Promoting enterprises to accelerate digital transformation is of great significance to enhance the core competitiveness of enterprises, empower the upgrading of traditional industries, generate new forms of business, as well as drive China's digital economy to become better and stronger. From the perspective of enterprises, this paper analyzes the antecedents of enterprises' digital transformation, constructs related indexes based on the text analysis method, proposes a two-factor theoretical model of manager characteristics and dynamic capabilities, and uses the structural equation model based on partial least squares estimation (PLS-SEM). The empirical results show that manager characteristics such as entrepreneurship, digital evangelist and coordinator, as well as corporate dynamic capabilities such as sensing, learning, integrating and coordinating, have a significantly positive role in promoting the tendency and output of digital transformation of enterprises. In addition, manager characteristics can significantly improve the level of enterprises' dynamic capabilities, and the effect of manager characteristics on enterprises' dynamic capabilities and digital transformation is moderated by managers' perception of policy uncertainty. In addition, the above effects are heterogeneous between state-owned and private enterprises, enterprises in the eastern, central and western regions, as well as enterprises in provincial and non-provincial capitals. This paper fills the research gap on the antecedents of digital transformation, and provide a feasible practical path for enterprises to cultivate managers in the digital era and improve their dynamic capabilities.

In recent years, China's food delivery industry has undergone substantial growth, driven by the rapid expansion of the platform economy and the influence of the COVID-19 pandemic. Food delivery services have not only lessened customers' sensitivity to delays associated with in-person dining but have also generated increased market demand for merchants. It is noteworthy that the majority of merchants employ a centralized operational mode, which combines food delivery and dine-in services within a single establishment. However, certain merchants opt for a decentralized approach, wherein they establish dedicated food delivery outlets exclusively handling food delivery orders while maintaining an offline restaurant. To examine the impact of food delivery channels on merchant decision-making, this study establishes a dual-channel service system operating within a congestion-prone environment. It characterizes the equilibrium strategy of customers under the two operational policies and investigates how the quality of food delivery services affects merchant profits. Furthermore, the research reveals the optimal operational approach based on varying levels of delivery quality. The key findings of the study are as follows. 1) In the case of decentralized operations, the service capacity allocated to the food delivery channel by the merchant exhibits a non-monotonic relationship with its quality. This implies that higher food delivery quality may gradually prompt the merchant to shift its focus toward the offline channel. 2) Despite the fact that higher food delivery quality has the potential to attract more customers, the study surprisingly finds that improving food delivery quality may actually reduce merchant profits in both centralized and decentralized scenarios. 3) While decentralized operations may lead to decreased order processing efficiency, adopting this approach can effectively mitigate the cannibalization effect of the food delivery channel and result in higher profits, particularly when food delivery quality is high. Consequently, centralized mode is recommended only when the food delivery quality falls within an intermediate range. Additionally, we further validated the robustness of this conclusion from various perspectives, including marginal costs and delivery fees.

In the context of the new era, the fundamental way to promote high-quality economic and social development is to improve urban development efficiency, and digital economy plays an important driving role in the process. This paper constructs a theoretical analytical framework for digital economy-driven urban development efficiency improvement, and empirically tests the impact of digital economy on urban development efficiency and spatial spillover effects using a spatial and temporal double-fixed spatial Durbin model. This paper finds that: Firstly, digital economy significantly contributes to urban development efficiency in the region and surrounding areas, and the finding still holds through a series of robustness tests. Secondly, digital economy contributes to urban development efficiency by enhancing social, economic and ecological benefits, but the enhancement is limited by the reduction of land benefits, while industrial integration, technological advancement, and urban-rural integration play an important role in its mechanism. Thirdly, the effect of digital economy in driving the improvement of urban development efficiency shows a non-linear trend of "downward and then upward" and spatial spillover characteristics. Fourthly, there is city-level heterogeneity and geographic-area heterogeneity in the impact of the digital economy on urban development efficiency, which means that the role of digital economy in driving urban development efficiency is more pronounced in cities with high administrative levels and large populations, as well as in the eastern and northern regions. The above findings imply that at present, China should take urban development efficiency as an important target to consider for the high-quality economic development, and take the development of digital economy as the main driving force to improve urban development efficiency.

Insufficient aggregate demand is the prominent contradiction facing the current economic operation, we must restore and expand consumption in a priority position. This paper empirically investigates the impact of the housing provident fund system on household consumption using data from three editions of the China Household Finance Survey in 2015, 2017, and 2019. The empirical results show that household contributions and withdrawals to the housing provident fund significantly increase household consumption levels and improve household consumption structure. Robustness tests show that the above conclusions remain robust after replacing the way the core variables are defined, replacing the instrumental variables, and relaxing the exclusivity constraints on the instrumental variables. The Heterogeneity analysis shows that the housing provident fund system has a greater impact on the consumption of housed, low-income, as well as young and middle-aged households. Further research finds that contributing to the housing fund reduces households' precautionary saving incentives, withdrawing from the housing fund increases households' disposable income and eases liquidity constraints, thereby boosting household consumption. This paper provides micro-level evidence that housing funds promote household consumption and improve household consumption structure, which can provide important references for relevant policy formulation.

