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In the digital context, using data and digital technology to realize value creation has become an important decision-making issue faced by platform service supply chain (PSSC) members. In this study, we build a PSSC structure that includes service providers (SPs), platform operators (POs) and demand markets (DMs). To realize value creation, SPs and POs improve service quality and carry out collaborative innovation through data and digital technology. Therefore, based on the mutual transformation relationship between variational inequality and the optimization problem, we construct a PSSC network equilibrium model and obtain the conditions for the network to be in the optimal state. Through five numerical examples, we analyze the influence of factors such as service quality improvement level cost coefficient, service innovation ability, and digital application level on the equilibrium state of the PSSC network. Our study finds that under digital empowerment, the high cost of service quality improvement is not only a difficult challenge for SPs and POs, but also hinders DMs from accessing high-quality and low-cost services. We also observe that a high service innovation capability is conducive to the value creation of PSSC members. This is not only a cost saving for PSSC members themselves but also has a “spillover effect” on their partners. Further, for SPs, the improvement of the digital application level does not achieve the expected revenue growth in the early stage, and POs may have “free riding” behavior in digital investment. Against the backdrop of digitalization, these findings provide new insights into PSSC’s service quality improvement and collaborative innovation activities. [ABSTRACT FROM AUTHOR]

Green credit policy is a policy enacted by the government to induce enterprises to balance environmental management and green economic development, but how green credit policy affects the green productivity of enterprises in practical situations is a topic worth exploring. This paper uses a double difference model to investigate the impact of green credit policies on green productivity of corporate from 2007 to 2020. It is found that the implementation of the Green Credit Guidelines can significantly improve the green production efficiency of heavy polluting enterprises. The implementation of the Green Credit Guidelines has a greater effect on the green production efficiency of enterprises among enterprises with smaller commercial credit financing scale and enterprises with lower capital use efficiency than other enterprises. The impact of the Green Credit Guidelines on state-owned enterprises, large-scale enterprises, and enterprises in the central and western regions is more obvious. And the implementation of the Green Credit Guidelines can affect the green production efficiency of enterprises through the financing scale effect and financing cost effect. This study provides insights for the government to further standardize the green credit system and ensure the effectiveness of green credit policy implementation, and provides ideas to promote green development of enterprises by analyzing the influencing factors of their green production efficiency. • Demonstrate the impact of green credit policies on the efficiency of green production of enterprises. • The scale of commercial credit and the efficiency of capital use play a regulating role. • The financing scale effect and financing cost effect are channels. • The nature, scale and spatial-regional differences in the location of enterprises determine this linkage. [ABSTRACT FROM AUTHOR]

Using a quasi-natural experiment and city-level panel data from 2009 to 2018 in China, this paper investigates the impact of broadband infrastructure on green total-factor energy efficiency. Empirical results show that Broadband China Strategy has improved the green total-factor energy efficiency by an average of 2.61%, and the improvement effect is only found in central and western as well as small and medium-sized cities. Broadband infrastructure can promote trade openness and improve green total-factor energy efficiency in cities with higher initial trade costs and those with lower initial trade openness. Besides, broadband infrastructure promotes green total-factor energy efficiency through technology diffusion rather than innovation. • Investigate the impact of broadband infrastructure on green total-factor energy efficiency (GTFEE). • The policy intervention of Broadband China has improved the GTFEE by an average of 2.61%. • The reduction effect is only found in central and western as well as small and medium-sized cities. • Broadband infrastructure can promote trade openness and improve GTFEE in cities with higher initial trade costs. • Broadband infrastructure promotes GTFEE through technology diffusion rather than innovation. [ABSTRACT FROM AUTHOR]

