Development Of Digital Economy Research Articles

A two-stage stochastic collaborative planning approach for data centers and distribution network incorporating demand response and multivariate uncertainties

As a critical infrastructure to support the development of digital economy, the scale of data center (DC) power consumption has been growing continuously in recent years. The plug-in of a large number of DCs to the distribution network (DN) presents both opportunities and challenges for the secure, stable, and sustainable operation of the system. In order to address the planning issues arising from the integration of DCs into the DN, this paper proposes a two-stage (planning stage and operation stage) collaborative planning method for DCs and the DN while considering the source-demand uncertainty. Firstly, spatial-temporal demand response characteristic of DCs is explicitly elaborated, and based on the energy consumption model, a two-stage stochastic planning model considering conditional value at risk (CVaR) for DCs and the DN is constructed using probabilistic stochastic simulation, which obeys low-carbon and security, and satisfies the source-network-load constraints of the system. The siting and sizing for DCs and renewable generation, feeder expansion for the DN are determined to minimize the investment cost during the planning stage, while the power output for the devices considering uncertainties from load and renewable energy are optimized to minimize the operation cost during the operation stage. Secondly, the L-shaped decomposition algorithm is proposed to solve the two-stage stochastic optimization problem by reconstructing the problem into a master problem and subproblems, where the dual multiplies are calculated to generate feasibility cuts and optimality cuts to achieve iterative solving. Finally, numerical case studies on a 33-bus distribution system demonstrate that the participation of DCs in demand response can achieve a significant reduction in the investment and operation cost of the DN, and further promote the consumption of distributed renewable energy sources.

Study on the Coupling Coordination Development between the Digital Economy and Innovation Efficiency: Evidence from the Urban Agglomeration in the Middle Reaches of the Yangtze River

The urban agglomeration in the middle reaches of the Yangtze River holds a crucial strategic position in China’s economic and social development landscape. Exploring the coordinated development effects within the digital economy and innovation in this area is conducive to promoting the development of the central region of China and the Yangtze River Economic Belt. This paper uses the 28 sample cities in urban agglomeration in the middle reaches of the Yangtze River as the study sample, and constructs a digital economy indicator system and an urban innovation efficiency indicator system. Based on the coupling coordination degree model, we use kernel density estimation, the Markov chain algorithm, and the Dagum Gini coefficient decomposition method to empirically investigate the dynamic trends in coupling coordination development between the digital economy and urban innovation efficiency from 2012 to 2021. The research results reveal an overall upward trend in the digital economy, innovation efficiency, and coupling coordination development stages. However, the upward trend is accompanied by the risk of recession. Moreover, there are significant differences between cities, as highlighted by the differences between Wuhan and other cities. In the light of the findings, it is recommended that government departments take measures, including being alert to the risk of regressive development, developing cities in a realistic manner, and drawing on the experiences of outstanding cities in development. This research can provide new insights and empirical references for government entities to take measures for a more coordinated development of the digital economy and innovation efficiency in the urban agglomeration in the middle reaches of the Yangtze River.

Has the Advancement of the Digital Economy Improved the Well-being of the Population? --Empirical Study Based on Chinese Provincial Panel Data

Promoting the long-term prosperity of a country by exploring the relationship between the digital economy and residents' happiness holds great significance. This research quantifies the extent of digital economy progress through the utilization of the Critic approach. The investigation assesses the evolution in disparities in digital economy development levels across various provinces. Since happiness is a discrete ordered response variable, this paper utilizes an ordered probit model to investigate the impact relationship, incorporating individual characteristic variables. Furthermore, this study takes the sense of social justice as the mediating variable to test whether the development level of digital economy has a mediating effect on residents' happiness. The empirical results imply that the disparity in digital economy development levels among provinces gradually decreases over time, and boosting digital economy development positively make contributions to improving residents' happiness. The impact effect comprises both direct and indirect effects; specifically, digital economy development directly affects residents' happiness and indirectly influences it by enhancing their sense of social fairness. Based on these conclusions, this paper offers relevant recommendations to promote national prosperity and enhance residents' happiness.

Does digital economy development affect urban environment quality: Evidence from 285 cities in China.