China's high-quality development and carbon peaking and carbon neutrality goals both require an overall consideration to economic benefits and environmental cost. Transnational investment promotes the reconstruction of global industrial and supply chains, which also leads to dispute of environmental responsibilities under the accounting of economic benefits based on the ownership principle and the accounting of carbon emission based on the territorial principle. In this paper, we employed an inter-country inter-industry input-output database that distinguishes the activities of multinational enterprises (MNEs) and introduced counterfactual analysis and scenario analysis to evaluate impact of structural change in GVC on China's gross national income (GNI) and CO$_2$ emissions. There was significant industrial shift toward China from 2005 to 2016, boosting China's GNI and CO$_2$ emissions by 15.23% and 20.50% respectively compared to 2016 levels. For the future shift, the scenario analysis shows that compared with the relocation of GVC led by developed economies, the relocation led by China would yield lower negative impact on China's GNI when reducing same amount of China's CO$_2$ emissions. The negative impact on GNI and CO$_2$ emissions varies by sector initiating the relocation and by economy undertaking the relocation. Our analysis provides policy implications for China's future GVC relocation and high-quality development.

Identifying and addressing various financial risks on the way toward low-carbon transition is crucial for China to achieve its dual carbon goal. By performing textual analysis of newspaper articles, this paper constructs a novel index of climate policy uncertainty for China to examine the impact of the climate policy shock on the corporate bond cost as well as the mechanism behind the relationship. From a climate policy-cash flow sensitive perspective, this paper develops a theoretical model of financing decision-making under climate policy uncertainty and empirically verifies the hypothesis with a dataset of Chinese-listed companies from 2009--2020. The results show that bond spreads of climate policy-sensitive firms are significantly higher than that of climate policy-insensitive firms, which indicates that climate policy uncertainty significantly deteriorates corporate bond costs in China. Moreover, this effect increases with the maturity of the corporate bond and the level of climate policy uncertainty and is more profound in firms with a negative sensitivity to changes in climate policies. The results also prove that internal environmental governance and external regulatory enforcement intensity are two key channels by which the climate policy shock can impact the cost of corporate bonds in China. This paper contributes to the research of climate finance by providing a theoretical framework and empirical evidence on the relationship between climate policy shock and corporate bond cost and thus is crucial for policymakers to understand micro-level financing and investment risk in China under the dual carbon goal.

Exploring the underlying causes and contexts of corporate ESG greenwashing is essential due to its adverse consequences, such as the harm of consumer benefits and social trust crisis. This paper takes Chinese A-share listed companies from 2011 to 2021 as samples to test the relationship between legitimacy pressures from different institutional sources and corporate ESG greenwashing, as well as the moderating effects of financing constraints and industry competitiveness. The results show that regulatory legitimacy pressure significantly negatively relates to corporate ESG greenwashing; The pressure of standardization and imitation legitimacy significantly positively relates to corporate ESG greenwashing. Mechanism analysis shows that financing constraints and industry competitiveness strengthen the negative effect of regulatory legitimacy pressure on corporate ESG greenwashing, whilst financing constraints strengthen the positive effect of imitation legitimacy pressure on corporate ESG greenwashing; the institutional legitimacy pressure affects corporate ESG greenwashing through internal control. Heterogeneity analysis further shows that the relationship between institutional legitimacy pressure and corporate ESG greenwashing is more pronounced, in state-owned enterprises and heavily polluting industry enterprises. Based on the perspective of organizational decoupling, this paper contributes to clarify the deeper motives and constraints of corporate ESG greenwashing, which is significant for promoting ESG practices, green transformation, and sustainable development in China.

As a new financial service, supply chain finance plays an important role in improving financing efficiency and reducing transaction costs for enterprises. Behind the huge benefits there are often frequent incidents of pseudo supply chain finance, and "supply chain security" is gradually elevated to the level of the macro national security system. This paper uses the data of A-share non-financial listed companies in Shanghai and Shenzhen Stock markets from 2007 to 2021, and we find that supply chain finance can significantly reduce firms' risk-taking, while this negative relationship is more obvious in non-state-owned enterprises and small enterprises. Further analysis shows that supply chain finance will enhance the resilience of the industrial chain and supply chain by improving the company's operating efficiency, alleviating underinvestment, stabilizing supply chain relations to reduce the risk-taking level. In addition, enterprises with good bank-enterprise relationship, higher industry competition and higher risk preference of management can enhance the reducing effects to a greater extent. Under the background of high environmental uncertainty faced by enterprises at present, this paper provides feasible ideas for enterprises to carry out supply chain finance to reduce production and operation risks and financial risks, and then maintain the security of industrial chain and supply chain.

Disruptive events, such as natural disasters and manmade attacks, could lead to multi-site structural damages and functional failures with various severities for road transportation systems. These events result in degraded system level of service and even disconnectivity between some origins and destinations. To enhance the resilience of road transportation system, various protection/restoration countermeasures can be taken for system components before/after the occurrence of disruptive events. These countermeasures help the system to resist to, to response to, and to recovery from disruptive events with better accumulated system performance over the time span. This paper briefly reviews the definition of transportation system resilience and the state of art for transportation system resilience assessment methods. Then, research efforts regarding the strategies' optimization for transportation system components' protection and restoration to enhance system resilience is highlighted. Last but not least, the outlook for future research directions in this field is discussed for the reference of audience.

Our country is in the crucial process of industrial structure reformation, and expanding the new infrastructure investment, which has a feature of digital technology application, has a practical significance in pushing the upgrading industrial structure. This article picks China's 2004-2021 provincial panel data as samples to empirically prove the spatial effect of new infrastructure investment on industrial structure upgrading. Empirical results illustrate that the new infrastructure investment will accelerate the upgrading of the province's industrial structure, and have a positive spatial spillover effect. New infrastructure investment will inhibit the coordinated transformation of industrial structure, but this negative impact is not contagious among regions; The impact of new infrastructure investment on the upgrading of industrial structure is heterogeneous among different infrastructure types and eastern, central, and western regions. The above conclusions have certain policy implications for China to grasp the direction of new infrastructure investment, improve the efficiency of resource allocation, and accelerate the pace of industrial structure optimization and upgrading.

