In recent years, with the significant increase of various security risk events, the supply chain of a large number of enterprises has been impacted or even interrupted. Supply chain resilience has become the common focus of academy, industry and government. From the perspective of single and multiple configurations, this paper constructs research models for the influencing factors of supply chain resilience. Based on 622 valid samples of enterprises, this study applies structural equation model (SEM) and fuzzy set qualitative comparative analysis (fsQCA) for empirical analysis. The research shows that: 1) Flexibility, agility, reconfiguration, visibility and supply chain cooperation can have positive impacts on supply chain resilience. 2) High flexibility, high agility, high reconfiguration, high visibility and strong cooperative relationship cannot be the necessary conditions for high supply chain resilience alone. 3) There are three driving configurations for high supply chain resilience, namely, high agility configuration consisting of agility * reconfiguration * supply chain cooperation, high visibility configuration consisting of ~flexibility * reconfiguration * visibility * supply chain cooperation, and agile visual dual configuration consisting of ~flexibility * agility * visibility * supply chain cooperation and flexibility * agility * visibility * reconfiguration. The high supply chain resilience is the synergy of multiple factors, and the effective combination of various factors promotes the supply chain resilience in the way of "different paths lead to the same goal". This research systematically discusses the influencing factors of supply chain resilience, which can provide theoretical guidance and managerial insight for enterprises to improve supply chain resilience.

High-quality development focuses on total factor productivity. As a pioneer and demonstration zone of China's economic development, it is of great practical significance for national high-tech zones to effectively play a driving role in the region. Therefore, based on the data of Chinese prefecture-level cities from 2003--2018, the green total factor productivity was calculated as a measure of high-quality development. To alleviate the bias of the traditional DID model due to the neglect of policy spatial spillover, we constructed a spatial DID model to analyze the effect of the national high-tech zones on the green total factor productivity of local and neighboring cities. The results showed that the national high-tech zones increased the green total factor productivity. This policy had a clear promotion effect on cities without a national high-tech zone, and the effect was related to the original development level of the city and the spatial distance between cities; however, the cities with national high-tech zones has not shown a "strong team" or a "race to the top" spatial connection. In addition, the impact of national high-tech zones on regional green total factor productivity worked mainly through improving the regional innovation and entrepreneurship environment. Based on this, we suggest that the high-tech development highlands should to be created with national high-tech zones as the nodes, and the diversified regional cooperation system of national high-tech zones should to be built by breaking down the administrative boundaries.

In the context of the "double carbon" target, promoting the green and low-carbon transformation of economic and social development is a major systemic project. Developing renewable energy and improving energy efficiency will help to build a more efficient green energy system. Analyzing the effect of energy transformation has important reference value for formulating a reasonable carbon emission policy and achieving medium and long-term emission reduction targets. This study takes this as a starting point. Firstly, static panel and dynamic panel system generalized method of moments (GMM) are used to estimate the impact of energy transformation, renewable energy efficiency and non-renewable energy efficiency on major macroeconomic variables. Secondly, the intermediate production sector is subdivided into renewable energy production sector and non-renewable energy production sector. The dynamic stochastic general equilibrium (DSGE) model is constructed to analyze the short-term impact of energy transformation impact, renewable energy efficiency impact and non-renewable energy efficiency impact on major macroeconomic variables. The analysis shows that: 1) energy transformation promotes the transfer of resources between sectors, the output of renewable energy production sector will increase, while the output of non-renewable energy production sector and carbon emissions will decrease; 2) The improvement of two kinds of energy efficiency will produce economic expansion effect, but it will also produce energy rebound effect and increase carbon emissions; 3) At the end of the simulation period, the implementation of the carbon emission intensity policy will promote the growth effect of three shocks on output, but will also hinder the emission reduction effect and aggravate the rebound effect in the process of energy transformation. The implementation of the carbon tax policy will inhibit the rebound effect of two types of energy efficiency shocks on carbon emissions. In the process of energy transformation, we should rely on a reasonable carbon emission policy and formulate medium and long-term emission reduction targets. This study has important reference value for China to analyze the effect of energy transformation.

Climate damage and adaptation are key modules in the integrated assessment modelling on climate-economy system, both of which will directly affect the stringency of climate policy. This paper explores the recent academic advancement in these two aspects. As for climate damage, an emerging strand of literature not only focuses on the overall impact of rising temperature on economic production, but also sheds more spotlights on how rising temperature can cause economic losses through shocks to capital stock, labor supply, technical change and natural capital. Although recent studies illuminate directions for improving damage function under varying degrees of temperature rise, enormous disputes still hang over the concrete settings of the damage function. Existing climate-adaptation models commonly resort to either adaptive investment or market mechanisms. However, additional examinations should be warranted of related constraints on adaptation to avoid overestimating the effects of climate adaptation, as well as the regional heterogeneity in adaptation strategies. Future research should take into account social damages caused by climate change, other climate risk characteristics in addition to rising temperature, and how they channel corresponding effects. Furthermore, more empirical studies are needed to help refine the constructions and calibrations of the damage function, and probability tools are called for to investigate the uncertainties of climate damage and adaptation, in a shared effort to provide references for guiding climate policy practices.

