Against the backdrop of deepening globalization, the widespread adoption and application of digital technologies are reshaping global trade patterns and providing new momentum for low-carbon economic cooperation. Based on panel data from 10 ASEAN countries for the period 2010–2020, this study investigates the role of digital trade in the trade-environment nexus. The findings reveal an inverted U-shaped relationship between digital trade and carbon emissions, which is explained through the scale effect, structural effect, and technological effect. Furthermore, the study examines the influence of economic development levels and industrial structures on this relationship, identifying significant heterogeneity. Countries with higher levels of economic development and more advanced industrial structures exhibit a more pronounced inverted U-shaped relationship between digital trade and carbon emissions.

The development of digital economy is becoming an important path to promote the kinetic energy of China's tax revenue development. Based on the panel data from 2011 to 2018, this paper uses Gini coefficient to analyze the regional differences of China's digital economy, and uses fixed effect model, spatial Durbin model, multi-period double difference model and other empirical methods to examine the tax effects of digital economy development. The results show that the regional disparity is the main reason for the regional disparity of digital economy development in China. The development of digital economy directly increases the tax amount of local digital industry, and at the same time it also radiates and drives the increase of local total tax revenue; The tax effect of digital economy has a negative spatial spillover, showing a "siphon effect" to neighboring areas; Mechanism analysis shows that the development of digital economy mainly promotes the increase of local tax revenue through growth effect.

Based on China's 30 provincial panel data from 2006 to 2018, this paper uses the spatial Durbin model to empirically study the influence path and transmission mechanism of financial development on regional technological innovation, and introduce digital finance environment, marketization degree, and government environmental management as an adjustment variable to verify its regulating effect on financial development and regional technological innovation. The study found that the overall promotion of digital finance to local technological innovation is not significant. Besides, the characteristics of ownership discrimination and weak risk appetite in the bank's medium and long-term credit market have led to its failure to promote regional technological innovation. In contrast, the stock market and bond market in direct financing channels have enhanced local innovation capabilities. When the external environmental system is used as the adjustment variable, the results show that an excellent digital finance development, marketization degree, and government environmental management can effectively and positively regulate the effect of financial development and technological innovation.

In the context of digital economy, Hebei Province, as an important province in central China, has a huge manufacturing base and potential, and the development of digital economy has driven the transformation and upgrading of manufacturing industry to a certain extent. In order to better play the driving role of digital economy in the transformation and upgrading of manufacturing industry, this paper establishes an intermediary effect model based on three intermediary variables: enterprise resource allocation ability, enterprise cost and enterprise innovation ability, and conducts an empirical study on the panel data of 11 prefecture-level cities in Hebei Province from 2017 to 2022. The mechanism of digital economy driving manufacturing upgrading in Hebei Province was discussed. The results show that: (1) there is a significant positive correlation between the development of digital economy and the transformation and upgrading of manufacturing industry, which indicates that the development of digital economy has a direct driving effect on the transformation and upgrading of manufacturing industry; (2) There is also a positive correlation between the development of digital economy and the resource allocation ability and innovation ability of enterprises, indicating that the development of digital economy can improve the resource allocation ability and innovation ability of enterprises, and is conducive to the stable development of enterprises in the future; (3) Enterprise resource allocation ability and enterprise innovation ability play a significant intermediary role in the relationship between digital economy development and the transformation and upgrading of manufacturing industry, indicating that digital economy can indirectly accelerate the transformation of manufacturing enterprises' R & D achievements by improving enterprises' resource allocation ability and innovation ability, thus improving enterprises' market competitiveness and increasing enterprises' earnings. Drive the transformation and upgrading of the manufacturing industry. Based on this research conclusion, the government should give full play to the role of guidance and support, and introduce relevant policies to help the digital economy drive the transformation and upgrading of manufacturing enterprises. Manufacturing enterprises should seize the tide of the development of the digital economy, use digital technology to improve their resource allocation ability and innovation ability, enhance core competitiveness, and accelerate the transformation and upgrading of enterprises.

