This study examines the spillover effects between China's carbon market and related markets, considering geopolitical factors. By using the spillover index method, MEMD decomposition, and the TVP-VAR model, the paper quantifies the spillovers at multiple scales. The findings indicate that: (1) significant spillover effects exist among China's carbon, energy, and financial markets, with the oil market being the major risk spillover source and the foreign exchange market playing an important intermediary role in risk transmission; (2) spillover effects are heterogeneous across time scales, with medium to long-term spillovers being the most prominent, suggesting long-term fundamental factors primarily drive risk spillovers; (3) spillover effects exhibit time-varying characteristics, with intensified spillovers typically triggered by economic crises, geopolitical events, policy changes, and other major incidents; (4) geopolitical risks have a significant impact on spillovers within the “carbon-energy-finance” system, though the impact's magnitude and direction vary depending on the specific geopolitical event. These results provide valuable guidance for policymakers and investors in China and other developing countries on the operation and investment of carbon markets.

This study empirically examines the impact of government dual-target management of economic growth and environmental constraints on bank credit structure, by taking 231 local commercial banks in China from 2008 to 2022 as the sample. It was found that although economic growth target increases the similarity of bank loans’ industrial structure, the introduction of environmental constraint target significantly weakens this impact. Mechanism analysis suggests that the implicit guarantee role of the government and intensifying competition among banks are important influencing mechanisms. Furthermore, the effect exhibits heterogeneity due to differences in economic cycles, city development levels, and bank capital adequacy ratios. The findings have important implications for government target setting and management, as well as for preventing banking financial risks.

Stepping into the new stage of trade openness, shipping city initiatives have attracted increasing attention. An integrated five-dimension system is constructed to investigate the construction level of shipping city. The entropy-weighted TOPSIS method is applied to assess typical shipping cities in China from 2006 to 2021. And the center radiation-driving force is measured by the gravitational model. Furthermore, the distribution dynamics and regional differences are examined to reveal the spatial structure behind urban transition. The results highlighted that (1) center radiation-driving force had excellent performance compared with other indicators. (2) As for the ranking of cities, Shanghai and Ningbo had a relatively high evaluation values thanks to their radiation-driving power. (3) Through the reginal analysis, the degree of comprehensive benefits took the following in order: eastern region > northern region > southern region. Based on the empirical results, the government should formulate suitable policies to form an exemplary and leading effect of shipping city ultimately.

Mixed teaching strategies have caused a fierce debate about teaching quality in China's higher education. Based on theories of constructivism and self-regulation, we examine the impact of mixed teaching strategies on learners' ambidextrous innovation capacities. Utilizing a questionnaire survey of 412 undergraduate and graduate students from 36 Chinese higher education institutions, this research demonstrates that combining metacognitive strategies with motivational and collaborative approaches enhances exploratory innovation ability, while the pairing of metacognitive and collaborative strategies promotes exploitative innovation. Furthermore, the study identifies significant differences in the effectiveness of mixed teaching strategies based on students' self-efficacy and teaching acceptance levels. These findings highlight the importance of tailoring mixed teaching strategies to individual characteristics for optimal learning outcomes and fostering students' innovative potential. This research contributes to the discourse on effective teaching practices in Chinese higher education by proposing a mixed teaching strategies matrix informed by self-efficacy and teaching acceptance, offering valuable guidance for educators seeking to cultivate students' innovative abilities.

Accurate prediction of crude oil prices is important for national energy security and socioeconomic development. Research on crude oil price forecasting has primarily focused on the overall price, overlooking the differentiated investment needs of different entities. To solve this problem, we introduce the Seasonal and Trend decomposition using Loess (STL) method into the Mixed Data Sampling (MIDAS) model. This enables us to more accurately analyze the predictive capability of predictors for crude oil prices at different frequencies. Selected predictors include the Dow Jones Index, US Dollar exchange rate, economic policy uncertainty, related crude oil and energy prices, carbon asset prices, and investor attention. Empirical results indicate that these predictors significantly enhance the forecasting accuracy across all components, with the strongest impact in the trend component. Interestingly, a lag effect is observed in the predictors' impact on the seasonal and residual components, but not on the trend component. Moreover, we calculate the duration of each predictor's effectiveness for different components of crude oil prices, distinguishing short-term and long-term effective predictors. This research offers novel insights into the design of crude oil price forecasting models, which is crucial for enhancing investor returns and maintaining stability in the energy market.