It is of great theoretical and practical significance to accurately model and forecast the volatility of financial assets in the complex and changeable financial market environment. Therefore, based on a variety of volatility decomposition methods, and embedded with the Markov regime-switching approach, this study reconstructs multiple new heterogeneous autoregressive realized volatility models, and further takes Shanghai Stock Exchange 50ETF as the research object to compare the prediction accuracy of each model. The main empirical results are as follows. First, the model confidence set (MCS) test shows that the newly constructed model (MS-PHAR) combined with Markov regime-switching and quantile array volatility has the best predictive performance and various robustness checks confirm the above conclusion. Second, during the periods of high and low volatility, before and after the COVID-19 epidemic, and considering the leverage effect, the newly constructed MS-PHAR model still has a good performance.

In light of recent events such as "sweatshops", "environmental pollution", and "child slave labor", it has become imperative for enterprises to shift their focus from solely pursuing short-term economic gains to fulfilling social responsibilities in order to achieve sustainable and high-quality development. Focusing on how to coordinate the participation of brand firms and suppliers in fulfilling the social responsibilities of the upstream supply chain and taking account of the prosociality and reference effects of consumers, we use differential game method to build the decision-making model of decentralized decision-making, centralized decision-making, and unilateral cost-sharing contract between brand firms and suppliers. Furthermore, we design the bilateral cost- and revenue-sharing contract to achieve perfect coordination of the supply chain. The results suggest that: 1) An increase in the proportion of prosocial consumers will prompt brand firms and suppliers to improve their efforts of fulfilling social responsibility. However, excessive reliance on brand reputation to determine the level of social responsibility performance of the upstream supply chain may reduce the willingness of supply chain members to fulfill their social responsibilities. 2) The unilateral cost-sharing contract encourages suppliers to improve the efforts of fulfilling social responsibility, but do not affect the brand firm's efforts of fulfilling social responsibility. The contract stimulates the improvement of brand goodwill and consumer reference prices, thus promote the increase of profits for brand firms and suppliers. Moreover, when the reference effect for the level of social responsibility fulfillment of the upstream supply chain has a significant impact on the formation of consumers' reference price, the reference price under this contract will instead be higher than the centralized decision-making model. However, the contract is difficult to promote brand firms and suppliers to jointly improve social responsibility performance, and cannot maximize the total profit of the supply chain. 3) When the revenue sharing ratio of brand firms is at a moderate level, it can promote both brand firms and suppliers to participate in a bilateral cost- and revenue-sharing contract, and coordinate the supply chain perfectly.

To address the issues of information misrepresentation, false propaganda, and supervision difficulty in the e-commerce supply chain consisting of brands, MCNs, and e-commerce platforms under the background of “Live streaming+”, this paper first establishes a three-party game model based on evolutionary game theory, and then analyzes each player's game behavior and evolutionary stability strategy. Second, numerical simulation is used to investigate the influences of some key factors on the evolutionary trend of the dynamic system and its evolutionary stability strategy in terms of lower, medium, and higher return rate. It has been discovered that the standardized operation of the live streaming e-commerce supply chain is influenced by multiple factors. Under the lower return rate, no matter whether the e-commerce platforms supervise actively or not, brands and MCNs tend to operate in violation; under the medium and higher return rate, higher latent reputation loss, lower false propaganda factor, and lower trending channel effect would promote this system to evolve to the desired stable state. Finally, this paper puts forward constructive suggestions for the live streaming e-commerce supply chain to achieve standardized operations according to the practical operations.

Integrating the DY spillover index and BK spillover index methods, this paper examines the time-frequency spillover effects between climate policy uncertainty, energy and metal markets, and constructs a spillover network model to portray the cross-market risk contagion paths between climate policy uncertainty, energy and metal. The results show that there are significant spillover effects between climate policy uncertainty, energy and metal markets, and they are mainly high-frequency spillovers. The spillover effects between climate policy uncertainty, energy and metal markets are time-varying and vulnerable to extreme emergencies. In the event of extreme contingencies, low-frequency spillovers can overtake high-frequency spillovers as the main driver of spillovers between climate policy uncertainty, energy and metal markets. In different frequency domains, clean energy markets are the exporters of spillovers and conventional energy markets are the recipients of spillovers. In addition, climate policy uncertainty plays an important nodal role in the cross-market spillover mechanism, and cross-market risk is transmitted along the path of “clean energy → metal markets → traditional energy”, fueled by climate policy uncertainty.

With the explosive growth of investable assets and asset information, portfolio selection faces the dual challenges of high dimensionality in both assets and characteristics. This paper proposes a portfolio selection framework based on machine learning and asset characteristics. Leveraging the inherent advantages of machine learning, the framework utilizes asset characteristics to directly predict portfolio weights, bypassing return distribution prediction in the conventional two-step portfolio management paradigm. The framework is applied to asset allocation research in the Chinese stock market. The research results show that: 1) The proposed investment strategies capture incremental information within high-dimensional characteristics and uncover both linear and non-linear relationships between asset characteristics and portfolio weights, resulting in a significant enhancement of investment performance. 2) Trading friction-related characteristics are the most important indicators for predicting portfolio weights. 3) These strategies yield higher returns on stocks with stricter arbitrage restrictions while exhibiting lower sensitivity to changes in macroeconomic conditions. Under other economic constraints, these strategies remain robust. This paper expands the research framework of modern portfolio theory, contributing to the development of artificial intelligence and quantitative investment.

