Green manufacturing is an important part of ecological civilization construction and industrial transformation and upgrading. Realizing green transformation of enterprises from the perspective of green manufacturing construction is crucial to the high-quality development of Chinese enterprises. Based on the data of China's A-share listed firms from 2012~2023, a staggered DID model is used to empirically test the impact of green factory ratings on corporate ESG performance. The study finds that the certification of green manufacturing, represented by green factory ratings, is beneficial to the ESG performance of firms. Mechanism analysis shows that the green factory can promote corporate ESG performance through two channels: accelerating the green and low-carbon transformation of enterprises and alleviating corporate financing constraints. Heterogeneity analysis finds that the impact effect of green factory certification is stronger in enterprises with higher media attention, non-heavily polluting industries, and the eastern region. In addition, the green factory certification policy can improve the economic performance of enterprises and realize emission reduction and efficiency. Moreover, there is a spillover effect on upstream and downstream enterprises, which plays the role of a model enterprise as a benchmark. The study provides important policy references on how companies can achieve green and sustai-nable development.

基于2008～2017 年中国30个省域大中型上市工业企业面板数据， 本文选用固定效应分析（FEM） 测度， 实证分析主要的两种针对高新技术企业的所得税优惠政策的激励效果； 应用双重差分法（DID）， 实证分析一种税收激励政策局部变动所带来的政策效应； 基于国际上其他国家先进经验， 结合之前研究， 为我国税收激励政策体系的改进及政策环境下企业研发效率的提升提供建议： （1） 调整已有税收激励的对象， 改变税收优惠方向； （2） 建立企业研发投入的税收优惠税率动态享受机制； （3） 针对行业特点， 调整研发支出抵免优惠年限及设定“ 研发准备” 科目， 进而提升税收政策的执行力； （4）创立一个以研发投入为主体的政策效应动态监查系统。本文对于提升我国科技水平、经济实力， 进而影响我国的国际竞争力提供了政策数据支持。

The explosion of artificial intelligence technology and the leap of big model and big data function, as well as its deep integration with future industries and traditional industries, have greatly promoted the development of new quality productivity. The following eight articles are published, ranging from"theoretical innovation of total factor productivity from the perspective of big data function"to"big data driving the development of new quality productivity", from"digital transformation of supply chain to promote enterprise efficiency"to"transformation and upgrading of traditional industries from the perspective of new quality productivity", from"China's 6G industrial Internet development strategy"to"the practical path of artificial intelligence driving the development of new quality productivity", from"low-altitude economy under the background of large model landing"to"develo-pment of brain-computer interface industry based on large model", profoundly reveal the prospects of deep integration between ar-tificial intelligence and the real economy, outlining a blueprint for high-quality development empowered by new quality productivity.

Under the wise leadership of the Party Central Committee with Comrade Xi Jinping as its core, the development of AI industry, and the R & D and application of large language models in China have been in the first echelon in the world.In August 2025, the State Council's Opinions on the In-depth Implementation of the Artificial Intelligence Plus Action drew a grand blueprint for further promoting the extensive and deep integration of artificial intelligence with various sectors of the economy and society.The vigorous development of intelligent economy is inseparable from the rapid progress of intelligent technology, critically, it also requires enterprises to renew their organizations and adjust strategies to grasp new opportunities and tap into new potential.However, the intelligent economy with unlimited potential also contains greater technological and social risks, such as data security, unemployment of vulnerable workers and so on.Therefore, the society should actively foresee all kinds of risks and formulate countermeasures to promote the stable and healthy development of AI economy.

The marketization of data elements can accelerate the release and circulation of data value, enable enterprises to acquire and utilize data resources more efficiently, thereby providing key impetus for the integration of the digital and real economies and driving high-quality economic development.This article takes the establishment of a data trading platform as a quasi natural experiment and uses the difference in differences method to empirically test the impact of data element marketization on the integration of data and reality at the micro enterprise level.Research has shown that the marketization of data elements can significantly promote the integration of data and reality in enterprises, and the conclusions are stable after robustness and endogeneity tests.Mechanism analysis shows that the marketization of data elements promotes the integration of enterprise data and reality by enhancing the level of urban technological innovation, improving the digital financial environment, alleviating financing constraints, and reducing information asymmetry.Heterogeneity analysis shows that this effect is more significant in enterprises with low management myopia, more prominent in high-tech and stronger in enterprises with lower levels of national unified market construction and factor market development.This article provides decision-making basis for the government to optimize data element allocation policies and promote the deep integration of digital economy and real economy, which has practical value for high-quality economic development.