This article analyzes the impact of enterprise information transparency (TRANS) on CSR, while examines intrinsic mechanism, nonlinear relationship as well as the heterogeneous effect, taking the data of Chinese 711 listed enterprises from 2010 to 2020. This article finds: The improvement of TRANS is conducive to the fulfillment of CSR, noticeably there is a nonlinear relationship of inverted "U-shaped". Corporate reputation, internal control and external concerns play a part in mediating the influence of TRANS on CSR. The impact of TRANS varies significantly according to the responsibility orientation of different stakeholders. Multiple heterogeneity analysis reveals there is a more promotional effect in large-scale, non-state-owned and high marketization intensity enterprises. motional effect in large-scale, non-state-owned and high marketization intensity enterprises.

As a new economic innovation, live streamers have widely accepted video streaming technology combined with specific business activities in real time. To predict live streamers’ continuous streaming marketing intention on live streaming platforms, the study refers to the theory of planned behaviour (TPB) and designs influencing factors from attitude, subjective norm, and perceived behavioural control. Meanwhile, given the interactive nature of live streaming platforms, the paper divides the subjective norm into online and offline subjective norms and considers the influence both from online and offline communities. The data analysis based on the partial least squares path modelling and variance-based structural equation modelling (PLS-SEM) shows that attitude, online subjective norm, offline subjective norm, and perceived control towards the continuous streaming marketing have positive relationships with live streamers’ continuous streaming marketing intention and result in their final behaviours. Related scholars and platform managers should consider the impact of online and offline subjective norms when they analyse live streamers’ marketing psychology. Properly guiding live streamers to carry out marketing activities can not only be beneficial to their mental health but also contribute to the stable development of live streaming economy.

With the continuous advancement of technological revolution and industrial transformation, digital finance supported by big data and artificial intelligence has become an important engine for promoting carbon neutrality. We measured the industrial structure transformation index (ISU) of 30 provinces in China, and discussed the spatial spillover effect and transmission mechanism between digital finance and ISU using the spatial Durbin model. The research results demonstrate that the digital finance development can significantly improve the local ISU. Interestingly, the impact of digital finance on the ISU of adjacent areas has a significantly negative spatial spillover effect, which still exists under the different spatial weight matrix. Digital finance can improve ISU by improving green technology innovation, upgrading industrial structure, and alleviating capital allocation. We also found that the higher degree of marketization and environmental regulation can increase the positive influences of digital finance on ISU. This research proves the effectiveness of the digital finance in improving energy efficiency, and it encourages policymakers around the world to rely on digital finance to promote ecological governance and achieve high-quality economic development.

The digital economy based on digital technology is an important force for high-quality economic growth and industrial transformation, and has great potential for value creation. Based on the data of 30 provinces in China from 2007 to 2017, this paper uses entropy method to calculate the industrial green transformation (IGT), and empirically analyzes the impact of Digital economy on IGT. The DE can significantly reduce IGT of local and neighboring areas after excluding the influence of macro system factors and replacing the spatial weight matrix. The DE can indirectly reduce the IGT by accelerating the accumulation of human capital, and green technology innovation. The impact of digital economy on IGT is a non-linear relationship. With the further improvement of environmental regulation, financial development and intellectual property protection, the role of digital economy in IGT is more obvious. To this end, it is necessary to speed up the construction and improvement of digital infrastructure, build an integrated layout of "digital infrastructure", give full play to the radiating role of the digital economy, and implement differentiated development paths based on regional comparative advantages.