Agency Theory (AT) is widely accepted and used for its simplicity. However, the mechanism proposed by AT to reduce agency costs has yet to be unanimously supported, which has led to controversies. To address the rigid assumptions' shortcomings, behavioral agency theory (BAT) revises the idealized risk assumptions in AT from a cognitive perspective by combining governance mechanisms, problem framing, and decision-making. After analyzing the reasons for the failure of the AT mechanism to reduce agency costs, BAT systematically depicts the logical basis of behavioral decision-making by introducing individual cognition. At the same time, BAT's portrays the “inner activities” of agents' risk-taking when facing internal governance and external factors, which provides a novel behavioral perspective for strategy and governance research. BAT also improves theoretical predictability, which is particularly suitable for studying differences in corporate governance in China due to institutional and cultural differences. Compared with European and American studies, domestic scholars have paid less attention to BAT, needing more systematic theoretical reviews and leaving a massive gap in its application. Therefore, this paper first sorts out BAT's origin and defines its core issues. Second, the paper reviews the literature on four topics according to its original theoretical framework: 1) how does problem framing affect decision-making cognition, 2) whether the incentive alignment is helpful in stimulating agents to take the risk, 3) whether monitoring is an effective governance mechanism, and 4) the expansion and application of BAT in the family business research, to clarify the research boundary. Finally, this paper puts forward suggestions on how to adapt the future research direction and theory to the Chinese situation to improve the development prospect of the theory and provide a reference for scholars to deepen their research further.

There are great differences between domestic and foreign enterprises in terms of business decisions, sensitivity to the international economic patterns, etc., which leads to their completely different characteristics in participating in the international industry relocation. Therefore, with the frequent outbreak of international emergencies that cause deep adjustment of global value chain, clarifying the heterogeneity of domestic and foreign enterprises in the international industry relocation will be an important prerequisite to promote the "dual circulation" development pattern and ensure the security of supply chain. This paper proposes a quantitative model to measure the magnitude of industry relocation that distinguishes between domestic and foreign enterprises. Based on that, the empirical study captures the scale, mode, industry heterogeneity and mutual substitution between China's domestic and foreign-funded enterprises in participating in international industry relocation during 2005--2016. The empirical evidence finds that: 1) From the magnitude perspective, both domestic and foreign enterprises in China are generally receiving production activities. However, the growth of relocation slowed down after 2014, followed with the trend of relocation outward. The magnitude of the international industrial relocation of domestic enterprises has always been about 80.0% of the total. However, in terms of the ratio of industrial relocation to output, domestic enterprises have always been much lower than foreign enterprises, and the difference reached 14.1 percentage points in 2005-2016. 2) From the mode perspective, domestic enterprises mainly participate in international industry relocation through intermediate products, while foreign enterprises participate more through final products. 3) From the industry perspective, domestic enterprises is dominated by the capital-intensive manufacturing, while foreign enterprises mainly focus on technology-intensive manufacturing and producer services. 4) Generally, China's domestic enterprises have a strong substitution effect on foreign enterprises in China. However, a "reverse substitution (foreign enterprises substitute domestic enterprises)" is continuously taken place in the technology-intensive manufacturing.

Based on the two-dimensional Hotelling model, this paper builds a game model that simultaneously considers the differentiation of platforms and merchants, to explore the adoption of different exclusive strategies by dominant platforms and the impacts of such strategy. The results show that, there are two types of exclusive strategies, namely monopoly-driven and differentiation-driven exclusivity. The monopoly-driven exclusivity can be promoted by low commission rates of strong platform, low horizontal differentiation between platforms, high vertical differentiation between platforms, and high horizontal differentiation between products; Otherwise, the differentiation-driven exclusivity will be strengthened. Second, the differentiation-driven exclusivity is also beneficial for weak platforms. To avoid the monopoly-driven exclusivity, weak platforms can increase horizontal differentiation between platforms and reduce vertical differentiation or commission rates. Finally, fierce competition among merchants can stimulate the differentiation-driven exclusivity implemented by dominant platforms, which in turn reduces competition among merchants and improves their profits. Overall, the research clarifies the drivers of exclusivity strategy of dominant platforms and distinguishes the influences of different exclusivity strategies on both platforms and merchants, providing strong policy implications for the regulation of dominant platforms and anti-monopoly in the platform industry.

This paper uses the data of A-share listed companies in China during 2010-2019, and investigates the impacts of TMT faultlines on corporate social responsibility (CSR) by unbalanced panel fixed effect models. The results show that TMT faultlines have a significant negative impact on CSR. TMT faultlines negatively affect internal, external and positive CSR rather than negative CSR. TMT task-faultlines significantly reduce CSR, while TMT bio-faultlines have no significant effect on CSR. Corporate internal governance environment has a significant moderating effect on the relationship between TMT faultlines and CSR. CEO power intensifies the negative effect of TMT faultlines, while CSR committee and top management diversity inclusiveness weaken the negative effect of TMT faultlines. TMT faultlines can inhibit CSR by increasing agency costs and decreasing internal control quality. This paper reveals the importance of TMT construction and regulatory governance from the perspective of CSR, and provides empirical evidence for governments to formulate and improve corporate governance policies, and for firms to improve their social responsibility and enhance sustainable competitiveness.

