China's robust renewable energy sector expansion has spurred academic inquiry into the underlying driving forces. Recent studies have highlighted the correlation between the growth of renewable energy and project financing and the pivotal role of information management in financing. Based on this, we use business data from Chinese listed companies from 2007 to 2021 to investigate the relationship between renewable energy business development and financing. Furthermore, we introduce social and enterprise information to explore their impact on this relationship. Our findings reveal that: (1) Expansion of renewable energy businesses enhances fund availability mainly through endogenous financing. (2) “Anti-dumping and countervailing” (“Double-anti”) investigations significantly hinder financing for expanding renewable energy businesses, while industrial policies mitigate these effects. (3) Complex international backgrounds combined with domestic market-government interactions promote renewable energy enterprises to apply information management technology for financing.

Coal plays an important role in China's economic and income growth. This paper uses provincial panel data from 2007 to 2022 in China and employs the panel ARDL model to explore the impact of coal prices on regional and urban-rural income inequality in China based on information of coal price shocks. Empirical results show that: (1) Coal price shocks have a significant long-term effect on income inequality in coal exporting provinces, but have no significant effect on importing provinces. (2) This impact is asymmetric, indicating that the decrease in coal prices has to a greater extent damaged income equality in coal exporting provinces. (3) Coal price shocks have a significant effect on urban-rural income inequality, supporting the energy ladder theory of urban-rural disparity in China. Overall, this research provides an energy perspective for China to improve income inequality issues. Stable coal prices and orderly energy transition have important practical significance for coal exporting provinces and rural areas in China.

Recent studies indicate that Artificial Intelligence (AI) technology, characterized by its integration of information and communication technology attributes, exerts a multifaceted influence on the energy system. The authors employ Difference-in-Differences (DID) and Triple-Difference (DDD) models to investigate the effects of AI. The research initially demonstrates that AI may exhibit dual attributes of constraining energy structure. Specifically, the rapid development of AI tends to increase the proportion of fossil fuel-based electricity generation while optimizing the consumption of renewable energy. Furthermore, the degradation of energy structure stems from the surge in electricity consumption by AI, which the renewable energy consumption capacity is unable to satisfy. Lastly, industrial agglomeration effects and the construction of the digital economy have positive impacts on development of renewable energy; technological innovation aids in mitigating the negative shocks to the energy structure. This study provides a new perspective on the role of AI technology in energy transition.

Low-carbon travel is widely recognized as an important strategy for reducing energy consumption, mitigating pollution emissions, and alleviating traffic congestion. This study utilizes a sample of 2167 residents from four Chinese cities and employs the Theory of Planned Behavior (TPB) in conjunction with Structural Equation Modeling (SEM) to obtain more information about the determinants of Low-carbon travel behavior (LTB). Key findings include: (1) The extended TPB proved to be highly applicable to the analysis of LTB, with perceived behavioral control (PBC) exhibiting the most influential factor, and the relationship between PBC and LTB is partially mediated. (2) Gender, education, and commuting distance positively affect LTB, while income, private car ownership, and possessing a driver's license demonstrate significant negative effects. (3) Concern for environmental quality significantly enhances LTB. In contrast, perceived traffic congestion significantly reduces LTB. Based on the empirical results, targeted and implementable policy recommendations are proposed.

The pressure of climate change and policy guidance has attracted plenty of enterprises to expand their renewable energy business, presenting an opportunity to investigate whether latent information can contribute to improved performance in their transformation. This context also offers a broader application scenario for studying information management theory. Therefore, this paper explores the above topic using business data from listed Chinese renewable energy companies between 2003 and 2021, focusing on three aspects of latent information related to diversification. The findings reveal that: 1) Market power information plays a fundamental role in explaining the performance enhancement from renewable energy business expansion, and non-dedicated resource information is a significant factor for understanding the enhancement, whereas agency problems have no significant effect. 2) The latent information exhibits notable heterogeneity concerning the expansion of renewable energy business among enterprises with different transformation backgrounds.

Given the significant growth potential in households' energy consumption in China, studying household consumption behavior becomes even more valuable. This study explores factors influencing the shift in households' energy-saving preferences from habitual energy-saving behavior to consumption-oriented energy-saving behavior, as well as to analyze the potential for using other green alternatives to traditional energy in energy consumption. Empirical results reveal an inverted U-shaped relationship between household income and energy consumption, occurring when energy-saving awareness (ESA) exceeds a critical threshold. Below this threshold, household income is positively correlated with energy consumption. Further analysis indicated that once income exceeds the turning point, households' higher ESA leads to reduced energy consumption, indicating potential for green alternatives in higher-income households. Overall, the study highlights how awareness and income interact to shape energy-saving choices, emphasizing the potential for sustainable energy options in affluent households.