With the intensification of the global ecological crisis, promoting green development has become a key path to achieve sustainable development. Based on the panel data of 30 provincial-level administrative regions in China from 2011 to 2022, this paper systematically examines the impact of scientific and technological talent agglomeration on regional green development and its mechanism of action. The study constructs a comprehensive evaluation index system of regional green development level, adopts location entropy to measure the degree of scientific and technological talent concentration, and empirically analyses it by using the fixed effect model, mediation effect model and moderating effect model. The study finds that (1) scientific and technological talent concentration has a significant promotion effect on green development, and this conclusion still holds after various robustness tests and endogeneity treatment; (2) from the perspective of regional heterogeneity, the green development effect of scientific and technological talent concentration is significant in the eastern region, while it is not significant in the central and western regions; from the perspective of period heterogeneity, the promotion effect of scientific and technological talent concentration is more significant after the introduction of ‘The Outline of National Innovation-Driven Development Strategy’; from the perspective of Internet development, the promotion effect is more significant; from the perspective of the heterogeneity of period, the promotion effect is more significant; from the perspective of heterogeneity of the level of Internet development, scientific and technological talent agglomeration shows a stronger promotion effect in regions with a lower level of Internet development; (3) the mechanism test shows that scientific and technological talent agglomeration can promote green development through two paths of enhancing the level of public environmental concern and promoting green technological innovation, and at the same time, the level of marketisation and the government's attention to scientific and technological talent can positively regulate this kind of promotion. Based on the conclusions of the study, this paper puts forward policy suggestions to systematically improve the level of regional scientific and technological talent concentration, and to give full play to the effects of external supervision and technological innovation.

Given the rapid development of live streaming commerce in China, this study focuses on the interactivity and sociability of live streaming shopping activities and explores online consumers’ real-time interaction intentions and trust-building behaviours with online merchants. To discover the real-time interaction between online consumers and online merchants, this study builds a research model based on the Theory of Planned Behaviour (TPB). Through the data analysis based on the partial least squares path modelling and variance-based structural equation modelling (PLS-SEM), the key findings state that, three factors, including attitude, subject norm, and perceived control, positively affect online consumers’ real-time interaction intentions and lead them to build trust with online merchants. Meanwhile, control variables, including gender, age, and educational background, demonstrate insignificant effects across the model. Unlike existing literature, the current study pays much attention to the interactive characteristics of live streaming shopping activities and can provide some valuable suggestions both for online consumers and online merchants, which can promote the co-development of the commercial and social aspects of live streaming platforms.

Cloud computing is one of the fastest growing domains of the IT industry, however, the growth rates for each of the models on a global and local (Russian) scale have not been generalized, despite the obvious value of such analysis. Modern business and industry in Russia is going through another period of instability and at the same time is forced to follow the trend of digitalization. That is why a balanced scientific analysis and forecast of the development of cloud technologies is needed, as the main factor in improving business efficiency. The purpose of the study: is to review the main models of cloud services for modern business and industry, describing their capabilities separately and the prospects for the market as a whole. The materials for the study were analytical reports of leading consulting companies and materials from specialized web-sites. Result: The article considers cloud technologies as the main global technological trend, describes popular models of cloud services, their opportunities for business and industry. Russian and global leaders in the provision of cloud services are also described, the growth rates of these markets for each of the models are indicated. The most popular and promising cloud service models in 2022 are: UCaaS, CaaS, SaaS, IaaS, RPAaaS, PaaS. The cloud technology market will show strong growth until 2030, generating both hybrid and absolutely new service models. The private business, industrial and public sectors will increasingly move to cloud services. The main trends in the development of cloud technologies until 2030 are: hybrid cloud, artificial intelligence (AI) and cloud computing, deployment of cloud services in the planetary orbit. The results obtained are very valuable for analysts and industry experts. The above trend analysis provides valuable predictive data to research economists, investors, business and industry leaders and other stakeholders on how the cloud services market will grow in the next 5-7 years. The results of the study also have a general theoretical nature, substantiating the importance of further forecasting the development of this market (especially using mathematical methods).

Improving energy conservation and emission reduction (ECER) efficiency is a virtuous cycle of economic development and environmental protection, promoting countries around the world towards sustainable development. As a strategic technology leading a new round of technological revolution and industrial transformation, the large-scale application of artificial intelligence (AI) is driving the transformation of manufacturing production methods, which is increasingly essential for improving the effectiveness of environmental governance. This study aims to analyze the impact of AI technology on ECER in the manufacturing industry, as well as the specific impact paths and heterogeneity. We contribute to previous literature by measuring ECER of Chinese manufacturing sector using the EBM model. The mediation effect model is used to analyze the impact mechanism between AI technology and ECER. The results indicate that AI promotes the ECER efficiency in the manufacturing sector. The positive effects are attributed to the development of energy consumption structure and technological innovation. The impact of AI on ECER exhibits an evident heterogeneous effect across industries with different pollution intensity, R&D intensity and labor intensity, and ownership dominant industry. Additionally, higher levels of environmental regulation lead to an increase in the positive effects of robot promotion on ECER. The research conclusions provide important reference for understanding the relationship between AI technology and ECER, and contribute a new way to promote environmental governance and carbon neutrality.