Under the real demand that Chinese manufacturing industry is advancing to the high end, servitization empowered by digital technology has become an important strategy for manufacturing enterprises to achieve high-quality development, which can stimulate the innovation vitality and create new development opportunities, enabling them to provide customers with intelligent solutions that integrate products, software and services. This study firstly collects foreign and domestic literature that is closely related to digital technology and servitization, selects to form a sample database, and constructs a theoretical analysis framework. Secondly, on the basis of introducing the servitization and digital technology, the evolution trend of the digital servitization is revealed, and the realization approach of the empowerment is analyzed. Thirdly, based on the division of the value chain of manufacturing enterprises, this study expounds the application scenario of servitization empowered by digital technology from the perspective of front-end product innovation, middle-end hybrid product generation and back-end service innovation. Finally, the "double-edged sword" effect of the empowerment with potential value and risks is analyzed, the countermeasures and suggestions are put forward, and the future research directions of this topic are provided.

This study constructs the digital innovation index of A-share listed companies from 2008 to 2020, and empirically examines the impact of the "specialization effect of intellectual property (IP) judicial protection" brought by the establishment of IP courts on corporate digital innovation. We find that: 1) the establishment of IP courts has a significant positive effect on digital innovation in companies; 2) the establishment of IP courts mainly motivates digital business model innovation in companies; 3) the establishment of IP courts promotes digital innovation in companies through mechanisms such as optimizing the judicial environment, reducing spillover losses, and alleviating external financing constrains; 4) the promotion effect of the establishment of intellectual property courts on digital innovation is more pronounced in small, non-state-owned, and low-competition industry firms; 5) the establishment of IP courts significantly increases the market value of firms' digital innovation (especially digital business model innovation).

Improving enterprises' technological innovation capacity is the key to the high-quality development of China's economy and the improvement of China's core competitiveness. This paper incorporates digital finance and corporate risk-taking into an endogenous growth model that includes the financial sector, as well as deduces and analyzes the mechanism by which digital finance drives enterprise technological innovation from a risk-taking perspective. On this basis, the empirical test is carried out using data of A-share listed companies from 2011 to 2020. It has been discovered that corporate risk-taking is an efficient channel for encouraging technological innovation in businesses. This paper attempts to collect relevant data using crawler technology in order to construct a digital financial development index, and it confirms that digital finance plays a significant role in increasing patent applications through corporate risk-taking. Furthermore, according to heterogeneity analysis, digital finance improves the risk-taking level of high-tech enterprises, enterprises with CEOs with a background in R&D, enterprises with low financial supervision, low financial development regions, and high reliance on external financing, and significantly promotes R&D innovation activities. The study expands the mechanism of digital finance's impact on enterprise technological innovation and provides critical insight for corporate governance and regulatory system design.

Data ownership can either be considered as an indivisible monistic right or separated into ownership and usufruct, but the economic significance of data ownership and usufruct separation remains controversial. Digital enterprises' data-based services incentivize users to provide data, but also result in loss of privacy for users through personalized pricing. This paper constructs a monopoly firm model to explore the impact of data collection behavior and welfare under the definition of lack of usufruct and possession of usufruct when there is personalized pricing and privacy loss. The study finds that without usufruct, data collection will not occur if the privacy cost is high, but excessive data collection will occur if the privacy cost is low. When the collector has the initial usufruct and the user has ownership of the data, efficient data collection can be achieved, improving user surplus and social welfare. Data ownership only affects the distribution of social welfare between the collector and user. Therefore, we should consider the right definition framework of data ownership and usufruct separation and discuss the ownership of data usufruct in different scenarios. When the privacy cost is low, data collectors should be granted usufruct, and users should be allowed to exercise ownership through the "deletion right" and other ways to improve social welfare and user surplus. When the cost of privacy is high or users underestimate the cost of privacy, the method of prohibiting data collection should be adopted to protect sensitive data, rather than confirming rights.

The paper proposes the LOU-RV-HAR pairs trading strategy by the Lévy process of the double-exponential compound Poisson distribution to capture the jumps of stock pairs spread, the Ornstein-Uhlenbeck (OU) process to characterize the mean-reversion, stock pairs selection with the mean-reversion spread and realized volatility (RV), and the heterogeneous autoregressive (HAR) model to predict the volatility of the spread. The empirical results of the five-minute high-frequency data of the constituent stocks of the CSI 300 index show the LOU-RV-HAR strategy achieves a better pairs trading performance and the Sharpe ratio is 1.6072, greatly exceeding performance of the CSI 300 index during the same period. Comparing with the four comparative trading strategies established by adjusting the spread model, stock selection method and trading threshold, the annualized return and Sharpe ratio of the LOU-RV-HAR strategy are better than those of the comparative strategies. Further analysis shows that the LOU-RV-HAR strategy displays robust results in different market conditions or different trading thresholds, and the overall pairs trading performance of CSI 300 component stocks is higher than the performance of sub-industries.