Chinese Emission Allowances (CEAs) pledge credit provides a new way for banks to reduce green credit risks and for low-carbon enterprises to improve the credit availability. However, insufficient supply and demand is the main dilemma of CEAs pledge credit in China. One of the reasons for this dilemma may be the neglect of the forward value of CEAs in value assessment. This research explores the decision-making behavior of the supply and demand subjects in the CEAs pledge credit market under different value types of CEAs. First, the improved B-S options pricing model with consideration of transaction costs is used in the construction of the payoff matrix to measure the option value of CEAs. The new matrix aims to place both the option value (corresponding to forward value) and the market value (corresponding to spot value) in the CEAs pledge value evaluation framework. Then, based on the new matrix, an evolutionary game model between key emission enterprises (KEEs) and commercial banks (CBs) is built to dynamically analyze the equilibrium state of supply and demand as well as the strategic interaction of participants in CEAs pledge credit market. Finally, numerical simulations demonstrate the driving factors of supply and demand for CEAs pledge credit. The research results show that compared to market value, the option value of CEAs is more conducive to stimulating the supply and demand of CEA pledge credit; and the shorter the remaining valid period of CEAs, the higher the participation enthusiasm of supply and demand parties. Furthermore, reducing low-carbon technology risks and increasing the carbon emissions trading prices at the end of pledge period can significantly improve the supply and demand of CEAs pledge credit, but the loan and deposit interest rates of CEAs pledge credit are ineffective.

The forecasting of carbon prices is critical to understand China unified carbon market dynamics. In this study, in order to reduce the noise and modal aliasing of carbon price sequence, a novel hybrid forecasting model is presented to predict carbon price in China unified carbon market. First, a three-stage algorithm that combines the improved complete ensemble empirical mode decomposition with adaptive noise (iCEEMDAN), variational mode decomposition (VMD), and reconstruction of fine-to-coarse (REC) data is proposed. Time series data are decomposed and reconstructed by this three-stage algorithm into three subsequences. Secondly, the model which combines the long short-term memory (LSTM) and convolutional neural networks (CNN) is utilized for prediction. Finally, the empirical results indicate that the prediction accuracy of this hybrid forecasting model is improved around 65 % higher than that of traditional LSTM. The proposed hybrid forecasting model can help the enterprises to make decisions facing non-linear, non-stationary and irregular carbon price more effectively. It is conducive to the implementation of energy conservation and emission reduction policies for the governments.

To control energy consumption, China issued the environmental regulation policy of the Top-1000 Energy-Saving Program in 2006, and it remains to be examined whether this policy will impact enterprises’ labor demand while promoting energy conservation and consumption reduction. Based on the panel data of Chinese enterprises (2000–2010), this study employs the difference-in-differences (DID) method to investigate the impact of the Top-1000 Energy-Saving Program on the labor demand of enterprises. It is found that the policy significantly reduces enterprises’ labor demand, a finding that passes several robustness tests. Second, the effects of the policy show heterogeneity across enterprises of various sizes, ownership structures, and regions. Finally, the mechanism analysis verifies the existence of an output effect leading to a decline in enterprises’ labor demand, while the substitution effect manifests itself in the substitution of enterprises’ labor demand with the increase of capital and technological innovation. This study provides important empirical evidence for the improvement of energy efficiency policies.

This paper examines the correlation between network relationship of institutional investors and the degree of corporate financialization. The results show that network relationship of institutional investors is positively related with corporate financialization, verifying the guiding effect hypothesis. After considering the heterogeneity of institutional investors, above relationship is merely evident in the sample of long-term institutional investors. Further research shows that the influence of institutional investors is particularly prominent in enterprises with information inferiority and high financial constraint as well as under tight monetary policy conditions.

Growing concerns surrounding urban investment bond (UIB) defaults in China necessitate a thorough examination of risk mitigation strategies. This study investigates the impact of local government implicit debt governance on UIB credit risk using a propensity score matching difference-in-differences (PSM-DID) approach. Our findings reveal that effective debt governance significantly reduces UIB credit risk, particularly for bonds issued by local government financing vehicles (LGFVs) with "high bargaining power". However, financial technology development may obscure credit risks and dampen the positive effects of governance. Further analysis, grounded in the "financial potential energy" framework, highlights the mediating roles of asset extension and risk warranty. Comparing the 2014 "Document No. 43" with the 2018 debt governance policy, we find the latter to be more effective in mitigating UIB credit risk. This study offers valuable insights into the micro-level effects of local government debt governance and provides guidance for policymakers in managing credit risks.