Promoting supply chain digitization is one of the core paths for the deep integration and development of the real economy and digital economy, and it is also an important lever for driving sustainable development of enterprises at present. This article is based on micro panel data of listed companies, systematically exploring the impact mechanism of supply chain digitization on the sustainable development performance of enterprises. The research found that: firstly, the benchmark regression results confirmed that supply chain digitization has a significant positive promoting effect on the sustainable development performance of enterprises, and this conclusion still holds true after robustness testing; Secondly, innovation investment plays an intermediary role between the two, and supply chain digitization can indirectly empower sustainable development of enterprises by increasing the intensity of research and development investment. Thirdly, heterogeneity analysis shows that this impact exhibits regional and firm differentiation characteristics, with more significant positive effects observed in enterprises in the eastern region, as well as in state-owned and private enterprises. This study is helpful for enterprises to accurately promote the digital transformation of their supply chain, enhance their sustainable development capabilities, and provide empirical reference for the government to formulate differentiated support policies.

Taking the relevant data of China's A-share listed manufacturing companies from 2012 to 2021 as a sample,this paper uses the two dimensions of construction text and quantification,uses the entropy method to construct comprehensive indicators to measure the digital transformation of enterprises,and empirically studies the relationship between digital transformation and enterprise performance.The results show that:Digital transformation has a significant effect on enterprise performance.Furthermore,based on the value chain theory,this paper analyzes the impact of digital transformation on enterprise performance in each link of the value chain.and the results show that:from the perspective of each link,R&D digitalization,production digitalization,operation digitalization,marketing digitalization and enterprise performance are significantly positively correlated.Finally,the heterogeneity of the impact of digital transformation on enterprise performance in different enterprise clusters,finds that:compared with non-technology-intensive enterprises,state-owned enterprises and small and medium-sized enterprises,the role of digital transformation in promoting enterprise performance is more obvious in technology-intensive enterprises,non-state-owned enterprises and large enterprises.

The paper investigates the dynamic evolution characteristics of the global PV industry chain's core product trade network from 2007 to 2022, and analyzes its influencing factors using the QAP method. It is found that: (1) the overall network indicators of the upstream, midstream and downstream of the industry chain increase sequentially. However, the upstream network is stable and the midstream and downstream tend to be denser, the midstream of the industry chain is most affected by trade protection policies. (2) Global PV trade tends to be active; sanctions and circumvention make the industry radiate from China to Southeast Asia, and intra-European industries move to Central and Eastern Europe. (3) Economic scale, manufacturing capacity, and distance have had a sustained impact on trade in each link of the PV industry chain. In summary, the market expanded by the PV industrial policy can ensure a certain level of manufacturing scale and technological progress, and then gain a dominant position in trade and feed the trade policy to ensure its effectiveness. This paper provides data support for grasping the future trade direction of China's photovoltaic industry and formulating differentiated policies.

Against the backdrop of the digital economy, exploring the transformation and upgrading of digitalization and servitization in China's manufacturing enterprises to achieve high-quality development has become a focal point of current research and practical attention. From the perspective of digital technology innovation, this study using a sample of China's A-share listed manufacturing enterprises from 2012 to 2024, empirically analyzes the influence mechanism of the synergy between digitalization and servitization on the high-quality development of manufacturing enterprises. The research findings are as follows. The synergy between digitalization and servitization facilitates the high-quality development of manufacturing enterprises through the mediating role of di- gital technology innovation. Compared to basic servitization, the synergy between digitalization and advanced servitization has a more significant promoting effect on the high-quality development of manufacturing enterprises, and is conducive to enhancing digital technology innovation, thereby achieving high-quality development of manufacturing enterprises. Robustness test indicates that the above research conclusions are robust. Heterogeneity analysis reveals that non-state-owned enterprises, labor-intensive enterprises, technology-intensive enterprises and non-equipment manufacturing enterprises can more fully leverage the potential of the sy-nergistic effect of digitalization and servitization, demonstrating a stronger promoting effect on high-quality development of enterprises. This paper provides theoretical basis and practical insights for manufacturing enterprises to synergistically promote digitalization and servitization, realizing high-quality development.

