Amid the rapid progression of technological and industrial revolutions, China's traditional low-cost advantages are gradually diminishing, necessitating a shift toward competitive advantages grounded in core technologies. In response to this pivotal transformation, President Xi Jinping proposed the theory of "new quality productive forces", summarizing the developmental trajectory of advanced productive forces, and the recent trends in technological innovation, intelligentization, and green development, along with the crucial role of new technologies, industries, business models, and forms in contemporary productivity growth. The concept of new quality productivity has emerged in the wake of the digital economy's rapid expansion in recent years. This burgeoning economic paradigm is increasingly integrating with, enhancing, and redefining the contours of the real economy, serving as a pivotal force in its structural evolution and transformative energy dynamics. In this new phase of rapid technological and industrial transformations, the deep integration of the digital and real economies has become an essential pathway for advancing new quality productive forces.
To drive the development of new quality productive forces through the integration of the digital and real economies, it is essential to foster the convergence of digital and physical technologies. This convergence creates both the necessity and possibility for the integration of the digital and real economies. On one hand, digital technological innovation and application can leverage the diversity and rich application scenarios of physical technologies, accelerating the fusion of digital technologies with various applications and promoting the transformation of scientific achievements into actual productivity. This facilitates the scaling and industrialization of emerging technological fields, enabling enterprises to explore new domains and create new opportunities, thus providing new momentum for the development of new quality productive forces. On the other hand, physical technological innovation and the digital transformation of enterprises can capitalize on the additive, synergistic, and multiplying effects of digital technologies. This drives digital and intelligent transformation across R&D, production, and distribution processes, enhancing cost reduction, efficiency improvement, and revenue growth. It promotes the advancement of foundational capabilities and fosters new technologies, business models, and forms, all of which contribute to the development of new quality productive forces.
Therefore, this study, using data from China's A-share manufacturing enterprises from 2012 to 2022, explores the impact and mechanisms of digital-physical technology integration on the development of new quality productive forces. In light of the three foundational elements of new quality workers, production tools, and labor, this study expands upon these by incorporating the dimensions of technological innovation, digital transformation, and sustainable development. It proposes new indicators to evaluate the productivity of this new quality labor force. It is found that the integration of digital and physical technologies significantly promotes the improvement of new quality productive forces in enterprises. By exploring the mechanisms of enterprise transformation and upgrading, the study confirms that the integration of digital and physical technologies enhances new quality productive forces through channels such as high-tech, high-efficiency, and high-end transformations; it further reveals the role of production relations, demonstrating that the ownership attributes of state-owned enterprises, intensified inter-enterprise competition, deepened inter-enterprise cooperation, and government regulation all contribute to the enhancement of new quality productive forces through digital-physical technology integration;it uncovers that digital industrialization enterprises, industry digitalization enterprises, and new real economy enterprises are differentially influenced by regional digital infrastructure and digital innovation capabilities in terms of how digital-physical technology integration drives new-quality productive forces development.
In brief, this study provides a new quantitative measurement of new quality productive forces, and the findings of this study enrich the literature on the measurement methods and mechanisms of new quality productive forces and provide data-based evidence for the formulation of relevant policies. Future studies could examine the technological dichotomy between digital and physical technologies. Additionally, it would be insightful to investigate how the maturity and modularity of physical technologies influence their integration with digital counterparts. Beyond the synthesis of digital and physical technologies, future studies might also focus on the dynamic interplay and convergence of digital economy constituents—such as data elements and digital platforms—with traditional real economy components. This convergence at the elemental level can be perceived as a mechanism for integrating the digital and real economies.

It is of strategic significance to break through the bottlenecks of core technologies in key fields, and these breakthroughs are strongly related to the technological gap and self-reliance in science and technology, and existing research has roughly been divided into two divisions: at the micro level, the concept, characteristics, identification methods, mode paths, and breakthrough factors of core technologies in key fields are summarized; at the macro level, the breakthrough paths of core technology innovation are discussed from the perspectives of system structure, mechanism system, and supporting policies. The relevant research focuses primarily on theoretical speculation, with little empirical research on specific cases, and its guiding value in management and policy in practice needs to be improved. Thus, this paper uses the exploratory single case study method to analyze the specific innovation activities of enterprises and opens the "theoretical black box" for enterprises to break through core technology mechanisms from the perspective of dynamic capability evolution.#br#By analyzing the development process of BGI′s gene sequencer technology in China, this paper proposes a breakthrough mechanism model for core technologies in key fields based on dynamic capability evolution. The model demonstrates that enterprise-led breakthroughs in core technologies in key fields generally occur through four stages of dynamic capability evolution: preface, transformation, transition, and diffusion, and it is a positive feedback process in which dynamic capability evolution and ecological innovation promote each other. Among them, the pre-order of competence accumulates strength for breaking through core technologies in key fields through the commercial application of foreign technology products, focusing on perception and capture, so that enterprises can occupy a higher niche in the commercialization of the industrial chain′s middle and lower reaches. The breakthrough difficulty of core technologies is in the stage of capability transformation, and it develops in three dimensions: perception ability, capture ability, and reconstruction ability. In the transition period, the capability transition stage is critical for core technology breakthroughs. Chinese enterprises started by learning foreign technologies, and they have occupied a niche in technology research and development, and initially formed the trend of core technology breakthroughs on a technical level. Through large-scale R&D, independent and controllable core technology systems and product systems are formed to occupy a high niche in the technological R&D link in the upstream of the industrial chain. In the capability diffusion stage, enterprises use the core technologies in key fields they control to develop the innovation ecosystem, relying primarily on the ecological reconstruction ability to expand the dynamic capability of enterprises into the dynamic capability of the innovation ecosystem, and realize independent control and domestic substitution in the two main links of technology research and development and market adoption, driving the entire industry to achieve self-reliant development.#br#To successfully break through core technologies in key fields, businesses must follow a set of rules, including completing the reverse breakthrough of "application-research and development", adopting a "different technical route from foreign enterprises" in order to construct a "technology-product" system, creating and maintaining an independent and controllable supply chain system, and setting up an ecosystem of platform-based innovation. It should be noted that the breakthroughs of core technologies led by enterprises are time-sensitive catch-up activities that frequently require catching up under the established technological paradigm and competing with foreign enterprises by building an independent and controllable technological system, supply chain, and innovation ecosystem to replace or even expel foreign enterprises′ products. As a result, it is necessary to begin at a higher technical level and select appropriate methods for directly obtaining international cutting-edge technology. More importantly, in order to truly complete the breakthroughs of core technologies in key fields, Chinese enterprises must accelerate the diffusion of core technologies, promote related enterprises to form an autonomous and controllable supply chain, and then build an autonomous and controllable innovation ecosystem around core technologies in key fields, widely absorb different types of innovation subjects, and establish various forms of collaborative research and development.#br#

Stimulating regional green innovation's vitality and harnessing the enabling effects of digital industry agglomeration on regional green innovation are crucial for high-quality economic and social development. Green tech innovation supports economic transformation and sustainability, enhancing efficiency and achieving sustainable development goals. Digital industries alleviate corporate costs, reduce pollution, and provide financial backing for green innovation.Understanding the impact and internal mechanism of digital industry agglomeration on regional green innovation is key to unleashing their potential and improving regional green innovation systems.
Therefore, this study first constructs a theoretical framework and discusses the impact of digital industry agglomeration on regional green innovation from the two dimensions of innovation factors and innovation environment. On the one hand, digital industry agglomeration can accelerate the agglomeration of innovation factors such as human capital, technology and capital, provide factor support for regional green technology innovation, and thus help improve regional green technology innovation capabilities; on the other hand, digital industry agglomeration will also impact external environmental factors that affect green technology innovation, such as government environmental regulation,green financial development, and market competition pressure, thereby enhancing regional green innovation vitality. In addition, considering that digital industry agglomeration is closely related to the government's digital support, marketization level, and digital foundation level, the above factors will not only directly affect the speed and scale of digital industry agglomeration,but also have an impact on the green technology innovation effect of digital industry agglomeration. Therefore, the study analyzes the possible differential impacts of digital industry agglomeration on green technology innovation from the three dimensions of government digital support, marketization level, and digital foundation level.
The study employs the panel fixed effects model, the mediation mechanism model, and the instrumental variable method to conduct tests, using the panel data of 30 provinces in China from 2011 to 2022. It draws three conclusions. First, digital industry agglomeration significantly improves regional green technology innovation level,and the conclusion still holds true after robustness testing by adding interactive fixed effects,adjusting samples,changing variable measurement methods,instrumental variables, etc. Second, digital industry agglomeration can not only accelerate the aggregation of technological innovation factors such as human capital, technology, and R&D funds, but also strengthen government environmental regulation, accelerate the development of green finance, and increase market competition pressure, thereby promoting the improvement of regional green innovation levels. Third, the agglomeration of digital industries has strong digital support for the government and a high level of marketization, the promotion effect of green innovation in areas with low digital basic level is stronger than that in areas with weak government digital support, low marketization level and high digital basic level.
Corresponding policy recommendations are proposed from three perspectives. First,with the development of digital industry clusters as the starting point, it is essential to promote the innovation of production technology and methods through green technology innovation,and further stimulate the two-way progress effect between digitalization and greening. To be specific, it is necessary to continue to refine the digital ecosystem to leverage the benefits of shared resources, collaborative innovation, enhanced efficiency, and cost reduction from the agglomeration of digital industries, and stimulate new momentum for regional green technology innovation and the development of a green economy. Meanwhile, it is crucial to reinforce policy guidance, align the orientation of digital industries towards green development through strategic macroeconomic policies, and improve the coordination between the growth of the green and digital economies to ensure the harmonization of ecological, economic, and social benefits. Secondly, in the future, local governments should optimize the allocation of innovation factors such as talents,technology,and capital,realize the effective connection between the innovation chain and the industrial chain,and further optimize the regional green innovation ecology,accelerate the development of green finance,and ensure the function of green finance in promoting high-quality development. Finally, different regions should adopt different development strategies, adapt to local conditions and time, avoid the "one-size-fits-all" approach, and build the advantages of digital industry clusters and release the dividends of green technology innovation in combination with their own characteristics.

Along with the Sino-U.S. trade dispute , the complex geopolitical situation and other variable factors, supply chain friction has become the norm. The risks associated with the flow of capital, information, and logistics in the supply chain have dramatically increased, making it urgent to improve the chain's resilience in order to mitigate disruption risk and maintain the chain's security and stability. At this stage, the importance of data elements in empowering supply chain governance is becoming more and more prominent, and the scale of data assets owned and the ability to transform them into productivity have become important factors in gaining new competitive advantages. From the perspective of supply chain network characteristics, the penetration and application of data elements in the subject and structural elements of the supply chain have significantly revolutionized the operation mode of the supply chain, and become a key driving factor to enhance risk-taking and ensure the continuity of supply and demand.
This study investigates the enabling mechanisms of data elements on the subject and the structural resilience of the supply chain in order to reveal the supply chain resilience enhancement paths in a more thorough and detailed manner. As a result, given the network characteristics of the supply chain, the subject element and structural element may show different resilience mechanisms against risks. By employing the OLS regression model, the study collects data from Chinese listed companies between 2015 and 2022 and uses text analysis to create indicators that show the application level of enterprise data elements. It then uses supply chain subject resilience and structural resilience to characterize the overall resilience of the supply chain and empirically investigates the impact of data elements on resilience.
The research results show that data elements can effectively enhance the level of enterprise risk-taking and the stability of supply-demand relationship, and the findings remain robust after a series of endogeneity and robustness tests, showing that data elements can effectively enhance both supply chain subject resilience and structural resilience. In addition, the application of data elements by enterprises can effectively enhance the innovation effect and the information effect, thus improving the innovation capability of enterprises and obtaining the information advantage to promote the resilience of the supply chain. At the same time, the enabling effect of data elements on supply chain resilience can be differentiated by the internal and external environments of enterprises, that is, the enabling effect is stronger when the enterprise is large, operates in a highly competitive industry, and is situated in an area with a poor supply chain operating environment and high marketization.
Compared with the results of previous studies, this study expands the research perspective of supply chain resilience, constructs enterprise-level supply chain resilience measurement indexes from the perspective of network characteristics, and enriches the research scope of supply chain in the era of digital economy; and it further empirically examines the two indirect empowerment mechanisms of innovation effect and information effect, which provides a useful supplement to the research on the empowerment mechanism of data elements on supply chain resilience. Through the analysis of the research findings, this study proposes to accelerate the construction of data element marketization, further activate the potential of data elements in enhancing supply chain resilience, and formulate targeted data elements application solutions according to the differences in the internal and external environments of enterprises, which will help the government optimize the policies on data elements and supply chain and support the scientific decision-making of enterprises, and have certain theoretical significance for the implementation of the strategic plan of "focusing on enhancing the resilience and security of industrial chain and supply chain".
Future research may integrate the two dimensions of supply chain entity resilience and relationship resilience into a comprehensive index for research, further combine the characteristics of the supply chain to reveal the mechanism path involving more data elements to empower supply chain resilience improvement, and the subsequent economic impacts of data elements empowering supply chain resilience improvement could be predicted.

At the moment when AI technology is fully penetrated into all fields of social life, the rise of AIGC(Artificial Intelligence Generated Content) represented by ChatGPT, Sora and ERNIE Bot marks the leap of AI technology to a new stage of development, and indicates the approach of the era of "artificial general intelligence". However, while AIGC greatly amplifies human innovation potential, it also presents considerable challenges to the existing ethical governance system. Against this backdrop, this article examines the current state and future trends of AIGC in China, analyzing its ethical risks and generative logic. Drawing from the ethical risk governance trends of AIGC globally, the article proposes a governance framework that is not only attuned to China's national context but also forward-looking. This is aimed at providing robust theoretical guidance and practical paths for the standardized development of AIGC.
This study commences with an analysis of the potential ethical risks associated with AIGC, considering its technical attributes. Initially, it addresses the risk of ethical value imbalance, primarily evident in the intensification of algorithmic discrimination. Following this, it examines the risk of ethical norms being beyond control, which is predominantly showcased in the challenge of accountability. Lastly, it explores the risk of ethical relationship imbalance, which is chiefly characterized by a diminution of human agency. From the perspective of technological risk, the root cause of AIGC ethical risk lies in the complexity and uncertainty of technology. Particularly under the 'black box' phenomenon of algorithms, the behavior of AIGC becomes challenging to anticipate and manage, thereby amplifying ethical risks. At the same time, the tension between technological rationality and value rationality, as well as the limitations of human risk perception and response, further deepen the complexity of ethical risks.
Considering the trends in AIGC governance, this article advocates "trusted governance" as the core strategy to mitigate AIGC ethical risks. It underscores the importance of technology being controllable, accountable, fair, reliable, interpretable, and secure, with the goal of ensuring that technological advancements are transparent, equitable, and contribute positively to society. At the same time, the Artificial Intelligence Law (scholars' proposal draft) also provides important governance basis and guides the legal path of AIGC trusted governance.
Under the principle of 'trusted governance, this article proposes three core strategies. First, it calls for the establishment of a robust data risk governance framework. By integrating cross-border collaborative governance and internal fine governance, it emphasizes adherence to 'reliability' standards. This includes enhancing regulations for cross-border data flows and promoting data ethics and compliance within enterprises to ensure data usage is reliable and secure. Second, it advocates for an optimized liability attribution mechanism to address AIGC infringement risks. This involves assessing subject obligations, product defects, and infringement liability in light of AIGC's technical characteristics to enforce the 'accountability' standard. Third, it recommends integrating a 'people-oriented' approach into the AIGC ethical governance system. This aims to find technological solutions that are tailored to China's context and capable of addressing its unique challenges. In practice, it shall involve two aspects: first, at the organizational level, creating a dedicated AIGC ethical governance body to oversee ethical governance and supervision, thereby enhancing AIGC's controllability; and second, at the normative level, harnessing the 'complementary advantages' of policies, laws, and technology to uphold standards of 'fairness,' 'safety,' and 'interpretability,' guiding AIGC towards positive development.
In the future, it is essential to further integrate market development with China's national conditions, adopting 'trusted governance' as the core and the 'Proposal Draft' as the foundation to construct a comprehensive ethical risk governance system for AIGC. Moreover, there is a need for ongoing exploration in the realm of ethical governance, focusing on the organic integration of technological ethics with legal governance. This approach aims to devise AI ethical governance strategies that are distinctively Chinese, thereby equipping to adapt to and potentially spearhead the high-quality development of the new round of the global digital economy.

International industrial transfer is an important way for emerging countries to participate in globalized mass production and to be embedded in the global value chain division. Since the fourth international industrial transfer, intra-industry transfers have replaced inter-industry transfers, with transnational corporations taking the lead in globalized mass production on the basis of factor endowments. Many countries only take on a part of the production chain; developed countries firmly control the high-end segment of the value chain by virtue of their advanced technologies, and developing countries generally occupy the middle- and low-end production segments. China and the ASEAN countries are typical of the outward-looking economic development model, and under this "low-end embedded" global value chain model, China and ASEAN countries are mainly engaged in low-end processing, assembly and other labor-intensive production processes in the manufacturing industry, and they are still locked in the middle and lower ends of the global value chain by developed countries. At present, how to promote China and ASEAN countries to make leaps forward in the manufacturing global value chain has become an important issue to be resolved.
In order to determine the general rule of the impact of international industrial transfer on the status of global value chains, the article measures the scale of international industrial transfer between China and ASEAN countries from 1995 to 2018 based on the OECD-TiVA (2021) database, using the input-output model and the GVC decomposition method, and further divides the international industrial transfer into two categories, namely, international industrial transfer of intermediate products and international industrial transfer of intermediate products. The theory analyzes the mechanism of the impact of industrial transfer on the status of global value chain, and the positive impact mainly stems from the three aspects of technology spillover, financing constraints and product quality improvement. Negative impacts mainly stem from FDI technology lock-in, "crowding-out effect" and "low-end lock-in" effect. Technological innovation is the endogenous driving force for the upgrading of GVCs in China and ASEAN countries. Firstly, technological innovation can improve the labor productivity of the manufacturing industry, enhance the international competitiveness of products, and achieve product upgrading; secondly, technology can also promote the improvement of the original production process and the research and development of new products, so as to achieve the upgrading of the manufacturing industry's functions; lastly, technological innovation can promote the enterprises to leap from the low-end to the high-end, and ultimately achieve the upgrading of the GVCs.
The research results show that international industrial transfer has an inverted U-shaped relationship with the GVC status of manufacturing industries in China and ASEAN countries, which implies that, in the long run, there is a ceiling effect on the upgrading of manufacturing GVCs in China and ASEAN countries. At present, most of the manufacturing industries have not yet crossed the inflection point, and are in the "moderate range" of international industrial transfer to promote the upgrading of manufacturing GVC status, which is conducive to promoting the upgrading of manufacturing GVC status in China and ASEAN countries, and the inverted U-shape relationship is still robust after a variety of robustness tests. The moderating effect of technological innovation is significant, weakening the inverted U-shaped relationship between the two, and contributing to flatten the inverted U-shaped curve of the impact of international industrial transfer on the GVC status of the manufacturing industry than that in the benchmark regression results. In the short term, technological innovation will increase the innovation investment of enterprises in China and ASEAN countries, which increases the cost and risk of enterprise application; in the long term, as the embedded position in the GVC of China and ASEAN countries continues to improve, technological innovation can reduce the technological dependence on developed countries, achieve technological independence and autonomy and enhance the international competitiveness of enterprises. Extended analysis reveals that forward GVC participation weakens the inverted U-shaped relationship between international industrial transfer and manufacturing GVC position, while backward GVC participation strengthens this "low-end lock-in" effect; the inverted U-shaped curve between international industrial transfer of final products and manufacturing GVC position is steeper than that of international industrial transfer of intermediate products.

Enhancing the resilience and security levels of industrial and supply chains is critical for new developmental strategies. It also represents a crucial strategic choice for a nation's medium-to-long-term economic and social development. Moreover, it serves as an essential cornerstone in building a manufacturing powerhouse. A comprehensive, large-scale, and competitive industrial system has been fundamentally established in China, wherein the overall security and resilience of the industrial chains are being consistently fortified. However, the current global socio-political and economic landscape is fraught with complexities and uncertainties, exposing industrial chains to external risks such as disruptions and decouplings. Internally, these chains suffer from deficiencies like inadequate foundational innovative capabilities and a low position in the global value chain. Therefore, exploring avenues for augmenting industrial chain resilience is paramount for realizing the strategic objectives of high-quality development. Leading firms, acting as the 'architects' in constructing and evolving the entire industrial ecosystem, play a pivotal role in guiding industrial objectives and integrating relationships between upstream and downstream stakeholders. These firms can spearhead concerted efforts in critical cross-cutting technologies within the chain and facilitate the flow and sharing of innovative resources among entities within the chain. Hence, it is instrumental in enhancing industrial chain resilience by fully leveraging the ecological leadership of leading firms.
Existing literature has delved into the roles of leading firms and industrial chain resilience. However, it lacks a nuanced and differentiated analysis of the ecological leadership dimensions exerted by leading firms. Additionally, scant research has been conducted from a micro-enterprise perspective to examine the unique mechanisms through which leading firms, as dominant actors in the industrial ecosystem, contribute to enhancing industrial chain resilience. To bridge this gap, the present study employs grounded theory methodologies and conducts case studies comparing BYD and the Chinese new energy automotive industrial chain to investigate the capability dimensions of ecological leadership by leading firms and the processes by which they enhance industrial chain resilience.
The findings reveal that (1) in their development, leading firms progressively establish ecological leadership capabilities that enhance the resilience of industrial chains. These capabilities are categorized into three dimensions: technological innovation leadership, industrial collaboration and integration, and digital transformation empowerment. Specifically, technological innovation leadership is manifested through capabilities in technological innovation and leading innovation. Industrial collaboration and integration are demonstrated through resource integration and relationship coordination capabilities. Digital transformation empowerment is embodied in digital concept empowerment, digital resource empowerment, and digital structure empowerment. (2) The ecological leadership exerted by leading firms enhances the resilience of industrial chains through three distinct pathways: breakthroughs in key technologies, coordinated industrial linkages, and digital transformation of the industrial chain. Firstly, relying on their capabilities in technological innovation, the leading firms disseminate technology, knowledge, and information to firms within the chain. Then, through autonomous innovation and open, collaborative innovation with intra-chain firms, significant advancements in key technologies are achieved, thereby filling the gaps in weak technological links and considerably bolstering the resilience of critical elements within the industrial chain. Secondly, on the basis of their capabilities in industrial collaboration and integration, leading firms collaborate with large, medium, and small enterprises, as well as upstream and downstream entities, facilitating the development of a stable system for coordinated industrial linkages. This enables prompt adjustments to be made, thereby maintaining stability when disruptions impact the industrial chain. Thirdly, anchored by their capabilities in digital transformation empowerment, leading firms realize comprehensive digital transformation in R&D, production, and product intelligence, markedly enhancing product quality, user experience and competitive advantage. Concurrently, this drives the acceleration of digital transformation among smaller firms within the chain, thereby promoting an ascendancy in the value of the industrial chain and augmenting its efficiency and resilience.
This study, while clarifying the specific dimensions encompassed by the ecological leadership of lead firms, also provides an in-depth and expanded analysis of the essence, manifestation, and functionality of each dimension. From a micro-enterprise perspective, the study unveils specific pathways for augmenting the resilience of industrial chains, enriching the viewpoints in existing resilience studies, and extending the scope of research on the resilience of individual industrial chains to the new energy automotive industrial chain.

Promoting the sound and fast development of new quality productive forces is a crucial step for China to respond to the new challenges of the global science and technology revolution and industrial transformation in the new era and achieve high-quality economic development. In the context of the digital era, the infiltration of digital technologies such as big data, artificial intelligence, and blockchain into the real economy has given rise to new models and industries such as smart manufacturing and digital agriculture, and changed the way traditional industries produce and operate. The integration of digital economy and real economy has become an important systemic base and strategic driving force for the development of new quality productive forces. However, infrastructure bottlenecks and uneven regional development limit the role of digital-physical integration in promoting the development of new quality productive forces. How to further promote the integration of digital economy with real economy, with a focus on developing new quality productive forces, is a key question that must be addressed at present.
Existing research has addressed the role of economic activities generated in the process of digital-physical integration in promoting new quality productive forces, but it has not yet clarified how digital-physical integration can better form new quality productive forces. In fact, no single factor can adequately elucidate the intricate dynamics propelling the advancement of new quality productivity; thus, a broader perspective is essential for a more holistic understanding. While a one-size-fits-all approach is insufficient for guiding regions in selecting development drivers that align with their unique circumstances, necessitating further investigation into diverse pathways tailored to specific realities. Additionally, empirical research that systematically examines the evolution of data-physical integration and its qualitative influence on new quality productivity remains scarce.
Considering the complex interactive effects of the elements of digital-physical integration, this paper, based on the view of complex systems, constructs an analysis framework of "digital foundation-digital industry-digital finance-industrial structure-industrial agglomeration-industrial chain modernization" for digital-physical integration. It uses the dynamic qualitative comparative analysis method to analyze and reveal the relationship between the path evolution of digital-physical integration and the emergence of new quality productive forces in the case of 30 provinces, autonomous regions, and municipalities across China from 2013 to 2022.
The research results show that (1) neither the digital economy nor the real economy possesses a single, indispensable condition for fostering high new quality productive forces. (2) In the aggregated configuration analysis, there are mainly three constituting pathways, namely, digital finance empowerment type, full-chain digital upgrade type, and high-tech industry agglomeration type. (3) A comparison of the configuration results indicates that a robust digital foundation and a thriving digital industry are pivotal in catalyzing new quality productive forces during digital-physical integration, whereas digital finance and industrial agglomeration exhibit a substitutable relationship. (4) The inter-group analysis shows that the aggregated configuration has a temporal universality, while the formation of new quality productive forces has undergone an evolutionary process from high-tech industry agglomeration-oriented to digital finance empowerment-oriented and further differentiation. (5) The intra-group analysis indicates that the formation of new quality productive forces requires tailored development, and the agglomeration-oriented configuration of high-tech industries is suitable for areas where the industrial chain is not yet fully developed, while areas with better digital finance development are more poised to cultivate new quality productive forces.
This paper establishes an analytical framework of "digital economy-real economy" linkage configuration for the emergence of new-quality productive forces, revealing the complex causal relationships behind the emergence of new-quality productive forces. It analyzes the development of new-quality productive forces, which has undergone a transformation from the regulation of a materialized economic system to the regulation of a virtualized economic system. The paper has developed the perspective of complex systems regarding the creation of new technologies.Furthermore, it offers tailored recommendations for enhancing new-quality productive forces, tailored to local contexts, such as bolstering the construction of digital infrastructure and the digital industry, encouraging and supporting the development of digital finance, and accelerating the industrial chain's modernization.

Elevating the level of intelligence is a pivotal measure for enterprises to expedite the formation of new quality productive forces. As a new generation of digital technology, artificial intelligence has realized subversive innovation in production methods, production processes and models, accelerated the transformation of production factors to production capacity, and provided new momentum for developing new quality productivity. However, most existing research on artificial intelligence focuses on the macro level. More literature needs to be examining how artificial intelligence technology empowers the development of enterprises' new quality productive forces.
Therefore, this paper delves into artificial intelligence's empowerment path for enterprises' new quality productive forces. This study focuses on A-share listed companies from 2013 to 2022 to explore the impact of artificial intelligence on the new quality of productive forces within enterprises and the mechanisms that facilitate this influence. Drawing on the theoretical insights, it develops a regression model to assess the effects of AI and further examines the mechanisms through three key lenses: technology empowerment, efficiency empowerment, and information empowerment. To ensure the robustness of the findings, the study performs a series of rigorous checks. These include substituting variable indicators, applying the Propensity Score Matching (PSM) technique, conducting Two-Stage Least Squares (2SLS) regression analysis, and employing a quasi-experimental design centered on the smart transformation of pivotal industries. The results consistently demonstrate the robustness and reliability of our conclusions. Lastly, the empowering effect of artificial intelligence on new quality productive forces can significantly differ because of the distinct internal characteristics and external environment of enterprises. Consequently, the study conducts a heterogeneity analysis of the main effects across three core dimensions of enterprise-level,industry-level,and regional differences.
The study finds that artificial intelligence significantly enhances the development of enterprises' new quality productive forces. Mechanism analysis further reveals that this enhancement is achieved by strengthening digital innovation capabilities, improving the efficiency of supply chain, and mitigating the information asymmetry. Heterogeneity analysis demonstrates that there exist notable disparities in the enabling effects of artificial intelligence on new quality productive forces among different types of enterprises. Specifically, state-owned enterprises, labor-intensive enterprises, those situated in high-tech industries, and those located in regions with substantial fiscal support all exhibit more prominent improvements in their quality new productive forces, being empowered by artificial intelligence. This paper enhances the comprehension of the role of artificial intelligence in the production process at the micro-enterprise level, thereby providing valuable insights for promoting the efficient development of enterprises' new quality productive forces.
The innovations of this paper lie in the following three aspects: Firstly, this paper studies the impact of artificial intelligence level on enterprise development in micro-enterprises. Existing research on artificial intelligence primarily focuses on macro-level effects, such as its influence on regions, industries, and labor markets, with relatively scarce studies at the micro-enterprise level. Furthermore, previous works often measured the artificial intelligence level of enterprises using industrial robot penetration rates, whereas this paper employs text analysis and machine learning methods to construct an artificial intelligence index for enterprises. Secondly, this paper enriches the research on new quality productive forces in enterprises. As a newly proposed concept, the new quality productive forces have predominantly been studied qualitatively, exploring its connotations, characteristics, and formation logic. By leveraging data from listed companies, this paper empirically analyzes the influence of artificial intelligence technology on enterprises' new quality productive forces. Thirdly, this paper provides theoretical support for promoting the enhancement and development of enterprises' new quality productive forces. This paper delves into the mechanisms through which artificial intelligence empowers new quality productive forces from the perspectives of technology, efficiency, and information. The heterogeneous effect on the main effect is further discussed in relation to the differences at enterprise ,industry and regional levels. It offers valuable insights for upgrading enterprises' new quality productive forces.

New quality productive forces are the inherent requirement and important focus for promoting high-quality economic and social development, and they put forward new requirements to construct a new model and new mechanism for the in-depth integration of scientific and technological innovation and industrial innovation.At present, the complexity of global science and technology innovation is getting higher and higher, and the competition system has shifted from single-point technology in the past to the competition of technological ecosystem, from the competition of application technology to the competition of basic research, and the cross-fertilization and convergence and integration between science and technology are accelerating the evolution.At the same time, a new round of industrial change led by digital science and technology has reached the "technological singularity" of application transformation, and frontier technologies such as general artificial intelligence, gene editing, brain-like science and technology, and quantum information are gradually moving towards the critical "window period" of technological life.Therefore, major scientific and technological research and breakthroughs in original technologies increasingly require in-depth cooperation, open synergy and cross-fertilization among multiple disciplines and multiple innovation subjects.How to strengthen the status of enterprises as the main body of scientific and technological innovation and play the role of innovation consortium as a "new quality carrier" has become an important issue to promote the in-depth integration of industry, academia and research, accelerate the transformation of scientific and technological achievements into real productivity, and develop the new quality of productive forces.
On the basis of the typical practice cases of innovation consortiumempowering new quality productive forces, this paper follows the ground theory to critically combs related classical theoretical literature, process data, and code the collected textual information step by step, mainly including open coding, main axial coding and selective coding, and refines the sub-category, main category and core category in order to identify the theoretical mechanism of the innovation consortium that empowers new quality productive forces.Against the backdrop of national "four oriented" major needs, the theoretical mechanism and practical path of innovation consortiumempowering new quality productivity are analyzed in depth from the "strategy-led + market-led + context-driven" perspective.
This study proposes a three-dimensional "strategy-led-market-oriented-context-driven" framework for innovation consortiumto empower new productive forces.Using the cases of Xiaomi, Huawei, and Baidu, it further analyzes the main practical paths for innovation consortiumto empower new productive forces, including (1) strengthening basic research and original technology curation to accelerate the cultivation of pioneering capabilities; (2) building high-energy innovation consortiums to accelerate the breakthrough of key core technologies; (3) accelerating the transformation of scientific and technological achievements into real-life productive forces according to diversified contexts; (4) strengthening the four-chain integration and empowerment to build a modernized industrial system; and (5) integrating "active government" and "effective market" to enhance the overall effectiveness of the national innovation system.
By revealing the theoretical mechanism and practical path of innovation consortium to empower new quality productive forces, this study provides an important theoretical basis and practical inspiration for the state and regions to efficiently coordinate and lay out industrial innovation consortium, promote industrial innovation through scientific and technological innovation, accelerate the cultivation and development of new quality productive forces.Firstly, major scientific and technological research should be carried out through innovation consortium to enhance the technological support capacity of industrial innovation and development.Secondly, innovation consortium should be utilized to promote the integration of industry, academia and research, and accelerate the transformation of scientific and technological achievements into real productive forces.Third, innovation consortium should be used to empower the industrial chain and innovation chain, and boost the construction of modernized industrial system.

Nowadays, major countries in the world have attached great importance and priority to promoting disruptive innovation which is of high investment, high risk and high return, and China urgently needs to establish a normalcy mechanism for discovering, selecting, and cultivating disruptive technology, focus on excavating and discovering a number of disruptive technology directions, improve the quality and supply efficiency of disruptive technology, and rapidly improve the national comprehensive powers. In order to accurately select and deploy technologies with disruptive potential, it is essential to master the regularity of disruptive technology development ;thus, this paper constructs an evaluation index system, and proposes a multi-data source fusion analysis framework, for studying the development and evolution of disruptive technologies.
Academic papers and invention patents are important carriers of scientific and technological innovation, and government policies are important factors in promoting scientific and technological development. It is important way for studying the regularity and path of disruptive technology development to exploiting the latent data information in academic papers, patents, and the Natural Science Foundation, and establish the interactive relationship between these information and disruptive technology. This paper constructs an indicator system of seven dimensions to evaluate the development and evolution of disruptive technology, including the number growth rate of published papers, the citation growth rate of published papers, the cited growth rate of published papers, the number growth rate of filed patents, the citation growth rate of filed patents, the cited growth rate of filed patents, and the funding growth rate of Natural Science Foundation. Then, for each indicator, temporal variation characteristics are analyzed with the major historical events of the disruptive technology from a quantitative analysis perspective. Finally, the coefficient of variation method (CV) is used in fusion analytics of multi-type indicators, obtaining a fitting curve, and then the law of disruptive technology development is analyzed with major historical facts.
GPS technology is a typical disruptive technology that experiences a relatively complete technology lifecycle, and it is going into the large-scale application stage. Therefore, this paper takes the GPS technology as an empirical case to research the law of disruptive technology development. According to the principles of authority and completeness, this paper collects data from the Web of Science Core Collection Database, the Patsnap Patent Database, the Natural Science Foundation Database of the U. S. , and open-source data on the internet. Then, these data are analyzed using the proposed method, such as extracting related indicator features from papers, patents, and natural science foundations, and conducting analysis on the temporal variation characteristics of the indicators with the relevant historical events.
The case of GPS technology reveals that the development of disruptive technology requires several rounds of technical innovation breakthroughs, and these breakthroughs are achieved under the synergistic effects of military need, scientific theory, technology application, and the policy environment. Among these effects, military need and market demand are the direct driving forces for the formation and development of disruptive technologies. Basic theory is the source power for the formation and development of disruptive technologies. Technological innovation is the important driving force for the formation and development of disruptive technologies, and government policy is the catalyst for the formation and development of disruptive technologies.
On the basis of the research results, this paper suggests that it is pivotal to strengthen research on the development and evolution of disruptive technology, utilize advanced scientific methods, technical tools, and expert experience to study, identify, and predict disruptive technologies, improve awareness, understanding, and insight of disruptive technology. Then it is essential to sustain funding on scientific frontier and interdisciplinary research, provide long-term and stable support for basic interdisciplinary research, promote the cross-integration of natural sciences and engineering fields, and keep obtaining the source force for the development of disruptive technology. Finally, it is need to construct a multi-stage intervention mechanism for disruptive technology. According to technological development and market status, it is necessary to input different degrees of policy intervention and resource investment at different technological stages to improve the efficiency of resource utilization.

Disruptive technological innovation has important strategic significance for China's strategic emerging enterprises to break through foreign technological blockades and achieve independent control of key technologies. It is precisely through the evolution and development of a series of disruptive technological innovations that China's new energy vehicle enterprises have achieved a profound transformation in key technologies and market patterns. Therefore, it is of significance to clarify the internal mechanism of disruptive technological innovation in China's new energy vehicle enterprises, which can provide reference for the innovation and development of strategic emerging enterprises.#br#Disruptive technological innovation is endowed with strong exploration, a long research and development cycle, and high risk. The relevant technological and market changes evolve through the interaction of technological iteration innovation and market segmentation diffusion. Therefore, revealing the evolutionary laws of disruptive technological innovation in China's new energy vehicle enterprises from both technological and market perspectives is the underlying logic for exploring its realization mechanism. However, the existing research on the realization mechanism of disruptive technological innovation of China's new energy vehicle enterprises is mostly based on the guiding role of macro-policies and the synergistic effect of middle-level industries, and insufficient attention is paid to the innovative main role of new energy vehicle enterprises; the evolutionary laws of disruptive technological innovation in technology iteration and market diffusion in China's new energy vehicle enterprises are not clear, and the dynamics and complexity of disruptive technological innovation in enterprises are in need of deconstruction; moreover, the interaction between resource-focused actions and dynamic capabilities and their mechanism of action on disruptive technological innovation are in the vague.#br#Therefore, this study aims to answer the following questions: (1) What are the laws of the occurrence and evolution of disruptive technological innovation in China's new energy vehicle enterprises? (2) How do enterprises conduct resource-focused actions and build dynamic capabilities at different stages of development? (3) How does the interaction effect of resource-focused actions and dynamic capabilities affect the disruptive technological innovation of China's new energy vehicle enterprises?#br#To address the issues, the paper selects 5 typical cases of China's new energy vehicle enterprises for longitudinal exploratory research, and forms 87 000 words of cross-verification data through diversified data collection methods. It firstly identifies the key milestone events of three enterprises for stage division. Then it extracts 3 core categories, 9 main categories and 27 subcategories from 392 pieces of evidence through open coding, axial coding and selective coding, and further constructs the process model of disruptive technological innovation of China's new energy vehicle enterprises in combination with stage markers. Thirdly, the study conducts a theoretical saturation test on the process model using the remaining two enterprises. On the basis of the process model, the paper constructs a realization mechanism model of disruptive technological innovation in new energy vehicle enterprises in order to explore the interaction effects between resource-focused actions and dynamic capabilities on the realization and evolution of disruptive technological innovation.#br#The study finds that (1) the disruptive technological innovation of new energy vehicle enterprises presents three characteristics: continuous enrichment of technological innovation methods, continuous iteration of technological life cycle, and sequential realization of niche market development, medium and high-end market penetration and high-end market introduction; (2) enterprises have gradually realized the combination, capability and leverage of resources through the resource-focused actions of resource bricolage-resource choreography-resource orchestration, while the dynamic capabilities have experienced the evolution process of externally oriented environmental perception, internally driven learning and innovation, and internal and external collaborative integration and expansion capabilities, realizing the upgrading from the first-order ability to adapt to the environment to the second-order ability to create new capabilities; (3) as the key factors for the realization and evolution of disruptive technological innovation, the interaction between resource-focused actions and dynamic capabilities of enterprises has experienced a three-stage transition from factor aggregation to knowledge innovation to system symbiosis, and they have respectively played foundation, promotion and leading roles in the emergence, development and upgrading of disruptive technological innovation. The research conclusions provide strategic support for promoting China's new energy vehicle enterprises to carry out organized disruptive technological innovation activities.#br#

The development and application of emerging information technologies, such as artificial intelligence, has promoted the digital and intelligent transformation of enterprises and changed the way people work. This has also sparked a wave of hybrid work in China. Innovative working modes may affect employee innovation outcomes. Hybrid work combines technology, platforms, and innovation capabilities, which impacts employees' innovative performance, yet the impact of hybrid work on employee innovation performance has not been fully explored. Existing research has overlooked the dual effects of hybrid work on innovation performance. On one hand, hybrid work allows employees more time for personal pursuits, family, friends, and hobbies, achieving a win-win situation for both employees and organizations. This promotes better work-family balance, thereby enhancing employee innovative performance. On the other hand, the workplace presence is a unique contextual feature of hybrid work. The use of communication technologies and other media in hybrid work can reduce employees′ workplace presence, potentially negatively affecting their innovation outcomes. Additionally, employees′ cognitive evaluations play an important moderating role in how hybrid work impacts innovative performance.#br#Thus, this paper integrates the stimulus-organism-response (SOR) theory and social presence theory, focusing on the characteristics of hybrid work. These characteristics include the impact of information technology on the relationship between family and work, as well as how the use of information technology changes the workplace presence. By introducing work-family balance and workplace presence, the study delves into their mediating roles between hybrid work and innovative performance. Additionally, it explains the boundary roles of challenge appraisal and hindrance appraisal.#br#This study conducted a questionnaire survey among employees with hybrid work experience in various regions, including Central China (Hubei, Anhui), Northwest China (Ningxia), South China (Guangdong), and East China (Shanghai). Over three phases, a total of 432 valid responses were collected. The scales used in the questionnaire are adapted from established scales both domestically and internationally. Data analysis was performed using the Bootstrap method by the Mplus 8.3. The results indicate that hybrid work enhances employees' innovative performance through the mediating role of work-family balance, with challenge appraisal playing a positive moderating role. Conversely, hybrid work reduces employees' innovation performance through the mediating role of workplace presence, with hindrance appraisal playing a negative moderating role.#br#Following the SOR theory and the social presence theory, this study investigates the double-edged sword effect of hybrid work on employees' innovation performance, and examines the moderating roles of challenge appraisal and hindrance appraisal. The main contributions are threefold. First of all, it constructs a research model to verify the double-edged sword effect of hybrid work on employees' innovation performance, breaking through the one-sidedness of previous studies on hybrid work performance. Secondly, from a research perspective, it studies employees' innovation performance in hybrid work based on SOR theory and social presence theory. By introducing workplace presence and work-family balance, it partially opens the "black box" of the impact mechanism of hybrid work on employees' innovation performance, expands the application of social presence theory in the field of human resource management, and opens new theoretical perspectives for subsequent research. Thirdly, in exploring boundary conditions, it introduces individual cognitive appraisal to study its role in the double-edged sword effect of hybrid work on innovation performance, providing a more comprehensive explanatory framework for understanding the role of individual cognitive factors in innovation performance.#br#Finally, this study proposes some effective management strategies and suggestions to improve employees' innovation performance in hybrid work environments. These include (1) preventing the negative impact of reduced workplace presence on innovation performance by emphasizing the key role of workplace presence in hybrid work and implementing measures to mitigate its reduction; (2) recognizing the positive impact of work-family balance on innovation performance by paying attention to the essential needs of employees for work-family balance in hybrid work and supporting these needs; and (3) clarifying employees' cognitive differences towards hybrid work by understanding and addressing the different perceptions and cognitive evaluations about hybrid work. These strategies aim to enhance the positive aspects of hybrid work while mitigating potential negative effects, thereby improving overall innovation performance among employees.#br#

Shareholder activism in modern enterprises has a positive impact on corporate reputation as well as long-term growth, and thus it is an important factor affecting corporate operations. The demands of activist shareholders include not only improving financial performance, but also actively seeking the improvement of corporate social performance and paying attention to the sustainable development of enterprises. Environmental shareholder activism has emerged in the context of a growing global consensus on environmental and climate issues, and enterprises that are targeted by shareholder activism are more likely to respond positively to environmental needs. Green innovation is the most effective way for firms to tackle pollution, especially those in heavily polluting industries, but few studies have yet explored the impact of environmental shareholder activism on corporate green innovation. The most important influencing factor for enterprises in heavily polluting industries to carry out green innovation comes from the enterprises themselves. Among them, differences in corporate governance will have different effects on corporate green innovation. Shareholders will naturally pay more attention to green innovation in order to enhance the profitability of enterprises. Thus, this paper explores the impact of environmental shareholder activism on corporate green innovation based on the fact that enterprises in heavily polluted industries are the focus of attention in the promotion of green development in China.#br#This study selects A-share listed enterprises in the heavy pollution industry in China's Shanghai and Shenzhen stock markets from 2013 to 2022 as the research sample. After screening the preliminary matched samples, it obtains a total of 1 037 enterprises and 8 076 observation samples. Then, the study collects data on environmental shareholder activism and green innovation of sample companies, empirically examines the impact of environmental shareholder activism on corporate green innovation, and explores the role mechanism of management's environmental attention on this effect. Further, it examines the heterogeneous effects of contextual factors such as the level of environmental regulation, the degree of marketization in the region, and the nature of corporate ownership on the relationship between shareholder environmental activism and corporate green innovation.#br#It is found that environmental shareholder activism can significantly promote green innovation in enterprises, and after specifically categorizing green innovation into green utility innovation and green invention innovation, environmental shareholder activism can play a significant role in promoting both types of green innovation, which verifies the important role of environmental shareholder activism in promoting green governance. The mechanism test results suggest that increasing managerial environmental attention is an important mechanism path for shareholder environmental activism to promote corporate green innovation, shareholder environmental activism can raise managerial environmental attention, and then promote corporate green innovation. Heterogeneity analysis finds that the promotion effect of environmental shareholder activism on corporate green innovation is more pronounced in firms that are subject to stronger environmental regulations, located in regions with a higher degree of marketization, and with the nature of state-owned property rights. Once again, stronger environmental regulation and a good market environment constitute a favorable external environment for promoting green innovation in enterprises, and the government should design appropriate environmental regulation tools, create a good market environment and play the role of market facilitation.#br#There are three potential marginal contributions in this study. Firstly, it enriches the research on the antecedents of enterprise green innovation. From the perspective of shareholder governance, this study confirms the role of environmental shareholder activism in promoting the green innovation of enterprises, and provides a new perspective for investigating the green innovation of enterprises. Secondly, it enriches the research category of shareholder activism. There are few studies exploring the impact of shareholder activism on corporate green innovation. This paper expands and deepens the research on shareholder activism by confirming the positive governance effect of shareholder environmental activism on corporate green innovation. Thirdly, starting from the factor of management environmental attention, this paper pioneers the study on the path mechanism of shareholder environmental activism's influence on corporate green innovation, which is conducive to understanding the transmission path of shareholder governance's influence on corporate green innovation, and promoting managerial rational distribution of attention and resources, so as to promote corporate green innovation.#br#

With the new generation of technological revolution and the acceleration of industrial transformation, it is increasingly urgent to promote China's high-quality development through new quality productive forces. The innovation network is a more suitable platform for the repeated exchange of tacit and embedded knowledge than market transactions. It is effective in enhancing enterprise innovation capabilities, achieving breakthroughs in key technologies, and forming new quality productive forces. To promote the qualitative leap in the advanced productive forces of innovation network member enterprises and achieve high-quality development, this paper attempts to answer the following key questions: How does core enterprises' knowledge spillover drive network members' new quality productive forces? What roles do network homogenization and relationship capital play in this process?
On the basis of the knowledge-based view and resource-dependence theory, this paper analyzes the relationship between core enterprise's knowledge spillover and network member's new quality productive forces. The research adopts survey data from 392 enterprises and conducts an empirical analysis using SPSS and Amos. The results show that (1) there is a significant positive relationship between core enterprise's knowledge spillover and network member's new quality productive forces. The influence of core enterprises on network members mainly stems from knowledge spillover, and under its continuous influence, the new quality productive forces of network members can be improved. (2) Network homogenization negatively moderates the impact of core enterprise's knowledge spillover on network member's new quality productive forces. Network homogenization implies a lack of resource, skill, and capability complementarity among members, rendering enterprise resources less unique, valuable, and scarce. Consequently, core enterprise's knowledge spillover cannot provide deeper knowledge and technology interaction for network members, reducing the chance for network members to increase their knowledge diversity and ultimately affecting the development of network member's new quality productive forces. (3) Relational capital positively modulates the relationship between core enterprise's knowledge spillover and network member's new quality productive forces. Strong relationships among innovation network members benefit enterprises in obtaining more social capital, which promotes the exchange and sharing of knowledge and information, and fosters the growth of new talents and the accumulation of new labor materials.
Theoretically speaking, this paper firstly supplements the empirical study of new quality productive forces at the enterprise level. Then it constructs a measurement scale of network member's new quality productive forces, which provides ideas and methods for further empirical research related to new qualitative productive forces at the enterprise level. Secondly, from the perspective of the interaction of innovation network members, this paper explores the impact of core enterprise's knowledge spillover on network member's new quality productive forces, enrich the theoretical connotation of existing research and promote the development of knowledge spillover related theoretical research. Thirdly, by integrating the knowledge-based view and resource dependence theory into the research on the knowledge spillover effects of the core enterprise, the applicability of these theories is enhanced, offering a new perspective to understand the knowledge spillover effects of core enterprises. Lastly, it is a valuable addition to the research on the knowledge-based view and resource-dependence theory to incorporate network homogenization and relational capital into the research framework. This expands the scope of research on the knowledge spillover effects of core enterprises and responds to scholars' recognition of the core enterprise's knowledge spillover effects.
The results hold practical significance as follows: (1) The transformation and enhancement of productive forces quality in innovation networks can not be separated from core enterprise's knowledge spillover. If network members aim to develop new quality productive forces, they must realize the importance of core enterprise's knowledge spillover and expand the channels for enterprises to obtain new knowledge, technical information and other resources. (2)The findings affirm the importance of enterprise knowledge heterogeneity, and suggest that enterprises should select partners based on their own existing knowledge, in innovation networks, members should be clear about who to approach in order to gain more reconfigurable knowledge. (3) Strong relationship capital is the effective support to promote new quality productive forces, and the continuous accumulation of relationship capital can ensure that network members have an advantage in choosing partners for core enterprises. (4)In the process of high-quality development of innovation network, it is necessary to adopt tailored measures for different enterprises.

Since the signing of the Paris Agreement, global climate governance has entered a new stage, and some governments have been actively deepening international cooperation to promote global green and sustainable development. Green finance is a new financial model that combines environmental protection with economic profits, playing a significant role in environmental governance. In this context, green finance policies have greater impacts on the financial costs of high-pollution and high-energy-consumption enterprises with two mechanisms of action; on the one hand, green finance policies directly raise the financial threshold for high-energy-consumption and high-pollution enterprises, increasing their debt financing costs; on the other hand, these enterprises can establish good social images through green technology innovation and green information disclosure, which not only helps to gain the favor of investors but also obtain green financial policy support, and to some extent alleviates their costs of debt financing. The purpose of this study is to explore the mechanism and effectiveness of green finance policies, for it would be conducive to improving China's green finance policy system and guiding the green transformation and upgrading of high-energy-consumption and high-pollution enterprises, thus providing important theoretical and practical significance for China's green transformation.#br#The current research on green finance policies has some inadequacies. Firstly, the existing literature assumes that green finance policies increase the difficulty of financing for high-energy-consumption and high-pollution enterprises, thus increasing their total financial costs. In fact, this confuses the total quantity effect and cost effect. Secondly, the existing research ignores the strategic behavior of high-energy-consumption and high-pollution enterprises. Enterprises can take "signaling warfare" to deal with the impact of adverse policies on their financing costs, such as reducing their external financing costs by creating adverse selection through environmental disclosure. Furthermore, the role of green finance policies is a dynamic process, and the policies themselves are committed to stimulating green technology innovation and achieving green transformation in enterprises. After the transformation, the financing costs of enterprises have been significantly reduced, and thus relevant research is insufficient.#br#Following the theory of incomplete information dynamic game, this study reveals the relationship between strategic behavior and financing activities of high-energy-consumption and high-pollution enterprises against the backdrop of green finance policies. Green finance policies can trigger "signal warfare" and green innovation behavior of enterprises, forming multiple Nash equilibria, and having different impacts on the financing of high-energy-consumption and high-pollution enterprises. In order to verify the correctness of the theory, on the basis of the relevant data of 537 listed companies, this paper adopts the chain mediation effect model to examine the impact of green financial policies on the financial costs of high-energy-consumption and high-pollution enterprises. The study finds that green financial policies can not only directly alleviate the financing costs of high-energy-consumption and high-pollution enterprises, but also play the mediating role of environmental information disclosure and green technology innovation. Then, the three indirect paths of environmental information disclosure and green technology innovation as chain mediators reduce their financing costs.#br#This study provides a new perspective for the study of the mechanism of green finance policy, and suggestions for policy improvement are presented. First, the environmental protection department should establish environmental information review agencies which are expected to collect and evaluate the environmental information disclosed by high-energy-consumption and high-pollution enterprises, and then issue relevant evaluation reports. The review of environmental information by third-party institutions and the issuance of relevant reports are conducive to reducing information asymmetry and improving transaction efficiency in the capital market. Second, the government should establish an incentive mechanism for promoting green innovation through the joint participation of the government, enterprises, and the public by making favorable policies to attract and cultivate elite talent, improving the intellectual property protection system, and increasing public awareness and understanding of green innovation. Third, for the enterprises with green innovation capabilities but insufficient R&D investment, the government should establish special funds to support these enterprises and expand their financing channels.#br#

New-quality productive forces are generated by scientific and technological innovation and the realization of key disruptive technological breakthroughs, and it is a powerful engine for high-quality development. New quality productive forces, with strategic emerging industries and future industries as the leading industries, are mainly involved in fields with strong innovation and advanced technologies and are committed to empowering regional high-quality development through scientific and technological innovation. In order to maintain a leading position in the competitive global environment and promote China's high-quality economic growth, it is necessary to stimulate industrial innovation through major disruptive scientific and technological innovations, facilitate transform and upgrade the industrial structure to create a new competitive advantage, and endeavor to cultivate the new quality productive forces.
The high-quality development of cities, as important spatial carriers and geographic activity units for economic and social development, remains an important issue of our time. Can new productive forces, as a key initiative to reshape new dynamics, be an important way to help cities develop in a high-quality manner If so, what is the internal logic of new-quality productive forces influencing the high-quality development of cities？ An overview of the existing literature shows there is a relative lack of empirical research on the relationship between the two. In view of this, this paper tries to put the new quality productive forces and high-quality urban development in the same research framework, and takes entrepreneurial activity as the starting point to explore the mechanism of new quality productive forces on high-quality urban development, so as to further provide a theoretical and practical basis for China's high-quality development.
Employing the panel data of 244 prefecture-level cities in China from 2011 to 2021, this study explores the intrinsic mechanism by which new quality productive forces affect the high-quality development of cities, using new quality productive forces as the entry point. Building on this foundation, the study examines the transmission mechanism through which new quality productive forces influence high-quality urban development by enhancing entrepreneurial activity, with entrepreneurial activity serving as the mediating variable. Subsequently, it delves into the non-linear influence of new quality productive forces on high-quality urban development at varying stages of industrial structure upgrading, talent concentration, and scientific and technological innovation. Then, the study investigates the non-linear impact of new productive forces on high-quality urban development when industrial structure upgrading, talent concentration, science and technology innovation are at different stages, and finally, it analyzes the spatial spillover effect of new productive forces on high-quality urban development according to the spatial levels.
The study finds that (1) new productive forces have a direct role in promoting high-quality development, and from the perspective of the financial environment of entrepreneurship and the level of talent capital, cities with a higher level of financial development and talent capital have an obvious role in promoting high-quality development; at the same time, entrepreneurial activity is an important channel through which the new productive forces promote the high-quality urban development. (2) The impact of new quality productive forces on high-quality urban development is affected by the threshold effect of industrial structure upgrading, talent concentration, and scientific and technological innovation level, and the impact of new quality productive forces on high-quality urban development presents a non-linear effect of increasing marginal utility under the development level of higher threshold variables. (3) The impact of new quality productive forces on high-quality development has a significant positive spatial spillover effect, and the development of local new quality productive forces can drive the high-quality development of areas with close economic ties.
Possible marginal contributions of this article are that,firstly, from the perspective of empirical measurement, the study explores the mechanism of the impact of new quality productive forces on high-quality urban development, and focuses on the impact of new quality productive forces on the high-quality development of cities; moreover, by incorporating industrial structure upgrading, talent concentration and scientific and technological innovation level into the analysis framework, it explores the threshold effect of the new quality productive forces on the high-quality urban development.

In recent years, small and medium-sized enterprises (SMEs) have encountered frequent operational emergencies, such as urgent cash flow and blocked supply chains. How to promote enterprises to improve organizational resilience to cope with challenges has become an important topic in management practice. In the present digital era, digital knowledge and information resources have become key production factors. Relying on digital resources to improve and reshape systems and processes has become an important means for enterprises to build organizational resilience and enhance competitive advantages. However, most of the existing studies have paid too much attention to the endpoint effect of resources and neglected to explore resource management actions from the perspective of process, that is, the mechanism of resource orchestration on the formation of organizational resilience. In fact, the effective management of digital resources plays a more important role in fostering organizational resilience. Thus, it is an urgent issue to clarify the specific process of how resource orchestration affects the formation of organizational resilience.#br#In view of the above research status and practical background, this paper constructs a theoretical framework among resource orchestration, digitalization ability, transformational leadership and organizational resilience. Then it takes the resource orchestration theory as the research perspective to discuss the relationship between resource orchestration and organizational resilience of SMEs, and explores the mechanism mediating the role of digitalization ability and the moderating role of transformational leadership. By collecting the data from 334 SMEs samples, the hypothesis is empirically tested by structural equation modeling (SEM), bootstrapping, and the Johnson-Neyman (J-N) method.#br#The results show that (1) resource construction and resource coordination in crisis situations have a positive impact on organizational resilience in SMEs; (2) digital operational capabilities and digital collaboration capabilities mediate the relationship between resource orchestration and organizational resilience, while the mediating role of digital perception capabilities is not confirmed; (3) transformational leadership positively moderates the relationship among digital operational capabilities, digital collaboration capabilities and organizational resilience.#br#Theoretical contributions are as follows. First, following the resource orchestration theory, this study provides a new perspective on how digitalization affects the formation of organizational resilience and expands the theoretical research boundaries of existing research on resource orchestration and organizational resilience. Second, the research framework of“resource orchestration-digitalization ability-organizational resilience” is built from the perspective of digitalization, which further clarifies the intrinsic relationship between resource orchestration and organizational resilience. The study remedies the limitation that the relationship between resource orchestration and organizational resilience has not been effectively explored. Third, this study considers transformational leadership as an external intervention that influences resource orchestration to have an effect on organizational resilience through digital capabilities, which extends the research content of transformational leadership in the digital era, complements and improves the boundary conditions for the formation of organizational resilience.#br#The managerial insights into how SMEs can develop organizational resilience in the digital economy are presented. First, SMEs should focus on taking resource orchestration actions to achieve effective access to and management of required digital resources. Due to limited resources such as capital, technology and human resources, SMEs should fully consider the professional advantages of third-party service organizations in the process of digitization. Second, it should enhance the digital perception, operational and collaboration capabilities that drive the formation of organizational resilience. Resource orchestration action for enterprises to adapt to the required digital resources is a prerequisite for leveraging the transformation and development of enterprises, while digital capabilities determine the extent to which enterprises can benefit from their digital technologies and infrastructure, so as to better empower the building of organizational resilience. Finally, transformational leadership should play an important role in facilitating value co-creation among organizational members. In the digital economy, managers need to develop a strategic plan for transformation and continuously promote its implementation, playing the role of“helmsman” to help companies stand firm in the rapidly changing digital economy.#br#

An innovation ecosystem (IE) is the evolving set of actors, activities, and artifacts, along with the institutions as well as complementary and dependency relations. Artificial intelligence (AI) is increasingly adopted by organizations for innovation,giving rise to platform-based innovation ecosystems for collaborative innovation and value co-creation. However, most research has focused on the co-evolution of platform architecture and platform governance and the role of boundary resources provided by the platform owner, while heterogeneous artifacts provided by complementors are rarely explored. Specifically, the industrial and managerial literature still lacks information about how heterogeneous artifacts can foster collaborative innovation in the AI innovation ecosystem.
Thus, this paper presents a framework for the collaborative innovation process of technological complementarity by using a comprehensive research model to examine the impact of collaboration in the AI innovation ecosystem. The conceptual framework termed “elements-process-performance” from the perspective of complex system, captures the intrinsic mechanisms of collaborative innovation between platform owners and complementors. The elements of innovation refer to the technological components within the ecosystem, comprising both core components and complementary technologies. The process of innovation encompasses the way complementors integrate these technologies to foster innovation. The innovation performance assesses how the empowerment of core technical components affects collaborative innovation performance.
After reviewing the relevance of studying the innovation system, the study proposes a bipartite network (BN) model to describe the relationships between complementors and technology components based on real-world data from “Baidu Brain” which is an AI open platform in China; then through analyzing the properties of the projected network of the bipartite network, it quantifies the structural features of component interdependency at the node-level, group-level, and whole network-level; the process of innovation is modeled as a bounded, iterative, trial-and-error search over a complex landscape using an NK model, and several simulation experiments are conducted to observe the complex relationship patterns between innovation performance and components' interdependency; finally the study manages to predict the ecosystem innovation performance based on empirically observed patterns from the Baidu Brain ecosystem.
The analysis reveals that complementary component strategies can affect collaborative innovation in ecosystems in four ways: (1) the level of technological interdependence formed by embedding complementary components into the ecosystem through component strategies has a negative impact on the potential for collaborative innovation; (2) the higher the proportion of core components in the system (C-Ratio), the lower the performance of collaborative innovation; (3) it hampers collaborative performance by raising the ratio of core components above a threshold, indicating over-reliance on the platform's core elements without enough complementary components impedes synergy;(4) an inverted U-shaped relationship exists between component interdependency E-I index and innovation performance. These important findings further emphasize that collaboration among different actors in the ecosystem plays a critical role in achieving higher innovation outcomes.
The findings provide insights for management innovation in platform enterprises. Platform enterprises as ecosystem builders and leaders, should effectively manage complementary innovation. As a coordinator, it is necessary to pay attention to the network pattern among collaborative innovation entities and effectively manage and coordinate the actions of internal complementarity through institutional design. In addition, platform enterprises also need to pay attention to the management and coordination of modular components. When the E-I Index of a partition of the complementary dependency network deviates from the optimal level, adjustments can be made by enhancing the standardization and flexibility of core components, encouraging participation from complementary enterprises, increasing the diversity of complementary components, reducing the proportion of core components, and modifying the complementarity of technical components.
This study focuses on how platform enterprises manage and coordinate with complementor enterprises. Given the complexity of technology dependence, integrated application of innovation ecosystems and collaboration innovative theory, it utilizes data-driven and simulation modeling methods to explore the complex relationship logic between technological dependence and collaborative innovation. This paper advances the understanding of the intersection of innovation and AI and provides suggestions for complementary innovation and the ecosystem development.

The high-quality development of China's economy necessitates the unlocking of the potential of data elements, the advancement of productivity reforms and innovation, and the creation of new forms of high quality productive forces. However, current research fails to elucidate the mechanisms by which data elements influence the development of new high-quality productive forces within enterprises. It also falls short in addressing how traditional production factors interact with these data elements. As a result, enterprises struggle to understand how to leverage both data elements and traditional production factors to foster the development of their new high-quality productive forces in their day-to-day operations Therefore, this paper comprehensively constructs a theoretical analysis model of the data elements on the development of enterprises' new quality productive forces from three aspects: direct effect, indirect effect and multiplier effect.
Using the panel data of Chinese listed companies from 2011 to 2022, this study examines the impact of the data elements on the development of new quality productive forces from the perspective of effect decomposition. The results show that (1) data elements can effectively empower the development of new quality productive forces of enterprises, and the conclusion is robust;(2) enterprises' new quality innovation and labor skill structure have a mediating effect in the development of enterprises' new quality productive forces empowered by data elements; (3) data elements has a multiplier effect in the process of new quality innovation and labor skill structure promoting the development of enterprise new quality productive forces; (4) the enabling effect of data elements is only obvious in highly competitive, high-tech and non-heavy pollution industries, and is more effective in regions with complete digital infrastructure, high level of data talent agglomeration and open data.
According to the derived conclusions, data elements exert multiple influences on the development of new high-quality productive forces within enterprises. In terms of direct effects, firstly, data elements can improve the decision-making efficiency and quality of enterprises by driving their management decisions. Secondly, through data sharing and integration, on the one hand, enterprises can improve the communication efficiency among various departments;on the other hand, enterprises can improve the collaborative production efficiency within their respective supply chains. Thirdly, the application of enterprise data elements can promote the transparency of enterprise information to alleviate the information asymmetry between enterprises and investors, thus improving the financing efficiency of enterprises. Finally, the intricacy of a company's production processes can be significantly streamlined through the application of data elements. In terms of indirect effects, first of all, on the one hand, enterprises can realize the efficient connection between innovation supply and demand through the application of data elements, reducing the cost and risk of R&D innovation, and thus improving the efficiency of new quality innovation of enterprises. On the other hand, the application of data elements can optimize the technological process and product design of enterprises to ensure the improvement of the quality of new quality innovation. Secondly, through the application of data elements, enterprises will create jobs of high-skilled labor and have a substitution effect on low-skilled labor, which can improve the skill structure of enterprises' labor and thus promote the formation and development of enterprises' new quality productive forces. In terms of the multiplier effect of data factors, the core logic is that it can help enterprises re-understand the traditional factors of production, expand the allocation space of traditional factors, improve the efficiency of traditional resource allocation, and thus magnify the role of other factors in the development of new quality productive forces. This study specifically focuses on the multiplier effects of data elements on two key traditional factors: technology and labor. It finds that the multiplier effect of data elements on technology is reflected in the expansion of innovation boundary and the acceleration of technology iteration, and the multiplier effect on labor is reflected in the further improvement of the comprehensive quality of labor. To summarize, by constructing the analysis model of “direct effect—indirect effect—multiplier effect”, this paper provides empirical evidence and policy implications for clarifying the enabling effect of data elements on enterprises' new quality productive forces and releasing the potential of data elements' new quality productive forces.

Entrepreneurial activities are key factors driving regional economic growth, creating job opportunities, and promoting economic transformation. However, with the intensification of global economic pressures and the entry of the Chinese economy into a "new normal", traditional drivers of economic growth are gradually weakening, posing significant challenges to the entrepreneurial environment. Potential entrepreneurs not only need to contend with increasingly fierce market competition but may also face lower success rates, leading to a decline in entrepreneurial activities across various regions.
As the core driving force of the new wave of technological revolution and industrial transformation, artificial intelligence (AI) is rapidly integrating into various fields in China, spawning new industries, new technologies, new business forms, and new business models, thereby demonstrating its tremendous potential to drive a new wave of innovation and entrepreneurship. This rapid integration has transformed traditional industries, leading to breakthroughs in automation, data analysis, and customer engagement, which in turn accelerates economic growth. However, existing research indicates that the impact of AI on regional entrepreneurial activities has dual characteristics, with both positive creation effects, such as the emergence of new markets and job opportunities, and negative substitution effects, including the displacement of certain jobs and sectors. The complex interplay of these positive and negative effects makes the direction and intensity of AI's impact on regional entrepreneurial activities still inconclusive, leaving uncertainty around the overall outcomes for different regions and industries.
Looking back at past technological revolutions, although technological advancements may temporarily replace certain jobs in the short term, they ultimately stabilize total employment by generating emerging industries and creating new job positions. Therefore, with the rapid development of AI technology and its profound impact on the economic landscape of China, accurately assessing the role of AI in regional entrepreneurial activities is of great significance for improving entrepreneurial theory, guiding entrepreneurial practice, and promoting high-quality regional economic development. To this end, this paper takes the construction of national new-generation AI innovation development pilot zones as a typical case, exploring the intrinsic connections and mechanisms between AI development and regional entrepreneurial activities from the perspective of entrepreneurial choices, utilizing county-level panel data from 2012 to 2022 and a double machine learning model.
The research findings indicate that the construction of national new-generation AI innovation development pilot zones has a significant effect on enhancing regional entrepreneurial activities. Mechanism analysis reveals that AI development indirectly promotes entrepreneurial activities by enhancing entrepreneurial capabilities, alleviating financing constraints, and increasing capital returns, with a synergistic effect between entrepreneurial capabilities and capital returns. Further analysis finds that AI can stimulate entrepreneurial activities in technology-intensive industries and productive service industries, effectively driving regional economic structural transformation and high-quality development. Heterogeneity analysis shows that the positive effect of AI on entrepreneurial activities only becomes apparent when the regional population reaches a certain threshold.
This study contributes to the literature in three aspects: Firstly, by revealing the experiments of AI policies and national new-generation AI innovation development pilot zones, it proposes an innovative research perspective to explain the impact of AI on regional entrepreneurial activities. This not only integrates theoretical explanations from the perspective of entrepreneurial choices but also provides empirical support for institutional theories in the AI era. Secondly, the paper introduces a new chain construction path, namely "entrepreneurial capability—financing constraints—capital returns", providing strong support for further clarifying the complex mechanisms between AI and regional entrepreneurial activities. On the basis of the synergistic mechanism between "entrepreneurial capability—capital returns", it proposes enhancing entrepreneurs' AI literacy and resource integration capabilities, forming a positive feedback loop of "capability enhancement-capital appreciation-reinvestment of capabilities", maximizing the synergistic effect of the mechanism, and further promoting the virtuous interaction between technological innovation and capital flow. Thirdly, methodologically, the paper adopts double machine learning methods to solve the problems of model mismatch and curse of dimensionality in complex analyses, thereby effectively improving the accuracy of the conclusions.

In order to narrow the gap between domestic and foreign key technologies, it is critical for China to promote the innovation of key technologies so that it can deeply participate in global economic development. At the same time, in order to mitigate the dilemma of key technologies being controlled by other countries, many scholars at home and abroad have focused on the breakthrough paths of key technologies.
Some related research focuses on exploring the real essence of key technologies or exploring the key technologies′ breakthrough path from internal reasons or the perspective of grand strategy; a systematic research framework has not yet been constructed. In view of this, this article interprets the connotation and characteristics of key technologies from the technological essence and conceptual intersection dimensions and analyzes key technologies′ national dynamic characteristics by overviewing different countries′ invention patents and fundamental research. On this basis, in order to analyze key technologies′ situation in China, this paper further investigates the industries with key technologies and the entrepreneurial differences. Other studies mainly use interdisciplinary theory to explore breakthrough paths with innovative applications of TRIZ theory to solve issues about key technologies. However, existing research fails to systematically consider the practical application of research organizations, TRIZ tools and methods in the key technology system. This paper argues that expanding TRIZ theory to the research of key technological innovation can provide a new systematic framework for the design of key technologies′ breakthrough paths.
On the basis of the above research analysis, this paper finds that key technologies exhibit the nonlinear exponential iteration characteristic and can maintain national security in military, economic, social and other aspects. Meanwhile, the success of its innovation has basic research dependency, breakthrough mechanism systematization, high risks and technological monopoly. From a practical perspective, compared with other major countries′ key technologies, China is leading the world in the quantity but not the quality of its innovation. In terms of China's internal reality, compared with firms from non-manufacturing and low contract-intensive industries, manufacturing and high contract-intensive industries′ have a higher quantity but lower quality in key technological innovations. In addition, compared with state-owned enterprises, mature and declining enterprises, non-state-owned enterprises and growing enterprises have more quantity advantages. Compared with small and medium-sized enterprises, large enterprises have a higher quantity and quality of key technologies.
Hence, the study finds that the TRIZ theory introduces new logical thinking and provides scientific and implementable breakthrough solutions for the key technology system. Through analyzing TRIZ architecture and core principles, it confirms that TRIZ invention theory enlightens the importance of government deployment, enterprise application and system support in the key technologies′ breakthrough path system; while classified breakthroughs, cross-domain knowledge integration, and sustainable basic research are essential elements. Therefore, combined with key points such as generic breakthroughs, basic research, and cross integration,this study makes full use of TRIZ theory, tools, and methods to solve technological conflicts as the principle from the perspectives of enterprises, governments and organizational systems, providing a comprehensive framework for the breakthrough path of key technologies in China. On the overall path, it is proposed that multiple entities should jointly deploy interdisciplinary integration systems. Furthermore, the government should decompose technology conflicts based on the key technology systems′ hierarchical decomposition and then create a hierarchical iterative research pattern. At the same time, by combining methods such as technology innovation levels and invention problems, enterprises should carry out scientific research activities reasonably. Finally, enterprises should provide feedback on the effectiveness of technology market applications, highlight their innovative applications, and optimize the breakthrough path of key technologies.
This paper emphasizes the long-term deployment, maintaining national security, non-linear changes, and other core characteristics of key technologies. Besides, it is particularly important to design differentiated breakthrough plans for key technologies across China because of the reality of imbalanced development. Overall, introducing TRIZ to assist enterprise innovation is a useful solution to effectively make breakthroughs of bottleneck issues in key technologies.

Digital technology can provide technical support for cutting-edge products or services, reshaping core information technology. By reducing manual labor in production processes and optimizing the allocation of traditional production factors, it empowers various production and operational activities, shaping efficient value creation models and accelerating comprehensive enterprise innovation, thereby improving performance. However, the inherent characteristics of digital technology edit-ability, scalability, openness, and interconnection—make its innovation process complex, rendering traditional innovation paradigms unsuitable.
Scenario-driven innovation is an emerging innovation paradigm that integrates multiple innovation elements such as strategy, organization, and market, bringing together various innovation entities. It features strategic, comprehensive, and open characteristics, providing an innovative ecological carrier for breakthroughs in key technologies and the transformation of achievements. In the context of the digital economy, scenario-driven innovation has become the new dominant innovation paradigm, making it significant to explore the multi-factor-driven digital technology innovation of enterprises.
In terms of digital technology innovation, some scholars have analyzed the net benefits of single driving factors, failing to reflect the characteristics of multi-factor interactive driving, thus limiting the formation of a comprehensive digital technology innovation paradigm for enterprises. Additionally, due to limited research on scenario concept definition, governance models, and mechanisms of action, scenario-driven digital technology innovation remains in a black box state. Enterprises lack clear innovation path references, leading to numerous challenges and bottlenecks in implementing digital technology innovation. Furthermore, at different stages of digital technology development, it is still necessary to explore how to integrate various innovation resources, form organizational and management transformations, and achieve technological innovation breakthroughs.
As a high-tech digital innovation company that integrates research and development, production, sales, and service, Huawei has possessed a variety of digital technologies and a rich array of digital products, and it is remarkable in the field of digital technology innovation. