Narrow Results

With the rapid advancement of the digital economy, the financial market confronts unprecedented complexity and interconnectivity, rendering the precise prediction of credit bond default risk particularly crucial. This paper introduces a novel credit bond default risk measurement model (GST-GRU) predicated on a spatio-temporal attention network and genetic algorithm, designed to enhance the accuracy and robustness of risk prediction. Initially, data preprocessing is undertaken, encompassing time series data cleaning, completion of missing values for historical financial information and bond default statuses, and extraction of spatial discrete information through independent vector coding. Subsequently, a spatio-temporal attention mechanism is employed to amplify feature information in both domains, while the GRU network captures the long-term dependencies within the time series data. Thereafter, model parameters are refined using a genetic algorithm to ensure global optimality. Experimental results demonstrate that the GST–GRU model markedly improves prediction accuracy across multiple public and self-constructed datasets, surpassing traditional models. This research furnishes robust technical support for risk management in the financial market, fosters the evolution of credit bond default risk prediction technology, and lays the groundwork for the intelligence and automation of future financial systems.

Digital economy development is important for promoting industrial upgrades and high-quality economic growth. As excessive carbon emissions are a threat to sustainable economic growth, whether digital economy development contributes to reducing carbon emission intensity has gained attention. This study employs the fixed effects model and spatial Dubin model to examine the effect of digital economy development in 275 cities in China on the reduction of carbon emissions intensity. The results show effectiveness in reducing carbon intensity with a spatial spillover effect to neighboring areas. Urban economic primacy plays a positive modulating role in carbon reduction. Policy implications are discussed.

As a new way of promoting high-quality economic development, whether the digital economy can enhance energy use efficiency by improving resource allocation is of great practical significance to global energy conservation and emission reduction efforts. This research employs principal component analysis and slacks-based measure data envelopment analysis in a case study of 30 provinces in China between 2014 and 2020 to evaluate the digital economy and energy efficiency. The analysis explores how the digital economy impacts energy efficiency, considering direct impacts, mediating effects, and their nonlinear relationship. The findings indicate a declining trend in China’s energy efficiency before it starts to moderate. The digital economy can boost energy efficiency by encouraging industry upgrades and reducing labor mismatches. The threshold regression model reveals that when the capital mismatch level exceeds 0.8871, the digital economy adds considerably to energy efficiency. The study’s findings confirm the linear and nonlinear energy efficiency impact trajectories of the digital economy, offering useful references for sustainable development policymaking.

The impact and operational mechanisms of the digital economy on China’s zombie firms cannot be ignored. From the theoretical perspectives of advanced industrial structure and rational industrial organization, this paper empirically tests the effects of the digital economy on zombie firms using data from China’s A-share listed companies from 2013 to 2020. The baseline regression results indicate that the digital economy significantly revitalizes zombie firms. Heterogeneity studies show that the revitalizing effect is more pronounced for zombie firms in the western region, larger zombie firms, and state-owned zombie enterprises. Mechanism tests reveal that the digital economy revitalizes zombie firms by promoting rational industrial organization, advancing industrial structure, and alleviating financing constraints. The conclusions of this paper not only offer new ideas for the transformation of China’s zombie firms but also provide insights for other developing countries undergoing digital transformation.

This paper evaluates the impact and role of digital economy on industrial green total factor productivity based on the perspective of China’s industrial green transformation and provides a realistic basis and decision-making reference for industrial green transformation. This paper constructs the industrial green total factor productivity and digital economy development index of 30 provinces from 2013 to 2019, and empirically tests the spatial-temporal evolution relationship between them and the impact of digital economy on industrial green development by using time-fixed effect and spatial Durbin model. The results show that the digital economy and industrial green total factor productivity digital economy are unevenly developed, basically showing a distribution trend of high in the east and low in the west, and the two have a significant positive spatial correlation in the years observed. The results of local spatial autocorrelation analysis show that there is a high clustering of digital economy and total factor productivity in the eastern coastal region and low clustering in the western region. The regional heterogeneity analysis shows that the development of digital economy is beneficial to optimize the distortion of capital and labor allocation and thus improve industrial green total factor productivity, but the indirect effect of digital economy on industrial green total factor productivity is not significant and the direct effect plays a dominant role.

