Search

Despite increasing awareness of the need to promote diversity, equity and inclusion in regional science, it remains unclear how and to what extent underrepresentation exists in the field. In addition, although inequalities in science along these lines have been studied empirically across a wide range of fields and disciplines, they have yet to be examined specifically in the field of regional science per se. This study aims to fill this research gap by investigating the extent to which there are disparities in publication and citation rates based on race, gender and region, and how topic selection affects these differentials. To achieve this goal, we analyzed 4,930 bibliometric records for nine journals with an explicit regional science brand over the period from 1961 to 2021, we apply Latent Dirichlet Allocation (LDA) technique regression modeling to assess how citation impact is affected by the gender, race, nationality of authors, topic selections, and other relevant factors. The results of this study provide evidence on patterns of inequality in regional science and help to understand the distribution of scientific productivity and impact by gender, race and origins. While the field is becoming more diverse and inclusive in terms publications and citations, significant gaps and disparities remains, especially regarding the Global South and minorities. We conclude with policy and programmatic recommendations for promoting broader participation in regional science in the future. [ABSTRACT FROM AUTHOR]

The passing of Professor Arthur Getis in May of 2022 initiated a number of events to both reflect on and remember the tremendous contributions he has made over his career to geographical systems more broadly, but also spatial analysis, spatial statistics, regional science, geography and GIScience, among others. This began with a series of sessions at the North American Regional Science Council meetings held in Montreal, Canada in November of 2022, followed by an invitation from the editors of Journal of Geographical Systems, Manfred Fischer, Antonio Paez, and Petra Staufer-Steinnocher, to organize a special issue in his honor. Soon thereafter, an open call was initiated to solicit submissions to this special issue, seeking original contributions that overlap and complement the broad range of research undertaken by Professor Getis over a distinguished career and life. This paper offers an overview of prominent geographical systems work carried out by Professor Getis. Reflections on his many contributions are also detailed. A summary of the contributions to this special issue is given, along with final thoughts. [ABSTRACT FROM AUTHOR]

This paper discusses different spatial complex networks construction models useful in Regional Science, and different associated issues and problems. First, we define two different models of spatial networks: Collaboration (SCN) and Competition (SCtN) network, both based on distances among nodes. We then discuss several problems related to Regional Science in these types of spatial networks, showing alternative cases and possible computational solutions. Evolutionary algorithms are proposed to solve these problems both in SCN and SCtN. The experimental part of the paper is comprehensive, and it discuses several approaches for spatial network modelling and construction by means of different computational experiments and simulations, including the evolution of SCN and SCtN in Regional Science problems. [ABSTRACT FROM AUTHOR]

The purpose of the article is to analyze the general problems of the work of insider scientists in the conditions of Russian sociocultural reality and the organization of Russian science. The main attention is paid to researchers dealing with the problems of the ethnic culture of which they are representatives. As an example, we consider the work of a team of tuvinologists and the authors of this article, working on the same research project in 2021-2023. Scientific insiders living in the regions of Russia work in the system of Russian science; they are subject to the general professional and sociocultural conditions in the country. This article examines the work of insiders from different angles: customers of research, the scientific community (Russian and regional), culture, sociocultural environment and scientists in culture. This relationship contains a significant imbalance of power and interests. It is argued that the work of insiders is more difficult because scientists in their own culture can be both insiders and outsiders in relation to the issue under study, an aspect of the lives of fellow countrymen. The results of the authors’ own experience in solving similar problems are presented, and a way out is proposed called the joint circle strategy, which includes constant formulation and discussion of paradoxical questions.

József Nemes-Nagy was born in 1948 in Budapest, but due to his family ties, he spent a lot of time in Sárvár, Vas County. He studied Mathematics and Geography at the Eötvös Loránd University between 1966–1971, and received his doctorate in natural sciences in 1973. Afterwards he worked on spatial analysis and research at the Institute of Planning Economics of the National Planning Office. In 1994 he returned to the Department of Regional Geography (now the Department of Regional Sciences) at ELTE, where he became head of the department. He is credited with the reform of geography education and the consolidation of social geography and regional science in university education. The interview provides an opportunity to learn about his career, the professional challenges he faced before and after the change of regime, and the process that led to the regional science and social geography of today.