Gaining a comprehensive understanding of the energy-saving behaviors (ESB) of college students, who represent the backbone of the future society, is imperative for advancing energy conservation initiatives. This paper employs a PLS-SEM model with 2786 valid responses to investigate the determinants of college students' ESB within the comprehensive action determination model (CADM). The results show that (1) the applicability of CADM, including the theory of planned behavior, norm activation model, and ipsative theory of behavior, was confirmed in the context of college students' ESB. (2) The cultivation of energy-saving habits significantly contributes to the promotion of ESB. (3) The availability of energy-saving access has a positive impact on ESB. (4) Media's energy-saving promotional activities positively influence the energy-saving intention. (5) Energy-saving policy incentives exert a positive moderating influence on the transition from energy-saving intentions to ESB. Based on these empirical findings, this paper provides specific and target policy recommendations.

The rapid development of Fintech (financial technology) urges Fintech platforms to better understand users’ perceptions and behaviors toward Fintech use. Based on the theoretical framework of trust, risk perception, platform governance, and information system continuous use theories, we construct a model to explore how users’ different trust perceptions on Fintech platforms affect their risk perception, platform governance perception, and continuance intention of using Fintech. Our findings indicate users’ institutional trust, technology trust, and interpersonal trust all impact their risk perception, perception of Fintech platform governance, and continuance intention to use Fintech in different ways and magnitudes. Furthermore, platform governance perception mediates between institutional trust, interpersonal trust, and continuance intention. Our research helps the practitioners of Fintech platforms attract and retain users in the highly competitive market and provides a reference for the governance of their platforms.

In recent years, the economic effects of the belt and road initiative have attracted much attention. However, few related studies have explored how this initiative affects the investment efficiency of enterprises. This article regards the ‘belt and road' initiative as a quasi-natural experiment and investigates its effects on the investment efficiency of Chinese enterprises. The difference in difference model was used based on data on Chinese listed companies in 2011-2018. According to the findings of this study, the belt and road initiative significantly increased the investment efficiency of Chinese enterprises. On this basis, this paper explores the paths with which the belt and road initiative affects the investment efficiency of Chinese enterprises from the perspectives of both environmental uncertainty and tax incentives. The mediating effect of environmental uncertainty between the belt and road initiative and the investment efficiency of Chinese enterprises assumes a significant “masking effect,” while the mediating effect of tax incentives between them is not obvious.

Fostering pro-environmental behaviors (PEBs) among the young generation is imperative. Based on a micro-survey of Chinese college students, the authors used Logit and ordered Logit model to obtain empirical information on perceived past environmental quality and current PEBs. The authors found that environmental improvement positively impacted various PEBs, including green travel, plastic bag use, garbage sorting, and energy conservation. Better perceived environmental quality leads to increased environmental expectations, motivation to adopt PEBs, and awareness of environmental responsibility. The positive effect is more pronounced for individuals engaged in environmental protection activities, familiar with environmental advocacy, and with a family consensus on environmental protection. These findings were corroborated through robustness tests of alternative methods, samples, and measures. There is a positive feedback loop between a sustainable environment and human behavior. Policy recommendations are offered to further strengthen this symbiotic relationship.

As one of the important pillars of China's industrial sector, the mining industry is critical to China's modernization and energy security. Based on China's provincial panel data, this paper collects the information on government's environmental management and estimates the impact of environmental regulation on China's mining industry's energy and carbon performance. The study further collects information on the industries' technological innovation and analyzes the technological innovation's moderating effect on environmental regulation. The research results indicate that the interconnection between the intensity of environmental regulations and the energy and carbon performance of the mining industry is inverted U-shaped, and mining enterprises with high levels of technological innovation have better adaptability when facing pressure from external environmental regulations. Regarding policy recommendations, it is imperative that the government should enhance the environmental policy framework, develop clean energy, and incentivize mining firms to advance technological innovation.

China has been actively developing wind power for several decades, and its installed capacity has grown rapidly, which can be largely attributed to the favorable policy support and subsidies provided to wind power investments. However, China's resource-based strategy for wind power layout may not be fully taking into account the information on electricity demand. Therefore, the authors aim to identify the key factors driving the regional distribution of wind power in China, with a particular focus on the relationship between wind farm investments and local electricity demand. The study reveals that, compared to earlier stages of development, wind power installation growth is now more concentrated in regions with high electricity demand rather than just in resource-rich areas. Moreover, the model results demonstrate that the leading effect of demand on wind investment is more pronounced in resource-rich regions than in other areas. Demand information and mechanism analysis highlight the significant role of zoning policies in moderating the impact of demand on wind power siting and investment.