The rise of the digital economy has had widespread and profound impacts on the economy and society. Extensive literature exists on digital economy and carbon emissions. However, there is a lack of literature focusing on the impact of the digital economy on the relationship between economic development and carbon emissions. This paper examines whether the digital economy has changed the relationship between economic growth and carbon emissions using panel and spatial econometric modeling. Using a panel dataset of 278 prefecture-level cities in China for the period from 2011 to 2019, the results show that there is a significant inverted U-shaped relationship between economic growth and carbon emissions, which is consistent with the Environmental Kuznets Curve (EKC) model. Moreover, the digital economy brings the turning point forward. In terms of spatial decomposition effects, both direct and indirect effects of economic growth on carbon emissions are significant, suggesting that economic growth has a positive impact on carbon emissions both in local cities and in neighboring areas. Overall, these findings provide valuable policy insights for promoting the synergistic development of the digital economy and accelerating the transition to a low-carbon economy.

This study uses the panel quantile regression model and conducts path analysis to examine the impact of inter-provincial digital economy development in China on carbon emission reduction. Results reveal several key points: First, the impact of digital economy development on carbon emission reduction varies significantly across quantiles; it can promote or inhibit emissions and shows an inverted “U” relationship. Second, the inhibition effect of the digital economy on carbon emissions is significantly stronger than the growth effect. Third, more than half of the studied regions show an inhibitory effect of the digital economy on carbon emissions, primarily through indirect impact paths. Among these paths, the three most significant ones are the improvement of urbanization level, resident affluence level, and per capita gross domestic product (GDP). Policy recommendations are discussed.

In order to facilitate the high-quality advancement and digital innovation of the wine industry, a method based on principal component analysis (PCA) and improved quantum particle swarm optimization (IQPSO) to optimize support vector machine (PCA-IQPSO-SVM), was proposed to solve the wine classification problem. First, the feature extraction ability of PCA was used to reduce the input dimension of the model and improve the classification efficiency. At the same time, aiming at the problems that the quantum particle swarm optimization (QPSO) is easy to fall into local optimum and the convergence ability is decreased in the later stage of optimizing SVM, a variety of improvement strategies are used to improve QPSO to find the best parameters of SVM. The experimental results demonstrate that the model of PCA-IQPSO-SVM exhibits superior evaluation indices compared to other models. Moreover, the optimization efficiency of the PCA-IQPSO-SVM model is enhanced by 1.64% to reach an impressive 85.2%, showcasing its remarkable optimization effect. Simultaneously, this study provides a scientific approach for quality classification in the wine industry, thereby facilitating its high-quality development.

Cooperative information systems (CIS) are at the core of a digital economy that is dedicated to providing hyper-connected citizens with access to intuitive and sophisticated technology. No longer are commercial applications the only driver of development activities, but wider societal and individual deployment areas are now explored. CIS researchers have for more than two decades studied the nature and requirements of cooperative systems linking latest technologies with hybrid user bases. However, the current opportunity-rich landscape of digital technologies such as mobile and social computing, advanced data analytics, robotic process automation or smart devices has triggered entire new, exciting research questions. In light of this setting, the 23rd International Conference on Cooperative Information Systems took place within the context of the 14th OnTheMove Federated Conferences and Workshops in Rhodes, Greece, in October 2015. This Special Issue features the carefully selected and comprehensively reviewed best papers from this event.

In order to improve data security and network data security in the digital economy-driven environment, this paper combines data security technology and network security technology to build a digital economy security management and control system. Moreover, this paper describes the data encryption of the data owners before the framework index and the composition and construction method of the corresponding EncIR tree, and analyzes the spatial keyword group query algorithm on the EncIR tree. In addition, this paper analyzes the experimental performance of index building and spatial query, and builds an intelligent digital economy security system on the basis of these algorithms. The experimental research results verify that the data security technology and network data system driven by the digital economy have good security performance, and on this basis, follow-up security regulations can be formulated.

