Differentiation of regional tourist-recreational systems using self-organizing neural networks

Methods. The study uses general scientific and specialized methods, including: theoretical generalization – to synthesize theoretical principles and analyze international experience in the development of tourism systems; logical-analytical and static methods – to characterize the current state of development of Ukraine's tourism sector; clustering based on self-organizing neural networks and Kohonen maps – to identify the optimal structure of tourism activities by determining the key factors that constrain their development. Results. The theoretical foundations and practical experience of differentiating socioeconomic systems of different levels is analyzed in the research. Taking into account the availability and quality of statistical data characterizing the state of the regional tourism sector of Ukraine, the optimal tools for differentiating the relevant regions were identified. The analysis made it possible to divide the regions of Ukraine into 3 clusters and establish the key factors of their differentiation, which vary significantly from region to region. Natural and cultural-historical conditions, such as the presence of nature reserves, environmental threats and climatic features, and the presence of outstanding historical and cultural monuments, have a significant impact on the differentiation of regions. Novelty. The authors proposed a scientific and methodological approach to assessing the level of development of the regional tourism sector, taking into account the structure of tourist flows (in terms of tourism goals), costs for the organization and support of tourist complexes and other factors and limitations. The factors of regional differentiation of tourist and recreational systems were determined based on the clustering method. The structure of indicators of consumer (tourist) attractiveness, based on financial performance characteristics, was used as a key indicator for such grouping. Practical value consists in planning and optimizing the structure of tourism activities of regions on the basis of sustainable development, depending on tourist flows, gross regional product, entrepreneurial and investment activity, and tourism expenditure. This leads to strategic development priorities for such groups of regions of Ukraine that are related in terms of the organization of tourism business. In addition, the proposed methodology allows for the formulation of practical recommendations for business and authorities and local self-government and to ensure a balance between the needs of tourism and the preservation of the natural and cultural environment.

Authors

Publication Details

Journal
Economic Bulletin of Dnipro University of Technology
Published
2024-12-01
DOI
https://doi.org/10.33271/ebdut/88.170
Primary Topic
Diverse Scientific Research in Ukraine
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Differentiation of regional tourist-recreational systems using self-organizing neural networks

Марія Бєлобородова, O.Yu. Mints
Economic Bulletin of Dnipro University of Technology
Diverse Scientific Research in Ukraine
article

Differentiation of regional tourist-recreational systems using self-organizing neural networks

Марія Бєлобородова, O.Yu. Mints
article en

Abstract

Methods. The study uses general scientific and specialized methods, including: theoretical generalization – to synthesize theoretical principles and analyze international experience in the development of tourism systems; logical-analytical and static methods – to characterize the current state of development of Ukraine's tourism sector; clustering based on self-organizing neural networks and Kohonen maps – to identify the optimal structure of tourism activities by determining the key factors that constrain their development. Results. The theoretical foundations and practical experience of differentiating socioeconomic systems of different levels is analyzed in the research. Taking into account the availability and quality of statistical data characterizing the state of the regional tourism sector of Ukraine, the optimal tools for differentiating the relevant regions were identified. The analysis made it possible to divide the regions of Ukraine into 3 clusters and establish the key factors of their differentiation, which vary significantly from region to region. Natural and cultural-historical conditions, such as the presence of nature reserves, environmental threats and climatic features, and the presence of outstanding historical and cultural monuments, have a significant impact on the differentiation of regions. Novelty. The authors proposed a scientific and methodological approach to assessing the level of development of the regional tourism sector, taking into account the structure of tourist flows (in terms of tourism goals), costs for the organization and support of tourist complexes and other factors and limitations. The factors of regional differentiation of tourist and recreational systems were determined based on the clustering method. The structure of indicators of consumer (tourist) attractiveness, based on financial performance characteristics, was used as a key indicator for such grouping. Practical value consists in planning and optimizing the structure of tourism activities of regions on the basis of sustainable development, depending on tourist flows, gross regional product, entrepreneurial and investment activity, and tourism expenditure. This leads to strategic development priorities for such groups of regions of Ukraine that are related in terms of the organization of tourism business. In addition, the proposed methodology allows for the formulation of practical recommendations for business and authorities and local self-government and to ensure a balance between the needs of tourism and the preservation of the natural and cultural environment.

Economic Bulletin of Dnipro University of TechnologyVol. 88
Openalex Percentile: Top 77%
Diverse Scientific Research in Ukraine
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.