Finding the balance between economy and low emission of an integrated energy system (IES) has become one of the current research hotspots. This article introduces the carbon tax and carbon capture (storage) technology within the framework of the IES model. The IES comprises of components such as combined heat and power units equipped with carbon capture facilities, wind power generators, photovoltaic panels, and energy storage systems. The objective function of the model is the minimization of operational costs. Low-carbon economic operation dispatching problem under the constraints of energy conversion, energy balance, and operation cost is studied based on a mix-integer linear programming model. Through sensitivity analysis, this study explores the impact of varying carbon tax levels on the operational costs and emissions of an IES while considering peak and valley price differences. The emission reduction potential of the IES under different policy and technology scenarios is also estimated.

China has committed to achieving carbon neutrality by 2060, primarily focusing on reducing carbon intensity. Understanding the regional embodied carbon emissions is critical for managing carbon efficiency and carbon equity in this process. Using the input-output and SBM-DEA models, this article first calculates China's regional embodied carbon emissions. The results reveal substantial carbon transfers between China's different regions. Therefore, designing reduction pathways solely based on production-based carbon emissions raises fairness concerns. To address this, this article employs the SBM-DEA model to calculate the regional reduction potential and marginal abatement costs using the regional embodied carbon emissions and optimize China's pathways of regional carbon emission reduction. The new pathways consider consumption-based reduction potential, marginal abatement cost, and reduction equity, and are all in line with China's carbon reduction target. These schemes are of practical significance for China to develop a more efficient and equitable regional emission reduction plan.

Through innovative application of the multi-regional input-output model (MRIO) and spatial econometric methods, this paper investigates the trends, scale, and environmental impacts of China's industrial relocation, providing new information from an input-output perspective. The findings indicate that the relocation of China's industrial sector has exhibited a distinctive trend of moving “westward” and “northward,” while the service sector has demonstrated a tendency to cluster in several developed regions. Moreover, the authors have identified that the energy efficiency in net inflow regions and other regions is affected differently by industrial relocation. Specifically, the net inflow of the industrial sector positively impacts the energy intensity of local provinces, but negatively affects neighboring provinces. Conversely, the net inflow of the service sector has the opposite effect. The research enriches the understanding of China's industrial relocation and provides targeted implications to further prove the high-quality of China's industrial relocation.

Starting with the natural credit relationship between financial institutions and enterprises, this paper examines the relationship between distance-based access to credit and green innovation by using the data of financial licenses and listed enterprises. Based on the resource dependence theory, the authors use the geographical location of bank branches and enterprises to build micro-level credit access indicators. It shows that enterprises with better access to credit have more motivation to carry out green innovation. Taking the number of branches of the Bank of China in 1937 as an instrumental variable, it still supports the above results. Its influence lies in the reduction of financing constraints of enterprises. This paper further discusses the impact of green finance and digitization. The development of green finance and digitization could replace the benefits of distance-based access to credit. Combined with the transformation process of traditional banks in the future, this paper puts forward some policy suggestions to promote green innovation and low-carbon development.

Resource utilization not only meets the needs of economic development, but also has a far-reaching negative impact on the environment. Environmental regulation is regarded as the key measure to solve environmental pollution. However, the rent-seeking behavior of local enterprises will seriously weaken the implementation effect of environmental regulations. Under the background of the development of big data era, the massive micro enterprise data provided by China's private enterprise survey database provides favorable conditions for this paper to study its impact effect from the direction of big data. This paper uses OLS model and Tobit model to investigate the impact of rent-seeking on the implementation effect of environmental regulation. The results show that environmental regulation will make honest enterprises actively reduce output to control the emission level. However, rent-seeking enterprises will further expand their output to gain greater profits because they are sheltered by local governments.

Under the background of carbon neutrality, the carbon sequestration of forest ecosystems is an important way to mitigate climate change. Forest could not only protect the environment but also an important industry for economic development. As an international climate policy that first recognized the role of forest carbon sinks on climate change, the question becomes, has the Kyoto Protocol promoted the development of forest carbon sinks in contracting parties? To explore this, data of forest can be obtained at the national level. Hence, data of economic, social, polity and climate in 147 countries is also collected. The generalized synthetic control method is adopted. The results show that the policy effect of the Kyoto Protocol was obvious and significant. Moreover, the effect was more significant after the enforcement in 2005. Especially after the first commitment period, the policy effect of the second period is more obvious. Some policy implications are drawn.

How to balance resources, environment, and economic growth to achieve sustainable development is a challenge for developing countries. In 2013, China implemented a high-stringency environmental regulation—the Clean Air Action, which has effectively controlled air pollution. To explore the economic cost of environmental regulation, this paper investigates the policy effect on employment in the industrial sector. However, there are still controversies about whether environmental regulations impact employment. Based on the city-level data and firm-level data, this study applied a quasi-natural experiment for policy evaluation and used the mediating effect model for mechanism analysis. The difference-in-difference estimation results show that environmental regulation has a significant impact on employment. The mechanism analysis verifies that output adjustment, capital input, and green innovation are the main channels, by which environmental regulation distresses employment. The findings of this paper could be extended to other countries at a similar stage of development.