The structures of regional economies play a critical role in determining both a region’s productivity and its resilience to shocks. We extend previous work on the regional occupation and skills structure by analyzing the effect of a region’s industry structure. We operationalize the concept of economic structure by constructing a network of interdependent economic components, employing ecological techniques of co-occurrence analysis to infer interactions between industries. For each U.S. metropolitan statistical area, we create an aggregate measure of economic tightness that captures the degree of interconnectedness among a region’s industries. We find that industry tightness, which we find is partly driven by rare industry pairs, is positively correlated with a region’s economic productivity, negatively correlated with a region’s change in productivity following the Great Recession. This study contributes to an understanding of the tradeoff between productivity and resilience, which is intended to help policy makers that face similar real-world tradeoffs.

In this TESG Forum, we revisit Torsten Hägerstrand's 1982 Diorama, Path and Project, a paper that significantly expanded Hägerstrand's time‐geographical conceptual vocabulary in the international geographical literature. The paper was the crystallization of a process where Hägerstrand tried to bridge regional science ideas with humanistic ones. The 'diorama' was introduced to discuss how imaginations emerge from the togetherness of objects and memories in localized space and initially formulated to help geography overcome the disciplinary fragmentation and paradigmatic rows that had splintered geography in the 1970s. 'Path' is Hägerstrand's well‐known concept describing people's spatial pattern of activities. Finally, the concept of 'project' tried to capture a broader conception of agency that was able to accommodate people's paths as the result of goal‐intended and value‐inspired actions. In this introductory essay, we contextualize the paper in the development of Hägerstrand's work and introduce the separate contributions to the Forum. [ABSTRACT FROM AUTHOR]

This study aims to provide a comprehensive examination of the evolution of regional science, a scholarly domain in the social sciences that applies analytical and quantitative approaches and methods to understand and address urban, rural, or regional problems. We conducted a bibliometric analysis of 8509 articles published in six regional science flagship journals (including the Journal of Regional Science, Annals of Regional Science, Regional Science and Urban Economics, Papers in Regional Science, Regional Science Policy and Practice, and International Regional Science Review) from 1958 to 2021. The analysis presents an objective data‐driven and unprecedented visualization of the field's intellectual, social, and conceptual structure and trends from the beginning to the present. It also provides a rich portrayal of the epistemology of regional science and illuminates matters related to regional science education and training. We find that regional science has moved well beyond its origins, shifting away from a heavy focus on theory and abstraction to modeling/simulation, empirical analysis, and policy research. We also find that there has been increasing attention to "people" in regions and the spatial characteristics of social problems, and some important shifts in the regional science community itself, particularly in terms of patterns of collaboration and the geography of scholarship. The findings of this paper provide implications for future directions of research and education for regional science. [ABSTRACT FROM AUTHOR]

Computational notebooks offer researchers, practitioners, students, and educators the ability to interactively conduct analytics and disseminate reproducible workflows that weave together code, visuals, and narratives. This article explores the potential of computational notebooks in urban analytics and planning, demonstrating their utility through a case study of OSMnx and its tutorials repository. OSMnx is a Python package for working with OpenStreetMap data and modeling, analyzing, and visualizing street networks anywhere in the world. Its official demos and tutorials are distributed as open-source Jupyter notebooks on GitHub. This article showcases this resource by documenting the repository and demonstrating OSMnx interactively through a synoptic tutorial adapted from the repository. It illustrates how to download urban data and model street networks for various study sites, compute network indicators, visualize street centrality, calculate routes, and work with other spatial data such as building footprints and points of interest. Computational notebooks help introduce methods to new users and help researchers reach broader audiences interested in learning from, adapting, and remixing their work. Due to their utility and versatility, the ongoing adoption of computational notebooks in urban planning, analytics, and related geocomputation disciplines should continue into the future.

