When human civilization is thriving to the rapid economic and social development, the deteriorating ecological environment has also pressured the society to put environmental protection issues on the agenda future development. Therefore, green innovation is not merely a requirement for a corporate’s long-term development but the basics of sustainable development of human society. As an objective indicator to measure a company's commitment to social responsibility, corporate environmental responsibility has an extremely important impact on a corporate's business philosophy and innovation strategy. However, the existing literature rarely studies between these two variables. This paper collects the data of listed companies from 2010 to 2019 and empirically tests the impact of corporate environmental responsibility on corporate green innovation. The study finds that corporate environmental responsibility can promote green innovation by reducing financing constraints, improving corporate governance and increasing government subsidies and R&D investment, and the result is still significant under a series of robustness checks. The placebo test suggests that the Jiangsu enterprise responsibility construction pilot has facilitated the development of enterprises' green innovation to a great extent. The conclusions enrich existing literature on corporate environmental responsibility and corporate green innovation, providing implications for government policy orientation, social atmosphere guidance and corporate strategic decision-making process.

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.

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.

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.

With the strengthening of China's economic power and the further implementation of China's open-door policy, China's outward investment has increased year by year. Some international comments are only concerned about the former and there are some public opinions about China's outward investment threatening the host country's environmental quality. This paper takes the carbon emissions of 49 countries along the “Belt and Road” and the acceptance of China's outward FDI as samples, studies the impact of China's outward FDI on the carbon emissions of the relevant countries, and comes to the conclusion that: China's outward FDI is a major factor in China's economic development. It is concluded that China's OFDI increases the total carbon emissions of the countries along the Belt and Road while decreasing the carbon intensity, and the impact is carried out through the three major paths of economic scale, technological level and structural effect.

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 objective of this research is to investigate, using time series data ranging from 1992 to 2021, the effects of information and communication technologies (ICTs) and foreign direct investment (FDI) on economic growth (GDP) in India. The stationarity of the data was examined by employing unit root tests, and an autoregressive distributed lag (ARDL) technique was used to investigate the link between the factors, taking both the long- and the short-run into consideration. According to the findings, an increase of one percent in both ICT and FDI will result in an increase of 0.56% and 0.71% in GDP over the long term, in addition to an increase of 0.11% and 0.29% over the short term. The findings of the investigation are of particular significance to policymakers because they can be utilized to establish sensible policymaking for long-term economic success, in addition to advancing the ICT sector and boosting FDI.

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.

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.

The digital economy has emerged as a crucial driving force for promoting China’s green transformation in the new development phase. The “Broadband China” initiative, a key policy aimed at fostering the digital economy, plays a significant role in enhancing green total factor productivity (GTFP). This paper, based on the "Broadband China" policy and panel data from 283 prefecture-level cities from 2009 to 2022, constructs a theoretical model and employs a multi-period difference-in-differences (DID) method to systematically analyze the impact of digital infrastructure development on urban green total factor productivity (GTFP) and its underlying mechanisms. The findings reveal that the “Broadband China” policy has significantly improved GTFP in pilot cities, with stronger effects observed in economically developed regions and large- to medium-sized cities. Mechanism analysis indicates that technological innovation, industrial structure optimization, and energy conservation and emission reduction are the main pathways through which digital infrastructure promotes the improvement of green total factor productivity (GTFP). The regional heterogeneity analysis reveals that policy effects are more significant in eastern regions and large or medium-sized cities, whereas the effects are relatively weaker in central and western regions and smaller cities. Robustness checks further validate the reliability of the research conclusions. Additionally, this study reveals the critical role of digital infrastructure development in enhancing green total factor productivity and promoting high-quality economic development from both theoretical and empirical perspectives. It provides valuable insights for optimizing digital infrastructure investment strategies and formulating regional development policies.

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.

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.