As a representative of the transportation systems in China, high-speed railway (HSR) network plays an extremely important role at many levels of economy and strategy. This paper focuses on the topological structure and resilience of China's HSR transportation network from a hyper-network perspective. Initially, we construct a hyper-network representation of China's HSR system. We visualize this network, revealing instances where specific HSR lines detach from the main network. Subsequently, we choose metrics tailored to the characteristics of HSR transportation for topological analysis. Finally, we employ natural connectivity as an indicator to quantify network resilience. Dynamic assessments using both random and intentional strategies are conducted to evaluate the network's ability to withstand disruptions. Our results highlight the pivotal role of a few key nodes within the HSR hyper-network, such as Zhengzhou East Station and Nanjing South Station, which hold significant value. Experimental findings underscore that prioritizing attacks on these nodes has the most significant impact on the network's natural connectivity. This paper integrates hypergraph theory with the HSR network, taking into account geographical relevance and operational considerations. This integration enhances the precision of our study on the topological characteristics and resilience of the HSR transportation network. The outcomes of our research offer valuable scientific insights for the planning, construction, and operation of HSR networks. They hold substantial practical significance in advancing China's railway transportation sector.

As a result of the transition of atmospheric environmental governance from territorial administration to joint management, regional joint prevention and control has become a crucial air pollution control measure. However, joint prevention and control cannot exist wholly without territorial governance, and how to coordinate joint prevention and control with territorial governance has become the key to air pollution control. This paper explores the policy relevance and impact of territorial governance from the perspective of policy governance, using 12166 air pollution prevention and control policy texts issued by Chinese local governments from 2000 to 2018, and combining unsupervised learning and spatial econometric models. Research has found that local prevention and control policies mainly focus on supervision and regulation, including emergency management of heavily polluted weather, total pollutant emission control, project control and dust control, and mobile pollution source control, but each has its own emphasis on specific prevention and control; And the higher the correlation between regional policies, the more similar their pollution emissions, energy consumption, and industrial development are. The results indicate that pollution emissions and some influencing factors, such as the spatial spillover effect of environmental regulations, are also caused by similar policy prevention and control systems. The prospective policy relevance in territorial governance can serve as the foundation for regional joint governance, and promote regional environmental collaborative governance by further integrating regions with high policy relevance. This study provides a new explanation for the spatial dispersal and transmission of air pollution, and a feasible direction for regional joint prevention and control.

This paper incorporates digitalization into the theoretical framework of bank risk preference from both the perspectives of income and cost. Based on this framework, it uses panel data from the Chinese banking industry for empirical testing. The results show that digitalization significantly enhances banks' risk preference. Mechanism testing suggests that digitalization improves risk preference by increasing the risk control effect on the income side and reducing management costs on the cost side. Heterogeneity analysis finds that the effect of digitization on risk preference is more significant for banks that are smaller, have lower capital adequacy ratios and are located in areas with weak financial sector development. In terms of loan allocation, digitalization significantly promotes credit loans and corporate loans, providing indirect evidence for the increase in risk preference. Further research also finds that digitalization helps drive banks to return to their roots and better serve the real economy, while also having a more positive impact on internal bank performance, reducing bankruptcy risks and increasing profits. This paper contributes to a deeper understanding of the micro-economic consequences of bank digitalization, thereby providing empirical support for economic policies designed to improve the quality and efficiency of financial services to the real economy.

In the trend of green economy, merchants on the platform have begun to gradually transform towards green development, where traffic marketing has had a significant impact on the merchants' transformation strategies. Therefore, this study establishes a single-product model (producing only traditional products) and a dual-product model (producing both traditional and green products), innovatively focusing on the traffic decision-making of merchants who produce both traditional and green products during the green transformation process. It analyzes the optimal traffic strategy of merchants undergoing green transformation and the impact of traffic marketing on their green transformation. The results indicate that merchants utilize traffic to provide greater support for products in weaker competitive positions, thus achieving a balance between traditional and green markets. However, excessive traffic is not necessarily beneficial, particularly in highly competitive markets, where higher traffic levels may compromise merchants' profits. With the increasing eco-consciousness among consumers, merchants consistently benefit from green transformation under traffic marketing. Furthermore, consumer preferences for eco-friendly products are a key factor influencing merchants' traffic strategies. Interestingly, as consumer preferences for green products increase, merchants tend to reduce traffic for green products, reflecting an inevitable choice by businesses to protect their traditional product lines.

Improving firm ESG performance is an important measure to achieve sustainable economic development. This study takes the implementation of the “Broadband China” strategy released in 2013 as a quasi-natural experiment and uses differences-in-differences method to evaluate the impact of digital infrastructure on firm ESG performance. The study finds that digital infrastructure has a significant promoting effect on firm ESG performance. The mechanism analysis shows that the impact of digital infrastructure on firm ESG performance is mainly achieved through pathways such as increasing government environmental concerns, incentivizing firms to fulfill social responsibilities, and improving firm information transparency. Heterogeneity analysis reveals that the promoting effect of digital infrastructure on firm ESG performance is more significant in large-scale firms, firms with high customer concentration, high-polluting industries, and firms with strong green innovation capabilities. This study evaluates the practical role of digital infrastructure from a sustainable development perspective, providing new empirical evidence for understanding the influencing factors of firm ESG performance and offering policy recommendations for strengthening digital infrastructure construction and promoting economic green transformation.

