Ekonomika Regiona-Economy of Region最新文献

{"title":"Influence of Infrastructure on Population Distribution and Socio-Economic Development of Russian Regions","authors":"R. Manshin, E. Moiseeva","doi":"10.17059/ekon.reg.2022-3-8","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-3-8","url":null,"abstract":"High divergence of demographic and socio-economic development significantly hinders the sustainable growth of the Russian economy. This article analyses the influence of infrastructure on population distribution and development of Russian regions. The study focuses on theoretical and practical issues related to identifying the features of infrastructure development as a factor of settlement and formation of population, considering the migration attractiveness of Russian regions. The research aimed to reveal a correlation between the regional infrastructure development and population distribution characterised by its density and net migration. To this end, we calculated the correlation between these indicators of population distribution and development indices of transport, energy, social, communal and telecommunications infrastructure. Additionally, the correlation between gross regional product and the same infrastructure development indices was estimated. The correlation analysis revealed the presence of a weak positive relationship between the regional population density, net migration, and all infrastructure development indices, except for social one. The strongest positive relationship is observed between the regional population density and the transport infrastructure development index. Good transport accessibility gives people easier access to other types of infrastructure and consequently increases the spatial connectivity and demographic potential of certain areas. Infrastructure development greatly influences not only social indicators of regional development but also economic ones, as shown by the correlation between gross regional product and development indices of transport, telecommunications and energy infrastructure. Thus, according to the conducted statistical analysis, the existing but weak relationship between infrastructure development indices and population distribution confirms the presence of a set of factors, where infrastructure is not the main one. Nevertheless, the removal of infrastructure constraints and an increase in the infrastructure quality and availability will help overcome both the demographic and economic contraction of Russia.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":"83 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73079960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Approach to Assessing the Digital Economy Development Based on Clustering of Russian Regions","authors":"T. Afanasieva, A. Kazanbieva","doi":"10.17059/ekon.reg.2022-4-8","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-4-8","url":null,"abstract":"The present article proposes and tests a new approach to the assessment of the digital economy development in order to obtain evaluative knowledge (qualitative assessments) from quantitative indicators of the constituent entities of the Russian Federation. The distinctive features of the proposed approach are the integration of cluster analysis and qualitative assessment, as well as the use of elements of the fuzzy set theory for modelling evaluative knowledge and presenting it in linguistic form at three levels of interpretation. Three methods (K-means, BIRCH, DBSCAN), differing in terms of grouping principles, were applied to improve the quality of clustering. The most suitable method for clustering the constituent entities of the Russian Federation was automatically selected based on a proven quality metric. The developed automated methodology for qualitative assessment of digital economy was tested on 15 indicators observed over 9 years, presented on the website of the Federal State Statistics Service for 83 regions of the Russian Federation. The study identified six clusters, for which three classes of qualitative assessments were determined, characterising the problems of digital economy development by indicators, their groups and year based on the aggregation of linguistic assessments. Thus, the level of the indicator (Low, Medium, High), as well as belonging to the problem according to the group of indicators (Problem/No problem) and according to all indicators (Developed/Developing) were estimated for each region in the clusters. Analysis of qualitative estimates obtained from various regional numerical indicators showed that the most «problematic» in 2010 and in 2018 was the group of indicators «Science and Innovation». Additionally, the group of indicators «Economic Efficiency» demonstrated a negative trend in the period 2010-2018, while a positive trend was observed in the group of indicators «Information Society» and «Labour Market».","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":"70 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73803325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Organisational, Methodological and Economic Foundations for Creating Rural Resorts in the Hinterland of Sochi","authors":"A. V. Ryndin, A. Platonov, A. Saryan, L. S. Kocharsky","doi":"10.17059/ekon.reg.2022-4-14","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-4-14","url":null,"abstract":"The resort city of Sochi includes both coastal and mountain tourist and recreational clusters. Nowadays, the city needs to involve natural and recreational resources and historical and cultural heritage assets of underdeveloped low-mountain areas and subtropical agricultural lands in the tourism industry. The present research aims to determine scientific, methodological and organisational foundations for sustainable development of the aforementioned areas. The study reveals the organisational, managerial