A new wave of technological revolution and industrial transformation is in full swing, and competition among major powers is escalating.Developed economies are intensifying the implementation of industrial policies to promote frontier technologi-cal innovation and the development of future industries, aiming to secure strategic advantages.In the face of a complex international environment and daunting domestic tasks of reform, development, and stability, Xi Jinping creatively proposed the important concept of developing new quality productivity.Promoting the development of new quality productive forces requires constructing new types of production relations that align with them, further advancing systemic, institutional, and mechanistic reforms.This involves both leveraging the decisive role of the market in resource allocation and enhancing the role of the government.The empowerment of new quality productivity by the government and the market is not a simple linear relationship.Systematic research is urgently needed to explore how the dual forces of government and market can synergistically empower the development of new quality productivity.Therefore, this paper elucidates the intrinsic logic of the synergy between effective markets and proactive governments in empowering new quality productivity from three perspectives: theoretical logic, historical logic, and practical logic, and proposes corresponding recommendations.

Supply chain security and stability is an important prerequisite for coping with uncertainty risk and realizing the smooth flow of the"double cycle", and the existing literature mostly examines the impact of supply chain risk from the perspective of supply chain relationship changes. In this study, we use the data of Chinese A-share listed companies from 2008 to 2024 to exa-mine the impact of supply chain risk on their innovation quality from the perspectives of supply chain risk exposure and risk perception. It is found that supply chain risk exposure increases firms' innovation quality, while risk perception decreases firms' innovation quality. Mechanism analysis shows that risk exposure improves innovation quality through supply chain restructuring and digital empowerment, while risk perception reduces innovation quality through financing constraints and resource crowding out effects, which are mainly found in firms with high supply chain concentration, technology-intensive industries, and regions with high marketisation levels. Further, supply chain risk exposure and risk perception interact with each other to drive firms' innovation quality. The study is useful for coping with domestic and international uncertainty risks, building secure and stable supply chain relationships, and promoting corporate innovation.

In the wave of the digital economy, enterprise digital transformation, serving as an excellent booster for the digi-tal economy, provides new pathways for enhancing the resilience of industrial chains.This paper analyzes the connotation of indust-rial chain resilience from the perspective of the general characteristics of industrial chain networks.It posits that industrial chain resi-lience can be decomposed into two dimensions: the resilience of industrial chain network nodes and the resilience of industrial chain network structure.Utilizing data from A-share listed companies from 2010 to 2022, this study verifies the impact and mechanism of enterprise digital transformation on industrial chain resilience.The research finds that enterprise digital transformation significantly enhances industrial chain resilience.This enhancement primarily occurs through two mechanisms: reducing internal agency and production costs to strengthen industrial chain network nodes, and reducing external transaction costs to optimize the industrial chain network structure.Further research reveals that the presence of state-owned enterprises and technology-intensive enterprises amplifies the reinforcing effect of enterprise digital transformation on industrial chain resilience, while the presence of labor-intensive enterprises suppresses this reinforcing effect.This paper elucidates the intrinsic micro-mechanism of how enterprise digital transformation reinforces industrial chain resilience, providing a theoretical foundation and policy implications for promoting the digitalization of industrial chains to enhance their resilience and security.

