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).

The use of cloud computing by firms can be expected to go hand in hand with higher productivity, more innovations, and lower costs, and, therefore, should be positively related to export activities. Empirical evidence on the link between cloud computing and exports, however, is missing. This paper uses firm level data for manufacturing enterprises from the 27 member countries of the European Union taken from the Flash Eurobarometer 486 survey conducted in February – May 2020 to investigate this link. Applying standard parametric econometric models and a new machine-learning estimator, Kernel-Regularized Least Squares (KRLS), we find that firms which use cloud computing do more often export, do more often export to various destinations all over the world, and do export to more different destinations. The estimated cloud computing premium for extensive margins of exports is statistically highly significant after controlling for firm size, firm age, patents, and country. Furthermore, the size of this premium can be considered to be large. Extensive margins of exports and the use of cloud computing are positively related.

This research focuses on the digital transformation of retail banking in New Zealand, focusing on the challenges and opportunities elderly customers face. The banking industry is undergoing unprecedented change as technology evolves and customer needs change. However, elderly customers face physical and security challenges associated with digital transformation and lower acceptance of new technologies. This paper analyses the characteristics and needs of elderly customers, investigates the different needs of elderly and young customers, and recommends relevant solutions and suggestions. This investigation is based on secondary data, and recently published articles from various sources were used to collect information. In the wave of digital transformation, banks not only need to strive to provide convenient, safe, and high-quality services, but also need to innovate continuously to meet the needs of all customers and enhance their trust and satisfaction. This report provides exclusive digital service suggestions and solutions to help banks better meet the needs of elderly customers.

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.

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.

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.

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.

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 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.

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.

The Hospital Price Transparency Final Rule aims at reducing the cost of healthcare in the United States by making information about the prices of medical services more readily available to market participants. The economic rationale is that higher price transparency should reduce the level and the dispersion of prices by disincentivizing hospitals from charging higher prices than possible. Using data on 3789 prices for three diagnostic imaging procedures and on the compliance with the rule for 86 acute care hospitals in the Greater Los Angeles area, we test the hypothesis that price levels and price dispersion are lower among hospitals that are more compliant. We do not reject this hypothesis, although we do not observe strictly decreasing relationships in all analyses. Prices are lower at hospitals with high or medium compliance than at hospitals with low compliance, but there is not a clear difference between hospitals with high and hospitals with medium compliance. Prices are less dispersed among hospitals with high compliance than among hospitals with low compliance, but the evidence for hospitals with medium compliance is less clear. We conclude that high compliance with the Hospital Price Transparency Final Rule implies lower prices and less price dispersion among hospitals.

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 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.

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.

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 integration of artificial intelligence (AI) in video game design has transformed traditional workflows, allowing for the generation of text, images, music, videos, and code at unprecedented scales. However, this advancement presents complex challenges for copyright law, traditionally rooted in human originality and authorship. This article examines recent case law that underscores the evolving legal landscape, exploring landmark cases such as Zarya of the Dawn and Andersen v. Stability AI. These cases reveal the tensions between AI-generated outputs and copyright eligibility, especially in the dynamic, multimodal compositions inherent to video games. The review analyzes how various AI tools are employed across the stages of game development—from design documentation to character modeling, soundtrack composition, and cinematic sequences—and the legal uncertainties surrounding each. Emphasis is placed on the role of human input in determining copyright eligibility, proposing that human-AI co-creation models and enhanced metadata standards may offer pathways to reconcile AI-driven innovation with intellectual property protections. As video games exemplify the unique challenges in AI-generated, temporally interactive works, this study calls for a nuanced copyright framework that acknowledges both technological capabilities and the irreplaceable contribution of human creativity. The findings advocate for policy adaptations that align legal protections with the realities of AI-integrated creative processes, ensuring a balanced approach that supports both innovation and creator rights.

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.

We generalize the 3-player game introduced by Mêgnigbêto (2018) to analyze the synergies existing between universities, the industry and the government in the Triple Helix, a model of research and innovation introduced by Leydesdorff and Etzkowitz (1995). We consider situations involving any number of actors and we allow for a differentiation of their contributions. The resulting game has nonnegative Harsanyi dividends, implying its convexity. The relative size of the core measures the extent of the synergies and the Shapley value measures the contribution of each actor to these synergies. Incidentally, the resulting game lends itself to a wide range of applications.

Understanding how academia and industry operate and relate to each other is core to improving the efficiency of the entrepreneurial ecosystem. Reason why, this paper focuses on whether university prestige has a homogeneous effect on university entrepreneurship. Specifically, whether the relationship between academic prestige and entrepreneurship varies according to the nature of the firm, digital or not, or according to the size of the entrepreneurial partner. To answer this question, this paper uses a negative binomial regression model with panel data with respect to the number of intellectual property (IP) licences granted by the university, using mainly data from the Higher Education Statistics Agency. The results suggest that although university prestige affects the number of IP licences granted, its effect ceases to be significant when the nature of the licences is digital. Moreover, we cannot claim that the influence of prestige is greater when the licencee is a small company.

Based on the results of a simple Agent Based Model (ABM) six common and widely affirmed statements in financial economics are discussed: (1) The better an investor is informed, the higher his performance is expected to be, (2) There is a well-defined state of art how to make sound financial decisions, (3) High standards of public information create private as well as public value, (4) Highly skilled financial analysts usually decide better than their lousy colleagues, (5) The market loses informational efficiency if traders abstain from information, (6) To use Bayes’ updating rule means to make rational financial decisions. Financial markets are complex adaptive systems, in order to understand them, the interaction of autonomous agents has to be brought into the focus. As the ABM methodology allows to do this better than neoclassical methods, this simple technique is adopted and allows to evidence that all these beliefs, even if they may be deeply rooted in the profession, are probably false.