碳捕捉与封存(CCS)项目作为解决全球气候变暖问题的一种新兴减排措施,需要从多维微观视角探究其推广机制.本文将参与主体的碳情绪影响纳入博弈分析框架中,将等级依赖期望效用理论(RDEU)与博弈理论相结合,探究碳情绪影响CCS项目发展的微观作用机制.以国华神木富氧燃烧改造项目为例,仿真模拟了 5种异质情绪组合下政府和能源企业的均衡策略选择.研究结果显示:当双方处于理性状态时,能源企业和政府的CCS项目参与意愿都很低,这符合当前国际上CCS项目的发展现状;当双方处于悲观情绪时,悲观情绪越高,政府选择无作为策略和能源企业选择CCS技术改造策略的概率就越大,这是社会资源配置优化的表现;当双方处于乐观情绪时,适度乐观的情绪有利于刺激CCS项目的良性发展,过度乐观的情绪会阻碍CCS项目的发展.因此,本文从碳情绪引导方面提出了管理社会碳情绪相关对策建议,以期加快实现CCS项目的规模化和商业化运营.

In the information era, the fluctuation of consumer sentiments plays a key role in the green technology innovation of manufacturers. This paper introduces RDEU theory to the evolutionary game model to analyze the existence of equilibrium under different sentiment states. Then, the model is numerically simulated to study the influence of sentiments on the participants' strategies. The results indicate that under different sentiment states green technology innovation and green purchasing behavior present different evolutionary trajectories. The main conclusions are as follows: (1) When both parties have no sentiments, there is a stable equilibrium point, suggesting customers are willing to purchase green products and manufacturers choose green technology innovation strategies. (2) When both parties have sentiments, the rising consumer boycott sentiment will hinder optimistic manufacturers from choosing green technology innovation strategies. Furthermore, the rising support sentiment of the consumer promotes optimistic manufacturers' green technology innovations, and the more manufacturers deviate from the rational state, the more likely they are to maintain the current production mode. (3) When only one party has a sentiment, the manufacturer's rationality plays a more important role in promoting green technology innovation than the consumer's rationality. Based on the above conclusions, this paper proposes some sentiment guidance strategies that are conducive to green production and consumption. This study provides a new perspective and theoretical guidance for studying the behavior of green supply chain members to promote the development of green economy circulation.

The growth and management of the marine economy have received significant attention since the United Nations launched the "Our Ocean, Our Future: Call for Action" initiative. However, a lack of systematic review in the field of the marine economy has hindered progress. This study aims to address this issue by offering a unified knowledge analysis framework with bibliometric technology. We comprehensively analyze 6002 records from the Web of Science using software such as CiteSpace, VOSviewer, and ArcGIS for visualization analysis. This paper has drawn some interesting findings. Firstly, the development of the marine economy has experienced three stages: enlightenment, foundation and rapid growth, with the development process showing more and more apparent geographical cluster characteristics. Secondly, "Sustainable development", "Marine climate change", "Marine ecosystems government" and "Comprehensive performance evaluation" are identified as the mature clusters; meanwhile, "Sea level change", "Marine pollution treatment" and "Sustainable energy exploitation" are potential forefront clusters in marine economy. Based on this, the evolution of knowledge structure about marine economy is found, which changed from discussing the utilization of elements to studying the relationship between them to perform collaborative governance. Finally, this paper concluded by identifying research frontiers and future directions for further study, which includes the development of emerging industries, integration of marine and regional economy, protection of marine ecological and so on. This study can help researchers, policymakers and other participants better understand the knowledge structure and research frontiers of marine economy, and discover the future directions.

The improvement of eco-efficiency is strongly supported through blue carbon projects. However, the absence of incentive mechanisms makes risk aversion more alluring to commercial banks than profits, making project funding challenging. In this study, a "refinance for blue" mechanism is developed, and the evolutionary game model integrating the prospect theory (PT) is constructed. We are devoted to elucidating the impact of the perceived utility on player behaviors and confirming the efficacy of this incentive mechanism. Results indicate that: (1) Without any incentive mechanism, blue carbon projects are difficult to develop. (2) By modifying the perceived utility of both maritime enterprises and commercial banks, the "refinance for blue" mechanism helps marine enterprises to escape the financing limitation. (3) Commercial banks are more motivated by refinancing interest rates than by green credit interest rates. Finally, this research provides insightful information for commercial banks with the different perceived utility to assess the financial benefit of financing blue carbon projects and choose the most appropriate option in an unpredictable context.