Enterprise digital transformation is an important link to implement the digital economy strategy and promote the integrated development of the digital economy and the real economy. This paper focuses on the transmission mode of government digital attention-enterprise digital transformation, and empirically tests the influence and mechanism of government digital attention on enterprise digital transformation. Based on the data of China's Shanghai and Shenzhen A-share listed companies from 2007 to 2023, the study found that the government's digital attention significantly promoted the digital transformation of enterprises, and the above effect was more obvious when state-owned enterprises, small-scale enterprises, and regional digital infrastructure were better. The effect of government digital attention on enterprise digital transformation mainly plays a role through two transmission paths of government and enterprise. On the one hand, government digital attention improves digital subsidies; on the other hand, it plays a role in the peer effect among enterprises, that is, the imitation learning behavior that promotes enterprise digital transformation. The research conclusions are of great significance for enriching relevant researches on enterprise digital transformation and exploring how to give full play to the effectiveness of policies to solve the dilemma of enterprise digital transformation.

This paper selects data from Chinese A-share listed companies from 2008 to 2023 and uses the difference-in-differences model to investigate whether the green credit policy will have an incentive effect or a crowding-out effect on the green innovation of heavily polluting enterprises. The study finds that the implementation of the green credit policy has promoted the green innovation of heavily polluting enterprises, and the green innovation induced by this policy is an incentive effect superimposed on existing innovation activities and has not crowded out other technological innovations. Mechanism analysis shows that the implementation of the green credit policy can promote the green innovation of heavily polluting enterprises by strengthening the green cognition of senior executives. Heterogeneity analysis shows that the green innovation of heavily polluting enterprises is more obvious in the western regions, areas with strong environmental regulations, and highly competitive industries. This paper expands the research perspective on the impact of green credit policies on corporate green innovation and provides valuable policy inspiration for promoting the green transformation of the economy.

This paper takes the pharmaceutical collection policy implemented in China in 2019 as an exogenous shock, and uses the difference-in-differences method to examine the impact of this policy on the R&D efficiency of pharmaceutical enterprises from the perspective of market competition.The empirical results show that the pharmaceutical collection policy makes the market competition in the pharmaceutical circulation link more transparent and sufficient, and improves the R&D efficiency of pharmaceutical enterprises through the scale effect and competition effect of R&D respectively.Further research also shows that due to the scale effect of R&D, the promotion effect of centralized procurement on R&D efficiency is more obvious in pharmaceutical enterprises with weak financing constraints, high customer concentration and small scale.Due to the competitive effect of R&D, this effect is more obvious for innovative pharmaceutical companies.

Based on the digital input information of listed companies from 2015 to 2022, this article empirically tests the impact of digital transformation on total factor productivity. Research has found that the impact of digital transformation on total factor productivity has a time lag, and the positive effects of digital transformation gradually emerge and strengthen over time. Specifically, digital transformation in production and management has a positive impact on improving productivity, while digital transformation in user and technology has not yet empowered enterprise efficiency. Channel mechanism testing shows that digital transformation has increased total factor productivity by driving enterprise innovation, improving operational models, and reducing agency costs. The heterogeneity analysis results show that the positive effects of digital transformation are more significant for enterprises with better human capital structure, greater emphasis on collaborative and creative culture, and relatively smaller organizational inertia.

As a new core factor of production and strategic resource for enterprises, data assets are reshaping corporate value creation models and capital structures.This paper examines A-share listed companies in China from 2010 to 2023, analyzing the impact of corporate data capitalization on the cost of debt financing by quantifying the extent of enterprise data assetization.The study finds that data capitalization significantly reduces the cost of debt financing.Specifically, data assetization reduces debt financing costs not only through a defensive mechanism of lowering financial risk but also via a proactive mechanism of enhancing financial flexibility.The research conclusion not only provides empirical support for clarifying the reduction path and functional boundary of debt financing costs by data assetization, but also offers theoretical support and policy guidance for further developing specific data assets of enterprises.

In the context of increasing global changes in supply chain uncertainty, how to build resilient supply chains through digital transformation and drive total factor productivity growth has become a theoretical gap and policy proposition that urgently needs to beovercome in the digital economy era. This article takes A-share listed companies in Shanghai and Shenzhen from 2012 to 2024 as the research object, and deeply explores the impact path of digital transformation on the total factor productivity of enterprises. The mechanism test finds that digital transformation promotes the improvement of total factor productivity of enterprises by reducing the risk level of supply chain interruption. Heterogeneity testing finds that digital transformation has a more prominent effect on improving the total factor productivity of enterprises in areas with state-owned nature, high financing constraints, low supply chain discourse power, low supply chain efficiency, high digital infrastructure, and high government digital attention. This study focuses on the supply chain perspective, providing empirical evidence for enterprises toexplore effective strategies for digital transformation, as well as practical policy references for stimulating new drivers of economic growth and achieving high-quality economic development goals.