The impact of the digital economy (DE) on urban environmental quality (EQ) is a critical aspect of China's economic development. This study investigates the impact of DI on urban EQ using the data from prefecture-level cities spanning the period from 2011 to 2021 and updates some disparate conclusions of related studies. It is discovered that a non-linear correlation exists between DE and urban EQ. Currently, DE can effectively improve local city EQ. This conclusion remains valid even after robustness tests and endogeneity treatment. The impact of DE on improving EQ can be classified as the impact of technological innovation, industrial upgrading, resource allocation, infrastructure construction, environmental governance, and changes in public lifestyle. Heterogeneity analysis reveals that the influence of DE is particularly pronounced in cities located in central and eastern regions of China, those with higher levels of administrative management, resource-based urban areas, and those with more stringent environmental regulations.

The relationship between digital economy and industrial green innovation efficiency – based on the perspective of external knowledge sources

PurposeDriven by the development of the global digital economy, knowledge management in industrial enterprises offers more possibilities for green innovation. Based on the perspective of external knowledge sources, this study aims to construct a panel regression model to explore the relationship between digital economy and industrial green innovation efficiency.Design/methodology/approachPanel data from 30 regions in China from 2011 to 2020 were selected as research samples. All data are obtained from national and provincial statistical yearbooks. Coupling coordination degree analysis, entropy method, panel regression analysis, robustness test and threshold effect test by Stata 16.0 were used to test the hypotheses.FindingsThe empirical results demonstrate the hypotheses and reveal the following findings: the digital economy is positively related to industrial green innovation efficiency and external knowledge sources, and external knowledge sources mediate the relationship between them. Moreover, based on the threshold test results, the digital economy has a double-threshold effect on industrial green innovation efficiency.Originality/valueBased on the perspective of external knowledge sources, the proposed mediating mechanism between the digital economy and industrial green innovation efficiency has not been established previously, further enriching the research on the antecedents and outcomes of external knowledge sources. Moreover, this study estimated the direct influence mechanism and double-threshold effect of the digital economy on industrial green innovation efficiency from theoretical and empirical analysis, thus responding to the call of scholars and adding to existing research on how the digital economy affects the green transformation of industrial enterprises.

How Does the Low-Carbon City Pilot Policy Affect Enterprises’ Green Innovation? Empirical Evidence from the Context of China’s Digital Economy Development

The integrated development of green innovation and digital economy is crucial for addressing global climate change, promoting the application and popularization of digital technologies in the green sector, and achieving efficient, intelligent, and sustainable economic development and lifestyles. Using panel data from China’s listed enterprises from 2003 to 2021, this study examines the impacts of environmental regulations on green innovation in the low-carbon city pilot policy (LCCPP) context, which serves as a quasi-natural experiment in the digital economy. The results show that LCCPP effectively enhances enterprises’ green innovation by increasing enterprises’ environmental and research and development investments, and boosting digital transformation. Heterogeneity analysis reveals that the promotion effect of LCCPP on green innovation is highly pronounced for enterprises in the eastern region, for those with low financial constraints, and for technology-intensive enterprises. This effect is closely and positively correlated with the digital economy level in the regions where the enterprises are located. This study provides new empirical evidence for the relationship between environmental regulations and enterprises’ green innovation and discusses policy support for addressing global climate change challenges through environmental regulations in the digital economy context, thereby promoting global sustainable development.

Цифровые платформы как драйвер реализации проектов компаний по импортозамещению ИТ-инфраструктуры: опыт экосистемы «Сбер»

The development of digital economy is currently impeded by the complex geopolitical situation, causing negative influence on Russian companies’ IT-infrastructure stability. Given conditions determine the importance of technological products import substitution. The stimulating state policy and digital transformation of business which is based on progressive technologies determine a key role of Russian companies’ digital platforms in the import substitution of technological products. Therefore, the support of technological projects development is provided, the results of which are implemented at micro level or scaled in the form of end-to-end technologies at meso- or macro levels. This article considers approaches to the classification of digital platforms and analyzes the B2B segment services of Sber ecosystem as a platform for the implementation of Russian companies’ technological projects According to the results of the study, the directions of business solutions import substitution have been identified, as well as the development of the architecture model of Sber ecosystem B2B segment which contribute to the successful implementation of companies’ technological projects was developed.

Artificial Intelligence and Productivity Improvement in the Digital Economy

The digital economy and AI development have significantly revolutionized diverse sectors, profoundly influencing productivity. Focusing on agriculture and the artificial fiber manufacturing industry, this paper scrutinizes the impact of AI on productivity in these domains. By methodically analyzing prevalent literature, research studies, industry reports, and case studies, this investigation aims to elucidate how AI has heightened productivity within these sectors. The results exhibit substantial enhancements in resource optimization, yield enhancement, quality control, and efficiency resulting from the implementation of AI. Furthermore, the subsequent sections of discussion and conclusion elucidate these findings, emphasizing the potential advantages and enduring challenges concerning AI’s assimilation to ameliorate productivity within the digital economy.

