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Research on the Influence of the Digital Economy on Transforming Consumption Behavior Among Residents
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作者 Yang Shanshan Zhang Peng Xiao Man 《Contemporary Social Sciences》 2023年第3期1-28,共28页
Drawing on the essence of Marxist consumer economy theory,this paper argues that the innovations of digital technology can effectively facilitate the integration of economies of scale,economies of scope,and long-tail ... Drawing on the essence of Marxist consumer economy theory,this paper argues that the innovations of digital technology can effectively facilitate the integration of economies of scale,economies of scope,and long-tail economies.Through careful analysis of the practical case of Xiaomi’s business ecosystem,this paper highlights the notion that data serve as both a key production factor and a critical consumption carrier within the context of digital consumption.We thoroughly investigated the influence of the digital economy on transforming consumption behavior among residents by analyzing a range of typical business cases and the latest data that triggered this transformation.Based on the analysis,this paper argues that such transformation can lead to the platform agglomeration effect,the inclusive diffusion effect,and the push-pull effect by highlighting the specific ways in which the digital economy disrupts the consumption-production model and contributes to the upgrading and transformation of traditional industries.Additionally,this paper demonstrates how the digital economy can expand and promote emerging business forms,providing insights into the ways in which digital innovation is reshaping the contemporary economic landscape.This study intends to provide several policy suggestions that can expand domestic demand,promote consumption,drive the high-quality and integrated development of China’s digital and real economy,and position China as a strong cyber and consumer nation by using digitalized consumption as a starting point. 展开更多
关键词 the digital economy resident consumption economic effect high-quality development
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Information Models for Forecasting Nonlinear Economic Dynamics in the Digital Era
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作者 Askar Akaev Viktor Sadovnichiy 《Applied Mathematics》 2021年第3期171-208,共38页
The aim of this study was to develop an adequate mathematical model for long-term forecasting of technological progress and economic growth in the digital age (2020-2050). In addition, the task was to develop a model ... The aim of this study was to develop an adequate mathematical model for long-term forecasting of technological progress and economic growth in the digital age (2020-2050). In addition, the task was to develop a model for forecast calculations of labor productivity in the symbiosis of “man + intelligent machine”, where an intelligent machine (IM) is understood as a computer or robot equipped with elements of artificial intelligence (AI), as well as in the digital economy as a whole. In the course of the study, it was shown that in order to implement its goals the Schumpeter-Kondratiev innovation and cycle theory on forming long waves (LW) of economic development influenced by a powerful cluster of economic technologies engendered by industrial revolutions is most appropriate for a long-term forecasting of technological progress and economic growth. The Solow neoclassical model of economic growth, synchronized with LW, gives the opportunity to forecast economic dynamics of technologically advanced countries with a greater precision up to 30 years, the time which correlates with the continuation of LW. In the information and digital age, the key role among the main factors of growth (capital, labour and technological progress) is played by the latter. The authors have developed an information model which allows for forecasting technological progress basing on growth rates of endogenous technological information in economics. The main regimes of producing technological information, corresponding to the eras of information and digital economies, are given in the article, as well as the Lagrangians that engender them. The model is verified on the example of the 5<sup>th</sup> information LW for the US economy (1982-2018) and it has had highly accurate approximation for both technological progress and economic growth. A number of new results were obtained using the developed information models for forecasting technological progress. The forecasting trajectory of economic growth of developed countries (on the example of the USA) on the upward stage of the 6<sup>th</sup> LW (2018-2042), engendered by the digital technologies of the 4<sup>th</sup> Industrial Revolution is given. It is also demonstrated that the symbiosis of human and intelligent machine (IM) is the driving force in the digital economy, where man plays the leading role organizing effective and efficient mutual work. Authors suggest a mathematical model for calculating labour productivity in the digital economy, where the symbiosis of “human + IM” is widely used. The calculations carried out with the help of the model show: 1) the symbiosis of “human + IM” from the very beginning lets to realize the possibilities of increasing work performance in the economy with the help of digital technologies;2) the largest labour productivity is achieved in the symbiosis of “human + IM”, where man labour prevails, and the lowest labour productivity is seen where the largest part of the work is performed by IM;3) developed countries may achieve labour productivity of 3% per year by the mid-2020s, which has all the chances to stay up to the 2040s. 展开更多
关键词 the Schumpeter-Kondratiev Innovation and Cycle theory of Economic Development the Solow Neoclassical Model of Economic Growth Information Model of Technological Progress Symbiosis of “Human + Intelligent Machine” Labour Productivity in the Symbiosis of “Human + IM” and the digital economy
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