds potential for broader application within the urban agglomeration on the Tianshan Mountains and across Xinjiang. This study can offer insights for studies on regional population spatial distributions and inform sustainable development strategies for cities and their populations.

Concept of Smart Specialization as a Strategy for Sustainable Regional Development

The subject of this paper is a review of previous research on smart specialization as a concept which is one of the strategies for sustainable development of regions. Innovations are considered as one of the key drivers of growth. Recognition of innovation which was central point of strategy ‘Europe 2020’ where ‘smart specialization’ needs to make possible for the regions and countries pursue those industries in which they hold a comparative advantage and which have basis for further innovations. The main purpose of this paper is defining smart specialization and its role on the regional development. Analysis and comparison of the scientific literature and applications of smart specialization were used as methods for this paper. The main findings of this paper show that the basis of smart specialization are innovation, knowledge and research which are pillars of smart, sustainable development. Smart specialization means identifying the unique characteristics and potential of each country and region, with the aim of achieving competitive advantages and excellence. It also includes strengthening regional innovation systems, increasing knowledge exchange and spillover the benefits of innovation throughout the regional economy. By comparison method of the scientific literature this paper will contribute to the development of theoretical background of smart specialization as a strategic concept formed by a group of European Union experts with the aim of reducing the gap in competitiveness between the European Union and the United States, which arises from the lower economic and technological specialization of European countries, especially at the regional level. Also it will promote smart specialization as a concept that can contribute to strengthening regional innovation policy and regional development.

Spatial spillover effects of conversion of new and old driving forces on high-quality development: Evidence from 283 cities in China

Converting the forces driving is essential for breaking away from the traditional unsustainable development model and achieving High-Quality Development (HQD). Understanding how the conversion from old to new forces influences HQD is crucial for achieving sustainable development. Therefore, the assessment framework for Conversion of New and Old Driving Forces (CNODF) and HQD are established. From an efficiency perspective, the Super-Efficiency slacks-based model (SBM) model, considering undesirable outputs, is used to measure HQD levels in Chinese cities. The entropy weight method is applied to measure CNODF levels. By integrating coupling coordination degree and relative development degree, the matching and synchronization between HQD and CNODF are categorized. Further, the study introduces the Spatial Durbin Model to quantitatively identify the spatial relationships between HQD and CNODF at both national and urban agglomerations scales. The research findings indicate that from 2006 to 2019, the national average HQD level increased by 50.5 %, and the average CNODF level increased by 11.5 %. The association between the two has strong spatial heterogeneity. At the national scale, CNODF has significant nonlinear spatial spillover effects on HQD. These findings provide theoretical insights for advancing the conversion of driving forces, and can help inform regional high-quality development strategies.

Combined biomass network design: A new integrated approach based on ArcGIS

In light of contemporary energy and environmental objectives, a pivotal transformation of the energy system, encompassing biomass energy, is imperative. A notable challenge in biomass energy facility layout planning is the trade-off between high-efficiency production and the associated investment costs. To harmonize energy efficiency with economy viability, a hybrid layout with the simultaneous construction of centralized and decentralized biomass energy facilities has emerged as a crucial strategic solution. However, the delineation methods for these two layouts lack explicit data support. This study established a population density threshold (PDT) suitable for selecting the distributed layout and employed population density as the criterion for delineating the two layouts. Taking Fuxin City as an example, hybrid layout planning schemes were generated under different PDTs, and a cost and energy benefit analysis framework was developed for these schemes. The results indicated that the scheme with a PDT of 145 person/km2 exhibited the highest energy and economic comprehensive benefits. Compared to a single layout, the planning strategy proposed in this study could achieve nearly the same energy surplus level while saving an investment cost ranging from 2403.9 million CNY to 25,000.23 million CNY. The findings are applicable to other regions with similar conditions, and the analysis framework proposed in this study can be utilized in formulating biomass development strategies for other countries and regions.