Research on quantitative evaluation of digital economy policy in China based on the PMC index model.

The development of digital economy is a strategic choice to grasp the revolution of new science and technology and the new opportunities of industrial reform. The development of digital economy depends on the good support of policy and theoretical system. Therefore, the quantitative evaluation of policy texts provides the basis of decision-making and the suggestions of path optimization for the formulation and improvement of digital economy policy of China. By selecting the text of digital economy policy issued by China government, the paper constructs a quantitative evaluation model of digital economy policy using the methods of content analysis and text mining. The empirical research results show that the overall design evaluation of the selected policy is relatively reasonable. Six policies were evaluated as excellent and two as acceptable. In view of the problems such as lack of predictive policy in the policy type, lack of specific policy in the policy timeliness, imbalance in the use of policy guarantee, and lack of comprehensive coverage in the policy objectives, the paper puts forward corresponding countermeasures and suggestions.

The Spatial Role and Influencing Mechanism of the Digital Economy in Empowering High-Quality Economic Development

Based on the data from 2012 to 2022, this paper comprehensively uses exploratory spatial data analysis, the panel threshold model, and the spatial Durbin model to explore the spatiotemporal evolution characteristics and mechanisms of digital economy and high-quality economic development. The results show that the center of gravity of China’s digital economy development has gradually concentrated in the southeast region, and the level of high-quality economic development has improved rapidly, gradually forming a pattern of radiation driving the development of the central and western regions with the Beijing–Tianjin–Hebei region, the Yangtze River Delta, and the Pearl River Delta. The digital economy can significantly improve the level of high-quality economic development, but this effect has a lag effect, and it can be extended to the fifth stage. There is a single threshold for high-quality economic development of the digital economy, and the two stages of its development can significantly promote the high-quality development of the economy, but the effect of the latter stage is weakened, showing the nonlinear characteristics of first strong and then weak. The digital economy has a notable positive spatial spillover impact, and its development dividend will raise this province’s and its bordering provinces’ levels of high-quality economic development.

Research on the Effect of Digital Economy Development on the Carbon Emission Intensity of Agriculture

The integration of the digital economy with the real economy has facilitated the application of a variety of digital methods in agriculture, resulting in significant reductions in its carbon intensity. This study employs a spatial Durbin model to analyze the spatiotemporal effects of digital economic growth on agricultural carbon emissions, using Chinese inter-provincial panel data spanning from 2011 to 2020. The empirical results indicate a substantial decline in agricultural carbon emissions associated with the evolution of the digital economy. Additionally, a discernible spatial spillover effect is identified. The suppressive impact of the digital economy on agricultural carbon emission intensity exhibits clear heterogeneity, with more pronounced effects observed in the main grain-producing regions and western regions. Based on these findings, recommendations are proposed to accelerate the development of digital economy infrastructure tailored to local conditions, promote the integration of digital technology and agriculture, stimulate innovation in agricultural science and technology, and advocate for the adoption of energy-efficient and environmentally sustainable agricultural practices.

Carbon emission effect of digital economy development: impact of digital economy development on China’s carbon dioxide emissions

Carbon emission effect of digital economy development: impact of digital economy development on China’s carbon dioxide emissions

Digital economy development boosts urban resilience—evidence from China

Focusing on the impact of the digital economy on urban resilience is beneficial to the sustainable development of cities. This paper empirically examines the impact of digital economic development on urban resilience and its mechanisms by measuring urban resilience and the level of urban digital economy with the entropy-weighted TOPSIS method using the data of 252 Chinese cities from 2011 to 2020. The findings show that digital economic development effectively promotes urban resilience at the 1% significance level, and this conclusion remains valid after a series of endogeneity and robustness tests. The channel mechanism suggests that the development of the digital economy can improve urban resilience by optimizing urban distributional effects and promoting the upgrading of urban industrial structures. This paper discusses the nonlinear relationship between the two using the MMQR model and the threshold model. The results show that urban resilience development level is in a higher quartile of cities, and digital economy development has a greater impact on urban resilience improvement. Meanwhile, there are two threshold values for the nonlinear impact of the digital economy on urban resilience, which are 0.026 and 0.082, respectively. Further, the spatial effect between the two is also verified. From the perspective of heterogeneity analysis, the digital economy development of high-class cities, key city clusters, and cities in eastern and western regions has a greater effect on urban resilience. This study can provide ideas and inspiration for countries to enhance urban resilience and promote sustainable urban development through the development of the digital economy.