Renewable energy transitions depend on activities at both ends of the value-chain or lifecycle, from the development of new innovations and technologies to their widespread diffusion. Place-based at scale approaches to renewable energy landscapes create local value, incorporate multifunctionality and decentralisation, mitigate harm for ecosystems, address justice and local resilience. That the potential, demand, and production of renewable energies are place-based phenomena is not accounted for in dominant energy-economy models, requiring new methods of analysis for an energy transition. The emergence of renewable energy across landscapes is increasingly linked in practice to the concept of "renewable energy clusters" that acknowledge the emergence of renewable energy as spatially distributed, heterogeneous and place-based phenomena. Renewable energy clusters describe a range of place-based energy activities along the energy value chain, from production of technologies and innovations to their use. Despite their promise, there lacks a clear definition and typology of renewable energy clusters, and research has not yet synthesised the place-based factors that influence or inhibit their emergence, that could be used to inform place-based strategies that address local assets, actors, space, labour, knowledge issues, or localised justice issues. This work offers a first step by serving as a preliminary investigation of renewable energy clusters and the factors that may predict their emergence. First, a qualitative approach is used to identify three initial types of renewable energy clusters along the energy value chain. The fields of regional sciences, technology innovation systems, and energy geography are drawn upon to identify factors that may influence or inhibit the emergence and form of renewable energy clusters. The seven synthesised dimensions that can be tested to typify and predict renewable energy cluster emergence: actors, institutions, networks, knowledge and tools, proximity, location characteristics, and path dependency. These initial types can guide the development of a sample of empirical cases of renewable energy clusters that can be analysed through machine learning typification to identify a more nuanced articulation of vertically integrated cluster types along the energy value chain. Typification can reveal characteristics these renewable energy clusters have in common with others, and what outcomes emerge from these characteristics within the specific context of place-based energy transitions. • Renewable energy clusters potentially drive a reliable low-carbon energy transition. • Renewable energy clusters are place-based and heterogenous. • Industrial and material renewable energy cluster types are identified. • Seven dimensions are proposed to predict renewable energy cluster emergence. • The typification of renewable energy clusters will support policy development. [ABSTRACT FROM AUTHOR]

The work has as aim the highlighting of the importance of statistics as a science that provides the ensemble of methods and techniques for the study and analysis of regional development. For this, is trying a specific argumentation of the role of statistics in the quantification the different aspects of regional development, starting from the comparative assessment of the levels of macroeconomic aggregate of results of the Member States of the European Union, whose conclusions can be a good premise for the structuring of the territory on regions of development, a concept specific to regional science. Study of the specialized literature led to several important conclusions, including: in contouring and development of the regional science an important role had sciences as: statistics, econometrics, mathematics, sociology, politology and others, which gives regional science an interdisciplinary character; within the regional science, the regional economy is highlighted due to the wide range of addressed problems, at the three levels of knowledge: economic theory, method and practical applicability; among the methods of analysis used by the regional economy, the statistical methods have an essential importance in knowing the level, qualitative-structural dimensions, dynamics, correlations and interregional and intraregional dependencies among variables a.s.o.; statistics has an essential role in the substantiation of the regional development strategies, in the regional planning, in monitoring the results of the regional development policies a.s.o.; current evolution of regional science is achieved, not without the contribution of statistics, in directions such as: regional planning, regional forecast, urban economy, rural economy, land use planning, sustainable spatial development a.s.o. The work presents a comparative analysis of some key-indicators of the regional development, by regions of development in Romania, in 2015 and 2019.

The article describes the trend of interaction between government and science at the stage of institutionalization. On the example of the North Caucasus shows the influence of the state on the development of space science in the region, especially its formation and development in 1920-1930.

Copyright of News of Kazakhstan Science / Novosti nauki Kazahstana is the property of NCSTE (JSC National Center for State Scientific and Technical Evaluations) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article shows the potentials of georeferenced data for labor market research. We review developments in the literature and highlight areas that can benefit from exploiting georeferenced data. Moreover, we share our experiences in geocoding administrative employment data including wage and socioeconomic information of almost the entire German workforce between 2000 and 2017. To make the data easily accessible for research, we create 1-square-kilometer grid cells aggregating a rich set of labor market characteristics and sociodemographics of unprecedented spatial precision. These unique data provide detailed insights into inner-city distributions for all German cities with more than 100,000 inhabitants. Accordingly, we provide an extensive series of maps in the Additional file 1 and describe Berlin and Munich in greater detail. The small-scale maps reveal substantial differences in various labor market aspects within and across cities. [ABSTRACT FROM AUTHOR]

