Intelligent manufacturing is the main starting point for the high-end, intelligent, and green development of the manufacturing industry, and it is an effective way to reduce carbon emissions in the manufacturing industry. Based on the sample of Shanghai and Shenzhen A-share manufacturing listed enterprises from 2010 to 2024, this paper examines how intelligent manufacturing affects carbon emissions and explores its mechanisms. The findings are as follows: (1)Intelligent manufacturing can significantly reduce carbon emissions, and there is heterogeneity at the regional, industry, and enterprise levels; (2)Intelligent manufacturing reduces carbon emissions by optimizing human capital structure, promoting enterprise technological innovation, enhancing energy use efficiency, and improving supply chain efficiency; (3)Environmental regulation negatively moderates the carbon-reduction effect of intelligent manufacturing, whereas environmental information disclosure positively moderates the carbon-reduction effect of intelligent manufacturing. The findings provide theoretical support and empirical evidence for promoting the development of intelligent manufacturing and facilitating carbon emission reduction.
The localization or offshoring of data centers by cross-border platform firms affects both their global operations and data security governance. It is very important to explore the interactive relationship between data center location strategies and gove-rnment regulation in the scenario of asymmetric information, which helps to improve regulatory effectiveness, and guide cross-border platform firms' compliance decisions. Based on this question, we develop the signaling game model to make analysis of the mechanism, that is how firms make choices between data center localization and offshoring, as well as how government make response. We further take TikTok case to explore the sensitivity of critical parameters and changing in different equilibrium outcomes. The research results show that increasing government penalties can improve data security level in some extent; however, under the scenario of high data risk, excessively severe penalties may be detrimental for the government's ability to find data security risks. What's more, data security risk and per-unit data revenue have a nonlinear relationship. Although higher revenue expands the range of separating equilibrium, it cannot get rid of pooling equilibrium, even in some cases, pooling equilibrium has dominant advantages. Moreover, a higher tax rate can shrink the region of separating equilibrium, meaning that strengthening tax-based regulation is insufficient to distinguish the compliance types of cross-border platform firms. These findings indicate that improving the le-vel of cross-border data governance need to make balances between data security and operations efficiency. Government need to establish a differentiated and flexible regulatory system, while cross-border platform firms should enhance its identifiability and resilie-nce through lots of compliance investment and high quality level about information disclosure.
Given the combined effects of the digital economy and global supply chain risks, it has become urgent to investigate how digital transformation can strengthen supply chain resilience. This article uses a two-way fixed effects model to empirically examine, based on panel data from Chinese listed companies, the effects of corporate digital transformation on supply chain resilie-nce and the underlying mechanisms. The results show that, first, digital transformation significantly improves the supply chain resilience of companies. From an economic perspective, each standard deviation of the degree of digital transformation increases supply chain resilience by 1.897% relative to the sample mean. Second, mechanism tests show that incentives for technological inno-vation, reduction of financial constraints, and strengthening of market competitiveness are the three most important factors through which digital transformation enhances supply chain resilience. Third, heterogeneity analysis shows that the effects of digital transformation on strengthening resilience are more pronounced in highly digitised companies and non-state-owned companies. This effect is more pronounced in samples with low industrial concentration and better regional information infrastructure, and is significantly attenuated by companies' dependence on the supply chain. Fourth, a more detailed analysis shows that digital transformation not only strengthens the resilience of companies themselves, but also optimises the granting of trade credit and encourages supply chain diversification. This article enriches research in the field of supply chain management and offers useful policy guidance for strengthening supply chain resilience through digital transformation.
Against the backdrop of"Digital China", leveraging digital transformation as an opportunity to promote outward foreign direct investment(OFDI)holds significant importance for advancing high-level opening-up. This paper first constructs a theoretical framework for analyzing the impact of digital transformation on enterprises' OFDI. Based on data from A-share listed companies in China between 2009 and 2024, an econometric model is established to empirically examine the effects and mechanisms of digital transformation on Chinese enterprises' OFDI. The findings are as follows: (1) digital transformation significantly promotes Chinese enterprises' OFDI, a conclusion that remains robust after a series of rigorous tests. (2) The promotional effect of digital transformation on OFDI is notably stronger for high-tech enterprises compared to non-high-tech enterprises. Additionally, the impact of digital transformation on OFDI is more pronounced among enterprises in eastern China than those in central and western regions. (3) Digital transformation facilitates Chinese enterprises' OFDI primarily by alleviating financing constraints and enhancing product market competitive advantage. (4) Economic policy uncertainty negatively moderates the relationship between digital transformation and Chinese enterprises' OFDI, with higher uncertainty weakening the influence of digital transformation on OFDI.