This paper builds a parallel CNN-LSTM deep learning model, excavates the interactive text between investors and the management of listed companies on the interaction platform of Shanghai and Shenzhen Stock Exchanges, quantifies the information interaction process between investors and the management from the text content and semantic characteristics, and analyzes its impact on the company's stock price foam by identifying the content of investors' inquiries and the quality of company responses. The study found that investors' questioning and attention to different contents had significantly different effects on the stock price foam. Among them, questioning and attention to the company's stock and financial information could inhibit the frequency and intensity of the stock price foam, while questioning and attention to the company's research, development, production and sales information increased the frequency and intensity of the stock price foam; The higher the clarity of the management's response to investors' questions, the more significantly it can reduce the frequency of stock price foam, but it has no significant impact on the strength of stock price foam. Further, the worse the external information environment is and the lower the shareholding ratio of institutional investors is, the more obvious the impact of information interaction on the foam of the company's share price is. The transparency of company information plays a part of the intermediary effect in this impact. The research findings contribute to a micro perspective understanding of the impact mechanism of information exchange behavior on the operation of the stock market in China's investor interaction platforms.

Promoting carbon emission reduction of urban residents is of great significance for mitigating climate problems. Based on the panel data of 288 cities above prefecture level in China from 2009 to 2019, this paper calculated the living carbon emissions of urban residents, and combined population and economic characteristics to cluster cities into four types for analysis, and analyzed the influencing factors of living carbon emissions of urban residents. And BP neural network and scenario analysis were used to predict the carbon reduction potential of various urban residents. The results show that: 1) The total carbon emission of urban residents in China is increasing year by year, and the proportion of carbon emission from electricity is the highest, and the growth rate of carbon emission from heating is the highest. 2) Urbanization level, per capita disposable income, energy structure and total population size all have positive effects on the carbon emissions of urban residents, while energy intensity and consumption tendency of urban residents have negative effects, and the influencing factors of carbon emissions of various cities have certain differences. 3) All kinds of cities have great carbon reduction potential in residents' life, and there are great differences. The carbon reduction potential of the second type of cities is significantly higher than that of other cities. The first type of cities has the lowest carbon reduction potential overall. The change degree of carbon reduction potential of the third and fourth types of cities is similar, showing a trend of first increasing and then decreasing. All localities may formulate and implement carbon reduction measures for residents according to local conditions.

In order to alleviate traffic pressure, multiple cities in China have introduced various policies restricting the fuel vehicles, which to some extent has affected the competition between the new energy vehicles and the fuel vehicles. Based on the above reality, this paper constructs an automobile market competition decision-making model composed of a fuel vehicle automaker and a new energy vehicle automaker in consideration of consumers' anxiety about the new energy vehicles' range or energy replenishment. This paper analyzes the optimal decision-making of the two types of automakers under the government's three policy scenarios (license plate policy, license plate lottery, and the combination of the above two policies), and compares the equilibrium results of the various policies scenarios to explore the threshold conditions for the dominant policy choice of these two automakers in terms of demand and profit. The results show that these two automakers can always realize the optimal profits under the license plate policy, while they can realize the optimal profits under the license plate lottery and the combination of these two policies only when the degree of anxiety of consumers about the fuel vehicles caused by the license plate lottery is lower than that of the new energy vehicles. In addition, the license plate lottery and the license plate policy will not change the prices of these two types of vehicles. Finally, from the perspective of demand and profit, the combination of the license plate policy and the license plate lottery cannot be an optimal choice for the fuel vehicle automaker, while the license plate lottery cannot be an optimal choice for the new energy vehicle automaker. When consumers are highly anxious about the fuel vehicles and the new energy vehicles, the license plate policy can be an optimal choice for these two types of vehicle automakers. However, as the government imposes stricter restrictions on the lottery of the fuel vehicles, the likelihood that the license plate policy becomes a predominant choice for these two automakers will gradually decrease.

Corporate continuous green innovation activities are an important driver for promoting green and sustainable economic development. This paper uses a sample of A-share listed companies in China's capital market from 2009 to 2022 to empirically examine the influence of local government environmental protection concern on corporate green sustainable innovation levels. This study finds that local government environmental protection concern can enhance corporate green sustainable innovation levels, with stronger concern leading to higher levels of corporate green sustainable innovation. By distinguishing between types of corporate green sustainable innovation activities, the study finds that local government environmental protection concern promotes both upstream green sustainable innovation levels (source control) and downstream green sustainable innovation levels (end-of-pipe treatment), with a more pronounced impact on upstream green sustainable innovation levels. The analysis of the influencing mechanisms indicates that local government environmental protection concern improves corporate green sustainable innovation levels by increasing environmental resource compensation and strengthening managerial environmental awareness. Further heterogeneity analysis reveals that the positive impact of local government environmental protection concern on corporate green sustainable innovation levels is more pronounced in samples that CEOs with green experience, firms with stable institutional investors, heavily polluting industries, and cities with key environmental protection. The economic consequence test shows that local government environmental concern is beneficial for enhancing corporate environmental protection performance by improving corporate environmental outcomes, increasing corporate environmental advantages, and reducing corporate pollutant emissions and environmental governance costs. This paper uses the level of corporate green sustainable innovation as an entry point to explore the microeconomic consequences of local government environmental protection concern, providing theoretical references for promoting the current transition to green and sustainable economic development.