The claim that “there is no third way” besides the economic models of capitalism and communism has faced a challenge from a new and growing body of research into a “third way” economic paradigm known as democratic planning. In this paper, we explore one of these democratic planning models–Robin Hahnel and Michael Albert’s model of a participatory economy, focusing in particular on its allocation mechanism–a non-market, non-command-planning procedure known as “participatory planning.” This procedure has recently been implemented in computer programs to explore its feasibility, the encouraging results of which have been published elsewhere and which we summarize here. But I present here for the first time the detailed algorithms and related pseudocode powering all of these computer programs for others to consider, examine, and build as their own programs. I also describe future directions for this avenue of research.

The rapid evolution of information and communication technology (ICT) has resulted in significant transformations across a wide range of social and economic activities. As a result, the ongoing digitalization process is emerging as a critical force in determining progress and modernity. This study looks at the complex relationship between digitalization and economic growth in European Union (EU) countries from 2017 to 2022, using the Digital Economy and Society Index (DESI) issued by the European Commission. Our work employs a sophisticated panel data estimate approach and the fundamental Cobb-Douglas model and presents an empirical perspective on the relationship between digital technology and economic prosperity. Based on the fixed-effect panel estimate, our findings show a significant correlation: A 1% rise in digitalization (as measured by the DESI index) correlates with a 0.3838% impressive rise in GDP growth. This study emphasizes the need to comprehend and utilize digital technologies' revolutionary potential. It presents a solid argument for stakeholders and governments to embrace digital innovation and leverage it to achieve long-term, sustainable economic growth.

As governments worldwide grapple with the urgent need to mitigate climate change, understanding the nuanced relationship between fiscal targets and environmental innovation is crucial for crafting effective policy frameworks. Green technological advancement stands as the cornerstone of enterprise competitiveness, driving improvements in both economic prosperity and environmental sustainability. Government fiscal policies play a pivotal role in shaping the landscape of green transformation within enterprises, particularly through the establishment of fiscal revenue targets. Drawing upon data from prefecture-level cities and enterprise records, this study employs empirical analysis utilizing a fixed effects model and instrumental variable method. Our findings underscore the significant impact of fiscal revenue target setting on the trajectory of green technological advancement within enterprises. Specifically, the imposition of fiscal revenue growth targets exerts a dampening effect on the propensity for green technological advancement among enterprises. Notably, this disincentive is particularly pronounced among state-owned enterprises, as well as those with lower and moderate returns on capital, and those characterized by labor-intensive operations. Furthermore, our research delves into the underlying mechanisms of this inhibitory effect. We ascertain that the pressure associated with fiscal revenue growth targets hampers corporate green technological advancement by amplifying tax burdens and exacerbating financing constraints. In light of these findings, our study not only contributes to the theoretical understanding of the interplay between government fiscal policies and corporate innovation but also provides empirical evidence to inform strategies aimed at reconciling the imperative of fiscal revenue growth with the imperative of fostering green technological advancement within enterprises. In the broader context of governmental efforts to address climate change, this research underscores the importance of aligning fiscal policies with environmental objectives.

The knowledge-capital model explains outward foreign direct investment (FDI) of a country from its relative abundance of its knowledge assets. Early versions of the knowledge-capital theory model these assets as if they were only the results of knowledge investments by private firms. We extend the theory by a formal model of the public-private interaction in knowledge development. This sheds light on the role of the origin country of multinationals. The paper extracts four testable predictions from the model. We use the inter-country variation in national knowledge-creation systems and FDI performance to test the model using a new dataset; it holds knowledge-creation indicators for about 200 countries over the period 2000-2020. Based on a range of non-parametric tests, we can corroborate that the basic tenet of the knowledge-capital model is correct. Moreover, the results show the important role of public knowledge production for outward FDI.