Marketing of Regions as a component of sustainable development strategy: challenges, prospects, and tools

At this stage of development, the region's need for more competitiveness with implementing sustainable development concepts is becoming increasingly important. It has been established that with such sensitivity, the potential essence will be reversed due to the specifics of the concentration of production and capital. Currently, there is an increase in regional marketing tools, quizzes, and features of their implementation as a warehouse strategy of continuous development. Technologies and tools for implementing regional marketing were determined, and their advantages and disadvantages were analyzed. Problematic aspects of using these tools are also highlighted, which can be adjusted to optimize the marketing strategy in the future. Based on the analysis of sustainable regional development strategies, a list of crucial recommendations for forming relevant strategies to implement its provisions more effectively is presented. Adapting the sustainable development strategy to new challenges necessitates a comprehensive, long-term approach to regional recovery and inclusiveness. This approach involves each region setting priorities across various sectors (infrastructure, human capital, economy, security, institutions, e-government, environmental protection, etc.). Therefore, when updating the toolkit, it is crucial to consider the unique needs of each region and evaluate the protection of the interests of regions most affected by military actions. It is evident that effective regional marketing can only be achieved through the coordination of all aspects of its specificity in the social, managed, and reproductive spheres. This research also addresses the challenges and issues that arise in the formation of regional marketing strategies under the conditions of martial law in Ukraine. These include security concerns, a decline in investment attractiveness, reputational risks, the need to reorient marketing strategies, and specific communication requirements. Keywords: marketing of the region, strategy of sustainable development, technologies and tools of marketing, attractiveness of the region, investments, security, branding of the region.

Cryogenic Pits and Quaternary Glacial Evidence in Central Iran

Quaternary glaciation studies in Central Iran reveal that it is not implausible to anticipate glaciation traces in this region. It is feasible to provide conclusive evidence about the behavior of ice sheets by referring to geomorphological factors and climatic statistical analyses. Factors such as flatness and accidental geographical features contribute to the existence of ice sheets in the Namdan Fars region. The digital reconstruction of past climatic conditions، using the Wright method، along with the absence of lake terraces around Kaftar Lake، signifies the presence of ice instead of water in the lake. The multi-axial morphology of the Namdan Plain، the shape and form of main valleys and passes، and the existence of numerous glacial cirque traces in the surrounding heights are also indicators of this phenomenon. The lack of evidence of ancient settlements in the plain، despite the availability of water and fertile soil، can be attributed to the region's historical thermal conditions. Investigating ancient glaciers helps us understand the natural history of the land. This knowledge can aid planners in devising macro strategies for regional development and water resource management، as glacial performance has always been associated with optimal water levels. Although glacial activities can create aquifers، the movement of ice sheets or ice surfaces does not support the accumulation of sediments required for creating aquifers with sufficient water storage. Instead، their performance leads to the creation of suitable agricultural soil layers. In summary، regional glaciers play a positive role in transforming and creating favorable agricultural soils and can be beneficial in adapting to climatic changes and extending statistical periods.

Advancements in Expanded Clay Manufacturing Using "Clay-Desert Sand-Oil Sludge" Sludge Composite Materials

This study explores the development of resource-saving expanded clay technology utilizing underutilized clay raw materials and oil extraction waste. Traditional expanded clay production is energy-intensive and often employs high-quality clay; however, our research identifies technological modes and parameters for producing expanded clay through plastic molding, incorporating substandard raw materials and oil sludge. This method eliminates the need for costly energy-releasing additives and reduces energy costs associated with drying and firing by 25-30%. The research aims to demonstrate the feasibility of this novel production technique in the Republic of Kazakhstan, considering the local availability of raw materials, energy resources, and regional demand for thermal insulation materials in industrial and civil construction. Our findings suggest that integrating 'Desert Sand-Oil Sludge' into the batch composition can effectively produce granulated porous thermal insulation material, aligning with the region's development strategy and offering significant economic and environmental benefits.
 Highlights:
 
 Resource Utilization: Uses oil waste and substandard clay to produce expanded clay, reducing reliance on high-quality materials.
 Energy Savings: Cuts energy costs for production by 25-30% through innovative processing.
 Regional Benefit: Aligns with Kazakhstan's strategy by utilizing local resources and supporting construction needs.
 