Urban systems, and regions more generally, are the epicenters of many of today's social issues. Yet they are also the global drivers of technological innovation, and thus it is critical that we understand their vulnerabilities and what makes them resilient to different types of shocks. We take regions to be systems composed of internal networks of interdependent components. As the connectedness of those networks increases, it allows information and resources to move more rapidly within a region. Yet, it also increases the speed and efficiency at which the effects of shocks cascade through the system. Here we analyzed regional networks of interdependent industries and how their structures relate to a region's vulnerability to shocks. Methodologically, we utilized a metric of economic connectedness called tightness which quantifies a region's internal connectedness relative to other regions. We calculated tightness for German regions during the Great Recession, comparing it to each region's economic performance during the shock (2007–2009) and during recovery (2009–2011). We find that tightness is negatively correlated with changes in economic performance during the shock but positively during recovery. This suggests that regional economic planners face a tradeoff between being more productive or being more vulnerable to the next economic shock. [ABSTRACT FROM AUTHOR]

Single-industry regions, common to all industrially developed countries, need to overcome the economic crises. We assume that it is possible to achieve this goal based on new forms of cooperation between the main participants: business, state, education, and science. Based on the triple helix model, the study develops a mechanism for cooperation between higher education and business in depressed single-industry regions. The model was tested on the example of the Republic of Kazakhstan. We use the methodological principles of logical, statistical analysis and synthesis. To increase the impact of universities on the national economic growth, we propose a cooperation mechanism based on the Triple Helix model. This model is adapted to the specificity of single-industry and depressed regions, where regional universities play a dominant role as a source of innovation and innovative synergy for the cooperation of partners involved. Simultaneously, the creation of new forms of cooperation between higher education and business leads to the acceleration of social and economic development of regions. The mechanism of the proposed triple helix model aims to encourage all participants to generate innovations, provide high-quality educational services, conduct research and fill business orders. Local and state authorities in the field of economic management can use the results and conclusions of the survey for creating regional development programmes.

Introduction. The variety of elements of the field of regional studies in Japan makes it possible to state that the sources of regional studies are heterogeneous not only in content, but also in their relation to different historical periods. The objective of the study is to analyze the processes of development of proto-regional knowledge in Japan from ancient times until the middle of the 19th century Materials and Methods. Japanese works on history and geography, as well as works by Russian researchers in the considered fields were used as the materials of the study. Particular attention was paid to historical and geographical texts; other sources (religious texts, poetic texts, etc.) were also considered. The basic methods employed were those of systemic, comparative, conceptual and terminological analysis. Results. The article discusses the stages of development of proto-regional knowledge in Japan in the framework of traditional science. Based on the analysis of works created before the middle of the 19th century, the authors conclude that the basic factor in the formation and development of knowledge about regions was the opposition “We vs. Others,” characteristic of Japanese ethnoculture, and this knowledge itself is largely Japanocentric. The article reveals the role of several schools of traditional science: kokugaku (school of national sciences), rangaku / yogaku (Dutch / European studies) and kangaku (school of Chinese sciences), as well as the role of their cultural and ideological confrontation in stimulating the development of proto-regional knowledge. Discussion and Conclusion. The article presents the results of the initial stage of a comprehensive study, which will examine the history of the development of Japanese regional knowledge and the methodology of regional research in Japan. The results of the work may be useful to researchers and specialists in the field of history of regional development of various countries and regions.