Study on the spillover effect of digital economy development on CO2 emissions

To study the spillover effect of the digital economy development on carbon emissions, this study innovatively constructs different spatial weight matrices, based on 2011–2020 panel data covering 30 Chinese provinces, and it explores the direct spillovers, conducted spillovers, and spillovers from different spillover channels, such as human capital, service industry development, and information development of digital economy development on carbon emissions through the spatial Durbin model combined with a mediating effect model. The results show that there is significant spatial heterogeneity in digital economy development; in terms of regions, the eastern region has the highest average development level and the central region has the highest average annual growth rate. Digital economy development can directly suppress carbon emissions, and it can also indirectly suppress carbon emissions by driving technological innovation and optimizing the energy consumption structure, and there exists a spatial spillover effect. Under human capital, service industry development and information development matrices, the spatial spillover effect of digital economy development on carbon emissions is significantly negative. Regions with the same level of information development are more likely to exert a spatial spillover effect of digital economy development on carbon emissions.

Linear Programming-Based Fuzzy Alternative Ranking Order Method Accounting for Two-Step Normalization for Comprehensive Evaluation of Digital Economy Development in Provincial Regions

As digital technologies continue to reshape economic landscapes, the comprehensive evaluation of digital economy (DE) development in provincial regions becomes a critical endeavor. This article proposes a novel approach, integrating the linear programming method, fuzzy logic, and the alternative ranking order method accounting for two-step normalization (AROMAN), to assess the multifaceted facets of DE growth. The primary contribution of the AROMAN is the coupling of vector and linear normalization techniques in order to produce accurate data structures that are subsequently utilized in calculations. The proposed methodology accommodates the inherent uncertainties and complexities associated with the evaluation process, offering a robust framework for decision-makers. The linear programming aspect optimizes the weightings assigned to different evaluation criteria, ensuring a dynamic and context-specific assessment. By incorporating fuzzy logic, the model captures the vagueness and imprecision inherent in qualitative assessments, providing a more realistic representation of the DE’s multifaceted nature. The AROMAN further refines the ranking process, considering the interdependencies among the criteria and enhancing the accuracy of the evaluation. In order to ascertain the efficacy of the suggested methodology, a case study is undertaken pertaining to provincial areas, showcasing its implementation in the evaluation and a comparison of DE progress in various geographical settings. The outcomes illustrate the capacity of the model to produce perceptive and implementable insights for policymakers, thereby enabling them to make well-informed decisions and implement focused interventions that promote the expansion of the DE. Moreover, managerial implications, theoretical limitations, and a comparative analysis are also given of the proposed method.

The impact of digital economy development on agricultural carbon emissions——empirical research based on Chinese data

ABSTRACT This study examines the impact of digital economy development on carbon emissions in Chinese agriculture and its underlying mechanisms. Empirical analysis is conducted using panel data from 31 provinces in China for the years 2013 to 2021, employing a fixed-effects model.The study reveals that the development of the digital economy significantly reduces agricultural carbon emissions, with this effect showing a non-linear increasing trend. The impact of digital economy development on agricultural carbon emissions varies with climate types, and the reduction effect is more pronounced in regions with lower rainfall. Furthermore, the development of the digital economy lowers the intensity of agricultural carbon emissions by improving logistics efficiency and promoting industrial upgrading and transformation.This paper provides a theoretical basis and policy recommendations for the nation to reduce agricultural carbon emissions and promote green transformation. It suggests that the government should strengthen support and guidance for the development of the digital economy, actively promote the digitalization of agriculture, including the formulation of differentiated strategies for the development of digital agriculture, improvement of regulations and standards for agricultural product logistics, and enhancement of the application and innovation in smart agriculture.

The digital economy and job quality: Facilitator or inhibitor? --Evidence from micro-individuals

The improvement of workers' employment quality is an important manifestation of high-quality economic development. Based on 13,969 valid samples from the China Family Panel Studies (CFPS) data, the paper examines the impact of urban digital economy development level on individual employment quality from a micro perspective using a multilevel regression model. The study finds that the level of urban digital economy development significantly promotes individual employment quality. For every 1 unit increase in the level of urban digital economy development, the quality of individual employment will increase by 1.033 units. And air quality positively moderates the relationship between urban digital economy development level and individual employment quality, i.e., in cities with good air quality, the urban digital economy development level has a more important role in promoting the quality of individual employment. Further heterogeneity analysis reveals that the level of digital economy development in cities has a more pronounced effect on the employment quality of males, younger workers (40 years old and below), and party members. To be more specific, every increase of one unit in the development level of urban digital economy will increase the employment quality by 1.649, 0.787, and 0.897 units, respectively. The above findings are useful for the formulation of policies to achieve high quality of employment and the implementation of environmental management plans.