This article aims to explore the impact of the internet on income inequality among rural households. Through the analysis of data from China Family Panel Studies, it is found that although the internet can significantly alleviate the inequality in total income and wage income among rural households, its effect on alleviating inequality in entrepreneurial income is limited, and it may exacerbate inequality in household property income. Based on this finding, this article analyzes the mechanism of its impact from the perspective of household income sources, revealing that the internet mainly reduces the wage income gap by pulling rural labor force into the non-agricultural sector, thereby alleviating household income inequality. Meanwhile, households with original capital accumulation are more likely to benefit from the internet, which exacerbates property income inequality. In addition, this article introduces the causal forest algorithm and, from the perspective of human capital, analyzes the heterogeneous effects of the internet on individual-level inequality in wage income and property income among rural households. The results show that the alleviation of wage income inequality is mainly manifested in households with low human capital, while the exacerbation of property income inequality is mainly manifested in households with high human capital.

With the decreasing cost of intelligent capital compared to the labor costs of medium-skilled workers, artificial intelligence (AI) is poised to replace jobs in the middle-skilled segment, leading to labor market polarization. This article constructs a dynamic multi-sector general equilibrium model to compare three strategies to cope with this phenomenon: 1) improving the labor productivity of medium-skilled workers, 2) transitioning medium-skilled workers into low-skilled roles, and 3) upskilling medium-skilled workers into high-skilled positions. Findings reveal that all three strategies can mitigate wage polarization, but transforming medium-skilled workers into high-skilled workers can enhance the overall labor force skill level, reduce income inequality, and promote quality employment and shared prosperity. Automation of high (low) skill tasks will decrease the wages and labor income share of high (low) skilled workers, while the creation of high (low) skill tasks will increase their wages and labor income share. The government increasing the proportion of investment in new infrastructure and reducing the proportion of investment in education can increase total social output, but it will intensify wage polarization. The government increasing the proportion of investment in education and reducing the proportion of investment in new infrastructure will help reduce income inequality, but the economic growth effect will not be as good as Invest in new infrastructure.

The change of trade cost in services affects the cross-border flow of service elements, and under the division of global value chains, it can influence the production cost and final product price of each country through the input-output linkages and then affect the welfare of consumers. Based on WIOD database, this paper firstly calculates the level of China's trade cost in services from 2000 to 2014. On this basis, using global input-output price model and consumer welfare model, this paper examines the impact of the change of China's trade cost in services on consumer welfare in different countries from the perspective of equivalent variance and compensating variance. The results show that China's trade cost in services showed a downward trend from 2000 to 2014, with the most obvious decline in air transportation and financial services. The price effect of the change of China's trade cost in services on manufacturing industry is higher than that of service and agriculture, and the effect on knowledge-intensive manufacturing industry is the highest, followed by capital-intensive and labor-intensive manufacturing industries. The analysis of consumer welfare shows that the change of China's trade cost in services has improved consumer welfare of all countries, and it has brought more obvious welfare improvement to the United States, Japan, South Korea and Germany besides itself and the rest of the world. In terms of detailed service sector, distribution, postal transportation and finance and commerce services have the largest welfare effect among all services industry. Furthermore, international comparison shows that the welfare improvement to the rest of the world brought by the change of China's trade cost in services was about 3.3 times as much as that by the Unites States from 2000 to 2014, and China shows greater positive externality and provides more universal benefit to the world than the United States, Japan and the European Union. This paper can provide policy reference for further promoting the service trade openness and strengthening mutual cooperation among countries with the consensus of the community with a shared future for mankind.

Against the backdrop of economic globalization, the rapid advancement of cutting-edge digital technology has catalyzed a new wave of technological revolution. The AIGC technology, represented by ChatGPT, disrupts the technical landscape of traditional artificial intelligence. And it is widely embraced for its enhanced human-like functionalities, thus emerging as a pivotal milestone in the advancement of general artificial intelligence. Through the analysis of ChatGPT's impacts on the education and employment market, this research reveals that the implementation of AIGC technology can enhance social value exchange efficiency and invigorate the education and employment market. However, it also gives rise to legal and ethical concerns such as data privacy infringement. Therefore, management and supervision recommendations are proposed to address potential risks in order to ensure seamless operation of the economy and society.

At the city level, this paper uses a quasi-natural experiment to study whether green performance appraisal motivates local governments to improve air quality, and then measures the efficiency of urban air pollution control based on super-SBM model, and further identifies the influencing factors of the efficiency of air pollution control. The empirical results show that the performance assessment of air pollution control significantly promote local governments to improve air quality, and the average annual PM$_{2.5}$ concentration of experimental cities decreased by 3.38% more than that of control cities. Secondly, in recent years, the efficiency of air pollution control in China has gradually declined, especially in the central and western regions. While foreign investment has a negative impact on air pollution control efficiency, the development level of science and technology service industry has a positive impact on air pollution control efficiency, and the impact of science and technology investment level is not significant. Therefore, this paper proposes that China should maintain the performance appraisal system of air pollution control as a long-term system, and raise the admittance threshold of “two high” type industries in air pollutant discharge, so as to promote local governments to control air pollution. In addition, the city needs to increase investment in green science and technology and vigorously develop science and technology services to promote the green transformation of the city.

Based on the theoretical framework of multiple competing platforms, two forms of exclusive contracts are investigated: Traditional exclusive contracts and “pick one of two” contracts. We distinguish the differences in the incentives of the dominant platform to use these contracts, and analyze the impact of the different forms of exclusive contracts on market competition and the revenues of market participants. Our study shows that the degree of differentiation between platforms and between sellers are the core factors in determining the incentives for the dominant platform to use different forms of exclusive contracts and the impact on market participants. When the degree of differentiation between platforms and between sellers are both small, the dominant platform uses traditional exclusive contracts, while when the degree of differentiation between sellers is large, the dominant platform uses “pick one of two” contracts. Although both exclusive dealings reduce consumer surplus and social welfare, the impact on profits of other competing platforms and sellers is uncertain. Traditional exclusive contracts can reduce the profits of all competing platforms, whereas “pick one of two” contracts can reduce the profits of all sellers. This study provides a theoretical explanation for the use of different forms of exclusive dealing of platforms.

Various companies that once focused on online sales channels have considered expanding offline channels. In particular, their possible channel development strategies include no offline, direct, or indirect offline channels. By constructing a Stackelberg model, we study the offline channel development strategy of a supplier who only sells online through an e-commerce platform. As a result, we obtain the supplier's optimal offline channel development strategy and corresponding pricing decisions by comprehensively considering different online sales modes, consumer preferences about different channels, and sales costs in different channels. The findings show that the supplier should always extend the offline channel. In addition, the supplier's existing online sales mode vigorously influences his offline development strategy. Specifically, the supplier's optimal strategy is always developing the offline direct channel if the existing online sales model is direct sales. Alternatively, if the existing online model is indirect sales, his offline development strategy depends on the sales costs of different channels. When the sales cost of the online channel is higher, or the online and offline channel sales costs are both lower, the supplier's optimal strategy is offline direct sales. However, when the sales cost of the online channel is low, and the sales cost of the offline channel is high, the supplier's optimal strategy is offline indirect sales.

Understanding the driving factors of China's power sector decarbonization and the role of carbon emissions trading scheme (ETS) in the process of power sector decarbonization can help to formulate and improve policies related to power sector decarbonization to fulfill China's commitment to the international community. Based on a self-developed power sector $\rm CO_2$ emissions dataset, this study conducts a decomposition analysis of the driving factors of China's power sector $\rm CO_2$ emissions changes from the perspective of ETS implementation and analyzes the mechanism of these driving factors in the process of ETS promoting decabonization in power sector. The results show that the accelerated decarbonization process of China's power sector after the implementation of the ETS is mainly due to the slowdown in economic growth, the continuous optimization of the power generation structure, and the gradual increase in the efficiency of power generation and power consumption. The ETS has accelerated the process of decarbonization of China's power sector, and it mainly works by promoting the efficiency of power generation and electricity consumption. The research conclusions can clarify the priority and focus of policies related to decarbonization of China's power sector in the context of the ETS construction.

The Report to the 20th National Congress of the Communist Party of China especially emphasized that the pursuit of common prosperity for all the people should be integrated into the process of modernization. By constructing the social accounting matrix of China's rural residents' consumption, this paper simulates the changes of the consumption of social goods and services and the Gini coefficient of rural residents' consumption under different distribution policies, so as to explore the distribution policy path to promote the common prosperity of rural residents. The results show that: Expanding the distribution policy of the middle and support the weak can not only promote the growth of social goods and services consumption, but also control the consumption gap of rural residents within a reasonable range, which is the relatively better choice, while the absolutely fair and absolutely efficient distribution policy is the relatively inferior choice; The policy simulation showed that consumption of education, culture and entertainment and health care increased the most, while consumption of food, tobacco and alcohol decreased, indicating that effective distribution policies are conducive to the consumption upgrading and transformation of rural residents; the primary distribution system is the leading mechanism to promote the common prosperity of rural residents, the redistribution system is an important means to promote the common prosperity of rural residents, and the third distribution system is a beneficial supplement. To this end, the paper puts forward the following policy suggestions: Improve the income distribution system, promote the realization of common prosperity; narrow the income gap between residents and promote the prosperity of farmers; we will improve the social security system and improve people's wellbeing.

Using natural language processing (NLP) techniques to gain key information from unstructured data, such as corporate texts, news coverage and self-media language, to do financial and economic research which has attracted extensive attention from numerous scholars in recent years and a wealth of research literature has existed. This paper summaries the latest research progress on the application of NLP in financial problems to expatiate text analysis methods using NLP techniques, and focuses on literature about how to use annual reports and news text to study issues in financial areas including corporate finance, asset pricing, risk management, macro-finance and green finance. We evaluate some rough edges in the existing research literature and provide certain research directions for further research in the end.

Based on the customs trade database from 2000--2015, this paper identifies Chinese firms' tendency to export competitive strategies and examines the impact of internal and external product networks on firms' changing competitive strategies and their mechanisms. It is found that firms generally adopt cost-competitive strategies to participate in exports, but firms can reduce their cost-competitive tendencies by converging on internal and external networks. And when both convergence levels reach a high level, firms can shift from cost-based competence to quality-based competence. The mechanism analysis shows that higher product quality differentiation and greater market demand will weaken firms' cost competitive tendency; proximity to external product networks weakens cost competitive tendency mainly through the channel of strengthening product quality differentiation, and proximity to internal product networks improves quality competitive tendency mainly through the channel of strengthening export market demand. The heterogeneity analysis shows that this network effect is more effective for new entrants and domestic firms but is weakened by policy support, as the impact of information flow will be limited by the fluency of knowledge extraction, transfer and diffusion. The findings of the study not only reveal the feasibility of enterprises using information flow of product networks to enhance export competitiveness, but also suggest more diversified thinking on the optimization of industrial policy implementation.

