Purpose – the purpose of the article is to study the effect of digitalisation development indicators on per-capita GDP growth. Research methodology – the basic research method is the fixed-effects panel regression that describes the effect of the digitalisation development indicators on per-capita GDP between 1999 and 2017. Findings – research showed the most critical factors for per-capita GDP growth are the ones that linked with fixed and mobile subscriptions. Research limitations – The limitations of the research stem from the limitations of analysis as the method that has been employed makes it possible to measure the effect of the selected variables on per-capita GDP, but further research requires a detailed analysis of the factors being studied in application to each country. Practical implications – The findings can be used as a basis for choosing areas of more detailed factor analysis of the digitalisation process effectiveness and can support investment decision-making. Originality/Value – The study enables one to identify the most and the least important factors that are reflected by digitalisation indicators that have an impact on the per-capita GDP.
The application of chaos theory in economics is associated with an increasing level of uncertainty and external shocks faced by economic systems. This article reviews and systematizes the approaches to the use of chaos theory in economic research. To this end, we discuss the concept of chaos and its relevance; and identify those areas of research for which the application of chaos theory holds most promise. The research methodology comprises methods of system-functional and system-historical analysis. These methods are used to analyze the content of publications devoted to the application of chaos theory to study price fluctuations in individual markets, the behaviour of firms in the conditions of imperfect competition, the analysis of uncertainty of consumer behaviour, as well as cyclical economic development and disequilibrium associated with the balance of unemployment and inflation and geopolitical tensions. The study draws the distinction between the concepts of synergetics and chaos theory. It is shown that although these two research areas are related, they have a different focus of application. The study also identifies some common patterns in the use of chaos theory tools for economic research: at the first stage, elements of chaos, fractals and nonlinearity in the series of economic data are identified; at the second stage, researchers try to explain certain events by using the tools of chaos theory; and at the third stage, chaos theory is used to model and subsequently predict short-term and long-term trends. Chaos theory expands the mathematical apparatus of economic research, allowing researchers to access tools from the field of physics and other natural sciences, which enhances interdisciplinary synthesis.
Sustainable development was chosen by the United Nations as the key concept of the future in the 21st century, which led to the emergence of other economic concepts, such as green and blue economy, seen as contributing to the achievement of sustainable development goals (SDGs). In Russia, despite the ongoing processes of green transformation in some economic sectors and certain improvements in the green legislation and green finance, not all businesses and regions are ready to embrace sustainable development. This paper discusses two interconnected aspects of regional economic systems — their economic efficiency and environmental impact. The analysis focuses on the regions of the Ural Federal District and explores these regions’ transition to sustainable development by looking at their eco-intensity. Methodologically, the study relies on the methods of analysis and synthesis, statistical, comparative and causal analysis. Conceptually, we use the theoretical framework of sustainable development as a point of departure for our discussion. The results have shown, on the one hand, a decrease in the industrial pressure on the natural environment, related primarily to the enhanced resource efficiency of certain industries. On the other hand, less effort is now invested into minimising the negative impact on the environment in Ural regions. We have also identified those areas of sustainable development that hold most promise in the Russian context. Our findings can serve as a basis for the strategies of regional sustainable development and may be used for further research on socio-environmental and economic sustainability.
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