ESG rating is an important indicator to guide the strategic decision of enterprises.How will the inconsistency of rating results affect the investment decision of enterprises? In this paper, Shanghai and Shenzhen A-share listed companies from 2016 to 2022 are selected as research samples to empirically test the impact of ESG rating divergence on corporate green innovation efficiency.The results show that the greater the differences in ESG ratings, the lower the efficiency of green innovation.The cost of debt capital plays a partial mediating role between ESG rating divergence and green innovation efficiency.In firms with high analyst attention and governance, the negative impact of ESG ratings on green innovation efficiency is weakened.This paper extends the exi-sting research from ESG performance to the field of ESG rating divergence, providing reference and inspiration for improving the construction of ESG rating system and improving the efficiency of enterprises' green innovation.

Open government data(OGD)reduces the costs and technical barriers to corporate data acquisition, providing new momentum for high quality enterprise development.Leveraging the quasi-natural experiment of city-level OGD platform launches and using panel data from China's Shanghai and Shenzhen A-share listed firms(2009~2024), this study employs a multi-period DID model to identify the causal effect of OGD on firm-level high quality development and its underlying channels.The fin-dings reveal that OGD significantly promotes high quality firm development.These effects are more pronounced in cities with better digital infrastructure, and among firms in technology-intensive and capital-intensive industries, as well as those with stronger motivation and capacity for adjustment.Mechanistically, OGD drives high quality development through three synergistic channels: reducing data access costs to build a resource foundation, enabling digital transformation to enhance operational capabilities, and stabilizing market expectations to improve the institutional environment.

Industrial transformation is a natural part of the new round of industrial revolution, and the arrival of the artificial intelligence era has transformed the industrial productivity innovation in the sense of "Internet of Things" into a new industrial revolution of "data+algorithm+sensor+behavior tokenization+control system". Artificial intelligence has transformed industry from the meaning of the Internet of Things to the embodied AI meaning of "AlphGo+OpenAI", putting the era of intelligent industry on the eve of Grokking. On the one hand, AI deeply accelerates industrial transformation, and on the other hand, it directly reconstructs into an intelligent industrial system, thereby directly achieving the original goal of industrial transformation. However, at present, the shortcomings of energy and the old industrial production system urgently need to be addressed through industrial transformation, otherwise the era of intelligence will be difficult to truly achieve. At the same time, there are a large number of technical and hardware difficulties that slow down the marketization of intelligent industry. Without considering costs, it is possible to first achieve "laboratory intelligent industry" and then gradually realize it in real industrial application scenarios over the long term.

数据要素能否有效促进经济增长，对实现经济高质量发展至关重要。本文将数据要素引入新结构增长模型，研究数据要素驱动经济增长的直接效应和间接效应。直接效应是由数据要素投入直接带来的经济增长；间接效应是通过数据要素驱动生产结构升级和禀赋结构变迁间接促进的经济增长。理论研究发现，随着数据要素投入的不断增加，人均数据与人均资本之间的差距逐渐缩小，尤其是当人均数据超过人均资本时，数据/劳动禀赋结构占主导地位，经济增长主要由数据要素驱动。因此，充分发掘数据要素的直接效应和间接效应，可以为我国经济结构优化，加速经济增长提供新的动力。

With the development of digital economy, enterprise digital transformation has become the focus of academic attention. The 20th National Congress of the Communist Party of China (CPC) and the Third Plenary Session of the 20th CPC Central Committee of the Communist Party of China (CPC) emphasized the need to accelerate the digital transformation of enterprises, promote the comprehensive upgrading of R&D, production, operation, sales and other businesses, and use technologies such as AI and big data to lead the transformation of production methods, lifestyles and social governance. The study Taking high-tech enterprises as an example, this study uses structural equation model to study the impact of digitalization on the innovation performance of high-tech enterprises, and verifies the mediating role of absorption capacity. The results show that digital transformation has a positive impact on enterprise innovation performance. Absorption capacity has a positive impact on the innovation performance of enterprises. Digital transformation has a positive impact on absorptive capacity. Absorptive capacity plays a mediating role between digital transformation and enterprise innovation performance. This paper reveals the innovation mechanism of digital transformation to high-tech enterprises, so as to enhance the core competitiveness of enterprises.