The dynamic patterns of technology adoption among firms clustered by size are investigated to assess the implications arising from the digital divide. Using data from the “Survey on the Use of Information and Communication Technologies in Enterprises (IUTICE)" dataset for 2003-2022, provided by the Portuguese Institute of Statistics, the research centers on three key variables – internet connectivity, website presence, and computer usage – which are examined across a spectrum of firms’ scales, shedding light on the evolving trends in technology adoption. Employing a combination of descriptive statistical analysis, trend assessment, and cross-sectional comparisons, this research shows noteworthy insights. Interestingly, the adoption rates for all three technology variables exhibit a consistent upward trajectory, indicative of a movement towards digitalization within the business landscape. Smaller firms have demonstrated notable strides, manifesting a reduction in the technology adoption disparity relative to their larger counterparts. The findings underscore the influential roles played by resource constraints and digital competencies in shaping technology adoption trajectories, and their correspondence with the Resource-Based View (RBV) framework underscores the role of organizational resources and capabilities on the digital divide. The ramifications extend beyond individual firms, resonating with the global scholarly discourse and advocating for equitable integration of technology. As firms, irrespective of size, grapple with the challenges posed by the digital era, this study provides deep insights that can guide the formulation of strategies aimed at cultivating an inclusive and technologically empowered business environment.

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.

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.

Based on the provincial panel data of China from 2011 to 2019 for a total of 9 years, this paper uses the entropy method to construct a comprehensive measure of the digital economy and common prosperity. We theoretically analyzed the impact mechanism of the digital economy on common prosperity using the econometric model. The study found that the digital economy can significantly promote the realization of common prosperity. The digital economy has a significant impact on the development and sustainability of common prosperity. The results of the impact mechanism show that the digital economy promotes common prosperity by increasing entrepreneurial activity. Heterogeneity research shows that the role of digital economy in promoting common prosperity changes with different regions. Specifically, the digital economy in the central and western regions can significantly promote the realization of common prosperity, but this impact is not significant in the eastern region. From the regression results of the digital economy, we can see that industrial digitalization and digital infrastructure play a greater role in promoting common prosperity. Economic openness affects the promotion of digital economy to common prosperity. The conclusion of this work provides an important research reference for the development of digital economy and the realization of common prosperity.

This study analyzed whether the level of corporate governance of companies listed on the Brazilian capital market is related to the investment decisions of Brazilian pension funds. We start from the assumption that the corporate governance system mitigates the moral risk, that may arise in the relationship between corporate managers and investors and respective shareholders, Brazilian pension funds. Shareholding dispersion would enable opportunism for corporate managers, making decisions focused on their interests to the detriment of shareholders or investors. The governance system would signal that this behavior would be controlled, signaling safer behavior for investors. Thus, the hypothesis is that the level of corporate governance would attract pension funds that would understand this system as reducing investment risk. To test this, we used panel data, with a sample of 1,582 observations of companies listed on the Brazilian Stock Exchange (B3) from 2010 to 2017. The statistical results show that corporate governance positively correlates with investment in pension funds. This leads to the conclusion that, for Brazilian pension funds, companies' signaling about their corporate governance practices is a risk-mitigating factor. Furthermore, these results allow us to infer that the company's governance level associated with leverage is a differentiating signaling element as the evidence points to a positive relationship.

The digital transformation provides an opportunity for the development of a green and low-carbon economy. This study used panel data collected from 30 Chinese provinces between 2011 and 2018, and assessed the impact of digitization (Dig) on environmental efficiency (EE). Quantile regression is employed to scrutinize the evolution of the marginal effect. From the perspectives of population and institutional factors, this study empirically investigates nonlinear relationships and potential mechanisms using Hansen threshold and mediation models. The findings reveal several key insights. Overall, levels of digitization and environmental efficiency (EE) are increasing with regional dispersion expansion, indicating a “polarization” characteristic. The impact of digitization on EE exhibits noticeable stage and regional heterogeneity. Analysis of population factors reveals that population structure, population size, and human capital trigger a sharp “marginal increase” of positive effects with single thresholds of 0.8155, 7.2284, and 11.0497, respectively. Analysis of institutional factors highlights the significance of fiscal policy quality (tax proportion), education expenditure, and tax system structure as important intermediaries. Finally, this paper presents corresponding policy implications.

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.

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.