The coronavirus disease (COVID-19) pandemic stimulated a heated dispute about the quality of higher education through online teaching in China. Based on constructivism theory and self-regulation theory, this study examines the influence of diversified online teaching strategies on students' innovation capacities by questionnaire surveys. The sample included 367 students from 29 full-time regular universities in the mainland, including undergraduate and postgraduate students. The results show that online teaching strategies have a significant positive association with students' ambidextrous innovation capacities. Specifically, the teaching strategies combination constructed by social identification strategies and case guidance is conducive to the formation of exploitative innovation capacity during online teaching. The social participation strategies and flipped classroom are conducive to forming the students' exploratory innovation capacity. In further research, social participation strategy has a significant positive impact on students' ambidextrous innovation capacities for students with higher participation willingness. However, social identification strategies are helpful for the cultivation of ambidextrous innovation capacities for students with lower willingness to participate. Based on the empirical results, this study proposes the online teaching strategies matrix based on social presence theory and social identity theory to provide conducive guidance for improving students' innovation capacities.

随着天然气消费需求的快速增长,需求波动也显著加剧,导致部分地区天然气供需出现季节性和阶段性的失衡.本文基于混频采样框架、分位数回归模型和核密度估计的天然气需求混频概率预测模型,构建了包括天气状况、能源市场、资本市场和投资关注4个方面的综合性混频动态因子系统,以期更精确地预测我国的天然气需求.研究发现,天气状况、能源市场和投资关注对天然气需求的预测能力优于资本市场.在天气状况方面,每日温度是月度天然气需求的最佳指标;在能源市场方面,月度天然气需求呈现出显著的自相关特征,持续时间为3～5个月,石油现货价格和煤炭现货价格的影响持续天数较短,分别为11天和10天;在预测表现方面,样本外的月度天然气需求实际值大部分出现在概率密度曲线的最高点附近.本文所提出的模型不仅能够直接使用混频动态因子的前瞻性信息,还能够获得平滑的天然气需求概率密度曲线,预测精确度相较现有模型提升14.13％～29.15％.研究结论为保障我国天然气市场安全,完善"双碳"政策设计提供有益的决策参考.

建设现代海洋城市既契合了拓展海洋经济发展空间、建设海洋强国的战略任务,又与走中国式现代化道路的战略安排一脉相承.本文基于现代海洋城市的"海洋化"与"现代化"两大特征,从"对象—理念—空间"三个维度对现代海洋城市进行内涵解析,即以"海洋经济—海洋科技—海洋生态—海洋文化—海洋治理"五大子系统为现代海洋城市的发展对象,以"创新—协调—绿色—开放—共享"为现代海洋城市的发展理念,以"要素—产业—网络—地理—生活"空间拓展为现代海洋城市的发展路径,回答现代海洋城市"是什么"的问题.尔后围绕现代海洋城市的内涵构建现代海洋城市发展的"5+5+5"评判框架;设计多模块评判标准,立体化反映现代海洋城市发展的系统性、先进性、开放性、辐射带动性等特征,回答现代海洋城市发展"如何评判"的问题,为推动海洋强国战略切实落地提供理论指导.

This study examines the role of technical and financial support in promoting the upgrading of the marine industrial structure in the Bohai Rim region. Using panel data from coastal cities around the Bohai Sea from 2006 to 2020, the study applies financial constraint theory and resource endowment theory to analyze the spatial spillover of technical and financial support on the marine industry. The results indicate that technical and financial support positively affects the upgrading of the marine industrial structure. Still, technical support negatively affects coastal cities around the Bohai Sea. The study also reveals that financial support has a threshold effect, and once this threshold is crossed, the government can promote the upgrading of the marine industrial structure through financial intervention, environmental regulation, and improving market opening. The findings also suggest that upgrading the marine industry will promote local economic growth but may have a siphon effect and inhibit economic growth in surrounding cities. However, it will optimize the local environment and show a significant positive spillover effect on the environmental optimization of surrounding cities. The study's conclusions can inform the construction of cross-regional industry-university research platforms and facilitate the high-quality development of marine-related industries in the Bohai Rim region.

In order to accelerate the marine economic transformation, and promote the development of marine finance, the Chinese government has promulgated the first "Guidance on Improving and Strengthening Financial Services for the Development of the Marine Economy" in 2018. This paper constructs a quasi-natural experiment and ex-plores the impact of this policy on the total factor productivity (TFP) of marine enterprises using the difference-in-differences method. The results show that the policy has consolidated the micro foundation of marine finance to accurately serve the high-quality development of the marine economy, and is mainly achieved by reducing financing constraints and optimizing resource allocation efficiency. The promotion effect of TFP is more evident in marine enterprises with secondary industry, tertiary industry, and low government subsidies. In addition, the policy can affect the financing structure of marine enterprises, which can reduce the financing cost of enterprises and increase the number of equity financing of enterprises.