This research focuses on the direct and indirect systemic risk spillovers among East Asian, European, and U.S. stock markets under the COVID-19 pandemic. Based on the GARCH-Copula-CoVaR model, we construct the direct spillover matrix of systemic risk and further explore the indirect spillover path through R-vine. The empirical results first show via the direct path that Hong Kong exhibited the largest change in value of risk after the pandemic erupted. Second, the indirect path is that European and U.S. stock market risks are transmitted to China domestically via Hong Kong and Japan. The key nodes provide reference for risk prevention. • Focus on the direct and indirect systemic risk spillovers under the COVID-19 pandemic. • We construct the direct spillover matrix of systemic risk and further explore the indirect spillover path through R-vine. • Results first show in the direct path that Hong Kong exhibited the largest change value of risk after the pandemic erupted. • The indirect path is that European and U.S. stock market risks are transmitted to China domestically via Hong Kong and Japan. [ABSTRACT FROM AUTHOR]

While the use of industrial robots (UIR) promotes economic growth, it inevitably also has an impact on the ecological environment. This research explores the relationship between UIR and ecological footprint based on data of 72 countries from 1993 to 2019. First, whether based on overall or sub-industry data we confirm that UIR reduces the ecological footprint. After considering a series of robustness tests such as sample self-selection bias and endogeneity, this conclusion still holds. Second, the mediation effect model shows that UIR reduces the ecological footprint through the time saving effect, green employment effect, and energy upgrading effect and increases the ecological footprint through the industry driving effect, and that the impact of UIR's reduction of the ecological footprint is dominant. Third, the moderating effect model shows that as the levels of economic development and human capital increase, UIR can more effectively reduce the ecological footprint. Fourth, in OECD countries and at a high quantile of the ecological footprint, the effect of UIR on reducing the ecological footprint is more obvious. This paper presents a new perspective for UIR to achieve economic development and ecological protection at the same time. Governments of various countries should actively seize the opportunity to develop industrial robots, continue to increase human capital investment, and accelerate the upgrade of energy sectors. • Exploring the impact of the use of industrial robots (UIR) on the ecological footprint and the internal mechanisms. • In general, UIR could reduce the ecological footprint, whether based on overall or sub-industry data. • UIR reduces the ecological footprint through time saving effect, green employment effect, and energy upgrading effect. • UIR increases the ecological footprint through industry driving effect. • As the levels of economic development and human capital increase, UIR can more effectively reduce the ecological footprint. [ABSTRACT FROM AUTHOR]

With the digital transformation of the economy and society, high-speed Internet is becoming an important supporting infrastructure for international trade activities. This study treats the pilot policy of the Broadband China strategy as a quasi-natural experiment and investigates the ways in which broadband infrastructure development affects export trade in Chinese cities. Empirical results show that export trade in the pilot cities increases by 6.82%–18.8% on average as a result of the Broadband China policy intervention. Our study shows that this policy can effectively promote the use of Internet facilities, and broadband infrastructure can significantly promote the growth of a city's export trade. Broadband infrastructure influences export trade through the direct channel of improving information efficiency, which in turn lowers logistics costs, promotes trade efficiency, and reduces barriers to trade. There is no significant regional heterogeneity and urban characteristics heterogeneity in the export trade effect. Although broadband infrastructure can affect exports through the indirect channels of industrial structure and technological innovation, the direct effect accounts for much of the total effect. • This study treats the pilot policy of the Broadband China strategy as a quasi-natural experiment. • The policy of Broadband China can effectively promote the use of Internet facilities. • Export trade in the pilot cities increases by 6.82%–18.8% due to the policy intervention of Broadband China. • Broadband infrastructure influences export trade through the direct channel of improving information efficiency. • Broadband infrastructure can affect exports through the indirect channels of industrial structure and innovation. [ABSTRACT FROM AUTHOR]