 Keywords: Expanded Clay, Oil Sludge, Desert Sand

Measurement and Influencing Factors of Regional Economic Resilience in China

The COVID-19 outbreak in 2020 has underscored the paramount importance of regional economies’ capacities to withstand and adapt to external shocks. Enhancing regional economic resilience and mitigating the adverse impacts on both the economy and society have emerged as critical imperatives for ensuring the sustainable development and transformation of the national economy. This paper employs an improved counterfactual method to measure the economic resilience index across 31 Chinese provinces and cities from 2001 to 2021, coupled with empirical analysis using a dynamic panel model to identify the influencing factors of regional economic resilience. Building upon this foundation, the study delves into the heterogeneous effects of various factors and different degrees of marketization on economic resilience across different regions. Research Findings: (1) There has been a significant improvement in the economic resilience levels of China’s 31 provinces, with differences in economic resilience between regions far exceeding those in economic development levels, indicating substantial internal regional disparities. (2) Factors such as the marketization index, industrial structure, level of informatization, labor force size, labor quality, innovation capacity, and degree of government intervention all impact regional economic resilience and exhibit regional heterogeneity. Policy Recommendations: (1) It is crucial to address regional disparities while formulating regional development strategies and enhancing regional economic resilience. (2) Regions should accelerate market-oriented reforms, promote rational labor mobility, strengthen investment in human capital, foster innovation, and adjust the degree of intervention.

On the Classification of Regions of the Russian Federation by Level of Socio-Economic Development and Innovation Activity Index

The purpose of the study is to form an effective tool for classifying the regions of the Russian Federation in the context of innovation activity under technological constraints.Materials and methods. The information and empirical base of the research consists of Decrees of the President of the Russian Federation, normative legal acts of the Government of the Russian Federation, and open set of statistical data provided by the Federal State Statistics Service. The study provides a multidimensional classification of Russian regions using an indicative analysis of the innovative potential of territories and their socio-economic development, clustering by the Ward method and the Euclidean distance metric, as well as analysis, comparison and illustration of the results obtained using methods of visualizing information in tabular, graphical form, including the usage of cartograms.Results. While creating a model of typologization of Russian regions, a system of indicative indexes with both qualitative and quantitative characteristics was formed. Based on them, cluster analysis identifies five clusters of regions according to the level of innovation activity and socio-economic development, which is based on the final weighted average index (Iiv) of development. The results of the study determine the effectiveness of the author’s approach to the issue of typologization of regions, and emphasize the visibility and interactivity of the tools used within the framework of the model. The use of cluster and comparative analysis using weighted average indexes makes it possible to identify non-obvious patterns between the innovative activity of the region and its level of development, as well as to emphasize intuitively expected connections. All this can form a practical basis for developing effective strategies for regional development and improving the quality of life of the population.Conclusion. The study highlights the importance of analyzing the innovative activity of regions in modern conditions of sanctions wars and restrictions on technological imports. The developed model is a comprehensive tool for analyzing the innovative potential and level of development of regions, which allows identifying key factors of innovation activity and potential growth points, and thereby helping to form the basis for the development of strategies and programs for regional development aimed at improving the standard of living of the population.