Although recognised as useful, ambidextrous innovation also presents unique managerial challenges particularly when exploration and exploitation are pursued simultaneously. The paper aims to explore the forming mechanisms of firm’s ambidextrous innovation capabilities using the main approaches in strategic management. The authors theoretically examine the direct effects of the digital economy (DE) on ambidextrous innovation capabilities and the mediating effect of knowledge acquisition (KA) and use the stepwise regression method to conduct an empirical analysis of 178 high-tech companies listed in China’s A-share market from 2013 to 2019. The empirical results show that DE has significantly promoted the ambidextrous innovation capabilities of firms, and also has a significant positive impact on the balance effect between exploratory innovation and exploitative innovation; DE has a significant positive impact on both external knowledge acquisition (EKA) and internal knowledge creation; KA has a significantly positive effect on exploratory innovation, exploitative innovation and their balance effect, and the effect of KA on exploratory innovation is greater than that on exploitative innovation. Furthermore, KA plays a significantly mediating role in the relationship between DE and exploratory innovation/exploitative innovation. The findings of our study provide insights for knowledge management research and have important guiding significance for promoting ambidextrous innovation capabilities of firms in DE.

Technological singularity has seriously affected all the social, environmental, and economic genesis factors in mankind’s history. The problem of assessing the quality of life in the digital economy is acquiring new nuances including social services. The objective of this study is to investigate unique impacts of digital transformation on economic, environment, and social progresses on the quality of life improvement in China. Environmental statistical data on the impact of investments in social, state, and other spheres of economic activity are analysed at the machine learning level. Application of high-performance computing (HPC) and big data technologies for obtaining data on socio-economic statistics in real-time, the presence of feedback in the Web 4.0 concept, transfer of a significant part of economic processes to internet platforms provide the information necessary for analysis. As a result, a basis is proposed for implementing software products in the form of institutional decision-making support systems for a long horizon of planning investments in the quality of life.

The trade subjects of digital services have constructed and strictly implemented a more targeted system of trade barriers. Information Communications Technology (ICT) services, as an important trade subject in the digital services field, are more prominently affected by the digital services trade barriers. To investigate the trade effects of digital services trade barriers on ICT services exports, this paper conducts a series of empirical tests using trade panel data of 18 exporting countries and 38 importing countries during the period of 2014–2020. Our results in the benchmark regression show that digital services trade barriers significantly inhibit the expansion of ICT services exports. By the industry and country heterogeneity analysis, we first find computer services are most significantly affected by the negative effect of the digital services trade barriers; then it reveals that the degree of trade inhibition of high ICT countries exporting to low ICT countries is extremely significant, followed by low ICT inter-country exports.

With the rapid development of digital technologies based on information and communication technology (ICT), some studies suggest that the development of the digital economy is bound to have a significant impact on energy consumption. There are also studies demonstrating from different perspectives that ICT plays an important role in improving energy efficiency. Then, will the rapid development of the digital economy lead to a sharp increase in energy demand (electricity demand), thus affecting China’s socio-economic transition to green and low-carbon development? To this end, it is of great practical significance to explore the relationship between the digital economy and energy consumption from theoretical and practical perspectives. Focusing on the issue of ICT and its impacts on energy consumption, this paper clarifies the internal influencing mechanism between ICT and energy consumption. On this basis, this paper compares and analyzes the models, methods, and data in existing studies from the aspects of measurement of ICT’s direct energy consumption, empirical research on ICT and energy consumption, and discussions on rebound effects. After a brief summary, this paper identifies their shortcomings and explores future research directions.

Based on the data of 30 provinces in China from 2013 to 2021, this paper constructs indicators of the level of development of the digital economy, and explores the impact of the digital economy on the high-quality development of the economy based on the perspective of regional heterogeneity, using static and dynamic panel models. It is concluded that (1) the digital economy promotes high-quality development of the economy, and the eastern part of the country is particularly significant; and (2) the digital economy can promote high-quality development of the economy by promoting the innovation capacity of provinces and cities and reducing their carbon emissions. Finally, we put forward the recommendations of “vigorously developing the digital economy; improving the infrastructure construction and talent training in each region; establishing a regional coordination and linkage mechanism; and improving the development strategy of the digital economy”, so as to promote the high-quality development of the economy.