and legislative aspects of the contradiction between the legal status of rural areas and recreational objectives of the Sochi resort. Co-development of both agricultural activities and most promising types of tourism in hinterland (namely, medical, agrarian, ethnic and cognitive tourism) will help overcome this contradiction. The socio-economic impact of tourism and infrastructure development in rural districts of Sochi will contribute to the increase in employment and entrepreneurship, as well as improve the welfare of indigenous people. Subsequently, due to the creation of rural resorts, the potential of balneological and natural curative resources, unique historical and cultural heritage, natural landscapes and subtropical agricultural lands can be fully realised. The research findings can be used to elaborate and implement sound programmes for the spatial development of rural resorts and agro-tourism destinations in Sochi. Further research will focus on possible ways to transform rural resources into factors for the production of an integrated tourist product with unique valuable properties.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":"1 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82604680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of Energy Supply to the Yamal Peninsula Based on Fuzzy Multicriteria Analysis","authors":"M. Petrov, L. Serkov, K. Kozhov","doi":"10.17059/ekon.reg.2022-4-17","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-4-17","url":null,"abstract":"Provision of useful energy is the most important condition for realising the potential of underdeveloped regions. For new development areas, including the Yamal Peninsula, there are various energy alternatives. Based on well-known basic approaches, the article presents a procedure for formalising the analysis of alternatives mostly using qualitative initial data. At the pre-project stage, only limited and fuzzy information (predominantly in the form of expert opinions) is accessible. To achieve the set goal, six criteria for export assessment were selected and further processed using fuzzy multicriteria decision-making models based on fuzzy multicriteria analysis of alternatives in order to formalise logical reasoning with vague or imprecise statements. Due to insufficient measurements for constructing fuzzy sets, linguistic estimates of intuitive or logical pairwise comparisons were formalised using the Bellman–Zadeh model, the Saaty scale and the construction of membership functions. The fuzzy set was obtained by finding the eigenvector and the largest eigenvalue for the pairwise comparison matrix. Implementation of the maximin criterion along with the concession matrix allowed us to distinguish between alternatives when obtaining the same or similar estimates. As a result, the study showed the priority of diversification of primary energy source to provide useful energy to consumers in Yamal. According to the model, the most preferable source is atomic energy. In second place are gas turbine technologies, which are significantly ahead of wind energy sources. Diesel generators are considered the least favourable. Thus, the results of fuzzy modelling correspond with the explanatory factors of choice. The fuzzy set method with the transformation of linguistic estimates into quantitative ones can also be included in the apparatus of multicriteria selection with respect to combined options. The research findings can be used to prepare comprehensive strategies and schemes for location of industries and the energy infrastructure in remote Arctic territories.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":"1 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79007320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal Spatial Models of Interregional Economic Cooperation in the Field of Innovative Economy","authors":"A. Mosalev","doi":"10.17059/ekon.reg.2022-3-2","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-3-2","url":null,"abstract":"Domestic cooperation of companies in the field of innovative economy seems to be a promising research area in Russia, especially considering recent macroeconomic events caused by sanctions, in particular, restrictions on the import of high-tech goods. Thus, the present study examines the optimal spatial scale of interregional innovation cooperation. The article presents an analysis of approaches to determining the optimal number of k-matrices of relations between innovation active regions. It is hypothesised that the innovative activity of the business sector in one region does not influence the innovative activity of its neighbours and vice versa. Stepwise regression was applied to identify the core explanatory variable. Based on the spatial weights matrices, a spatial econometric model was constructed using the least squares method. Further, the global Moran’s I was employed to test the spatial correlation, in particular, local indicators of spatial association (LISA) using the queen criterion of contiguity were utilised to determine the dependencies of innovative activity between neighbouring regions. The analysis used panel data from all Russian regions for the period from 2010 to 2019, as well as spatial econometric modelling to identify the side effects of the optimal spatial scale. As a result, the study revealed the presence of spatial correlation in the levels of regional innovative activity, the size of markets, as well as institutional support for enterprises in individual regions. Additionally, the research identified factors positively affecting the scale of innovative activity of the regions and adjacent territories, such as regional domestic income, the number of participants in innovation processes and infrastructure facilities. It has been established that the neighbourhood of regions characterised by the presence of many participants in innovation processes (at least 100 units), as well as innovation infrastructure facilities (at least 810 units) will be seen as the optimal scale of regional cooperation.