Spatiotemporal variations and driving forces analysis of ecosystem water conservation in coastal areas of China

China's coastal zones, characterized by their ecological vulnerability and significant economic growth, demand effective water conservation management. Such management is pivotal not only for safeguarding water resources but also for ensuring ecological stability and promoting sustainable socio-economic development. In this study, based on the water balance model, the spatiotemporal dynamics of water conservation in the ecosystems of China's coastal areas from 2001 to 2021 were characterized by three dimensions: overall, zonal, and raster. The results show that: ① the distribution pattern of ecosystem water conservation in China's coastal areas from 2001 to 2021 is “high in the south and low in the north”, with a total amount of 117.726 billion m3/a, with the Pearl River Delta and Southwest Coastal Areas as the main high-value areas, and the overall water conservation and its capacity show a “ decreasing-rising-decreasing” pattern. The overall water conservation and its capacity show a fluctuating trend of “falling-rising-falling”. Additionally, water conservation capacity varied significantly among different vegetation types and across marine-terrestrial gradients, with the highest capacity recorded in evergreen coniferous forests and areas situated 140 km from the coastline. ②From 2001 to 2021, the water conservation capacity of China's coastal ecosystems exhibited significant temporal patterns and spatial differentiation along the marine-terrestrial gradient. The research suggests that these patterns of change are intricately linked with the stages of regional development strategies and ecological construction within these coastal zones. ③In China's coastal areas, a mere 11.63 % of the rasters showed significant changes in water conservation, dominated by highly significant and significant increases, mainly in the Southeast Coastal Area, the Pearl River Delta and Southwest Coastal Areas, and the Bohai Bay Coastal Area. This included areas such as the Yangtze River Delta silty coastal plain area, the Bohai Bay silty coastal plain area, the sandy silt coastal hilly terrace area of western Guangdong and Guinan, and other China coastal protection forest system construction projects. ④ Water conservation function within China's coastal ecosystems demonstrates a profound interconnection with both natural and socio-economic determinants. Natural elements such as elevation, slope, and precipitation positively correlate with water conservation metrics. Conversely, evapotranspiration and temperature are inversely related to conservation outcomes. In terms of social factors, water conservation has a significant negative correlation with GDP density and population density, with the highest negative correlation with the GDP2 density.

Special economic zones and the influence of transport modes: proposal of a theoretical model appropriate to the brazilian reality

Special Economic Zones (SEZs) have become in recent decades an important strategy for economic stimulation. The SEZs are associated with regional development policies and the fight against economic stagnation. The effectiveness of a SEZ depends on the regional economic context, its potential, incentive policies and investment attraction, as well as the supply of infrastructure for productive development. Thus, this study aims to establish a theoretical/hypothetical relational model that represents the influence of transport modes on the effectiveness of a regional development strategy of the SEZ type. To reach the proposed objective, an extensive Systematic Literature Review was carried out with the help of the scientific platforms Connected Papers and Ryyan, aligned with research in the main academic databases (Scopus, Web of Science, EBSCO host, ieeeXplore, Emerald insight). A qualitative approach, inductive logic, and interpretivist epistemology were adopted. The results of the study suggest a theoretical/hypothetical model composed of eight hypotheses and nine constructs (factors that enable SEZ effectiveness, factors that compromise the SEZ effectiveness, SEZ effectiveness, modals of transport, SEZ performance, SEZ program, SEZ characteristics, contextual factors and regional development. The study improves the regional development literature and especially the Special Economic Zones theme by establishing solid theoretical relationships among the suggested constructs.

Place-based strategies for sustainable and inclusive regional development in the south of Mexico

Place-based strategies for sustainable and inclusive regional development in the south of Mexico

Public sector digitalization, corruption, and sustainability in the developing world: A scoping review

AbstractE‐government presents one of the utmost opportunities and challenges for development and offers solutions to tackle corruption. Corruption generates even erratic impacts in developing and transition economies. Developing and transition economies can dramatically benefit from related technological innovation uptake that would spur public sector transparency and sustainability. The intersections of these areas have not received full academic consideration and appear to be under‐explored. In addition to a review of the existing literature on these topics, this study applies extensive reliance on existing metrics and indexes, including those developed by the World Bank and Transparency International. By accentuating relevant and recent findings, the results of this study can be used for a better conceptualization of national or regional growth and development strategies based on the nexus between corruption and e‐government advances among developing and transition countries.