The study’s aim is to compare qualitative and quantitative tools used to measure the effectiveness of innovation activities in an enterprise. The techniques examined in the study are the balanced scorecard, multilevel clustering, world indices or descriptive statistics, mixed approach, and statistical method. The research found that the balanced scorecard was the most cost-effective for measuring the business efficiency within an enterprise. Multilevel clustering and world indices/descriptive statistics can be applied to developed markets and businesses with sustainable entrepreneurial orientation. The results can be used by top-level managers to assess innovation performance and make informed decisions regarding the innovation-related policy.

The African prospects for the development of the digital economy can be exhilarating, in the next three years, the rate of internet penetration African will undoubtedly be fast growth, where the magnitude of African internet users could reach an astounding number of 800 million, a number which is on par with the current number of Chinese internet users. As the world’s second most powerful digital economy, China under the banner of the construction of the “Digital Silk Road” has already in the past decade signed numerous memorandums of understanding with various African nations. China and even more African nations can and will mutually and significantly cultivate in the field of new infrastructures. The urgent promotion and establishment of new African infrastructure shall and will greatly support Africans to be able to gain access to the highspeed internet, which will not only benefit Africa’s local economic growth but also bring new impetus to the global economy.

Digitalization has led to fundamental changes in the way people behave and live, and the way organizations, societies and nations operate. Although digitalization has brought about enormous benefits in general, it has also made the work of policymakers ever more challenging. A key responsibility of policymakers is consumer protection and this task is made ever more complicated with issues of data privacy and data ownership since many institutions and companies are now able to gather granular consumer data over transactions and the Internet of Things (IoT). For effective policy-making, policymakers need the right data and information. This is no longer straightforward with issues of valuation and measurement — how does one measure digitalization and its outputs, particularly with some new-age products and services being free and are readily available? Moreover, digitalization has brought with it wide-ranging implications for the labor market (such as with the rise of gig economy), education, tax laws, economic policies and financial stability, which force policymakers to continuously keep abreast on emerging technological trends and to ensure their policies are up-to-date. This paper attempts to analyze various literature studies and draw some insights on issues that policymakers need to be mindful of in the digital age. Some potential recommendations will be tabled for discussion and further research.

As we enter the digital era, the digital economy provides an opportunity for China’s manufacturing industry to achieve ‘smart manufacturing’ and provides important support for China to move from a ‘big manufacturing country’ to a ‘strong manufacturing country’. This paper constructs an indicator system for the level of digital economy development in Chinese cities by determining the connotation of China’s digital economy based on the characteristics of its digital economy development. Based on the application of entropy value method to measure the level of digital economy development of cities, we empirically investigate the impact of the level of digital economy development of cities on the innovation efficiency of manufacturing industry using mixed panel data of listed Chinese A-share manufacturing companies and cities from 2011 to 2019. The empirical study finds that the level of urban digital economy development is conducive to improving the overall innovation efficiency, innovation quality efficiency and innovation quantity efficiency of enterprises, and overall, the digital economy has a significant contribution to the innovation efficiency of manufacturing industry. There is regional, firm size and industry heterogeneity in the impact of urban digital economy development level on manufacturing innovation efficiency, and this heterogeneity is further manifested in the types of manufacturing innovation efficiency. For example, the urban digital economy enhances the innovation efficiency of small-scale firms mainly through the quantity of innovation rather than the quality of innovation.

The management, investment and exchange of funds are being transformed by digital technology, driving a technological revolution in the financial sector. The proliferation of digital technology has given rise to the emergence of “financial technology,” an umbrella term for cuttingedge digital finance solutions. Digital technology has enabled the transition from physical bank branches to online banking, granting clients convenient access to their financial transactions through mobile banking applications, electronic payment methods and digital wallets. Digital finance research and development (R&D) has yielded regulatory technology solutions that automate compliance processes, improve the accuracy of regulatory reporting and address concerns related to data privacy. Digital finance places significant emphasis on cybersecurity and risk management. Ongoing research endeavors aim to advance cybersecurity safeguards, threat detection systems and data protection procedures. Collaboration is of the utmost importance in the digital finance ecosystem, encompassing end users, banks, FinTech firms and programmers, in order to foster innovation and satisfy the financial needs of customers effectively. The increasing significance of international payments has prompted the digital banking industry to collaborate with neighboring countries, striving to streamline and reduce the expenses associated with cross-border transactions.