The work has as aim the highlighting of the importance of statistics as a science that provides the ensemble of methods and techniques for the study and analysis of regional development. For this, is trying a specific argumentation of the role of statistics in the quantification the different aspects of regional development, starting from the comparative assessment of the levels of macroeconomic aggregate of results of the Member States of the European Union, whose conclusions can be a good premise for the structuring of the territory on regions of development, a concept specific to regional science. Study of the specialized literature led to several important conclusions, including: in contouring and development of the regional science an important role had sciences as: statistics, econometrics, mathematics, sociology, politology and others, which gives regional science an interdisciplinary character; within the regional science, the regional economy is highlighted due to the wide range of addressed problems, at the three levels of knowledge: economic theory, method and practical applicability; among the methods of analysis used by the regional economy, the statistical methods have an essential importance in knowing the level, qualitative-structural dimensions, dynamics, correlations and interregional and intraregional dependencies among variables a.s.o.; statistics has an essential role in the substantiation of the regional development strategies, in the regional planning, in monitoring the results of the regional development policies a.s.o.; current evolution of regional science is achieved, not without the contribution of statistics, in directions such as: regional planning, regional forecast, urban economy, rural economy, land use planning, sustainable spatial development a.s.o. The work presents a comparative analysis of some key-indicators of the regional development, by regions of development in Romania, in 2015 and 2019. [ABSTRACT FROM AUTHOR]

Using bibliometric methods, this paper is aimed at providing an overview of Regional Science publications that address environmental issues. The analysis covers a corpus of 1145 articles that refer to the environment in their title, abstract or keywords and published in 18 journals between 1999 and 2020. Although these publications account for only 6 percent of the articles published in these journals over that period, their number gradually increased. To gain a clearer picture of the environmental issues addressed, we characterise them according to whether an integrative or topical approach is adopted and by their spatial dimensions. This analytical framework is first applied by searching for specific terms in their title, keywords and abstract. The results show that both approaches are equally effective; further, these articles address intraregional or interregional environmental issues more than global environmental issues. Second, we conduct a keyword co-occurrence analysis revealing four coherent thematic article groups treating environmental issues from the perspectives of amenities and migration, governance and policy, innovation and clusters, and land use and urban sprawl. More detailed analyses of each group allowed us to refine our understanding of how environmental issues were addressed. Finally, a cross-cutting view of the four thematic groups suggests that Regional Science approaches environmental issues through spatial disparities and inequalities, spatial interactions and interdependencies, and the spatial dimension of public action. The research perspectives in each of these areas are highlighted. [ABSTRACT FROM AUTHOR]

Ravenstein’dan beri ekonominin iç göç çıkışlarının belirleyicilerinden olduğu kabul edilmektedir. Ekonomide de tarım dışı üretim hacminin etkisi vurgulanmaktadır. Bu çalışmanın amacı da günümüzdeki iç göç çıkışlarında sektörlerin, sektörler bütününün ve GSYİH’nın iç göçteki etkisini sınamaktır. Genelde yöntem olarak giriş yapılan bölgedeki üretim hacmi veya giriş-çıkış yapılan bölgeler arasındaki farklılık kullanılmaktadır. Uygulamada giriş yapılan illerdeki ekonomik hacimler temel alınmıştır. İstatistiksel analizlerde ilk olarak Pearson korelasyonu kullanılmıştır. Pearson korelasyonunda anlamlı ilişki tespit edilen GSYİH bileşenleri içinse tekli doğrusal regresyon analizi uygulanmıştır. Uygulama alanı 2008-2018 yılları için Bilecik’tir. Veriler TUİK’ten derlenmiştir. Elde edilen bulgulara göre Bilecik’ten iç göç çıkışları tarım sektörü hariç üretimle ilişkilidir. Tarım dışındaki sektörlerin ve GSYİH’nın Bilecik’ten iç göç çıkışlarında anlamlı etkisi tespit edilmiştir. En yüksek etkileyense sanayi sektörüdür.

The goal of the article is to study academic foundations of territorial management established in the process of evolution of home regional economic science and specific features of their practical implementation at different stages of economic development of our country. By using the dialectic method of cognition and system approaches it is possible to reveal the diversity of historically formed scientific views dealing with such issues as shaping and managing administrative – territorial units in Russia as a federal state, to analyze positions of different scientists in defining certain basic categories of regional science, to systematize terms and ground the author’s position in defining the term ‘region’ in interconnection with other single-ordinal scientific categories. The author investigated the laws of functioning and trends of development of regional economy in connection with problematic issues of designing the concept of spatial development of the Russian Federation. The place of macro-region as a key taxonomic unit for studying the spatial structure of national economy is being identified, as well as its principle role as a forming link in the system of sub-federal management during the shift to the 6th technological structure. The author grounds the expediency of further research in the context of renewal of methodological tools and use of proposed organizational innovation aimed at development of basic provisions of science about regions in order to optimize territorial structure of economy and raise the quality of management of spatial development of the Russian Federation in conditions of digital economy formation.

