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Environmental Regulation Strategy Interaction on Corporate carbon performance --A Synergistic Perspective of Government-Commanded and Market-Incentivised Environmental Regulation. Wen, shuhui 文 2025, 46(12): 0-0-0.  DOI: 10.19571/j.cnki.1000-2995.2025.12.017 Abstract ( 2 )   Abstract: Achieving the 'dual-carbon' goal requires a top-level policy design that balances development and low-carbon. Policy innovation is crucial in realising the dual-wheel drive of the government and the market.Based on the panel data of Chinese listed companies from 2005 to 2018, this paper takes the dual pilot of carbon trading policies and top-10,000 energy?consuming enterprises program as a quasi-natural experiment, and explores the impact and mechanism of policy linkage on the carbon performance of enterprises from the perspective of the synergy between government-commanded and market-incentivised environmental regulation using dual machine learning. The empirical study demonstrates that:① the combination of government-mandated environmental regulations and market-driven incentives can effectively enhance the carbon performance of enterprises. The dual-pilot policy proves to be more effective in achieving the coupled governance of environmental protection and economic development compared to the single-pilot policy. ②Mechanism studies indicate that the dual-pilot policy is effective in mitigating the efficiency impacts of single-policy command-line environmental regulation. This is achieved through compensatory green innovation, mitigation of market distortions, and improvement of corporate financial performance. ③Heterogeneity studies indicate that the dual-pilot policy has a more pronounced promotional effect on the level of carbon performance in technology-intensive, capital-intensive, and high-polluting industries. Additionally, the policy has a greater impact on large-scale, high-growth firms with a good foundation for green innovation. This paper presents a new perspective on exploring the impact of heterogeneous environmental regulatory policy synergies on firms' green transformation. It provides micro-empirical evidence for governments to carry out environmental policy innovation. Related Articles | Metrics

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Research on the Connectivity of "Knowledge-Technology-Product" Multi-layer Innovation Network in the Field of Chip Manufacturing 2025, 46(12): 0-0-0.  DOI: 10.19571/j.cnki.1000-2995.2025.12.007 Abstract ( 0 )   The chip manufacturing industry is a strategic pillar for China’s technological self-reliance and high-quality development. The connectivity of its innovation networks directly affects China’s position and competitive advantage in the global innovation, industrial, and supply chains. However, existing studies have seldom explored the interactive connectivity of knowledge, technology, and product elements from a percolation-based multi-layer network perspective. This paper constructs multi-layer innovation networks for China and the world in the “knowledge-technology-product” dimensions, using data from research papers, patents, and product supply collaborations in the chip manufacturing sector from 2013 to 2022. By applying the generating function method based on percolation theory, the study characterizes the dynamic percolation process, measures the inter-layer and intra-layer connectivity, and reveals its structural evolution and connectivity thresholds. The findings are as follows: (1) There are significant differences in the connectivity of single-layer innovation networks in China’s chip manufacturing sector. The knowledge network remains stably connected, while the technology network has exhibited disconnection since 2018, and the product network shows an inverted U-shaped trend in connectivity. (2) The interactive connectivity of the “knowledge-technology-product” innovation chain is relatively low. The diffusion paths from knowledge to technology and from knowledge to products are technically connected but inefficient, and the path from technology to products is disrupted. (3) The distribution of the largest subgroups in the multi-layer innovation networks is uneven, with low aggregation of heterogeneous innovation resources, resulting in insufficient resilience across the overall network. Related Articles | Metrics

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Research on the impact of patent pledge on the digital transformation of enterprises 2025, 46(12): 0-0-0.  DOI: 10.19571/j.cnki.1000-2995.2025.12.021 Abstract ( 2 )   The digital transformation of enterprises is an important foundation for promoting the development of China's digital economy. Maximizing the driving effect of patent pledging on digital transformation is of great significance to the sustainable and healthy development of enterprises and the high-quality growth of China 's digital economy. Based on the data of China's A-share listed companies in Shanghai and Shenzhen from 2005 to 2022, this paper uses the multi-period difference-in-differences model to evaluate the impact of the patent pledging pilot policy on enterprise digital transformation and its underlying mechanisms. Research has found that pilot projects of patent pledge financing can promote the digital transformation of enterprises. Mechanism tests indicate that the pilot policy achieves this primarily by alleviating financing constraints and fostering technological innovation. Heterogeneity analysis shows that the promotion effect of pilot policies is more significant in non-state-owned enterprises and capital-intensive enterprises, and mainly concentrated in the fields of big data and business models, with no significant impact on enterprise intelligent manufacturing and informatization. This study theoretically enriches the research on the influencing factors of enterprise digital transformation and the economic effects of patent pledge, which has reference significance for promoting enterprise digital transformation and improving patent pledge financing pilot policies. Related Articles | Metrics