Artificial intelligence (AI), as an important driving force for industrial transformation and upgrading, will inevitably have a significant impact on corporate capital market performance while promoting firm digitization.This article empirically tests the impact and its mechanism of AI applications on capital market performance using A-share listed companies in Shanghai and Shenzhen from 2010 to 2024 as samples.The research shows that promoting the firm AI applications can significantly improve their capital market performance, manifested in increased stock liquidity.The channel mechanism indicates that AI applications promotes the improvement of capital market performance by alleviating financing constraints.Heterogeneity indicates that the promotion effect of AI applications on capital market performance is more pronounced in non-state-owned, weak management power, and low mana- gement age firm groups.The research conclusion of this article not only enriches the economic effects of artificial intelligence, but also provides empirical evidence to support the understanding of stock liquidity in the capital market.

Taking the data of A-share listed companies in Shanghai and Shenzhen from 2000 to 2023 as the research object, based on the dynamic capability theory, the resource base theory and the stakeholder theory, we constructed a double mediation model of enterprise digital transformation affecting organizational resilience through enterprise profit and enterprise scale.The results indicate that enterprise digital transformation significantly enhances organizational resilience, and the conclusion passes multiple robustness tests; enterprise profit and enterprise size empower the enhancement of organizational resilience through partial mediation effects; and the extent of the impact of enterprise digital transformation on organizational resilience shows significant differences among different enterprise natures, geographic locations, and age of enterprises.The empirical findings further explain the path of enterprise digital transformation on organizational resilience, enrich the relevant theories of digital transformation, and also provide useful references for enterprises to optimize operation management and decision-making in the process of digital transformation.

With China's economic development entering a new stage of improving quality and efficiency, cultivating and developing new quality productivity has become the key task of high-quality economic development at present.Patience capital is a practical requirement to guide the integration of innovative resources and factors and promote the formation of new quality productivity.Therefore, this paper focuses on how patient capital can empower the formation of new quality productivity, and analyzes its synergy in the transformation of innovation achievements, industrial structure optimization and talent gathering.Through empirical analysis, it is found that patient capital has a significant role in promoting the formation of new quality productivity, and patient capital can promote the formation of new quality productivity in areas with low economic development level, and its influence is mainly realized through three aspects: improving innovation level, rationalizing industrial structure and promoting talent gathering.Therefore, we should give full play to the guiding role of patient capital in technological innovation and structural transformation, promote the more stable and fair flow of capital elements, continuously release the potential of innovation, and form new quality productivity.

Against the backdrop of deepening reforms and accelerating the cultivation of new quality productivity, enhancing the resilience of industrial and supply chains has become a critical pathway to achieving high-quality economic development.This study employs balanced panel data from 285 prefecture-level cities in China from 2009 to 2023 to empirically examine the spatial spillover effects of new quality productivity on regional industrial and supply chain resilience, as well as the underlying mechanisms.The findings reveal that improvements in new quality productivity significantly enhance resilience and exhibit notable spatial spillovers, primarily through the alleviation of regional labor and capital misallocation.Heterogeneity analysis further indicates that non-resource-based, non-transport hub, and small to medium-sized cities benefit more prominently.These results offer important policy implications for place-based reform strategies, optimized resource allocation, and the cultivation of new growth drivers, thereby contributing to regional balanced development and stronger industrial and supply chain resilience.

The concept of“internet financial platform development degree” is introduced to study the influencing factors of platform development degree under the subdivided formats.The internet financial platform is divided into P2P online lending,crowdfunding and third-party payment platform.The empirical analysis results of 165 internet financial platforms show that:platform type,loan period and operation time have the greatest impact on the development degree of P2P online loan platform;company size,platform type and media exposure are the top three factors influencing crowdfunding platform;and innovation business ability,platform business scope and registered capital are the main influencing factors of hird-party payment platform.There are great differences in the influencing factors of the development of different subdivision formats,and the third payment platform is more different than the other two platforms.Finally,the suggestions for improving the development performance of the platform are put forward from the perspective of regulators and managers according to the situation of the platform.

