With the significant expansion of the breadth and depth of financial services for the real economy, the real sector's "be diverted out of the real economy" trend has become a structural contradiction, and the motivation and appropriateness behind the enterprise's financialization have become an urgent issue to be resolved. This paper starts from the enterprise's response to risk and uncertainty, as well as the financialization drive mechanism to pursue shareholder value, and constructs the optimization problem of the investment portfolio intending to minimize enterprise risk and maximize shareholder value, and then obtains the optimal allocation of financial assets under different objectives reflecting the relationship between enterprise risk, shareholder value and the non-linear relationship between the levels of enterprise financialization. On this basis, based on the fact that the enterprise's financialization driving mechanism reflects the characteristics of the financialization motivation, we start from the enterprise's asset allocation structure. Combined with the optimal allocation of financial assets under specific objectives, we propose the criteria for determining the enterprise's financialization motivation and the appropriate scope of the enterprise's financialization. Then, we selected the representative listed non-financial enterprises in China as a sample for empirical analysis:As for the identification of the motivation of financialization, this paper found that although the non-financial enterprise sector is still dominated by the "reservoir" motivation, the whole, the "investment substitution" motivation is more significant and cannot be ignored. There is heterogeneity among different industries and enterprises with different equity natures, among which the motivation of "investment substitution" in the wholesale and retail industry and real estate industry is significant, and the motivation of "investment substitution" in non-state-owned enterprises is significantly stronger than that in state-owned enterprises. Concerning the appropriateness of enterprise financialization, we find that the overall financialization appropriateness of the non-financial enterprise sector is low. Especially in the information technology industry and the power, gas, and water production and supply industry, the appropriateness of financialization is significantly lower than the average level, and the level of industry financialization is insufficient. In contrast, the wholesale, retail, and real estate industries have excessive financialization. The moderation of non-state-owned enterprises' financialization is significantly higher than that of state-owned enterprises, and there is also the phenomenon of excessive financialization. The conclusion of this paper provides guiding suggestions for financial investment decision-making and regulatory identification of enterprises.

Customization, as an important customer value strategy for corporate development, is of great significance to the improvement of customer satisfaction and the increase of firm revenue. As digital technologies such as artificial intelligence, big data, and cloud computing develop quickly, firms' customization practices and related academic research meet great opportunities and challenges. Based on this background, through systematic and comprehensive analysis of Chinese and English literatures on customization, this paper clarifies and analyses the definition and patterns of customization, the key influencing factors of customization capabilities, the performance outcomes and the corresponding theoretical mechanisms of customization strategy, and the boundary conditions of the effectiveness of customization strategy. On this basis, this paper then summaries an integrated research framework for customization literature and proposes future research directions for customization from the aspects of patterns, performance outcomes and their mechanism, influencing factors, and the new forms of customer customization in the digital environment, to provide a reference for the development of more in-depth and systematic customization theory, and to bring inspiration for understanding and guiding firms' customization practice.

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.

With the release of China's "dual carbon goals", individual investors' green concerns gradually cause strengthened pressure on listed companies. Using the data of investor interaction platforms of the Shanghai Stock Exchange and Shenzhen Stock Exchange, this paper constructs green concern indicators based on a sample of 2048 listed companies and empirically reveals that individual investors' green concerns can promote green innovation in terms of quantity and quality. This influence is more pronounced in non-heavily polluting industries and those with no pollution charges and fewer environmental protection subsidies, individual investors' green concerns play a supplement role in the environmental regulation policies. Improving the construction of the green financial system and guiding individual investors' green investment concept can promote listed companies' green innovation behaviors.

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.

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.

Green merger and acquisition (M&A) is an important mechanism to achieve carbon peaking and carbon neutrality goal, but its motivation and environmental effects remain unclear. This paper uses the quasi-natural experiment of the segmented implementation of the ambient air quality standard as the exogenous impact to test the impact of environmental regulation on green M&A decisions of listed?companies. It is found that the implementation of ambient air quality standards can significantly improve the probability of green M&A of heavily polluting firms, and cause a significant improvement on firms' green innovation achievements and environmental performance. Further research shows that the green M&As are not concentrated in target areas with relatively lax environmental regulation, which eliminates the alternative explanation of pollution transfer through green M&A. Meanwhile, the green M&As promoted by ambient air quality standard are characterized by low proportion of related M&A, high proportion of major M&A and low proportion of performance commitments, which goes some way towards indicating that green M&As are not a "greenwashing". Finally, the green M&As promoted by ambient air quality standard mainly occur in non-state-owned firms and firms with high external attention. This paper makes an in-depth analysis of green M&A behaviors, which has enlightening significance for understanding the specific coping strategies of firms under the pressure of environmental governance policy, and also provides a useful reference for deepening the reform of environmental governance system.