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Research on the impacts of intellectual property trade barrier on the innovation of Chinese enterprises 2025, 46(12): 0-0-0.  DOI: 10.19571/j.cnki.1000-2995.2025.12.020 Abstract ( 0 )   Intellectual property (IP) barriers have become one of the most significant non-tariff barriers in international trade today. Do they serve as obstacles to or catalysts for independent innovation by Chinese export firms? Existing research has yet to provide a clear answer to this question. Taking the United States' intellectual property infringement investigations against Chinese export firms (commonly known as Section 337 investigations) as an example, this paper empirically examines the impact of IP trade barriers on the innovation activities of Chinese export firms as well as the potential mechanisms at play, using data from Chinese manufacturing listed companies between 2007 and 2019. The results show that IP trade barriers significantly promote the innovation of Chinese export firms by encouraging firms to increase R&D investment, reduce reliance on external technology imports, and strengthen government R&D support, thereby significantly improving both the quantity and quality of their patents. Firm growth amplifies the positive effects of IP trade barriers on innovation capabilities, but the innovation-enhancing effects are weaker for non-state-owned enterprises than state-owned enterprises, and firms in highly marketized regions exhibit weaker innovation improvements than those in less marketized regions. Moreover, firms’ export dependency, asset specificity, and human capital levels positively moderate the incentivizing effects of IP trade barriers on innovation. The findings of this study not only deepen the understanding of the dynamics of innovation among Chinese export firms, but also provide policy implications for China to address technological suppression from Western countries and to reshape its new competitive advantages in the global market. Related Articles | Metrics

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The Impact of National Innovative City Pilot on Manufacturing Upgrading 2025, 46(12): 0-0-0.  DOI: 10.19571/j.cnki.1000-2995.2025.12.008 Abstract ( 1 )   This paper used the national tax sampling survey data from 2007 to 2015 to study the impact of the national innovative city pilot policy on the upgrading of the manufacturing industry. We found that the national innovative city pilot policy has significantly promoted the upgrading of the manufacturing industry. mainly through output adjustment and industry entry and exit; This policy significantly enhances the agglomeration of the high-tech manufacturing industry, R&D intensity, and capital deepening, thereby promoting the upgrading of the manufacturing industry; This policy significantly increases the labor, capital input, R&D expenditure, and performance of high-tech industry enterprises. The role of national innovative city pilot policies in upgrading the manufacturing industry is positively affected by the degree of marketization and government efficiency, and negatively affected by the degree of market segmentation; Its role is also influenced by the initial innovation level and the upgrading level of the manufacturing industry. Related Articles | Metrics

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Research on the Construction Path of China's Autonomous and Controllable Industrial Value Chain: Taking the Innovation of China's Large UAV Industry as an Example Tao-Hua, OUYANG 2025, 46(12): 0-0-0.  DOI: 10.19571/j.cnki.1000-2995.2025.12.002 Abstract ( 0 )   Abstract：Under the backdrop of de-globalization, the construction of China's industrial value chain not only pursues efficiency but also takes security into account. Especially for the strategic high-tech industries of latecomer countries, an autonomous and controllable industrial value chain that prioritizes security while considering efficiency profoundly influences a country's technological catch-up, economic development, and stability and security. In response to the theme of how to build an industrial value chain with the goal of autonomy and controllability in China, this paper conducts a longitudinal case study on China's large unmanned aerial vehicle (UAV) industry from the perspective of system resilience, exploring the typical characteristics, construction paths, and boundary conditions of the "China Chain". The research findings are as follows: Firstly, unlike mass-produced manufactured goods that can begin as "embedded participants" to cultivate competitive advantages through deep engagement in global value chain (GVC) divisions, complex sensitive products like large UAVs must start as "dominant players" to avoid the "low-end lock-in" risks of embedded participation and secure control over core value chain segments. This paper thus extracts five dimensions of the "China Chain" model—applicable products, initial conditions, actors, action pathways, and operational logic—anchored in the "dominant player" starting point. Secondly, a processual theoretical framework for building autonomy and controllable China Chains is proposed: The two ends of the industrial value chain (R&D and service sectors) constitute critical junctures. System resilience operates through anticipatory and process-based mechanisms across these junctures. Technological innovation and organizational synergy serve as dual drivers for achieving autonomy and controllability. Thirdly, opportunity windows and China’s aviation industry collaboration model emerge as necessary conditions for constructing autonomy-controllable value chains. This study contributes to expanding system resilience theory, enriching the academic discourse on "China Chain," and unveiling the "black box" of their construction. It also offers practical insights for "chain-leading" enterprises to strengthen their dominant positions and spearhead innovation in global industrial value chains Related Articles | Metrics