Green technologies are key factors in mitigating climate change and reducing carbon emissions, but, compared to other technologies, they are more complex and require close cooperation between countries. This research applies social network analysis and a quadratic assignment procedure (QAP) to explore the structural characteristics and determinants of a global green technological collaboration network from 2000 to 2018, based on 456,945 patents. The results show that the number of countries involved in green technology cooperation is rapidly growing; however, the cooperative network is far from complete or regular and presents obvious core–periphery structural features. The United States and Canada, Germany and France, and China and Japan are, respectively, at the center of the Americas, Europe, and Asia. Block model results indicate that the pattern of global green technological cooperation centers on core countries and is led by core countries and strong semi-peripheral countries. QAP regression analysis shows that economic proximity, technological proximity, social proximity, and strict environment regulations are key factors that promote international green technological collaboration. The determinants of green technology cooperation within each continent are also heterogeneous. Lastly, policy recommendations are provided based on the results. [Display omitted] • Green transition requires worldwide innovation network to develop and deploy green technologies. • A global green technological collaboration network (GTCN) is constructed based on social network analysis method. • The GTCN has a clear core-periphery structure, and traditional technology powerhouses have occupied central position. • Economic proximity, technological proximity, and environment policy are key factors that promote the development of GTCN. • Determinants of green technology cooperation on Asia, Americas, and Europe are heterogeneous. [ABSTRACT FROM AUTHOR]

Since the Belt and Road Initiative (BRI) has increased the economic growth of many developing countries in Asia, more attention should be paid to carbon dioxide (CO2) emissions in these regions. Based on the Tapio decoupling model and Kaya-LMDI model, this paper investigates the spatiotemporal evolution of decoupling and driving factors of CO2 emissions of 57 BRI countries from 1991 to 2016. The results are as follows. First, the decoupling statuses of higher income countries are generally better than lower income countries. Second, Northeast Asia, South Asia, and West Asia accounted for 68.5%, 16.8%, and 13.3% of CO2 emission increases in BRI countries from 1991 to 2016. Third, almost all countries' CO2 emissions significantly rise due to economic growth, while energy intensity reduces CO2 emissions to some extent. Energy exports increase CO2 emissions to varying degrees in Asia countries, but their impact has gradually fallen. Except for Europe, the population size effect increases CO2 emissions, especially in West Asia. China, India, Russia, and five OPEC countries show similar characteristics with the above regions. • The Tapio decoupling model is applied to analyze the CO 2 decoupling of 57 Belt and Road Initiative countries. • Five driving forces of CO 2 emissions are identified via the Kaya-LMDI model. • Spatiotemporal characteristics of decoupling and driving forces are highlighted. [ABSTRACT FROM AUTHOR]