With the advent of the information age, the Internet is a new tool for “mass entrepreneurship and innovation initiative” and contributes to the emergence of new products, new technologies and new business formats. However, the question of how the Internet development affects green technological innovation has not been well answered. This article measures the comprehensive Internet development level of 264 prefecture-level cities from 2003 to 2018 in China, and then conducts empirical research. The results show that Internet development can increase high-quality and low-quality green technological innovation. This conclusion remains robust after endogeneity testing. Secondly, Internet development can not only directly promote green technology innovation, but also indirectly play a positive role through financial development and industrial structure upgrading. Thirdly, the positive effect of Internet development on green technology innovations presents significant nonlinear characteristics of increasing marginal effect. It indicates that Metcalfe's law is valid in this paper.

Drawing on the self-determination theory, this study explored the effect of three kinds of low-carbon knowledge (LCB), including system knowledge (SK), action-related knowledge (AK), and effectiveness knowledge (EK), on college students’ low-carbon behavior (LCB) by focusing on the mediating role of low-carbon intrinsic motivation (LCIM) and the moderating role of climate change risk perception (CCRP). Using a sample of 2846 college students in China, this study found that SK has an inverted U-shaped relationship with LCB, but AK and EK positively affect LCB. Moreover, LCIM mediates the relationship between three kinds of LCK and LCB. The moderated path analysis also indicated that CCRP could strengthen the impact of LCB on LCIM. Finally, this study discusses the theoretical significance of these findings and provides some policy suggestions and practical implications for the government.

The Chinese government implemented the payment system for plastic shopping bags in 2008 and 2020. This study aims to analyze consumers' perceptions and purchase willingness of plastic shopping bags. Using information technology, a random survey was carried out in Chinese first-tier cities. After collecting the rich first-hand data, the ordered Logit model is applied to conduct the empirical investigation. The results show that the average willingness to pay is roughly equal to what supermarkets charge. For socio-demographic characteristics, male, younger, and higher-income consumers are likely to pay more money. Consumers with more positive perceptions of policy support, environmental threat, personal ability, and charging benefits tend to pay higher fees. Moreover, the marginal influence of different variables on purchase willingness is heterogeneous. This study finally puts forward targeted suggestions for reducing plastic shopping bag consumption based on findings.

This paper finds that informed residents are more willing to support renewable energy development. Respondents with a higher level of participation in renewable energy planning, satisfaction with the implementation of renewable energy policies, as well as recognition of the high cost of renewable energy are more willing to use renewable energy. They are willing to pay more for renewable energy power, which means that respondents with more green information (renewable energy) are willing to pay more for renewable energy electricity. Although respondents are more willing to use voluntary payment mechanisms, they are more likely to pay more for renewable energy power under the mandatory payment mechanism. There is a large gap between the actual green power purchase behavior of Chinese residents and the expected WTP, mainly because there are many problems in the voluntary subscription mechanism for green power certificates. Finally, this paper provides targeted policy recommendations for policymakers.

Under the background of electrification, it is significant to explore the changes in residential electricity consumption for energy conservation and emission reduction. Based on the staggered difference-in-difference (DID) approach, this paper investigates urbanization's effect on residential electricity consumption using the longitudinal dataset from 2010-2018 China Family Panel Studies (CFPS). It is found that China's urbanization has increased the average electricity consumption by 12.8% with electricity substitution as the main channel. After urbanization, the scale effect of population and area levels does not exist. The authors also find that this positive effect is affected by electricity price (i.e., the higher the price level, the smaller the positive impact). However, as the electric charge is insignificant relative to the income, the moderating effect of price remains small. This indicates that the positive effect of urbanization will not decrease soon in the future unless the residential electricity price system is reformed.

The information industry leads the digital revolution and innovation. With regards to what economic impact the development of the industry will bring about, there has been minimal focus from literature. This paper fills the knowledge gap by using a dynamic computable general equilibrium model. The results show the development will rapidly promote economic development and social welfare, promote the reduction of commodity prices and the rise of output by providing higher social productivity. Finance, public service, and some traditional industry (such as electricity) will benefit more when the information industry develops rapidly. At present, the industry development of the information industry is more directed at the service industry and final consumption. This paper implies the information industry can strengthen R&D investment towards supporting finance, public services and traditional industries, such as industrial control embedded software products, cloud computing technology, and emergency communication for traditional industries to increase the income.