How to correctly guide more capital to green projects and promote the transformation of enterprises to the green and low carbon emission have become a hot issue for the sustainable development of China. In this background, the paper proposes an equilibrium investment decision model with ESG investing and exogenous sudden shock. The theoretical results show that: 1) The expected return of portfolio is related to the ESG level from the market and the portfolio itself; 2) The impact of ESG level on the expected return of the portfolio is positively dependent on the degree of sudden shock when there is a sudden shock to the market. Using COVID-19 shock as a national experiment, all theoretical results are checked empirically by the stock funds data, and the impact mechanism of the ESG level on the fund performance are further analyzed. The empirical results are highly consistent with the theoretical prediction. The research of this paper will help guide social capital to the green and environmental protection projects of enterprises through ESG investment, or rather provide valuable helps for financial capital to promote green transformation of enterprises.

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.

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.

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.

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.

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.

We provide the first systematic analysis of the stock return lead-lag effect among firms connected through shared analyst coverage in China's A-share markets. We measure the shared analysts-weighted average returns of connected firms (CF) and show that CF is a significant positive predictor of future returns of the focal firms in the following one to 12 months. The CF-return-based long-short portfolio earns an abnormal return of 10% to 12% per year. The effect is robust to controls for the industry and geographic momentum effects. Further evidence shows that the CF momentum spillover effect is stronger when the focal firm shares more analysts with connected firms, is covered by more non-star analysts or analysts with lower levels of education, or is held by more stress-resistant institutional investors. Our findings contribute to the cross-asset momentum literature by documenting a new, strong, and long-lasting momentum spillover effect in the Chinese stock markets.

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.

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.

In the process of coping with climate change and promoting energy transformation, climate policy uncertainty has become an important incentive for risk contagion among energy markets. This paper uses the spillover index method based on conditional quantiles to study the risk spillover effect and its dynamic evolution between the energy markets under normal and extreme conditions, and further examines the driving mechanism of climate policy uncertainty on the risk spillovers of the energy system. The results show that:1) There are significant changes in the risk spillovers between energy markets under different market conditions, mainly occurring at the tail of the distribution in the energy market volatility, especially in the period of upward volatility, risk contagion is easy to occur. 2) In the post Paris Agreement era, although the risk spillover capacity of the clean energy market has increased, the fossil energy markets still dominate the risk spillovers of the energy system under extreme shocks. 3) Climate policy uncertainty is an important factor that exacerbates the extreme risk spillover among energy markets. Its impact relationship shows obvious asymmetry under two extreme market conditions, and the degree of influence is higher in the period of extreme volatility of energy prices. The research conclusions provide a new theoretical perspective for identifying the driving mechanism of risk spillovers in the energy market, and also provides an empirical basis for preventing and resolving risks in the international energy market.

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 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.

When building credit scoring models for new products or businesses, financial institutions often encounter the "high-dimensional, small samples" problem which results in unsatisfactory model performance. We propose a credit scoring method for small and micro enterprises based on a multi-source transfer learning technique. This method can transfer knowledge from other data sources (source domains) to improve the prediction performance of the credit scoring model of the target domain. Specifically, we first extract the multi-form knowledge from each source domain and then incorporate the information into the building process of the target domain model. The proposed method can take full advantage of the knowledge from source domains, and improve the prediction accuracy of the target domain model. In addition, throughout the modeling process, there is no need to obtain the original data of each source domain, which greatly reduces the risk of privacy leakage during data transmission. Simulation studies and real data analysis illustrate the superior performance of the method on variable selection, estimation, and prediction aspects. This method can effectively transfer the source domain information under privacy-preserving constraints to overcome the "high-dimensional, small samples" problem in the target data set.

With the core of embodied carbon intensity, this paper constructs a comprehensive analysis framework of cross-border economic and carbon emission impacts, assessing the impacts of the Belt and Road on China's economy and environment. The results show that the demand of the Belt and Road places a more critical effect on China's value-added, carbon emission, and aggregate carbon intensity. Compared with other countries, the proportion of industries with high embodied carbon intensity in the demand of the Belt and Road is relatively higher, resulting in China's higher embodied carbon intensity, indicating that China has to benefit from specialization through more carbon emission. To achieve the vision of Green Belt and Road, South Asia is a key region. Mining and quarrying, petroleum, chemical and non-metallic mineral products, metal products are key sectors. The difference in supply chain production structure effect is the main reason for China's higher embodied carbon intensity, suggesting that the supply chain transformation plays a significant role in Green Belt and Road. This paper first systematically analyzes the economic and carbon emissions impacts of the Belt and Road on China through international trade, clarifying the challenge of building Green Belt and Road that is ignored in the previous literature and proposes three policy implications on key regional governance, key industrial governance, and transformation of the green supply chain. The comprehensive analysis framework of cross-border economic and carbon emissions effects proposed provides a methodological basis for other environmental indicators.

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.

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.

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.

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 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.

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.