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":"125 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78459282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Regional Analysis of Digital Inclusion in the C2C Market of Russia","authors":"S. Kulpin, G. Savchuk, O. Iakimova","doi":"10.17059/ekon.reg.2022-2-10","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-2-10","url":null,"abstract":"Economy digitalisation creates new market mechanisms and regional development opportunities. In certain circumstances, the C2C (consumer-to-consumer) Internet market can act as a basis for establishing an entrepreneurial culture; subsequently, it can turn into an economic growth point of a region. However, since the entrepreneurial potential of regional digital markets varies, it is crucial to investigate these differences and the reasons for their occurrence. In the present study, the entrepreneurial potential of residents is measured through their digital inclusion in C2C Internet markets. The article analyses and characterises the active sellers of the Avito online classified in Russian regions. The data were collected using the content analysis of ads posted by individuals on the Avito platform (n = 1,597). Correlation and factor analysis were used for interpretation. The conducted analysis showed the following results. First, the study revealed a relationship between regional digitalisation and the size of the group of active sellers: a higher level of digitalisation of a territory (federal district) means that more residents start to actively use Avito for e-commerce. Second, the paper demonstrated the importance of locality, since the number of active sellers among Avito users is bigger in large cities. Third, it was proved that additional opportunities provided by the C2C market are more attractive for women than for men. The obtained findings can be used by authorities planning the regional development, as well as by researchers of the Internet economy describing and analysing the digitalisation processes. Further studies may identify and examine in detail the factors defining digital inclusion in C2C markets of Russian regions.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":"26 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90560882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Revisiting Rural Economic Structural Transformation from the Viewpoint of Regional Linkages","authors":"B. Truong Cong","doi":"10.17059/ekon.reg.2022-2-1","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-2-1","url":null,"abstract":"Regional studies, particularly in rural areas, have attracted great attention from scholars and policy-makers. However, almost all existing literature focused on the growth of these areas while giving little consideration to converting economic activities or economic structural transformation, which plays the main role in sustainable development. Additionally, the studies about economic structural transformation mainly mention the factors, which are changes inside certain economic areas and ignore the outside effects while any geographical area also has spatial relationships. To fill this gap, this study blends the economic structure and regional linkages theories to supply a comprehensive view of the relationship between inside and outside factors that influence rural structural transformation by using systematic reviews and meta-analysis methods. The study’s findings consolidate the importance of urban areas and regional linkages, especially spatial interaction, in rural economic structural transformation. More specifically, this study shows that the motivation for structural transformation of rural areas is emanated from urban areas and is transmitted through spatial flows, which are then absorbed in rural areas. The mechanisms through which the motivation affects rural economic structure are productivity, income, and agricultural land. Based on the review, the study lists several further research questions regarding empirical research of rural economic structural transformation through the relationship between rural and urban areas.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":"73 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73824253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interregional Differentiation of the Age of Exit from the Labour Market in Russia","authors":"V. Lyashok, E. Varshavskaya","doi":"10.17059/ekon.reg.2022-3-7","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-3-7","url":null,"abstract":"Actual retirement age is one of the most important characteristics of older people employment and retirement behaviour. Since the mid-1990s, the effective retirement age has been used to estimate the age of exit from the labour market of older workers. In the context of significant socio-economic differentiation of Russian regions, this parameter should be assessed not only at the national, but also at the regional level. The article presents estimates of the age of exit from the labour market (effective retirement age) in Russian regions for 2010-2019, as well as identifies the factors determining its interregional differentiation. For the first time, the effective retirement age and its determining factors were assessed using Russian data. In particular, Labour Force Survey and regional statistics were analysed. To calculate the effective retirement age, both static and dynamic approaches were applied; econometric modelling was used to identify its determinants. The study revealed that in 2019 the age of exit from the labour market was 62.4 years for men and 60.2 years for women. The effective retirement age for Russian men and women is higher than the normal retirement age in the country, but is lower than the average of most OECD countries. For the period 2010-2019, the age of exit from the labour market remained practically unchanged for men, while it slightly increased for women (by 0.7 years). The age of exit from the labour market is characterised by a fairly significant and stable regional differentiation. The determinants of the effective retirement age are the northern status of a region, the relative level of pensions in the region (the ratio of the average pension to the average wage), the share of employees with higher education. The research results can be used to develop measures to increase the older people employment. Changes in the age of exit from the labour market caused by the pension reform require a further study.