Achieving economic development and ecological protection simultaneously is an inevitable selection for sustainable development in today's world, so it is crucial to improve eco-efficiency (EE). According to Chinese panel data at the provincial level between 2010 and 2020, this research explores the nexus between green finance (GF) and EE. The results denote that GF can significantly improve EE, and the higher the level of EE, the stronger the effect of improvement. The upgrading of industrial structure, optimization of energy structure, enterprises' concern for environmental protection and the public's attention to the environment are all favorable factors that can enhance the promotion effect of GF on EE. Additionally, this facilitation can only be played under a good external environment and mature internal conditions. Our findings can provide new insights for improving EE by developing GF., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Food security is a vital material foundation for a nation's development and has been a topic of significant concern on the international stage in recent years. With a population exceeding 1.4 billion, China is not only a major producer but also a substantial consumer of food. Ensuring food security in China is not only a top priority for its socio-economic development but also a driving force in maintaining the stability of the global food supply chain and reducing the number of hungry people worldwide. However, a lack of comprehensive research into the Chinese food security system remains. This study addresses this gap by constructing a comprehensive evaluation framework encompassing four dimensions: food supply, accessibility, production stability, and sustainability. Utilizing the Moran's Index and generating LISA (Local Indicators of Spatial Association) maps, we analyze the spatial correlations of food security. The Dagum Gini coefficient and kernel density estimation are applied to assess heterogeneity and spatial disparities. Furthermore, this research employs the Exponential Smoothing (ETS) model to forecast food security trends. The findings reveal that the overall composite food security score exhibited fluctuations, initially increasing and reaching its peak of 0.407 in 2003, followed by a subsequent sharp decline after 2019. Spatially, food security exhibits correlations, with the Huang-Huai-Hai Plain and Northeast regions consistently showing high-high clustering. In contrast, the Western and Southern regions exhibit low-low clustering at specific periods. The Dagum Gini coefficient indicates that overall food security disparities are relatively small. However, these disparities have gradually expanded in recent years, with inter-group differences becoming predominant after 2005. As indicated by the kernel density estimation, the dynamic distribution of food security initially widens and then narrows, suggesting a shift from dispersed to concentrated data distribution. This phenomenon is accompanied by polarization and convergence trends, particularly evident after 2015. According to the ETS model, the study forecasts a substantial risk of declining food security in China over the next decade, largely influenced by the ongoing pandemic. In conclusion, this research provides a comprehensive assessment of the changing status of food security in China. It offers early warnings through predictive analysis, addressing the existing research gaps in the field of food security., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Carbon emissions are a critical concern in the realm of energy consumption, with many nations committed to curbing them and striving for carbon neutrality. This research addresses a specific gap in the literature by focusing on carbon emission reduction in the industrial sector through the application of supply chain management (SCM) principles under a monopolistic competition context and by utilizing carbon neutral indicators. Specifically, we develop a mathematical model integrated into an agent-based simulation framework and employ experimental design methods to determine the most optimal decision-making processes for incorporating supply chain carbon neutral indicators. Our findings highlight the effectiveness of two specific carbon neutral indicators within SCM: green-credit policies and the promotion of green products. These measures contribute significantly toward reducing global carbon emissions. This paper offers insights for government decision-makers regarding ideal implementation levels and strategies for green credit policies and the promotion of green products within supply chain environments. It also provides guidance to manufacturers on how to achieve profit maximization while progressing towards carbon neutrality., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Green bonds are adopted to exclusively finance or refinance green projects and thus is an important policy instrument for sustainable development. The development of these eco-friendly projects benefits the reduction of carbon emission. What impacts do green bonds have on carbon emission intensity and how? This issue needs to be revealed, including the dynamic spatial interactive rules and regional heterogeneity. This is especially true for China, with its vast territory and a short history of green bonds. Different with existing literature, this paper collects the data of the amount of green bond issued in each province in China rather than the policy dummy variable of green bond. The spatio-temporal interactions of both the impact of green bonds and the related mechanisms are studied. A dynamic spatial Durbin model (DSDM) combined with a STIRPAT (Stochastic Impacts by Regression on Population, Affluence and Technology) model reveals the negative impacts of green bonds on carbon emissions and the spatio-temporal interactions. On this basis, the mediation model is introduced to clarify the three impact mechanisms of green bonds and find the predominant role of technology mechanism. In addition, different characteristics in spatial interactive rules and impact mechanisms of green bonds are found in various regions of China. Finally, the study proposes some policy recommendations on how to effectively reduce carbon emissions with green bonds., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Research studies have recently diverted attention towards the determinant of ecological footprints, but related issues have not provided consistent results. Based on the IPAT model (environmental impact (I) is decomposed into three elements: population (P), affluence (A, economic growth), and technology level (T)), this paper empirically explores the validity of the green information and communication technology (GICT)-induced environmental Kuznets curve (EKC) hypothesis. The research applies a quantile regression (QR) that tests over 95 countries' panel data for the period 2000-2017 by using six types of ecological footprint (EF) as environmental degradation indicators and environmental regulations (ERs) as interaction variables. We confirm the vital role that GICT plays in lessening cropland, forest area, and grazing land, while increasing its impact on built-up land. Additionally, the findings partially support the existence of an inverted U-shaped GICT-induced environmental EKC hypothesis for a decreasing impact on cropland, forest area, and grazing land via consideration of non-market-based ER as the interaction term. GICT does not notably reduce carbon-absorption land usage; however, improvements of GICT and non-market-based ER in those nations have been accompanied by lower environmental degradation., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The study investigates the asymmetric effect of temperature, exchange rate, metals (rare metals and electrical conductors), and investor sentiments on solar stock price performance in China. The novel econometric techniques, i.e., QARDL (quantile autoregressive distributive lag) approach and Granger causality-in-quantiles to analyze the results. In both short- and long-run estimations, the findings suggest that rare metals (cadmium, germanium, indium, and selenium) and electrical conductors (silver, aluminum, and copper) have significant and positive linkage with solar energy stocks at different quantiles based on bullish, bearish, and normal market conditions. On the other hand, negative effects are found for temperature, RMB exchange rate, and investor sentiments in both the short- and long-run. In the short run, the effect of exchange rate varies across different quantiles but it confines to only lower quantiles (bearish market condition) in the longer run. Solar stocks are more prone to investor sentiments under higher quantiles (bullish market conditions). Lastly, we find that temperature is not merely a behavioral anomaly for the solar energy market as it spreads across middle quantiles (normal market conditions) in the longer run. The findings of Granger causality in quantiles further confirm the results of QARDL., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Using data from World Development Indicators (WDI), this research constructs panel data of 99 countries from 1996 to 2018 and employs a spatial econometric model to analyze the impact of air quality on international tourism arrivals. Evidence shows that Moran's I values are significantly positive, indicating a strong positive spatial dependence in each country and that poor air quality does have a negative impact on the number of tourist arrivals. The results of grouped data illustrate that middle-income countries, low-income countries, high concentrations of PM 2.5 , and countries with less numbers of tourists have negative effects on tourist arrivals in neighboring countries. The contrary groups, however, have positive effects on tourist arrivals - that is, the influence of air quality on the number of tourist arrivals exhibits heterogeneity. In addition, tests of the interaction term show that countries with higher R&D intensity have better air quality and thus attract more tourists. Therefore, countries with poor air quality should improve the environment through international cooperation and undertake technology transfer, thus ultimately increasing the number of tourists., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