Principal Component Analysis (PCA) is a widely applied statistical technique aimed at summarising a multidimensional set of input (partly redundant) variables into a restricted number of independent components that are linear combinations of the inputs. PCA transforms the original data matrix by performing a spectral decomposition of the related variance/covariance (or correlation) matrix. When decomposing a correlation matrix, Pearson product-moment correlation coefficients are traditionally used in the correlation matrix. The statistical properties of Pearson correlation coefficients (being insensitive to non-linear, high-order correlations) represent an intrinsic limitation of PCA, restricting its applicability to linear relationships among inputs. However, working with variables displaying (more or less intense) deviations from linearity is common in both socioeconomic research and environmental studies. Following the theoretical assumptions of earlier studies, a generalisation of PCA aimed at exploring non-linear multivariate relationships among inputs is illustrated in the present article by using non-parametric Spearman and Kendall coefficients to replace linear Pearson coefficients in the correlation matrix. The per cent share of 19 land-use classes in the total landscape in a given study area (the Athens metropolitan region, Greece), obtained from a high-resolution map at the local scale, were used as inputs. The results of the standard PCA (via decomposition of a Pearson linear correlation matrix) and a generalised approach (via decomposition of a nonparametric correlation matrix based on Spearman or Kendall rank coefficients) were compared using traditional diagnostics. The PCA performed by decomposing a Spearman correlation matrix exhibited the highest variance extracted by the principal components, giving refined loadings and scores that allow recognition of latent landuse patterns. Contributing to a recent debate on the use of multidimensional techniques in regional studies, non-parametric approaches are promising tools for analysis of large datasets displaying complex, almost nonlinear relationships among inputs. [ABSTRACT FROM AUTHOR]

The aim of the paper is to explore and map out regional science perspectives on global development, assessed on the basis of the Sustainable Development Goals (SDGs) proposed by the United Nations (UN). The issue is important, since in general the methodological glue that unites interdisciplinary approaches - like regional science - may not work without a uniform or shared view on the reality and the mutual consistency of societal aims. The question whether the hierarchy of UN Development Goals is supported by regional science approaches related to geographical space, disciplinary expertise, and sustainability viewpoints is addressed in the present study, using a Q-method technique. To that end, a survey questionnaire among a group of internationally renowned regional scientists from all over the world was systematically administered and analyzed. The results are related to characteristic features of the respondents (regional scientists) examined. Our findings indicate that location, disciplinary field, and cognitive mindset do influence the ranking by regional scientists of the sustainability goals concerned. The lessons are that it is important to specify explicitly the assumptions of each sustainable development study and to understand whether the researcher's attitudes regarding sustainable development require a 'complementary' perspective. [ABSTRACT FROM AUTHOR]

We have entered the 21st century facing a global trend of massive urbanization leading to an increasing concentration of population in relatively few, large cities. This exacerbates the share of GDP produced in cities (80%). Today, more than 54% of the world population lives in a city and this number will likely increase by the end of this century to 80%. This trend implies a redefinition of what a city, and what an agglomeration, is. There is then no doubt that the city has become the central point in various social sciences and that agglomeration economics have become an important topic in development economics. Smart Cities have become in this context an important topic in Regional science and in applied economics and geography. There is no doubt that the development of new technologies and especially information technologies have created their own issues. Actually, Smart cities are combining a production function and a housing and living environment one. But one can also see “Smart cities” as a new form of the industrial district issue. Regional science has known an important development since the late 1980 when the Marshallian concept of the “industrial district” came back to favour and became major a topic in development studies. The turn from the “industrial district” to “smart cities” is a much more recent one. But still in smart city studies as in industrial district ones, the same range of issues, some of them purely economic and others more politically oriented, are at stake