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":"88 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84291016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Configuration of Regional Entrepreneurial Ecosystems through the Prism of Spatial and Hierarchical Analysis","authors":"R. Malikov, K. Grishin, V. Timiryanova","doi":"10.17059/ekon.reg.2022-4-1","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-4-1","url":null,"abstract":"Nowadays, entrepreneurship should be analysed from the perspective of interconnectedness and mutual influence of elements of regional economic systems, since the type and intensity of their interaction determine the emergence of windows of opportunity for entrepreneurs. Thus, the present study uses an ecosystem approach. We hypothesise that the spatial configuration of the performance of regional entrepreneurial ecosystems (REES) largely depends on the interaction between local entrepreneurial ecosystems, as well as on the cumulative impact of REES on local entrepreneurial ecosystems. Using the methodology of spatial and hierarchical analysis, the study investigates the dependence of the development of local entrepreneurial ecosystems on their embeddedness in regional entrepreneurial ecosystems, assesses the spatial connectivity of REES, and considers relationships between small and large businesses in regional entrepreneurial ecosystems. The global Moran’s I and the Getis-Ord statistics for regional entrepreneurial ecosystems used to assess their spatial connectivity were calculated based on the analysis of data concerning the shipping volume of large and medium enterprises from 2315 municipalities of 85 constituent entities of the Russian Federation. At the level of local entrepreneurial ecosystems, the study revealed the link between the variation in the values of the shipping volume of business entities and their belonging to specific regional entrepreneurial ecosystems (constituent entities of the Russian Federation). In addition, a positive relationship was found between the shipping volume of large and medium enterprises operating in local entrepreneurial ecosystems, the shipping volume of goods produced by small enterprises and the average revenue of individual entrepreneurs. Considering the identified factors of spatial determination of regional entrepreneurial ecosystems and the closeness of interregional and intermunicipal ties of local entrepreneurial ecosystems, it is possible to generalise the best practices of spatial organisation of regional business communities and create effective development models.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":"IM-35 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84770742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of the Climate — Economy Relationship in Russian Cities","authors":"I. Manaeva","doi":"10.17059/ekon.reg.2022-3-15","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-3-15","url":null,"abstract":"Global climate change is an important factor determining the dynamics and significant parameters of the development of the world economy in general and Russian economy in particular. Thus, specific methodological approaches and models should be developed to assess the climate — economy relationship in order to make science-based management decisions. The research aims to create and test a methodology for analysing the relationship between climate and urban economic development in Russian cities. Data of the Federal State Statistics Service was examined; the average annual temperature was calculated according to the information presented on the Weather and Climate portal. The study considers Russian cities with a population of over 100 thousand people in the period from 2009 to 2019. A communication coordination coefficient (CCC), determining the existence and extent of the relationship between climate and economy in Russian cities, can be obtained using the calculations presented in the author’s methodology. Moscow and Saint Petersburg are characterised by stably high values of CCC. The coefficient values range from uncoordinated to base level. The best communication coordination is observed in economically developed cities. Generally, the climate — economy relationship in Russian cities is characterised by a high differentiation and spatial heterogeneity of the communication coordination coefficient, since the Gini coefficient for this indicator varies from 0.56 (Ural Federal District in 2019) to 0.88 (Central Federal District in 2017, 2019). The lack of significant changes in the dynamics of communication coordination in the period 2009-2019 indicates the stability of Russian urban systems. The obtained quantitative estimates may become a prerequisite for the creation of an environmental and economic development management section in urban strategies and part of the environmental policy of Russian regions.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":"4 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79723989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}