The deep embedding of artificial intelligence (AI) into industrial systems is driving industrial convergence from localized technological adoption toward cross-industry ecological collaboration. However, its intrinsic generative mechanisms and diffusion constraints remain insufficiently understood. This paper constructs a progressive analytical framework of "data elements—platform ecosystem—institutional provision" to reveal the mechanisms and practical pathways through which AI facilitates industrial convergence from three dimensions: resource foundations, network organization, and regulatory structures. The study finds that AI, through the coupling of data and algorithms and cross-domain reuse of model capabilities, reduces cross-boundary collaboration costs and enhances modularity of capabilities, promoting industrial convergence from isolated technological applications to cross-value chain structural collaboration. The availability boundaries and trustworthy circulation mechanisms of data factors constitute the prerequisites for initiating integration and scaling replication, determining whether cross-industry knowledge reproduction can be expanded within a compliant framework. The platform ecosystem amplifies network externalities and reshapes industrial boundaries through interface connections and multi-sided matching,though centralized control of core interfaces and data standards may generate lock-in effects and compress competitive structures. Institutional provision stabilizes market expectations through rule compatibility, standard systems, and inclusive and prudent governance, establishing enforceable constraints across data privacy, security, and competitive order. These three dimensions exhibit progressive constraints and transmission relationships, jointly determining whether industrial convergence can evolve from localized breakthroughs to ecosystem-wide expansion. Based on these findings, the paper outlines practical pathways for AI-driven industrial convergence and proposes policy implications, including optimizing data circulation regimes, improving platform governance structures, and strengthening cross-departmental regulatory coordination.

    Focusing on the core issues of global cross-border data flow governance, this paper develops a theoretical framework from three dimensions: institutional innovation, technological coordination, and scenario adaptation. It systematizes the characteristics of three major governance paradigms (the EU, U.S., and China) and uses the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) to analyze obstacles and improvement paths for regional cross-border data flow governance. Current data governance reforms feature regional rule "blocization" and "differentiation"; technology's borderlessness conflicts with governance's sovereign nature, demanding urgent institutional innovation. By defining data rights and obligations and introducing adaptive rules, institutional innovation underpins governance from order-building to risk mitigation, serving as a key driver of governance effectiveness alongside technological coordination and scenario adaptation. Globally, the EU adopts a "regulation-led" system, balancing data security and flow via rule mutual recognition; the U.S. employs a "technology-led" model, asserting digital hegemony through institutional-technological coordination; China uses a "scenario-applied" paradigm, aligning development and security through data classification. Given the GBA's unique "one country, two systems,three legal jurisdictions" structure, cross-border data flows there confront legal rule conflicts, inconsistent technical standards, and an industrial digital divide. Addressing these requires a cross-regional collaborative governance model with policy interoperability, enhanced technical support for infrastructure sharing, and promoted industrial collaboration and crossborder business scenario optimization. This study offers practical guidance for China's regional data governance and provides Chinese insights for global data governance reform.

    Jointly building a low-carbon development mechanism and jointly addressing climate change are important measures for China's international cooperation. As overseas economic and trade cooperation zones(COCZ) serve as a new window for China's opening up, whether it can have a positive impact on host countries' carbon emission reduction has attracted much attention and is related to the smooth development of subsequent cooperation. Based on the practice of China's COCZs, this paper uses double difference method to systematically examine the impact and mechanism of COCZs on the carbon emission intensity of host countries. This study found that the establishment of COCZs has significantly reduced the carbon emission intensity of the host country. The import of low-carbon products, energy efficiency improvement, energy structural optimization,and green total factor productivity improvement are the main ways for COCZs to exert its carbon reduction effect. Heterogeneity analysis shows that the carbon reduction effect of COCZs may be more significant in middle-income countries or in the ones with higher initial carbon intensity or lower environmental taxes; COCZs that have passed the confirmation assessment,COCZs which are invested by private enterprises, as well as light industry, logistics, and comprehensive COCZs have more significant carbon reduction effects. In addition, the establishment of COCZs can not only achieve synergistic efficiency in economic development and emission reduction, but also jointly contribute to global climate governance through in-depth integration with the construction of the "Belt and Road".The conclusion of this paper provides empirical evidence for China to join hands with the world to achieve a "win-win" of economic development and environmental protection, and also provides policy inspiration for global carbon pollution control in the next stage.