The international economic circulation affects China's economic growth through the production process of the product and the market demand of the product. In terms of production process, the mutual substitution of imported intermediate products and domestic intermediate products affects economic growth; in terms of market demand, foreign demand for China intermediate and final products affects China economic growth. Based on the structural decomposition analysis method, this paper decomposes the change of the Leontief inverse matrix into technology level change and import substitution, and decomposes the final demand change into domestic final demand change and export change, so as to measure the impact of international economic circulation on China economic growth from two aspects. The results show that: 1) Import substitution is an important channel for the international cycle to affect China economic growth, and it shows periodic characteristics. From 2000 to 2005, imported intermediate products replaced domestic intermediate products, which had a negative impact on economic growth; From 2005 to 2014, domestic intermediate goods substituted imported intermediate goods, and China gradually took control of more intermediate goods production processes. From 2015 to 2021, the share of imported intermediate goods again increased. 2) Compared to domestic final demand, the contribution of exports to China's economic growth has been continuously decreasing, and China's dependence on the final demand of international circulation has been gradually declining.

A supply chain consisting of suppliers, producers and consumers, and the suppliers and producers decide the carbon information disclosure degree and product premium according to the market situation. Parameters such as consumer information trust, consumer information sensitivity and information sharing benefit coefficient were introduced to construct a supply chain carbon information disclosure model under information asymmetry and a supply chain carbon information sharing model based on blockchain technology, and the optimal decision of different decision models was compared and analyzed. The results show that: 1) With the increase of the cost coefficient of carbon information disclosure, the decision-making of the supply chain is divided into three stages: Full disclosure of carbon information of suppliers and producers, full disclosure of carbon information of producers and partial disclosure of carbon information of suppliers and producers, and the optimal decision-making of the decision-making body shows a downward trend. 2) Except for the interval of the cost coefficient of a certain carbon information chain, the optimal carbon information disclosure degree of the manufacturer is always no lower than that of the supplier; when the initial price of the product is less than a certain threshold, the premium of the manufacturer's optimal product is higher. And the manufacturer's optimal decision is more sensitive to the change of related parameters. 3) When the cost coefficient of carbon information on-chain is less than the cost coefficient of traditional carbon information disclosure, the profit of the decision-making subject under the “blockchain + carbon information” sharing mechanism is much higher than the profit under information asymmetry.

Since the 2015 stock market crash, the trading activities of the “National Team” funds have drawn significant attention from investors. This paper uses A-share listed company stock trading data from the third quarter of 2015 to the fourth quarter of 2021 to examine the impact of “National Team” fund holdings on institutional investor herding behavior. Employing a fixed effects model for regression analysis, the findings indicate that “National Team” fund holdings exacerbate institutional investor herding behavior. Further analysis reveals a negative correlation between institutional herd behavior and stock price synchronicity, suggesting that this behavior is not merely blind following of “National Team” fund holdings but rather a pseudo-herd behavior influenced by shared market and private information. This effect is consistent across bull, bear, and volatile market conditions, though it is somewhat reduced during bear markets. The conclusions of this study enhance the understanding of the intervention effects of the “National Team” funds and provide valuable insights for their effective management.

Recently, China is promoting the construction of high penetration renewable energy systems, which urgently needs to study a market-based trading mechanism that can reveal both the economic and environmental values of renewable energy. This paper constructs a game model of electricity and carbon trading among multiple electricity prosumers considering the electricity and carbon coordinated mechanism, solves the equilibrium price of the electricity-carbon coordinated market by using the Walrasian general equilibrium theory, reveals the effect mechanism of the electricity-carbon coordinated mechanism on the market equilibrium price and social welfare, and analyzes the impact of key parameters such as free carbon quotas and the number of prosumers on the market equilibrium. The results indicate that the electricity carbon coordinated mechanism can lower the carbon market price, improve the overall social welfare of prosumers, reduce the cost of purchasing carbon, and motivate prosumers to consume more renewable energy. Besides, the greater the number of prosumers, the more significant the economies of scale. Free carbon quota reduction will raise the equilibrium price of the carbon market, better reveal the environmental value of renewable energy power, and promote the coordinated development of the electricity and carbon markets. The study forms an electricity and carbon linkage trading mechanism for prosumers considering the environmental value of renewable energy, which provides theoretical and methodological support for the coordinated operation of the electricity and carbon markets.

This paper addresses the location and capacity planning of battery swapping stations of electric vehicles, combining the charging and swapping operations in the stations. The charging and swapping operations within the swapping station are a crucial link connecting the swapping demand with the decisions on station location and capacity planning. However, previous research has overlooked providing a detailed characterization of this process. This study models the internal operations of the swapping station as a multi-period optimization problem and provides insights into the structural properties of the optimal solution to this problem. Building upon this foundation, considering the uncertainty in swapping demands, we integrate the internal operational aspects with the station location and capacity planning to construct a distributionally robust optimization model and a robust satisficing model. To deal with the hard multistage problem in the model, we utilize the linear decision rule to approximately solve the two models and extend the lifting technique by incorporating auxiliary variables into multistage scenario-wise robust optimization models. The theoretical analysis establishes the relationship between the models before and after lifting. Finally, numerical experiments are conducted to validate the effectiveness of the proposed model and lifting techniques.

