Regional Development Overview: Challenges, Adopted Strategies, and New Initiatives

Jackson, Randall; Hewings, Geoffrey J. D.; Rey, Serge; Gracia, Nancy Lozano

doi:10.1596/1813-9450-9056

Cited by 5 publications

(3 citation statements)

References 54 publications

(57 reference statements)

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“…Also, for the use of a-priori technique to nd rules, data were converted from numerical into classes. The selection of the attributes and/or their type/category is generally based on regional science and literature in both elds of theory and on specic examples of indicators used in models (e.g., Feldmeyer et al 2020, Jackson et al 2019, Munandar, Winarko 2015. The search for useful attributes was performed in many factors aecting regional resilience.…”

Section: Attributes Selection and Valuesmentioning

confidence: 99%

Prediction models and testing of resilience in regions

Manousiadis

Gaki

2023

REGION

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A significant amount of research has been conducted regarding the resilience of the regions and the factors that contribute to allow them to face challenges, crises, or disasters. The rise of promising sectors like Machine learning (ML) and Artificial Intelligence (AI) can enhance this research using computing power in regional economic, social, and environmental data analysis to find patterns and create prediction models. Through Machine Learning, the following research introduces the use of models that can predict the performance of a region in disasters. A case study of the performance of USA Counties during the Covid19 first wave period of the pandemic and the related restrictions that were applied by the authorities was used in order to reveal the obvious or hidden parameters and factors that affected their resilience, in particular their economic response, and other interesting patterns between all the involved attributes. This paper aims to contribute to a methodology and to offer useful guidelines in how regional factors can be translated and processed by data and ML/AI tools and techniques. The proposed models were evaluated on their ability to predict the economic performance of each county and in particular the difference of its unemployment rate between March and June of 2020. The former is based on several economic, social, and environmental data -up to that point in time- using classifiers like neural networks and decision trees. A comparison of the different models' execution was performed, and the best models were further analyzed and presented. Further execution results that identified patterns and connections between regional data and attributes are also presented. The main results of this research are i) a methodological framework of how regional status can be translated into digital models and ii) related examples of predictive models in a real case. An effort was also made to decode the results in terms of regional science to produce useful and meaningful conclusions, thus a decision tree is also presented to demonstrate how these models can be interpreted. Finally, the connection between this work and the strong current trend of regional and urban digitalization towards sustainability is established.

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Section: Attributes Selection and Valuesmentioning

confidence: 99%

Prediction models and testing of resilience in regions

Manousiadis

Gaki

2023

REGION

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“…Irmen ( 2005) argues that periods of extensive and intensive growth replace each other as capital accumulation leads to the introduction of labor-saving technologies. There are some mechanisms for the transition from extensive to intensive development that is widely discussed, especially in the BRICS countries (Brazil, Russia, India, China, and South Africa) (D'Costa, 2009;Jackson, Hewings, Rey, & Gracia, 2019;Lema, Quadros, & Schmitz, 2015). One of the main ideas is the organization of communication between innovation and economic centers to ensure the transfer of technology and knowledge.…”

Section: Literature Reviewmentioning

confidence: 99%

Re-balancing of intensive and extensive factors in the center-peripheral system under the influence of technological development

Preobrazhenskiy

Firsova

2021

J GEOGR INST CVIJIC

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Regional development prospects depend on a set of factors, among which the most essential are the population density, distance between actors, and the level of development. Those aspects are revealed, on one hand, while analyzing the type of regional development (intensive or extensive), and on the other hand, from the standpoint of the center-peripheral model. An assessment of the sectoral structure of employed people in the economy of the region and the population density are also used to identify the development type. The combination of these approaches makes it possible to identify the regional capacity for innovations diffusion and knowledge spillover. The aim of the research is to assess regional differences in the economy sectoral structure for identifying the innovative and extensive types of Russian regions. There are other methods used in the research as well: cartographic analysis, structural-sectoral analysis, and typology. The types of regions characterized by disproportions of intensive and extensive development have been identified. Measures are proposed to realize the regional economic potential. The issues of the territorial transformation of the settlement system and economic space are discussed. Further research is associated with an extended analysis of intensive development factors and cross-county comparison of the factors of innovations diffusion intensity and knowledge spillover.

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“…Kazakhstan is the largest among the Muslim-majority nations in Central Asia (Obaidullah and Shirazi, 2018). The country’s economy is the largest in Central Asia, with a GDP of US$170.5bn and a foreign trade turnover of US$93.5bn (Jackson et al , 2019).…”

Section: Literature Reviewmentioning

confidence: 99%

The experience and the prospects of Islamic finance in Kazakhstan

Shirazi

Kuanova

Ryskulov

et al. 2021

QRFM

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Purpose This paper aims to take stock of the Islamic finance experience and aims to identify an approach for further development in Kazakhstan, using qualitative and quantitative assessments. Design/methodology/approach The paper presents a conceptual framework based on literature review and content analysis. Furthermore, the study uses a survey-based methodology to collect data and determine the prospects, challenges and possible remedies. The quantitative parameters of the potential of Islamic finance in Kazakhstan are based on the assessment of funds on bank deposits, which can be considered potential resources for Islamic financial instruments. Findings The results suggest improving the legal framework and institutional environment to grow Islamic finance in the country. Raising trust levels in a Shariah-based system within the local population, reducing transaction costs and reducing information asymmetry allow raising public awareness of Islamic finance and integrating Islamic finance into the conventional financial system. Research limitations/implications This paper is not free from limitations and does not focus on implementing the suggested results. Social implications This work elaborates in what way the Islamic finance advancement affects the development of economics and focuses on co-financing of real asset-based projects, with the risk and loss sharing; charity; strict prohibitions on the financing of haram activities, pseudo-needs; and subordination of the individual’s interests to society. Originality/value The proposed study presents originalities and it identifies the significant challenges and barriers for further Islamic financial industry development in Kazakhstan by professionals survey. Furthermore, the study assesses potential Islamic finance assets and provides recommendations for successful Islamic finance advancement, considering the peculiarities of the national economy.

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Regional Development Overview: Challenges, Adopted Strategies, and New Initiatives

Cited by 5 publications

References 54 publications

Prediction models and testing of resilience in regions

Prediction models and testing of resilience in regions

Re-balancing of intensive and extensive factors in the center-peripheral system under the influence of technological development

The experience and the prospects of Islamic finance in Kazakhstan

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