As carbon emissions are one of the major problems of an emission-generating firm (EGF), there is a dire need to reduce them, and so this study fills this gap in the literature by considering the optimal behavior of environmental policies. This research develops policy measures under a duopoly game model such as carbon emission tax (CET) and subsidy on green investment (SGI). Additionally, we formulate a simulation model to measure the optimal behavior of CET, SGI, and production quantity to maximize profit and carbon emission reduction. The findings indicate that when green investment decreases, the EGFs are better able to pay CET and the government is also capable of providing SGI. Moreover, a lower unit production cost reduces more carbon emissions versus a higher unit production cost. In this way, the government receives revenue due to CET implementation and an EGF obtains revenue due to SGI. Both parties gain benefits at the same time and play important roles in cutting carbon emissions to make the environment clean. This study helps governments in finding their own optimal CET and SGI. An optimal SGI assists decision-makers at reducing carbon emissions and targeting profit maximization., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This research explores the effects of income inequality and country risk on CO 2 emissions and examines whether the effects change across countries with different development stages or income levels. A new panel quantile regression approach is used to conduct a comprehensive analysis of the impacts of affecting factors on CO 2 emissions at various quantiles, while addressing econometric challenges such as endogeneity and heterogeneity. From a global perspective, we can conclude that the marginal impact of inequality on emissions drops constantly with decreasing country risk at 10th to 50th quantiles, which even performs negative, whereas at the other quantiles, the marginal impact of inequality always remains negative. When we focus on the different income groups, the nexus of inequality emissions is negative first and then positive with decrease of country risk in low-income countries but shows no significant in low-middle- and upper-middle-income countries. Additionally, we validate the detrimental impact of income inequality in upper-income countries. Besides, country risk adversely moderates the nexus of inequality and emissions in low- and upper-income countries. Empirical results confirm that the nexus of inequality emissions lies in country risk, income level, and existing emission degree. These findings provide some important recommendations for policy-makers., (© 2020. Springer-Verlag GmbH Germany, part of Springer Nature.)

Using a monthly panel data of 13 Chinese provinces (cities) over the period from December 2019 to August 2020, this research investigates the impact of COVID-19 on the freight transport. We find that COVID-19 has a positive impact on the road freight transport turnover. This effect is pronounced under the higher numbers of COVID-19 confirmed cases and the lower level of gasoline production, and vice versa. In brief,•This study finds that COVID-19 has a positive impact on the road freight transport turnover.•This effect is pronounced under the higher numbers of COVID-19 confirmed cases and the lower level of gasoline production, and vice versa., (© 2020 The Authors. Published by Elsevier B.V.)