Enhancing human capital and attaining high-quality economic progress are fundamental imperatives for the comprehensive construction of a modern socialist nation. Against this backdrop, our study employs data from Chinese A-share listed companies spanning 2011 to 2019 to explore the influence of local economic growth targets on corporate human capital structure and its underlying mechanisms. Our findings reveal that heightened local economic growth targets tend to hinder the optimization and advancement of corporate human capital structures, consequently diminishing enterprises' total factor productivity. Further analysis indicates that these effects are more pronounced in regions exhibiting greater governmental intervention capacity and willingness, companies facing severe financing constraints, and industries characterized by non-high-tech and labor-intensive sectors. Mechanistically, elevated economic growth targets prompt local government officials to skew fiscal expenditure structures, curtail public service outlays, steer enterprises towards increased fixed asset investments at the expense of innovation expenditures, thereby impeding the optimization and enhancement of human capital structures. This research not only contributes to the body of literature on economic growth targets and corporate human capital but also furnishes empirical insights to facilitate the optimization of official assessment systems and the realization of high-quality economic development objectives.

New urbanization construction is an essential driver for expanding domestic demand and a critical measure to facilitate internal circulation. This paper evaluates the impact of new urbanization pilot projects on the consumption levels of the rural migrant using data from the China Migrants Dynamic Survey. The study reveals that, compared to non-pilot areas, the consumption levels of rural migrants in pilot areas have significantly improved, and a series of robustness checks support this conclusion. Mechanism analysis indicates that the pilot projects have increased income, enhanced access to public services, and strengthened a sense of identity, all of which contribute to the increased consumption levels of rural migrants. The pilot projects have a more substantial effect in regions with low dialect diversity and more effectively raise the consumption levels of employed and intra-provincial migrants. Additionally, the pilot projects have boosted both daily and housing consumption of migrants, with a more pronounced effect in counties and county-level cities. The findings provide theoretical explanation and empirical evidence for establishing a long-term mechanism to expand domestic demand.

In the digital economy era, data has emerged as a new factor of production. However, pervasive data quality issues pose significant challenges to releasing the value of data elements and may potentially become "grey rhinos" for digital economy development. Currently, the field of data science is advancing rapidly, highlighting the pressing need for further consolidation and summarization of research related to data quality. This is essential to effectively support the practice of data quality management and the establishment of reliable data circulation. This paper takes a systematic approach to explore the trajectory of data quality research. By employing a synthesis of diverse methodologies, we conduct a comprehensive review of relevant literature from domestic and international sources during the past 30 years. Our review reveals a logical progression in data quality research, characterized by the interconnected stages of "connotation-theory-method-application". Building upon this, we develop a framework for data quality research. Subsequently, we provide a retrospective summary encompassing the data quality connotation and dimensions, theoretical foundation development, assessment and optimization methods, and influencing factors and value effects. Finally, we explore trends in the development of data quality research and offers insights into future directions.

Nowadays, although global economic rebalancing has made great progress, seeking inclusive growth is still an important issue to be solved. We propose a global value chain-based accounting framework to quantify the global trend of inclusive growth, and further use structural decomposition analysis (SDA) to explore the driving factors accounting for the change of inclusive growth. Finally, considering the deviation between domestic value-added and national income, we also conduct a comparative study on the inclusiveness of global economic growth under the territorial and ownership calibers. We find that the global income gap (especially south-north gap) under the territorial and ownership calibers shows a downward trend, indicating that the inclusive level of global economic growth is improving. However, it should be alert that the global economic inclusive growth measured by national income shows sign of deterioration at the end of the analysis period. Further analysis shows that the input structure, final demand and population jointly contribute to the reduction of the global income gap. Among them, the derivation of value-added ratio between North and South has widened the global income gap, which is offset by the increasingly strengthened intermediate and final trade linkages between North and South. In addition, the expansion of final demand scale is also an important factor to narrow the global income gap. Our paper sheds light on the global economic inclusive growth and its driving factors, and also on how to boost inclusive growth.

Under the background of the “dual credit” policy of promoting the healthy development of new energy vehicles and energy saving and emission reduction of fuel vehicles, a competitive game model including the government, fuel vehicle manufacturers, new energy vehicle manufacturers and consumers is established. The emission reduction R&D investment of fuel vehicle manufacturers is included in the model, and the impacts of the dual credit policy and the government's gradually declining subsidies are theoretically studied. The findings are as follows: 1) Under certain conditions, the gradual decline of government subsidies will be more conducive to the increase of R&D investment of fuel vehicle manufacturers; 2) The impacts of the credit transaction price in the dual credit policy on the emission reduction R&D investment of fuel vehicles and the automobile market demand are non-monotonic. Therefore, under the background of the decline of government subsidies, a low credit transaction price should be set to stimulate the R&D investment of fuel vehicles and stimulate the market demand for new energy vehicles; 3) The impact of the decline of government subsidies on carbon emissions is non-monotonous, and the decline of subsidies will reduce carbon emissions in the automobile market.

Increasing labor income share is the core essence of optimizing the income distribution pattern and achieving common prosperity. This paper examines the impact of local fiscal pressure on the labor income share of enterprises using difference-in-difference method with a quasi-natural experiment of the nation-wide abolition of agriculture tax in 2005. We find that local fiscal pressure significantly reduces the share of labor income of enterprises. Moreover, we find that the negative relationship is more pronounced in small and medium-sized enterprises, regions with lower financial development, regions with lower fiscal self-sufficiency, and firms in labor-intensive industries. Further mechanism analysis shows that fiscal pressure leads local governments to raise tax and non-tax enforcement, increase debt raising, and thus intensify firms' financing constraints. Financing constraints firms cut human capital investment to smooth out fixed asset investment, which in turn leads to a decrease in firms' labor income share. This study not only enriches the research on local fiscal pressure and labor income share of enterprises, but also provides empirical evidence and policy implications on how to improve the primary distribution structure and achieve common prosperity.