This paper takes A-share listed enterprises from 2015-2021 as samples, and measures the level of corporate digi-talization based on text mining technology to explore the impact of corporate digitalization on financing constraints.The study finds that corporate digitalization has a mitigation effect on financing constraints, which is mainly achieved by reducing information asymmetry and reducing agency problems;when enterprises are in the mature stage, have rela-tively high strategic deviance and face relatively high economic policy uncertainty, the mitigative effect is more significant.The study not only provides new empirical evidence for understanding the economic effects of corporate digitalization, but also provides important enlightenment for accelerating the construction of a new development pattern and promoting high-quality economic development.

As a reverse regulatory mechanism in international capital flows, foreign capital withdrawal has emerged as a criti-cal issue affecting supply chain stability within the framework of national economic circulation.Utilizing supply chain data from Shanghai and Shenzhen A-share listed companies spanning from 2010 to 2023, the research reveals that the retreat of foreign capital notably diminishes supply chain resilience.Mechanism analysis identifies dual transmission pathways: the capital chain exacerbates corporate financing constraints, while the innovation chain diminishes bidirectional technology spillovers across horizontal and vertical dimensions.Heterogeneity analysis further indicates that this weakening effect is more pronounced in non-state-owned enterprises, asset-intensive enterprises, enterprises with high virtual agglomeration, and those with significant environmental sensitivity.Additionally, foreign capital withdrawal exhibits multi-level spillover effects within the industry, while the establishment of free trade zones exhibits dual positive impacts on optimizing capital structure and bolstering supply chain stability.This paper offers crucial policy insights for attracting and effectively leveraging foreign capital, as well as enhancing the quality and efficiency of China's supply chain.

In the context of deep integration between the digital and real economies, whether data assetization can help enhance supply chain resilience has become an urgent question to address. Based on data from A-share listed companies from 2007 to 2024, this study empirically examines the impact of corporate data assetization on supply chain resilience. The findings indicate that: (1) Corporate data assetization significantly improves supply chain resilience, and the results remain robust after a series of endogeneity treatments and robustness tests. (2) Data assetization primarily enhances supply chain resilience by increasing corporate information transparency, reducing supply chain coordination costs, and improving product competitiveness. Furthermore, information transparency and coordination costs play a chained mediating role in this process. (3) The empowering effect of digitalization is more pronounced in technology-intensive enterprises, competitive industries, and in the eastern and central regions of China. This study provides evidence and insights from the perspective of data assetization on how to enhance supply chain resilience under the Digital China strategy.

In the context of the "dual-carbon" goal, enterprises promote green technological innovation through digital transformation, which not only concerns their own survival and development, but also serves as the microfoundation for promoting China's sustainable economic development.Based on the data of A-share listed companies in Shanghai and Shenzhen from 2009 to 2022, the study examines the impact of digital transformation on enterprises' green technological innovation.The study finds that digital transformation helps to improve the level of green technology innovation of enterprises, and the estimation results are very robust.The mechanism test shows that digital transformation promotes corporate green technology innovation through enhancing internal capacity building, increasing external market attention and increasing government subsidies.Heterogeneity analysis shows that digital transformation promotes firms' green technology innovation more significantly in state-owned enterprises and regions with high environmental regulation intensity.This study provides empirical evidence for understanding that digital transformation empowers enterprises' green technology innovation, and provides theoretical and practical references for promoting digital transformation for sustainable economic development in China.