    As countries increasingly pursue sustainable development, the host countries have become more stringent in their requirements for the green transformation of China's overseas direct investment (OFDI). In this context, some Western media have seized the opportunity to spread negative narratives, such as "pollution manufacturing", which has severely damaged China's OFDI image. This article uses data from the World Bank Development Indicators and other sources from 2004 to 2020 to construct a non-balanced panel data model. It explores the green effects of Chinese OFDI on host countries and their mechanisms. The results show that Chinese OFDI has a significant and stable long-term effect on reducing green carbon emissions in host countries. The claim by some Western media that Chinese OFDI is pollution manufacturing is entirely false. The primary pathways for the spillover of the green effects of Chinese OFDI in host countries are the transfer of green technology and improvements in energy consumption habits. Bilateral government regulations in China and host countries tend to align in their performance during the process of reducing carbon emissions through OFDI. The 'social stability effect' derived from host country government regulations and the 'national image' cohesion shaped by Chinese government regulations both reinforce the carbon reduction effects of OFDI in host countries. Compared to other groups, Chinese OFDI has a more pronounced impact on carbon reduction in high-income countries, high R&D expenditure countries, and high carbon emission countries.In other words, Chinese OFDI accelerates the carbon reduction process in host countries through the 'multiplier effect','benchmarking effect', and leapfrog upgrades. The article fully confirms the positive impact of Chinese OFDI on host country environmental protection, which not only reveals the increasingly important role of responsible Chinese enterprises in building a new system of higher level open economy at the micro level, but also has important implications for conveying the image of responsible enterprises and great powers to the world.

    China's urbanization has made remarkable achievements in the past decades, but the problem of "semi-urbanization" remains prominent. In fact, there is a huge gap between the urbanization rate of China's resident population (67.00%) and the urbanization rate of household registration in 2024, indicates that a large number of rural migrants worked 

in urbans but have not been transformed into citizens, which is not conducive to unleashing the consumption potential and realizing the common wealth. Therefore, China released the National New-type Urbanization Plan (2014-2020) in 2014, and set Anhui and Jiangsu provinces as the first batch of new-type urbanization pilots in 2015, aiming to exploring the reform of household registration, equalization of social security, and innovation of urban-rural factor mobility mechanism and other mechanisms for the construction of new-type urbanization. However, existing research lacks a quantitative assessment of the effects of China's new-type urbanization pilot policies, especially from the perspective of rural migrants.

    This paper uses the 2015 national new-type urbanization pilot in Jiangsu and Anhui provinces as a "quasi-natural experiment" and combines data from the China Migrants Dynamic Survey (CDMS) from 2011 to 2017, to empirically investigates the policy effects of China's new-type urbanization provincial pilots from the perspective of labor mobility. It is found that after the pilot, the rural migrant in the pilot provinces significantly reduced outflow to other provinces, indicating the positive effects of new-type urbanization in the pilot areas. Mechanism analysis shows that wage income is not a motivation for individual flow shifts, but rather access to more social security and enhanced urban integration. In addition, the paper further finds that the new-type urbanization pilot not only promoted a higher probability of rural migrants staying in the urban areas of the province, but also increased family-based migration within the province, which suggests that the new-type urbanization pilot in China has played a substantial and positive role in enhancing the process of citizenship of the rural migrants.

    The findings of this paper have important policy implications. First, to further reduce the migrants’ barriers of rural to urban, urban areas which absorb the inflow of the rural migrants should pay more attention to the demands of the rural migrant in terms of public services, improve the migrant's sense of identity and belonging to the inflow area, enhance their willingness to realize citizenship, and accelerate the settlement of the rural migrant in the urbans, so as to improve the new-type of urbanization. Secondly, the beneficial practices of pilot provinces of new-type urbanization should be actively utilized to systematically summarize and promote practical experience. Third, the regional scope of the new-type urbanization pilots should be further broadened to form more experiences of new-type urbanization construction according to local conditions. Currently,China's less urbanized provinces are mainly located in the western region, so it is possible to further implement pilot newtype urbanization in typical western provinces, explore more innovative initiatives conducive to the promotion of new-type urbanization, and further enrich the regional samples of China's implementation of the new-type urbanization strategy.