Effectively promoting the widespread dissemination and application of green technology is an important way to achieve coordinated progress between the economy and the environment. Based on data from Chinese A-share listed enterprises from 2010 to 2024, this study establishes a quasi-natural experiment through a data trading platform to explore the impact effect and mechanism of data factor market building on enterprise green technology diffusion. The research results indicate that data factor market building significantly promotes enterprise green technology diffusion. Heterogeneity analyses find that for enterprises with advantages in capital, management, and innovation factors, the promotion effect is more significant. Mechanism testing shows that data factor market building accelerates enterprise green technology diffusion by increasing entrepreneurial activity and technology market activity. Both environmental regulation and market competition strengthen this promoting effect. The research conclusion provides theoretical support for deepening data factor market building and strong empirical evidence for promoting green technology diffusion.
Against the backdrop of heightened uncertainty in the global economic environment, innovation among Chinese enterprises faces severe challenges. Supply chain equity participation, as a novel model of deep supply chain collaboration, can more effectively mobilize high-quality resources, providing crucial support for enterprises to achieve resilient innovation. Using a sample of Chinese A-share listed manufacturing companies from 2013 to 2024, this study empirically examines the impact of supply chain equity participation on corporate innovation resilience and its underlying mechanisms. Findings reveal that supply chain equity participation significantly enhances innovation resilience through dual pathways: "reducing absorbed organizational redundancy" and "increasing unabsorbed organizational redundancy". Heterogeneity analysis indicates that this promotional effect is more pronounced in firms with weaker financial health, higher supply chain efficiency, higher governance levels and in the high-tech industry. This study expands prior research on the antecedents of corporate innovation resilience from the property rights perspective of supply chain governance structures, revealing the critical mediating role of organizational redundancy. It provides important theoretical foundations and managerial insights for firms seeking to enhance innovation resilience by optimizing supply chain equity partnerships in complex environments.
Against the backdrop of accelerated evolution of the global technological revolution and profound restructuring of the international competitive landscape, strategic emerging industries such as new energy and new materials have become the core engine driving high-quality economic development. As innovation entities breaking through key "chokepoint" technologies, "little giant" enterprises with specialization, refinement, differentiation, and innovation (SRDI) characteristics play a strategic role in achieving technological self-reliance and controllability through their radical innovation. Based on a collaborative framework of "market-government-enterprise", this study employs the fuzzy-set qualitative comparative analysis (fsQCA) method, using a sample of 89 SRDI "little giant" enterprises in China's strategic emerging industries from 2020 to 2022, and use interpolation to fill missing data, extend the time period to 2024, and conduct robustness tests., to explore the multiple driving paths of radical innovation. The findings reveal that radical innovation has no single necessary condition but is achieved through multiple factor configurations, with three main paths identified: government-enterprise-talent synergy type, market-led type, and government-empowerment type. Heterogeneity analysis further shows that differences in enterprise life cycle, scale, and region significantly affect path selection: enterprises in the growth stage rely on the dual drive of "government subsidies + entrepreneurial spirit", while those in the maturity stage exhibit more diversified paths; enterprises in the central and western regions and large-scale firms place greater emphasis on the external policy environment, whereas those in the eastern region and small-scale firms depend more on endogenous drivers from digital transformation.
Cultivating corporate innovation resilience is the only way to move towards becoming a world technology powerhouse. Using a sample of A-share listed companies in China from 2012 to 2024, this study examines the impact of supply chain common shareholders on corporate innovation resilience. The results show that supply chain common shareholders enhance corporate innovation resilience. Common shareholders enhance corporate innovation resilience by leveraging the effects of governance assura-nce, resource stabilization, and information transmission-sharing. These effects function to strengthen resilience-centric capabilities across the entire innovation chain. Heterogeneity analysis reveals that in firms with higher innovation capacity, greater ownership concentration and lower risk-taking levels, those located in regions with weak legal environments, the impact of supply chain common shareholders on corporate innovation resilience is more pronounced. These findings elucidate the contextual pathways through which this novel collaborative governance model fosters innovation resilience.