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Study on the Mechanisms of Foreign Access Enhancing Innovation Capability in High-Tech Enterprises —— A Case Study of BeiDou Navigation Technology 2025, 46(12): 0-0-0.  DOI: 10.19571/j.cnki.1000-2995.2025.12.011 Abstract ( 2 )   The mode of technological innovation in China has entered a critical transitional phase, shifting from imitative innovation to independent innovation, and from being a technological follower to becoming a parallel and leading player. In this process of transformation and development, market mechanisms are playing an increasingly important role, gradually becoming the endogenous driving force for high-tech enterprises to achieve technological updates and iterations for independent innovation. This paper takes the policy announced on December 27, 2012, which allowed foreign manufacturers to enter the market by publishing the interface control document for the Beidou Satellite Navigation System's space signals. Using panel data from 2000 to 2022 for Beidou Navigation technology enterprises, a breakpoint regression model is constructed to explore the impact of easing foreign market entry on the innovation levels of high-tech enterprises. The originality of this research lies in its micro-market mechanism analysis approach, which establishes a logical connection between micro-level enterprise behavior and macro-level innovation trends, providing theoretical justification for the independent innovation model of high-tech enterprises. The empirical results reveal three key findings:(1) Relaxed foreign market access enhances market competition intensity, driving continuous improvements in the innovation capabilities of BeiDou Navigation Technology enterprises. Concurrently, the BeiDou Navigation System has achieved global market competitiveness and world-leading status in critical technical domains; (2) Liberalized foreign entry leverages China's advantages of massive market scale, diverse market demands, and complete industrial systems to promote independent innovation in high-tech sectors; (3) Relaxed foreign access strengthens the role of the new national system in efficiently allocating innovation resources and accumulating capital, thereby accelerating innovation capacity building in high-tech enterprises. Related Articles | Metrics

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Smart Supply Chain Building and Enterprise Digital Innovation: Polarization or Inclusion? 2025, 46(12): 0-0-0.  DOI: 10.19571/j.cnki.1000-2995.2025.12.010 Abstract ( 1 )   Polarisation is a new feature of digital innovation, which makes it difficult for tail enterprises to break through key digital technologies; can the hand of digital public services be used to promote digital innovation from polarisation to inclusion? Based on urban supply chain innovation and application pilots, this paper characterises smart supply chain policies and examines the impact and mechanism of supply chain public digital services on enterprises' digital innovation. The study finds that the construction of smart supply chain significantly improves the digital patent application rate and authorisation rate of enterprises in the pilot cities, indicating that the public digital service of supply chain promotes the digital innovation of enterprises; the subgroups find that the construction of smart supply chain focuses on promoting the digital innovation of enterprises in the tail section of low-tech, low-efficiency, and overcapacity, indicating that the smart supply chain assumes the responsibility of the bottoming of the public digital service, and enhances the digital innovation of the tail section of enterprises by bridging the digital gap between the enterprises in the tail section. The test mechanism found that the information connectivity is a key factor in the development of the smart supply chain. The examination of the mechanism reveals that information connectivity, financial integration, and supply-demand connectivity are all important mechanisms for smart supply chain construction to promote digital innovation of enterprises. This paper further proposes policy implications in terms of accelerating the construction of digital public services in the supply chain and promoting digital innovation of tail-end enterprises. Related Articles | Metrics