In the era of digital economy, data monopoly manifests the deep coupling between capital logic and technological power. From the perspective of formation mechanism, data monopoly is essentially a process through which capital achieves exclusive control over data elements by technological means, specifically demonstrated by capital-driven centralized accumulation of data, technological barriers constructed by algorithmic power, and institutional monopoly formed by platform ecosystems. Such monopolistic structure not only distorts market competition order, but also intensifies the inherent contradictions of digital capitalism through data exploitation mechanisms. Governance innovation needs to break through traditional paradigms and establish an institutional system centered on"data commonality". At the property rights level, it is necessary to construct a fair distribution system for data rights and interests; at the technological level, advance the construction of public data infrastructure; at the governance level, promote transnational collaboration and multi-stakeholder governance. Through systematic institutional innovation, data elements can be transformed from tools of capital accumulation into carriers of public welfare, providing a new governance path for equitable development in the digital age.

As a strategic technology driving the new wave of scientific and technological revolution and industrial transformation, artificial intelligence(AI) plays a significant role in enhancing the total factor productivity(TFP) of enterprises. Based on the theories of regional innovation systems and endogenous growth, this study uses panel data from companies listed on the Shanghai and Shenzhen A-shares between 2016 and 2024 to examine the impact of AI innovation development pilot zone policies on improving enterprise TFP. The results demonstrate that this policy significantly boosts corporate TFP, and these results remain robust after a series of robustness tests. Heterogeneity analysis reveals that the policy has a stronger effect in the central and western regions and for non-high-tech industries. Further analysis indicates that the policy influences TFP through two channels: deepening the application of AI and improving resource allocation efficiency. The policy not only enhances enterprise TFP but also strengthens profita-bility. This study provides empirical evidence for the role of the AI Innovation Pilot Zone policy in fostering corporate TFP growth and offers important policy implications for improving enterprise productivity.

Innovation is an important measure to enhance the competitiveness of the supply chain.In the context of supply chain spillover effects, does customer ESG performance affect supplier enterprise innovation?This article takes the listed companies that disclosed the top five customers from 2010 to 2024 as samples to investigate the spillover effect of customer ESG performance on supplier enterprise innovation.The study has found that well ESG performance of customers promotes supplier enterprise innovation by alleviating financing constraints, reducing information asymmetry, and operational risks.Further research shows that when suppliers are in heavily polluting industries, the more stable the supply chain relationship and the stronger the bargaining power of customers, the positive ESG performance of customers has a stronger effect on the innovation of supplier enterprises.This paper expands the research on the influencing factors of enterprise innovation and the economic consequences of customer ESG performance in the context of cross enterprise relationships.The research findings provide empirical evidence for optimizing supply chain relationship management and improving supply chain autonomy and controllability.

The widespread application of artificial intelligence has had a profound impact on the economy and society. This paper analyzes the theoretical mechanisms through which artificial intelligence(AI) promotes high-quality development of enterprises and conducts empirical tests based on panel data of listed companies on the Shanghai and Shenzhen stock exchanges. Empirical results show that artificial intelligence significantly promotes the high-quality development of enterprises, and remains significant after robustness tests and causal identification considering instrumental variables. Mechanism tests show that artificial intelligence can promote the high-quality development of enterprises through ways such as promoting technological innovation, reducing costs, enhancing the level of human capital, and promoting common prosperity within enterprises. However, it has an inhibitory effect on the technological diversification of enterprises. Moreover, the impact of AI on high-quality enterprise development varies under different circumstances, including different firm sizes, different labor costs, and different ownership structures. The research conclusion provides a feasible path for the high-quality development of enterprises and also offers a basis for the government to promote the deep integration of artificial intelligence and the real economy.

The article selects the annual data of China's A-share listed companies from 2011 to 2022 as the research sample to examine the impact of digital transformation on the level of new quality productivity of enterprises, and explore the mechanism and heterogeneity factors between the two.The empirical findings show that digital transformation can significantly improve the level of new quality productivity of enterprises.The mechanism test shows that digital transformation can promote the increase of new quali-ty productivity of enterprises by alleviating financial constraints, strengthening managerial capabilities, and improving information transparency.The heterogeneity analysis shows that the implementation of digital transformation has a more significant effect on the improvement of new quality productivity in state-owned enterprises, technology-intensive enterprises, and enterprises in regions with weaker digital infrastructure.The conclusion of the article provides a useful reference for formulating relevant policies to promote the digital transformation of enterprises and the construction of new quality productivity.