Even though policy coordination is one of the oldest challenges that governments have to confront, as problems evolve and "New Public Management" concepts emerge, it has become even more essential. The current literature on policy coordination among government agencies, however, shows little regarding the way coordination is managed under centralized political systems. This study, based on the science and technology (S&T) policy documents issued by China's central government agencies between 1978 and 2020, provides a quantitative and dynamic analysis of the coordination of policies in China and presents a comprehensive overview of policy coordination paths and processes in centralized political systems. As a result, it provides a way that contributes to the analytical methods available for quantitatively analyzing policy documents. On the other hand, the key findings of the study show that, first, state council-administered ministries have taken the lead in coordinating policy while other types of organizations have collaborated in more subordinate capacities. Second, national themes that are democratic and driven by demand have been the core concern of coordination activities, such as social development, high-tech industrialization, and rural S&T. Third, policy coordination has evolved continuously and has mostly contributed to interpreting macrostrategies and implementing more specific implementation measures.

This paper explores the transformative journey from traditional e-commerce to the emerging realm of virtual commerce (v-commerce) within the metaverse, a collective virtual shared space created by the convergence of virtually enhanced physical reality and physically persistent virtual reality. The metaverse, with its immersive and interactive capabilities, is reshaping the landscape of economic activities, creating a paradigm shift in the way consumers shop, sell, and buy goods and services. The study delves into the impact of virtual reality (VR) technologies on consumer behavior, business models, and the overall economy. It investigates how VR is revolutionizing the shopping experience by offering immersive, personalized, and interactive platforms, thereby influencing con-sumer decision-making processes. The paper further examines the implications of these changes for businesses, particularly in terms of strategy, operations, and customer engagement. Moreover, the paper discusses the challenges and opportunities presented by the metaverse economy, including issues related to privacy, security, digital divide, and regulatory frameworks. It also highlights the potential of v-commerce to drive economic growth, innovation, and sustainability in the digital age. The paper concludes with a discussion on the future directions of v-commerce and the potential strategies for businesses to thrive in this new economic landscape.

We offer an extensive analysis of the significance of information within the realm of Gaussian quadratic economies. We build upon the seminal papers of Morris and Shin (2002, 2007) and consider a signal game of incomplete information. Particularly, we question the suitability of partial transparency portrayed by fragmented information in addition to the private signal in terms of welfare effects. We can summarize our findings in two main points. First, fragmented information, in conjunction with a private signal, can reduce the reliance on public signals. Second, a conflicting effect arises between increasing full disclosure and increasing the precision of fragmented (semi-public) information when examining different complex scenarios, involving for example endogenous private information or imperfect correlated signals. For a critical threshold, an optimal communication strategy designed by fragmented information should be implemented whenever that kind of information is acquired at a high precision.

In the context of the continuous deepening reform of the foreign investment negative list system and the increasing pressure on financial risk prevention and resolution, it is of great significance to study the impact of the foreign investment negative list system on banking risks. This study is conducted on the basis of systematically sorting out the mechanism of the foreign negative list system affecting the risks of domestic banks. Based on the panel data of 27 provinces (cities, districts) in China from 2006 to 2016, and comprehensively adopting the synthetic control method, the difference-in-difference (DID) model, mediating effect model, and other methods, this article systematically examines the impact of the foreign negative list system on Shanghai banking risks. The study found that the implementation of the foreign investment negative list system has significantly reduced the credit risk of the Shanghai banking industry, and this reduction effect has gradually strengthened over time. Additionally, the implementation of the foreign investment negative list system will also significantly reduce the liquidity risk of the Shanghai banking industry; However, the effect of this positive influence is short-lived and subsequently weakens. The analysis of the mechanism of action indicates that the foreign investment negative list system primarily reduces the risk of Shanghai's banking industry by stimulating the inflow of foreign capital and reducing government intervention. However, the effect of improving the level of the rule of law to mitigate commercial bank risk is not apparent. Regarding other influencing factors, the growth of local government financial resources and the increase in new loans have significantly reduced banking risks, while the rise in residents' leverage has substantially increased the level of banking risks.