Transforming Poverty Alleviation Policies: Adapting the Regional Innovation Architecture Approach

Poverty, defined as the inability of individuals to fulfill their basic needs, poses a significant challenge to achieving community welfare in many regions. Addressing this challenge requires a holistic and integrated approach that considers Indonesian society's diverse cultural and socio-economic contexts. Adapting innovative architecture is crucial in confronting Indonesia's various cultural and socio-economic landscapes. This approach provides new alternatives for regional development strategies and opens up new opportunities for transforming and adapting innovation to tackle poverty holistically and sustainably. This research aims to restructure innovation architecture and examine its potential to transform regions in poverty alleviation efforts. The study employs a qualitative research method with a literature review analysis. It explores novel approaches for developing a solution-oriented and applicable analysis and recommendations for communities. Additionally, the research analyzes several regions that have successfully implemented regional innovation and reduced local poverty levels. Data is collected through a literature search strongly relevant to the research objectives. The findings indicate that innovation architecture can drive regional transformation in poverty alleviation through 1) Enhancing collaboration and synergy among stakeholders, 2) Creating a conducive innovation ecosystem, and 3) Developing contextual and sustainable innovative solutions. These findings demonstrate the substantial potential of innovation architecture in transforming regions to achieve poverty alleviation. This aligns with existing theories emphasizing stakeholder collaboration and synergy as key factors in creating effective, innovative solutions. Innovation architecture can serve as an effective tool in transforming regions towards poverty alleviation. Proper and sustainable implementation of innovation architecture can assist regions in crafting contextual, innovative solutions and enhancing community welfare.

The Role of Economic Investments in Mitigating Poverty Across Urban and Rural Kazakhstan

This study employed a comprehensive analytical approach to examine the relationships between investments in healthcare, education, and other economic sectors and their impact on poverty levels in Kazakhstan in urban and rural contexts, allowing for nuanced insights into the differential impacts of investments across these settings. The analysis was structured around evaluating correlations, regression modeling, and ANOVA tests to assess the significance of the observed relationships. Results revealed significant positive correlations between investments in healthcare and education and poverty reduction, with these investments demonstrating a powerful impact in urban areas. Investments in other economic sectors, such as agriculture, industry, and construction, also showed correlations with poverty levels, underscoring the importance of integrated investment strategies. However, regional disparities in investment impacts were evident, highlighting the need for tailored approaches to address the unique challenges and opportunities in specific areas of Kazakhstan. Notably, the study identified particular regions requiring more focused attention due to fluctuations in sectoral contributions to the Gross Regional Product (GRP), variations in investment levels, and the distinct challenges rural areas face. The findings support the hypotheses that investments in healthcare and education significantly affect poverty reduction, with implications for policymakers and regional development strategies.

Peculiarities of regional development under martial law: State and administrative aspects

Considering the conduct of state policy in the conditions of the protracted Russian-Ukrainian war, it is important to characterize the main aspects of its development through the prism of the peculiarities of sustainable regional development. The purpose of the research is to determine the peculiarities of regional development in the realities of wartime based on the study of state-management aspects. The study is based on the analysis of modern works and reports of international organizations. Data collection was carried out in stages: first, a search was made for the main documents and reports of international organizations, then a search for scientific literature for the study was carried out. In general, such research methods as thematic analysis, categorization, comparative analysis, and graphic method were used. The results of the study demonstrated the effectiveness of the use of digital systems in regional development strategies improving the level of intellectual security, identified the peculiarities of planning and operation of regional budgets under martial law. Digital systems have proven effective in enhancing regional development strategies and improving intellectual security. They enable better planning and operation of regional budgets, even under martial law, by providing real-time data and facilitating communication among stakeholders. In the conclusions, it was noted that the military operations had a significant impact on the system of public administration and needed further adjustment in connection with overcoming the consequences of the military operations.