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Research on the impact of managerial ties on enterprises' responsible innovation 2025, 46(12): 0-0-0.  DOI: 10.19571/j.cnki.1000-2995.2025.12.014 Abstract ( 1 )   In the context of public concerns about ethical issues in innovation, how to drive enterprises' responsible innovation to promote sustainable and high-quality development has become a common concern in academic and practical circles. Based on social capital theory and resource orchestration theory, this study explored the impact of managerial ties on enterprises' responsible innovation, and constructed a moderated mediation model. Using survey data of 309 technology-based enterprises and applying regression analysis and Bootstrap method, the empirical test found that: Both business ties and political ties have a positive impact on enterprises' responsible innovation; resource orchestration partially mediates the impact of business ties and political ties on enterprises' responsible innovation; long-term orientation of top manager positively moderates the relationship between resource orchestration and enterprises' responsible innovation, and positively moderates the mediating effect of business ties and political ties on enterprises' responsible innovation through resource orchestration. The findings expands the research on the antecedent of enterprises' responsible innovation, reveals the path and boundary conditions through which managerial ties affect enterprises' responsible innovation, and provides a theoretical basis for managing enterprises' responsible innovation practices. Related Articles | Metrics

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A Study on the Impact of Artificial Intelligence Applications on Industrial Chain Resilience: A Digital Innovation Ecosystem-Driven Perspective Wei-Feng, JIA 2025, 46(12): 0-0-0.  DOI: 10.19571/j.cnki.1000-2995.2025.12.003 Abstract ( 1 )   Abstract：The construction and improvement of digital innovation ecosystems provide huge opportunities for artificial intelligence (AI) applications to enhance industrial chain resilience. Based on provincial panel data from 2008 to 2021, this study employs a dual fixed-effects model, a mediation effect model, and a moderation effect model to empirically examine the impact of AI applications on industrial chain resilience driven by digital innovation ecosystems. The findings are as follows:(1) AI applications positively influence industrial chain resilience, and this conclusion remains robust after a series of robustness tests and addressing endogeneity issues.(2) Driven by digital innovation ecosystems, digital innovation bodies and digital innovation platforms partially mediate the impact of AI applications on industrial chain resilience, while the digital ecological environment plays a moderating role in this relationship.(3) The heterogeneity analysis reveals that the impact of AI applications on industrial chain resilience is more pronounced in central and western regions, areas with high-level digital innovation ecosystems, and regions with lower levels of advanced industrial structures. This study not only unveils the intrinsic mechanisms through which AI enhances industrial chain resilience from a novel research perspective, providing empirical evidence for strengthening chain resilience amidst global transformations, but also advances quantitative research on digital innovation ecosystems, enriching the existing theoretical content. Related Articles | Metrics

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Empowerment of data elements: public data opening and enterprise investment efficiency yanxi, Li 2025, 46(12): 0-0-0.  DOI: 10.19571/j.cnki.1000-2995.2025.12.006 Abstract ( 2 )   Breaking public data monopolies, enabling seamless data flow, and releasing data dividends are crucial for constructing new national competitive advantages. This study employs a quasi-natural experiment utilizing the opening of China’s municipal government data to construct a staggered difference-in-differences (DID) model, assessing the impact of public data opening (PDO) on enterprise investment efficiency. Findings show that PDO significantly improves investment efficiency by mitigating both underinvestment and overinvestment inefficiencies, primarily through information empowerment and institutional empowerment mechanisms. Heterogeneity analysis reveals that the impact of PDO on investment efficiency is influenced by enterprise characteristics, public data quality, and policy convergence. Further analysis identifies supply chain diffusion, investment scale, and regional spillover effects. Furthermore, PDO has been found to drive "productive" investment through "efficient" investment. In addition, it has been determined that PDO can promote total factor productivity of enterprises. This study contributes to theoretical understanding of PDO's role in market decision-making, highlights its positive externalities of PDO, and provides empirical evidence for optimizing resource allocation through data—reflecting the micro-level implementation of the nation's "developing data productivity" strategy. It also underscores the significance of government data infrastructure in fostering high-quality economic development. Related Articles | Metrics

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Research on the Impact and Mechanism of the Specialized and Sophisticated “Little Giants” Enterprises recognition policy on Enterprise Innovation Liu Wei, 刘伟 2025, 46(12): 0-0-0.  DOI: 10.19571/j.cnki.1000-2995.2025.12.013 Abstract ( 1 )   Specialized and sophisticated “Little Giants”enterprises are an important force in the national innovation-driven development strategy, but the existing micro research on the innovation effect of the recognition policy of specialized and sophisticated “Little Giants”enterprises is not deep enough. For this reason, this paper takes the small and medium-sized companies listed in 2015-2021 and the national specialized and sophisticated “Little Giants”enterprises recognized during this period as the research samples, and adopts the double-difference method to examine the impact of the recognition policy on the innovation quality and innovation efficiency of enterprises and the influence mechanism. It is found that the policy of recognizing specialized and sophisticated “Little Giants”enterprises can significantly improve the innovation quality and innovation efficiency of enterprises, and this conclusion still holds after a series of robustness tests. It is further found that the recognition policy improves firms' innovation quality and efficiency mainly through alleviating financing constraints, improving human capital acquisition and facilitating digital transformation. At the same time, the effect of the recognition policy on innovation quality and efficiency is more significant in the second batch of selected enterprises, enterprises applying the financial subsidy support means, and enterprises in the maturity and decline periods. This paper provides intuitive and powerful evidence for the effectiveness of the policy of recognizing specialized and sophisticated “Little Giants”enterprises , which has important theoretical and practical value for better assisting the cultivation of specialized and sophisticated “Little Giants”enterprises. Related Articles | Metrics

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The mechanism of mega-projects collaborative innovation: Evidence from the China’s high-speed railway Tang, Fangcheng 2025, 46(12): 0-0-0.  DOI: 10.19571/j.cnki.1000-2995.2025.12.001 Abstract ( 2 )   Under the technology decoupling between China and the US, overcoming the challenges posed by key core technologies being “neck stuck” has become a primary problem for Chinese mega-projects. Based on the innovation ecosystem theory, using a longitudinal single case analysis, this paper explores the mechanism of collaborative innovation among numerous participants in mega-projects by analyzing China’s high-speed railway technology “catch-up” process. The results illustrate that: the changes in core platform promote the evolution of the innovation ecosystem; the collaboration models and mechanisms of collaborative innovation among participants evolve at different stages of the innovation ecosystem’s development in mega-projects; collaboration among institutions, organizations, and knowledge interacts mutually, supporting and promoting the formation, evolution, and technological innovation efficiency of the innovation ecosystem. The study enriches the theoretical framework of innovation ecosystems based on Chinese practices, expands the scope of research on platform theory and collaborative innovation theory, and provides enlightenment for overcoming the “neck sticking” of critical core technologies in mega-projects in China. Related Articles | Metrics

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AI for X: Typical Patterns, Formation Mechanisms, and Evolutionary Mechanisms 2025, 46(12): 0-0-0.  DOI: 10.19571/j.cnki.1000-2995.2025.12.005 Abstract ( 0 )   A salient trend in the evolution and application of contemporary artificial intelligence is its provision of novel impetus for creative endeavors, including scientific research, technological innovation, and artistic creation, thereby engendering the phenomenon of AI for X. This phenomenon holds significant value in both practical and theoretical contexts. To this end, this paper delineates AI for X as "artificial intelligence-driven creative activities," drawing on an analysis of current trends and theoretical contemplation to examine its typical patterns, formation mechanisms, and evolutionary mechanisms. Our research makes three theoretical contributions: First, AI for X encompasses three distinct patterns: outsourcing, teaming, and principal-agent relationships. Moreover, the extent and depth of artificial intelligence's engagement in creative activities differ across these patterns. Second, the formation mechanisms of these patterns are predicated on the collaborative creation between artificial and human intelligence, establishing a division of labor and cooperative relationships among operators, managers, and entrepreneurs within creative activities. Third, as artificial intelligence's capacity to engage in creative activities advances, AI for X undergoes an evolutionary process from "outsourcing" to "team" to "principal-agent" models. Furthermore, the cognitive transition of artificial intelligence from being perceived as a "technical tool" to a "collaborative partner," along with the relative structuring of creative activities, modulates the evolution of AI for X's patterns. In conclusion, this research not only enhance our comprehension of the development and application of contemporary artificial intelligence but also offer a reference for selecting and applying the different patterns of AI for X in practical applications. Related Articles | Metrics