This study investigates the effect of common ownership on the convergence of corporate governance characteristics in Chinese A-share listed firms using a pair model. Our analysis indicates that firms with common ownership exhibit greater convergence in their governance characteristics. We then identify that the convergence effect is stronger when firms have better internal information environments or weaker external ones, suggesting that common shareholders are better able to obtain and share internal governance information. Additionally, we find that higher common ownership levels and increased industry competition lead to more significant convergence, highlighting the importance of collaborative motivations of common owners. Furthermore, our mediating analysis shows that sharing board members, members of the board of supervisors, and executives mediates the relationship between common ownership and governance characteristic convergence. Finally, we conduct a series of cross-sectional analyses based on common owner and firm characteristics. Our research contributes to the literature by shedding light on the inter-firm governance effect of common ownership.

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.

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.

Most of the existing studies on modeling rail transit commute behavior did not consider the impact of the time-varying time utility preference, and the empirical results were mainly derived from the stated preference survey data. With the analysis of morning rail transit commuters' time-of-use decisions, multinomial logit, mixed logit and nested logit models are formulated to describe morning rail transit commuters' discrete choice of arrival time under the constant-step and constant-affine travel utility preference assumptions, and the smart card data and train timetable data from Tuqiao Station to Sihuidong station on the Beijing Subway Batong Line in October 2017 are synthesized for model validation and parameter estimation. By distinguishing between two riding behaviors at the starting station, i.e., taking the latest train or waiting for the second train to get a seat, the model can address self-selection bias caused by directly using the revealed preference data of smart card for parameter estimation, i.e., commuters would prefer to depart at the time when the train is more crowded. Econometric results show that the models under constant-step travel utility preference perform better than that under constant-affine according to the value of goodness of fit, and the estimation results of the three discrete choice models are relatively consistent. That is, the unit time cost of arriving late is greater than that of arriving early and the in-vehicle crowding cost per unit time is about 11% of in-vehicle travel cost when standing 5 passengers per square meter. The impact of commuter heterogeneity in daily commuting features on travel utility preference is also discussed.

The China Securities Investors Service Center (CSISC), established in 2014, is an important institutional innovation in China's securities regulation system. In this paper, we manually compile the data on the exercise of rights by CSISC and construct a PSM-DID sample to examine the investor protection effect of CSISC in terms of stock price crash risk. It is found that CSISC's right exercise significantly reduces the stock price crash risk of the exercised firms and that public voice and participation in shareholder meetings are more effective. This finding still holds after a series of robustness tests. The mechanism test shows that "information effect" and "governance effect" are two important mechanisms. On the one hand, CSISC attracts market attention by mining and disclosing private information of enterprises (in the form of increased media coverage), thereby reducing the degree of information asymmetry and the risk of stock price crash risk; On the other hand, the exercise of power by CSISC forces companies to regulate their operations and information disclosure behaviors (in the form of improved information disclosure evaluation ratings), thereby reducing the risk of corporate stock crashes. Finally, the effect of CSISC's right exercise on stock price crash risk is more pronounced in firms with low institutional investor holdings. This paper enriches the literature on investor protection and stock price crash risk, and provides important insights for furthering securities regulatory reform.

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.

Motivated by different carpooling strategies in ride sharing platforms, this work studies two models: A solo-ride which offers solo rides only and a mixed model which offers both solo and shared rides. We conduct queueing economics analysis under different information revelation policies (observable and unobservable queues), for which we derive the customers' equilibrium strategies and the platform's revenue-optimal service prices. We have several interesting discoveries. First, when the market size is relatively small (large), hiding (revealing) the queue-length information helps improve the platform's revenue. Second, the introduction of shared rides in the mixed model may cause unexpected backfires and be detrimental to the system's revenue, especially when the market size is small. These results help gain useful insights into the management of ride sharing platforms, which in turn can be used to better inform the managers of the most effective carpooling strategies and information provision policies.

This paper constructs the financial social media information index (FI) for the first time and investigates the predictive power of financial social media information on cross-sectional stock returns and its impact on market anomalies. The study finds that there is a significant monotonic increasing relationship between financial social media information and future cross-sectional stock returns, and this relationship remains robust after controlling for various risk or sentiment pricing factors. The predictive power of financial social media information on stock returns reflects the process of information entering stock prices through financial social platforms. Financial social media information injects fundamental stock information into the market. However, due to the hindrance of market arbitrage costs, the process of information entering stock prices is prolonged, resulting in the persistence of the predictive power of financial social media information on stock returns. Empirical evidence from this paper further finds that the stock price information provided by financial social media can help investors identify and eliminate market anomalies that hinder the reasonable operation of the market, thus effectively improving the efficiency of the capital market. The conclusions of this study have important theoretical and practical significance for further promoting Internet construction, accelerating the integration of the Internet and the capital market, and promoting the high-quality development of the capital market.

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.

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.