Digital economy and carbon emission: The coupling effects of the economy in Qinghai region of China

This study provides an in-depth analysis of the complex relationship between the digital economy and carbon emissions, fully drawing on essential principles of environmental economics, coupled economics, and sustainable development theory. Focusing on the Qinghai region in the western province of China, the study employs highly sophisticated methods such as multiple regression analysis and system dynamics modeling to reveal the multidimensional coupling effects between digital economy development and carbon emission dynamics. The study's results clearly show that in the Qinghai region of China, the booming growth of the digital economy is related to carbon emissions. Of particular interest, the study finds that this relationship exhibits a high degree of complexity and non-linearity and evolves gradually over time. Initially, the rapid expansion of the digital economy, accompanied by high energy consumption and increased carbon emissions, posed a significant challenge to environmental protection. However, a clear inverted “U"-shaped relationship has emerged as the digital economy evolves. This key inflection point signals a shift in the landscape as the digital economy begins to deliver some ecological benefits, potentially reducing the trend of carbon emissions in the future. The findings of this study go beyond simple causality and reveal a complex and evolving dynamic relationship between the digital economy and carbon emissions. Through such insights, this study provides a solid academic foundation and carefully constructs actionable policy recommendations to drive sustainable development. These insights apply to the Qinghai region of China and provide valuable references and lessons for other areas facing similar challenges.

The spatial and temporal situation of China's digital technology innovation and its influencing factors.

Digital technology innovation is the core driving force for the high-quality development of the digital economy, and in-depth exploration of the regional distribution pattern and formation mechanism of digital technology innovation in China is conducive to the rational layout and coordinated development of the inter-provincial digital economy. Based on the Reference Relationship Table of the Classification of Core Industries of Digital Economy and the International Patent Classification (2023), the patent authorization data of digital technology from 2012 to 2022 were obtained, and the spatiotemporal situation of China's digital technology innovation was analyzed by using ArcGIS software, Dagum's Gini coefficient, and Moran's I index, and the spatial Dubin panel model was used to explore the influencing factors of digital technology innovation. It is found that: (1) the scale and vitality of China's digital technology innovation have increased significantly, and there are obvious spatial differentiation characteristics, and the innovation level of "eastern coastal-central and western interior" is decreasing, forming a cluster distribution pattern in the Yangtze River Delta region, Beijing, Guangdong, and other places, and the degree of agglomeration is decreasing. (2) The overall regional differences in China's digital technology innovation are large, the differences between the East and the West dominate the interregional differences, and the net differences between regions are the main factors leading to regional differences. (3) There is a significant positive spatial correlation between the scale and vitality of digital technology innovation, which has a significant spatial spillover effect. (4) The results confirm that the level of economic development, digital access, financial scientific and technological support, technology market development level, and R&D intensity have a significant positive impact on the scale and vitality of digital technology innovation; The investment in scientific and technological talents has a significant positive impact on the scale of digital technology innovation, but has no significant impact on the vitality of digital technology innovation.

Influence and its spatial verification of digital economy development on carbon emission intensity from urban energy consumption

<p>In order to explore the influence of digital economy development on carbon emission intensity from urban energy consumption, digital economy development is incorporated into the reduction framework of carbon emission intensity from urban energy consumption in this paper. With carbon emission intensity from urban energy consumption in China taken as the research object, empirical tests and dynamic effect analyses were carried out on the factors influencing carbon emission intensity from urban energy consumption, using urban panel data for the period of 2012–2022. It is found that digital economy has a significant inhibitory effect on carbon emission intensity from urban energy consumption in China, with a coefficient of -0.348. Among the five selected control variables, PCG, UR, and IS show a positive correlation with carbon emission intensity from urban energy consumption, enhancing EI with corresponding influence coefficients of 0.472, 0.135, and 0.331 respectively; EGRI and TRL show an inverse correlation with EI, inhibiting the growth of EI with corresponding influence coefficients of -0.556 and -0.201, respectively. Policy suggestions were put forward to minimize EI on the basis of the test results combined with the actual situation of China's urban economic development.</p>