At present, the construction of "Reverse Innovation Enclaves" has become an important starting point to promote regional coordinated development. This paper systematically collects the information of "Reverse Innovation Enclaves" across the country, constructs relevant databases, and combines the panel data of 283 prefecture-level cities in China from 2010 to 2023 to empirically analyze the impact of "Reverse Innovation Enclaves" construction on urban innovation efficiency by using multi-time point difference-in-difference method. The study finds that the "Reverse Innovation Enclaves" significantly improves the innovation efficiency of the cities(especially large cities) in the central region, and has no significant impact on the eastern and western cities. The "Reverse Innovation Enclave" has a significant promoting effect on the innovation efficiency of the inflow cities in the enclave, which is particularly prominent in the developed eastern and central regions, but the effect has obvious scale threshold, mainly concentrated in the mega cities in the enclave. This paper can provide an empirical reference for the regions to carry out the construction of "Reverse Innovation Enclaves", which is of great significance to break the barriers of regional development and rea-lize the coordinated development of the region.
This study investigates how battery remanufacturers' capacity conditions at different development stages influence decision-making in a new energy vehicle closed-loop supply chain. A two-stage Stackelberg game is formulated between a vehicle manufacturer and a battery remanufacturer, in which novel production constraints induced by remanufactured battery transactions and the manufacturer's learning effect are incorporated. The analysis shows that when the remanufacturer is at an early development stage with remanufacturing capacity constraints, the remanufacturer's collection effort, collection volume, and profit admit a unique equilibrium and increase with the transaction price of remanufactured batteries, while the manufacturer's pricing, sales, and profit exhibit piecewise equilibrium characteristics. In this case, higher consumer acceptance of remanufactured products does not affect the remanufacturer's profit and does not necessarily improve the manufacturer's profit. When the remanufacturer enters a mature stage characterized by battery production constraints, the manufacturer's pricing, sales, and profit possess a unique equilibrium, with product prices positively related to the battery transaction price, whereas the remanufacturer's collection effort and profit vary with the transaction price, and increased consumer acceptance is not always beneficial to the manufacturer. Furthermore, in the absence of learning effects, the manufacturer's pricing decisions are identical across the two scenarios and independent of the remanufacturer's behavior. The role of learning is shown to be scenario-dependent: strengthening the learning effect does not necessarily reduce prices but always increases the manufacturer's profit in the early-stage scenario, while under the mature-stage scena-rio it can, under certain conditions, generate positive effects for all members and improve overall system performance.
Improving the carbon emission efficiency of China's power industry is an important approach to achieving the "dual carbon" goals. Using data from 30 Chinese provinces(autonomous regions and municipalities)from 2005 to 2024, this paper constructs a global super-efficiency EBM model to measure the carbon emission efficiency of China's power sector. A double machine learning model is used to examine the effects and mechanisms of the carbon trading policy on this efficiency. The findings indicate that: (1)The carbon trading policy can significantly improve the carbon emission efficiency of China's power industry. (2) Mechanism analysis reveals that the policy enhances efficiency through two approaches: the technological progress effect and the ene- rgy management effect. (3)Heterogeneity analysis shows that the positive impact of the carbon trading policy is more pronounced in eastern regions and areas with stronger environmental law enforcement. Based on these findings, the paper proposes relevant policy recommendations.
Environmental regulations are an important means to promote the green transformation of economic and social development. How to leverage the "complementary" effect of heterogeneous environmental regulations to accelerate the development of green productivity plays a crucial role in achieving the coordinated progress of environmental protection and high-quality economic development. Based on the panel data of 30 provinces (autonomous regions and municipalities) in China from 2011 to 2024, this study examines the impact of heterogeneous environmental regulations on economic high-quality development, the transmission mechanism, and the spillover effect. The findings are as follows: (1)Both formal and informal environmental regulations contribu-te to promoting the high-quality development of China's economy. After a series of robustness tests, the results remain valid and have a significant "promoting and increasing" effect. (2)Heterogeneous environmental regulations promote regional industrial structure transformation by encouraging enterprises to optimize their industrial structure and increase investment in high value-added industries, providing endogenous impetus for high-quality economic development. (3)Heterogeneous environmental regulations have a more significant impact on the "Belt and Road" regions, regions with abundant natural resources, and during the implementation period of the environmental tax law. (4)After considering spatial correlation, heterogeneous environmental regulations and high-quality economic development exhibit the characteristic of "like-minded people becoming similar", and heterogeneous environmental regulations have a clear "spillover effect" on the improvement of high-quality economic development in neighboring regions. This study provides theoretical support and empirical evidence for promoting a comprehensive green transformation and promoting economic high-quality development to a new level.
Guided by the strategic directive of the Fourth Plenary Session of the 20th CPC Central Committee—to "synergistically advance carbon peaking, pollution reduction, ecological expansion, and economic growth"—this study investigates how data-driven governance enhances environmental co-benefits. Using a panel dataset of 272 prefecture-level and above cities in China from 2011 to 2024, we exploit the staggered implementation of the National Big Data Comprehensive Pilot Zone policy as a quasi-natural experiment and employ a multi-period difference-in-differences (DID) model to systematically examine the impact, mechanisms, and heterogeneous effects of big data development on synergistic pollution reduction and carbon mitigation. The results show that: (1) the policy significantly and robustly improves the synergy level between pollution reduction and carbon mitigation; (2) this effect operates through two key channels—facilitating artificial intelligence adoption, and stimulating green technological innovation; (3) the effectiveness is significantly moderated by institutional context: market segmentation attenuates the policy impact, whereas heightened governmental environmental attention amplifies it; and (4) the synergy-enhancing effect is more pronounced in resource-dependent cities and regions with intense intergovernmental competition. These findings offer theoretical support and actionable policy insights for leveraging digital technologies to advance green and low-carbon transformation and implement China's dual carbon goals with precision.
Driven by the new round of technological revolution and industrial transformation, the new form of intelligent economy, represented by artificial intelligence, data elements and computing power systems, is accelerating its evolution and has become an important foundation for the development of new quality productivity. Theoretically, the intelligent economy gives rise to new types of production factors and economic entities, promoting the continuous innovation and expansion of Marxist political economy theories such as the labor theory of value and the theory of productive forces. In practice, the deep integration of the digital and real economies and the digital and intelligent transformation of industries have become the core paths for the construction of a modern industrial system, with local governments and innovation support mechanisms playing significant roles. In terms of governance, to address prominent issues such as the imbalance in the distribution of data rents, insufficient effective demand, and changes in the employment structure, it is necessary to build a fair, inclusive, safe, and efficient institutional guarantee system. The intelligent economy represents an all-round transformation of productivity, production relations, and governance systems. It is essential to base ourselves on national strategies and promote the coordinated development of theoretical innovation, practical advancement, and governance improvement to provide strong support for the high-quality development of the intelligent economy and the construction of Digital China during the 15th Five-Year Plan period.
Global lithium security hinges on a multi-tiered trade architecture—ore, salts, batteries, and scrap—yet cross-tier risk transmission remains under-explored. Integrating bilateral trade data from 2023~2024, this study quantifies network vulnerability via simulations of link severance, geopolitical decoupling, and cascading failure. Observations suggest a marked fragility in midstream lithium carbonate and hydroxide hubs, where a lack of alternative pathways led to accelerating efficiency decays during 2024. In contrast to physical route blockages, geopolitical decoupling triggers more extensive systemic damage, particularly within the raw-material tier, though scrap recycling networks offer a partial buffer. Crucially, cascading-failure models reveal a "bullwhip" amplification effect: a 20% upstream supply contraction can congest 75% of downstream nodes once midstream bottlenecks are breached. Compared to 2023, the 2024 system exhibits reduced redundancy and a narrowed window for policy intervention. These insights shift the analytical focus from single-node snapshots to a dynamic, full-chain transmission framework.
In recent years, against the backdrop of China's increasingly consolidated position as the "world's factory", developed industries such as the United States, Europe, and Japan have been striving to achieve new re industrialization and high-end manufacturing through exploratory deployment of "future factories" to ensure their leading position in advanced manufacturing. From the 2022 National Strategy for Advanced Manufacturing (NSAM) in the United States, to the European Factory of Future (EFoF) in the European Union, and to Japan's latest Manufacturing White Paper (2023 edition), similar forward-looking underl-ying logic can be seen: the "future factory" with rich "industrial innovation genes" is likely to change the global manufacturing development pattern, and developed economies around the world will strive to implant it into their respective industrial systems first to lead the direction of future manufacturing. In response to the future global manufacturing changes, China must introduce future factories, form new intelligent productive forces, build new carriers of green energy, and create flexible new industries. Chain, achieving new breakthroughs and triggering new qualitative changes.