    The report of the 20th National Congress of the Communist Party of China emphasizes that "Chinese-style modernization is the modernization of Common Prosperity (CP) for all people." General Secretary Xi Jinping has also stressed the necessity of "resolutely preventing polarization and promoting Common Prosperity." Against this backdrop, China's per capita disposable income has significantly increased, and the battle against poverty has achieved comprehensive victory. However,as of 2024, China's Gini coefficient is 0.465, which remains well above the international safety standard of 0.4, indicating a substantial urban-rural income gap and persistently low farmer incomes. Notably, achieving CP faces numerous challenges,particularly due to low comparative returns in agricultural production and operations, a weakening of the traditional momentum for farmers' income growth, and an urgent need to enhance farmers' endogenous development capabilities and selfdevelopment abilities. In this context, the construction of Digital Village Construction (DVC) serves as a significant strategic initiative for advancing rural digital transformation and accelerating agricultural modernization, providing a viable pathway for promoting CP.

    This article outlines the impact mechanism of DVC on CP and empirically examines the effects of DVC on CP using panel data from 1, 637 counties in China from 2019 to 2020. Utilizing two-way fixed effects and moderation effect models from the perspective of external environments, such as economic vitality and economic foundation, the study reveals that DVC not only promotes CP but also exhibits a significant catch-up effect that helps narrow the CP gap between regions. Further analysis indicates that the digitalization of rural economies and rural infrastructure are the primary factors driving CP, while the digitalization of rural governance and rural living conditions have relatively minor impacts. Additionally, DVC predominantly promotes CP in major grain-producing areas and eastern regions, while its effect is relatively smaller in non-grainproducing areas as well as in central and western regions. Finally, moderation effect analysis shows that the enhancement of economic vitality significantly strengthens the promoting effect of DVC on CP, whereas improvements in economic foundations somewhat weaken this promoting effect.

    The potential marginal contributions of this article are reflected in three main aspects: (1) It emphasizes that the empowerment of CP through digital technology should rely on the characteristics of practical application scenarios, making the embedded regulatory mechanisms of economic vitality and economic foundation more explicitly, which serves as a beneficial complement to research on DVC. (2) By utilizing panel data from 1, 637 counties from 2019 to 2020 and employing a two-way fixed effects model to assess the impact of DVC on CP, the study effectively mitigates the endogeneity bias caused by crosssectional data, thereby enhancing the accuracy of the estimation results. (3) The article underscores the multidimensionality of DVC, representing it from the perspectives of rural infrastructure digitization, rural economy digitization, rural governance digitization, and rural living digitization. It examines the impact characteristics on CP from both an overall perspective and four distinct perspectives, employing quantile regression models to verify the catch-up effect of DVC on CP, thereby providing theoretical foundations and more accurate practical references for improving the policy framework that empowers CP through DVC.

    As the backbone of the new round of information technology revolution, industrial internet has gradually become a strategic infrastructure, a new application model, and a brand-new interactive scenario for manufacturing enterprises to reshape their ecosystems, providing a brand-new approach to promoting the transformation of production efficiency in manufacturing enterprises. This article treats the promotion of industrial internet pilot demonstration projects as a quasi-natural experiment. Based on microdata from Chinese manufacturing listed companies on the Shanghai and Shenzhen stock exchanges from 2012 to 2023, the study employs the staggered difference-in-differences (Staggered DID) method to investigate the impact of industrial internet on manufacturing enterprise productivity and validates the influence pathways of industrial internet from a flexibility perspective. The study finds that the industrial internet has a significant positive effect on enterprise productivity. Mechanism analysis indicates that the industrial internet primarily enhances productivity through pathways that strengthen enterprise flexibility, specifically by improving enterprise flexibility in terms of equipment software, organizational management, technical architecture, and resource allocation. Heterogeneity analysis reveals that the industrial internet's im pact on productivity varies significantly depending on different internal characteristics and external environments of enterprises. Further research indicates that, compared to production-oriented industrial internet, collaborative integration has a more pronounced effect on enhancing enterprise productivity. This study deepens the understanding of the role that the industrial internet plays in the production processes of micro-enterprises, providing detailed empirical evidence to support government policy planning and the development of more comprehensive strategic guidelines for manufacturing enterprises.

 Industrial Internet Technology; Key Core Technologies; Total Factor Productivity; Technology Factor Mobility