The non-linear dynamics of South Australian regional housing markets: A machine learning approach

Traditional linear models often struggle to capture regional housing markets' complex, non-linear dynamics. This study addresses this gap by developing and applying advanced machine learning algorithms to unlock unique insights into South Australian housing price behavior. Leveraging a comprehensive dataset of over 10,000 regional house sales from 2010 to 2021, we explore the non-linear relationships between housing prices and microeconomic factors (e.g., house size, land area, building quality) and socioeconomic characteristics (e.g., proximity to amenities and income levels). Our analysis employs a multi-step approach, including feature engineering, spatial data integration, correlation tests, multilevel modeling, and non-linear machine learning algorithms including Decision Tree, Random Forest, Gradient-Boosted Tree, and Artificial Neural Network. The key finding is that machine learning models outperform traditional econometric models in predicting regional housing prices, with higher accuracy and greater goodness of fit. Furthermore, we identify specific non-linear relationships, such as the increasing marginal impact of proximity to the sea on house prices as distance decreases. These findings offer valuable insights for policymakers, real estate professionals, and stakeholders, informing regional planning, infrastructure provision, and economic development strategies. This study sheds light on the complex dynamics of South Australian housing markets and lays the foundation for further research.

ANALYSIS OF DATA ORGANIZATION SYSTEM ARCHITECTURES OF THE SMART EUROPEAN REGION "CENTER OF EUROPE" BASED ON THE DATA LAKE TECHNOLOGICAL SOLUTION

In the contemporary landscape of digital transformation, the concept of a "smart region" emerges as a key strategy for regional development, utilizing data integration technologies to enhance the quality of life, optimize service delivery, and promote sustainable growth. The designation of the "Centre of Europe" as a smart region is justified by its strategic geographical location, encompassing Transcarpathia and adjacent areas of neighboring countries, coupled with a relatively low population density. This unique context creates compelling premises for rethinking traditional urban frameworks of smart cities on a broader scale, transforming them into a comprehensive smart region model tailored to the specific needs and opportunities of Central Europe. The rationale for implementing the "Centre of Europe" as a smart region stems from its advantageous position at the heart of the continent, which generates unprecedented opportunities for cross-border collaboration, innovation, and connectivity. The low population density of the region further highlights the potential for the adoption of advanced technological solutions capable of addressing a wide array of challenges and needs. By achieving the status of a smart region, the "Centre of Europe" aspires to become a leading example of how digital and technological innovations can be utilized to create an inclusive, efficient, and progressive regional ecosystem. Objective: The primary objective of this research is to conduct a comparative analysis of advanced data organization system architectures and their role in facilitating the transformation of the "Centre of Europe" into an intelligent European region. It also aims to explore the capabilities of utilizing data lakes for the effective management of large data sets and regional development, taking into account the unique geographical and demographic characteristics of the region. The subject of the study encompasses the architectures of big data organization systems in the smart region of the "Centre of Europe". The object of the study involves the processes of storing and processing large data within the smart region. Main characteristics: This article illuminates the main aspects of implementing big data processing technologies in the smart region of the "Centre of Europe", necessitating scalable and flexible solutions for large data storage, the use of efficient data management practices, and the integration of advanced technologies such as cloud computing, the Internet of Things (IoT), and artificial intelligence (AI) to enhance data processing and analytical capabilities. Furthermore, recommendations for regional authorities on adopting these technologies have been formulated, highlighting the importance of collaboration, support for investments in the region's digital infrastructure as key components for achieving the smart region vision. The construction of modern, high-tech data storage facilities using the Data Lake architecture enables the simultaneous use and processing of large volumes of data from various fields and sources. The authors have proposed conceptual models for forming data complexes from different functional areas of the smart region.