Climate risk of supply chain, as an important form of climate risk, is directly related to the stability of the industrial chain. The existing literature has already paid attention to the economic and financial consequences of enterprises' own climate risk, but has not paid attention to the potential impacts of external supply chain climate risk on enterprises as well, as the core component of supply chain finance, will the trade credit contract be affected by the climate risk of external supply chain? Using the data of Shanghai and Shenzhen A-share listed companies from 2013 to 2020, the results show that the higher the climate risk of supply chain is, the more favorable the trade credit contract can be obtained. After a series of robustness tests such as instrumental variable regression and entropy balance matching, the above positive effects are still significant. The mechanism test shows that firms tend to accept suppliers with high climate risk for financial constraints and short-term arbitrage, while the cross-sectional test shows that, the above effects will be more significant in the sample of enterprises with low credit availability, high cost transfer ability and poor external institutional environment. From the economic consequences test, although it can gain a certain trade credit advantage, however, excessive climate risk of supply chain will have a significant negative impact on the development of ESG, the level of green innovation and the total factor productivity of enterprises, which is not conducive to the high-quality development of enterprises.

Social community and users are the key actors in the community e-commerce value creation. While previous research has identified the drivers of value creation in community e-commerce, their systematic influence on the overall value creation process is unclear. This paper aims to fill the academic gap by uncovering the evolution process of the community e-commerce ecosystem and examining the impact of key factors such as product design, commission incentives, product quality, cost performance, and logistics services on value creation, using the system dynamics approach. The results show that value creation, willingness of community owners to share, number of active consumers, number of active community owners, consumer perceived value and identity, and consumer engagement within the community e-commerce ecosystem increase with time under the given parameters. Product quality, cost performance, logistics services, product design and commission incentives are key factors influencing the value creation of the community e-commerce ecosystem. In addition, the impact of the five factors on value creation decreases in order. This study is the first attempt to examine the ecosystem evolution process and factors influencing the community e-commerce from a multi-agent value creation perspective. The conclusion of this research contributes to the sustainable operation and development of community e-commerce enterprises.

In the era of the digital economy, the overlap between antitrust and information protection issues poses a great challenge to the formulation and implementation of public policies. This paper constructs a duopoly model where there are vertical differences in product quality and consumers' sensitivity to the quality of different products is negatively correlated. It explores the impact of different information protection policies with different strength on the pricing strategies of duopolists and consumer decisions and analyzes the specific welfare effects of policies. The conclusion indicates that in the market where consumers' sensitivity to the quality of different products is negatively correlated, a strong information protection policy leads to the impairment of social welfare, and vice versa. The reason is that information weakens the monopoly power by promoting competition. Meanwhile, considering different product characteristics, a strong protection policy and a weak one exert different effects on consumers' surplus and manufacturers' profits because information will bring about the "monopoly effect" and "competition effect", both of which play against each other to make the market present different welfare distribution patterns. Thus, the conclusion of this paper has certain policy implications for promoting and deepening the actualization of China's antitrust and information protection.

To improve the effectiveness of the shared parking policy and maximize the expected benefit of the shared parking system, this study attempts to optimize the number of shared parking lots and operation cost while taking into account the parking demand uncertainty and the introduction of connected and autonomous vehicles (CAVs). Specifically, the implementation conditions of the shared parking policy and the existence conditions of the optimal operation cost are revealed. The results show that the proposed model of expected benefit maximization has a unique solution with an optimal number of shared parking lots and an optimal operation cost. Moreover, the precondition for the implementation of the shared parking policy is that the revenue of the shared parking system must be greater than its total loss (i.e., the sum of general loss and management loss). Additionally, the necessary condition for the existence of the optimal operation cost is that the upper bound of the maximal shared parking demand must be larger than its threshold value. Finally, there is a critical value of CAVs proportion under certain conditions, and the threshold value of the upper bound of the maximal shared parking demand increases (decreases) with the CAVs proportion when the CAVs proportion is smaller (larger) than the critical value.

How to analyze user-interested products and services effectively and dynamically, is a new challenge amid the development in intelligent commerce. Most of the existing recommendation algorithms only consider the accuracy of recommendations, ignoring the real-time and diversified demands of users, which leads to a delayed and homogenization in recommendation lists with dissatisfaction among users. According to the changing characteristics of users' interests in the process of choosing goods, a diversified real-time user interest recommendation based on self-attention mechanism is proposed to effectively mine users' potential interests. Firstly, users' real-time interest is mined based on the gated recurrent unit network of self-attention mechanism, and the products are classified by contrastive learning to obtain the diversified recommendation list. Secondly, the recurrent neural network is combined to predict the user's next behavior, which can effectively solve the problem of sparse data in real-time recommendation. Finally, the e-commerce data set Yoochoose and Tmall in RecSys and IJCA-15 competition were used to verify the accuracy, diversity and user satisfaction of the algorithm. The results show that our recommendation improved diversity and user satisfaction compared to other algorithms, while maintaining a competitive precision score, especially in the small sample data set with sparse data, it performs better.