Different from the traditional financial sector, science and technology finance can effectively support scientific and technological activities, which is of great significance to enhance our country's independent innovation capacity and achieve high-quality economic development. This paper uses the entropy method to comprehensively evaluate the development level of science and technology finance from four dimensions: resources, funds, financing and output. Based on the panel data of 31 provinces from 2007 to 2021, a spatial econometric model is constructed to empirically test the impact of science and technology finance on technological innovation. It is found that sci-tech finance not only has a significant promoting effect on local technological innovation, but also has an obvious spatial spillover effect. If the spatial spillover effect is not considered, the impact of sci-tech finance on technological innovation will be underestimated. Further research shows that in the eastern region, the direct effect and spatial spillover effect of sci-tech finance on technological innovation are more significant, and sci-tech finance improves the level of regional technological innovation by easing the financing constraints of enterprises and optimizing the industrial structure. The research of this paper provides data support for evaluating the impact of science and technology finance, and also provides policy reference for exploring the path of technological innovation promotion.

The high-quality transformation of the manufacturing industry structure is the key to further stimulate the potential of energy conservation and emission reduction. Taking growth, employment, energy saving and carbon reduction as multiple objectives, and the input-output equation and the goal of carbon peaking as the main constraint conditions, in order to accurately predict the adjustment trend of manufacturing structure, this paper constructs a multi-objective optimization model of manufacturing structure, and uses the dual population coevolution framework to solve it, drawing the following conclusions: Under the premise of carbon peaking, the adjustment of the manufacturing structure can effectively promote the balance, trade-off and coordination among the objectives. As their proportions continue to increase, the communication equipment, computers and other electronic equipment manufacturing, and the instrumentation and other manufacturing will ultimately become the two categories of industries with the largest proportion in the manufacturing industry. The low-carbon and high-quality development of manufacturing industry cannot simply rely on the reduction of energy-intensive production capacity, and its key is to achieve profound low-carbon transformation or structural optimization of raw materials, productive processes, and products.

The question of how extreme weather affects firms' internal governance and executives' self-interested behavior is a key issue in exploring the microeconomic consequences of extreme weather. In this paper, we empirically examine the impact of extreme precipitation on executives' opportunistic stock selling behaviors using data matching weather conditions and listed firms in each prefecture-level city from 2010 to 2020. It is found that the occurrence of extreme precipitation leads to undervalued firms, reduced stock liquidity, and more severe financing constraints, and executives' opportunistic share reduction behavior is less rewarding and potentially more risky. Thus, extreme rainfall has a dampening effect on executives' opportunistic stock selling behaviors. Further research finds that the dampening effect is more pronounced in firms that are more geographically concentrated and have less media coverage. This paper expands the external governance mechanism of executives' opportunistic stock selling behavior from the perspective of extreme weather and further enriches the research boundary of the economic behavior of micro firms, which is of significance to the understanding of the economic consequences of extreme weather.

Under the background of the accelerated reconstruction of the global industrial chain and supply chain, the United States tries to implement the friend-shoring and near-shoring strategy to reduce the dependence of its industrial chain and supply chain on China. Economies such as Southeast Asia and Mexico have become the main destination of China's industrial transfer, which is bound to have a negative impact on the impact scope, profitability and risk resistance of China's industrial sector in the global value chain. This paper uses the trade data of intermediate goods from the multi-regional input-output (MRIO) database to construct the global production network model, and extract the real network (null model) and artificial network (counterfactual model) that reflect the backbone of the global value chain from different perspectives, respectively. On this basis, it analyzes the potential impact of the United States' trade policy towards China on the restructuring of the global production network and the relocation risk of China's industrial chain. The results show that the friend-shoring strategy of the United States relying on Altasia and the near-shoring strategy relying on the United States-Mexico-Canada Agreement, and Canada will lead to the partial decoupling of the industrial chain and supply chain in the global scope, and moreover, the friend-shoring strategy has intensified the trend of economic anti-globalization and the risk of relocation of China's industrial chain. Finally, this paper puts forward policy suggestions to improve the resilience and security level of China's industrial chain and supply chain under the background of the United States' de-risking China-reliant supply chains.

This paper empirically examines the relationship between customer enterprises' ESG rating and supplier enterprises' green innovation, using all A-share listed companies from 2009 to 2022 as the research samples. The empirical results show that customer enterprises' ESG rating can positively influence supplier enterprises' green innovation; customer enterprises reduce the amount of funds absorbed from supplier enterprises, encourage supplier enterprises to increase innovation investment, and improve the managers' green cognition of supplier enterprises are the three mechanisms of promoting supplier enterprises' green innovation through customer enterprises' ESG rating; supplier enterprises' market power will negatively moderate the positive relationship between customer enterprises' ESG rating and supplier enterprises' green innovation. Heterogeneity analysis shows that the positive influence of customer enterprises' ESG rating on supplier enterprises' green innovation is more significant both when customer enterprises are under greater legitimacy pressure or have more substantive ESG practices, and when supplier enterprises lack credibility or face stricter environmental regulations. Further research shows that customer enterprises' ESG rating is more effective in promoting supplier enterprises' green innovation when the uncertainty of ESG rating results is low, and that supplier enterprises' green innovation contributes not only to supplier enterprises' own ESG rating but also to supplier enterprises' total factor productivity. This paper highlights the spillover effects of ESG rating pressure from the perspective of supplier enterprises, and provides empirical evidence and management enlightenments for effectively promoting enterprise green innovation.

Based on the daily stock data of China's A-share main board market from 2012 to 2020, this paper establishes an unbalanced panel spatial Durbin model (SDM) with time-varying spatial weight matrices to study the spillover effect of price limit hits. The empirical results suggest that the upper price limit hit (lower price limit hit) can predict the future return of the connected stocks negatively (positively), indicating a significant negative spillover effect (positive spillover effect). This study further finds that under the influence of the price limit hits, there may be a substitution effect of liquidity between connected stocks. The upper price limit hit of a stock can increase its own capital inflow, while the capital outflow of other related stocks may increase. The situation of the lower price limit hit is the opposite. In addition, due to speculative traders, the higher the limit of arbitrage of a stock is, the stronger the spillover effect caused by its price limit hit will be. Finally, the price limits have a significant volatility spillover effect on other stocks in the short-term future.

Aiming at the problem of high similarity and low degree of discrimination between fraudulent samples and normal samples and the confusion of marginal normal samples in medical insurance fraud identification, this paper proposes a medical insurance fraud identification algorithm based on isolation loss and deep autoencoder (ISDAE). Aiming at the easy isolation of marginal fraud samples and sparse fraud samples, the algorithm proposes a sample isolation measure to quantitatively analyze the differences between the two types of samples from the perspective of feature distribution. On the basis, using DAE's ability to mine linear and nonlinear features of medical insurance and considering the interference of margin normal samples on model training, an isolation loss is defined in the latent space to achieve the aggregation of center normal samples and the separation of edge normal samples, thereby increasing the difference between fraudulent samples and normal samples. To further improve the fraud detection performance of the model, the fraud degree of samples is evaluated by integrating the isolation value and the reconstruction error. Finally, the performance of the proposed algorithm is verified on the Tianchi medical insurance dataset. The results show that the overall fraud identification performance of the proposed ISDAE algorithm is better than the comparative methods, and its performance is more stable.

To systematically explore the impact of regional synergistic development on urban sprawl, this paper firstly constructs a theoretical framework of regional synergistic development on urban sprawl; Subsequently, the fixed effects model, threshold effects model, spatial measurement model and spatial threshold model were used to reveal the effects and non-linear mechanisms of regional synergistic development on urban sprawl, as well as the spatial threshold effects and spatial spillover boundaries of regional synergistic development on urban sprawl at different stages. The results show that: 1) Regional synergistic development has an inhibitory effect on urban sprawl. On this basis, the threshold effect indicates that the relationship between the two has a non-linear characteristic of "first promoting, then inhibiting, and then strengthening the inhibitory effect", and is constrained by the thresholds of population mobility, industrial development, environmental concerns and transportation construction. 2) The increase in the level of regional synergistic development of the local region will exacerbate the phenomenon of urban sprawl in the neighboring regions, which has the obvious characteristic of "beggar-thy-neighbor", but the boundary of the spatial effect of the attenuation is only 280 km. 3) As the level of regional synergistic development increases, its inhibitory effect on local urban sprawl will continue to increase, while its facilitating effect on urban sprawl in neighboring areas will continue to decrease. 4) The spatial spillover effect of regional synergistic development on urban sprawl at different stages shows a wavy spatial distance decay characteristic, and the radiation boundary shrinks as the level of regional synergistic development increases.

Using the survey data collected from rural households in Ningxia, Chongqing, and Sichuan provinces, this paper has identified the credit risk and measured the risk loss, under the context of land property rights controlled and the imperfect ecology of rural finance market in China. This paper uses machine learning method to identify farmers' credit risk and verifies the effectiveness of this method compared with the traditional model. Also, Credit Risk+ model is employed to evaluate farmers' credit risk. According to the survey statistics, the default rate of farmers' farmland management right mortgages is relatively high, and it was 10%. Results show that the random forest model could identify the key factors of credit risk and predict the default probability effectively. Moreover, the expected loss and risk exposure of each loan is relatively high, and the risk loss increases rapidly under the impact of extreme events. In addition, it is helpful for financial institutions to optimize the financial capital structure and improve the risk management strategy to increase the investigation of farmers' passive default motivation under the prior risk management framework. Thus, we conclude with several policy implications such as the accelerating development of fintech, improvement of rural credit investigation system, and innovation of risk pre-warning tools.

In the real world, the spreading of infectious diseases is commonly co-occurring with the competitive diffusion of relevant information (or "knowledge") and misinformation (or "fallacy"). This competitive diffusion has, in turn, remarkable effects on the spreading of infectious diseases, posing great challenges to the studies of the mechanisms of epidemic transmission and the prevention and control of public health emergencies. To overcome the deficiency on the studies on the coupled dynamic models of competitive information diffusion and disease spreading, a coupled dynamic model on multiplex networks is proposed to examine how the competitive diffusion of knowledge and fallacy influences the time-scale and range-scope of disease spreading. By comprehensively utilizing the dynamic system analysis based on the microscopic-Markov-Chain-approach (MMCA) and the simulative analysis, the results indicate that the information diffusion significantly affects the spreading of infectious diseases. The group cognitive level affects the spreading of infectious diseases by influencing the competitive diffusion of knowledge and fallacy. In particular, the prevalence time of knowledge and fallacy in the information layer and the initiation time for knowledge diffusion are crucial for the spreading of infectious diseases. The findings in this study may shed some light on guiding the precise prevention and control of epidemics.