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How does the Development of Digital Economy Affect the Green Innovation of Heavily Polluting Enterprises 2025, 46(12): 0-0-0.  DOI: 10.19571/j.cnki.1000-2995.2025.12.018 Abstract ( 1 )   Green innovation is a key way to achieve high-quality economic development, and how to promote green innovation in heavily polluting enterprises in the digital economy era is an important theoretical and practical problem that urgently needs to be solved. This paper selects the matching data of urban digital economy and China's Shanghai and Shenzhen A-share heavily polluting listed companies from 2011 to 2019, and uses the fixed effect model to analyze the impact, channels and economic consequences of digital economy development on green innovation of heavily polluting enterprises. Research findings: (1) The development of the digital economy has significantly promoted green innovation in heavily polluting enterprises, and this promotion effect is sustained. (2) The development of the digital economy reduces financing constraints, encouraging enterprises to increase investments in research and development as well as environmental protection, thereby fostering green innovation activities. (3) Further analysis shows that the high level of attention from external stakeholders, including the government, the public, and investors, has enhanced the driving force for corporate green transformation, making the development of the digital economy increasingly significant in promoting corporate green innovation. (4) The green innovation driven by the development of the digital economy not only brings economic benefits to heavily polluting enterprises, but also does not increase the risk of their stock price collapse. This article provides a new perspective for studying the impact of digital economy development on green innovation of heavily polluting enterprises, and also provides policy references for exploring the path to enhance green innovation of heavily polluting enterprises. Related Articles | Metrics

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Research on the impact of digital transformation strategy of enterprises on internationalization commitment Cong, Cheng 2025, 46(12): 0-0-0.  DOI: 10.19571/j.cnki.1000-2995.2025.12.015 Abstract ( 2 )   In the face of the ongoing impact of the digital age and profound adjustments in the global economic landscape, how multinational enterprises leverage digital transformation to cope with a complex and changing international environment has become an urgent and significant issue. This paper examines multinational enterprises listed on the Shanghai and Shenzhen stock exchanges from 2012 to 2021, utilizing panel regression methods to explore the impact of digital transformation strategy of enterprises on internationalization commitment and the moderating role of legitimacy contexts on this relationship. The study finds: (1) Both endogenous-driven strategy and platform-dependent strategy enhance the construction of internationalization commitment; (2) Successful experiences tend to solidify corporate mindsets and organizational structures, thereby weakening the promotive effect of endogenous-driven strategy on internationalization commitment. Conversely, failed experiences, by promoting corporate reflection and learning, strengthen this positive relationship; (3) The environments with a high degree of institutional voids and cultural loose enhance the positive impact of platform-dependent strategy on internationalization commitment by providing a more tolerant and supportive developmental atmosphere. The conclusions advance the theoretical understanding of how digital transformation strategy of enterprises impact internationalization commitment, provide new perspectives and empirical evidence for Chinese multinational enterprises to utilize digital transformation to carve out international competitive advantages and deeply integrate into the global economy. Related Articles | Metrics

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How AI boosts productivity of new quality--evidence from listed companies in the new energy vehicle industry 2025, 46(12): 0-0-0.  DOI: 10.19571/j.cnki.1000-2995.2025.12.004 Abstract ( 0 )   With the wide application of digital intelligence technology, artificial intelligence has become an important driving force for the improvement of new quality productivity.Based on the panel data of listed companies in China's new energy vehicle industry in 2011-2022, this paper discusses the influence of artificial intelligence on the new quality productivity of the new energy vehicle industry.The results show that: (1) artificial intelligence can not only directly promote the improvement of industrial new quality productivity, but also indirectly promote the development of industrial new quality productivity by reducing the stickiness of R&D costs and transaction costs, improving the quality and efficiency of innovation;(2) The promotion effect of artificial intelligence in promoting the new quality productivity of the new energy industry has obvious heterogeneous characteristics and threshold effect.In non-state-owned enterprises and eastern regions, after Tesla enter the Chinese market, as well as in enterprises with a short established time, moderate listing age and large scale of employees, the promotion effect is more obvious;(3) The conduction effect analysis of the industrial chain shows that the downstream industry has a stronger transmission effect on the upstream industry. This study provides important inspiration for the government and enterprises to make better use of the AI empower dividend and improve the new quality productivity of the new energy vehicle industry in the new development pattern. Related Articles | Metrics