Propose a complete framework for decomposing value added, the multiplier decomposition and structural decomposition methods are extended to the multi-country and multi-sector input-output model to quantitatively analyze the dual circulation evolution trend of China and the endogenous power of the domestic circulation from 2000 to 2020. Research Findings: The overall dependence of China's economic development on the domestic circulation is in a "U" shape, and the inflection point appeared in 2006. On the left side of the inflection point, the main reason for the decline of the domestic circulation is China's decreasing value-added rate; on the right side of the inflection point, the improvement of the final demand rate, the toal demand coefficient and the value-added rate become the main driving force for the domestic circulation to rise in turn. Compared with investment, consumption has always been the main factor affecting the domestic circulation change in final domestic demand. The countries relying on the external circulation have shifted from developed countries to developing countries and developed countries. The dependence of the development of manufacturing industry on the domestic circulation has also increased since 2008. During this period, the increase of the toal demand coefficient of the service industry for the manufacturing industry, the upgrading of the industrial structure, and the improvement of the manufacturing value-added rate have successively occupied the main position in the cyclical rise of the manufacturing industry. The change in the domestic circulation of digital industry is dominated by its own final demand rate or the total demand coefficient of non-digital industry, and the dominant industries in the domestic circulation of non-digital industry are mainly themselves.

This paper studies the optimal decisions of the green supply chain (GSC) under demand information asymmetry, and mainly focuses the following three situations: Both the manufacturer and the retailer are risk averse, only the retailer is risk averse, and only the manufacturer is risk averse. The impacts of risk-aversion coefficient and information asymmetry on the GSC members' optimal decisions and utilities are discussed. Then, the cost-sharing contracts are introduced to optimize the GSC's performance under three situations. The results show that: The GSC's equilibrium solutions are influenced by the value of risk-aversion coefficient, and the joint impact of green degree and retail price on the market demand; under three situations, information asymmetry always reduces the manufacturer's utility, and it is not necessarily beneficial to the retailer, which is related to the demand information value evaluated by the manufacturer; whether the information is symmetric or not, the preference sequences of the manufacturer and the retailer for three situations are fixed; meanwhile, given specific conditions, the cost-sharing contracts can improve the products' green degree and help the GSCs achieve Pareto improvements under three situations.

In online retail markets, uncertainty about the quality of emerging products and firms' dynamic pricing lead to the possibility that consumers may engage in strategic waiting and delay the purchase of products. When considering the endogenous time preferences, consumers choose their own purchasing strategy (myopic or strategic), while spending an additional sunk cost of time and effort (called strategic cost) if choosing to be strategic. Based on consumer utility theory, we develop a two-period game-theoretic model, where the firm and consumers simultaneously learn and update perceived quality from online reviews in the second period. We study consumers' purchasing strategies when they have endogenous time preferences, and the impact of such consumers on the firm's pricing strategy. The results suggest that the perceived quality and strategic cost affect consumers' purchasing strategies and lead the firm to implement different dynamic pricing strategy depending on consumers' purchasing strategies. An increase in strategic cost may either increase the firm's profit, consumer surplus and social welfare, or increase the firm's profit at the expense of consumer surplus and social welfare. In addition, an increase in the accuracy of review information does not always benefit the firm. When both the strategic cost and perceived quality are at a high level, more accurate review information may even hurt both the firm's profit and consumer surplus. Also, consumers do not always benefit from strategic waiting behavior compared with the case where all consumers stay myopic.

Multi-unmanned aerial vehicle (UAV) cooperative air combat will be an important air combat style in the future. Considering the antagonism, complexity and coordination, a gaming approach based on graph model for conflict resolution (GMCR) for multi-UAV cooperative air combat is proposed to improve its effectiveness. Firstly, the single-UAV air combat superiority model and multi-UAV air combat superiority model are proposed by taking the synergism into consideration. Secondly, a multi-UAV air combat gaming model with a group of stability definitions is developed based on GMCR, and a payoff function using "damage loss ratio" is introduced into the model. Finally, a two-stage multi-UAV air combat gaming target assignment algorithm is designed, where a multi-objective optimization algorithm is applied to obtain the Pareto frontier of multi-UAV air combat confrontation scenario, and then the optimal equilibrium target allocation schemes are determined by GMCR. The results show that the proposed model and method can effectively solve the multi-UAV cooperative air combat problem, which is proved to have certain practical significance for air combat. More specifically, the optimal target assignment schemes obtained by the proposed approach are superior to the traditional UAV gaming model that only considers Nash stability.

In the era of digital economy,the competition pattern of China's banking industry is undergoing tremendous changes,and various digital technologies affect the business model and development level of banks.Based on the perspective of the integration of big data and traditional data,this paper uses factor analysis to measure the digital finance development level of 120 commercial banks in China from 2009 to 2019.Then,the kernel density estimation and the spatial panel Dubin model are used to investigate the temporal and spatial variation characteristics of the digital finance development for banks in China from two perspectives of time and space,and the evolution feature of regional differences and sources of bank digital finance is analyzed.Finally,the interactive relationship between the digital finance development level of banks and regional digital inclusive finance is examined.It is found that the digital finance level of Chinese commercial banks shows polarization differences over time.In the eastern region,there is a mutual promotion effect between bank digital finance and regional digital inclusive finance,while in the northeast region,there will be a suppression effect.In the central and western regions,there is no obvious interaction between them.This paper enriches the construction system of digital finance level measurement,and provides important reference experience for revealing the differences in the development of digital finance.It also explores countermeasures for synergistic improvement with regional digital inclusive finance.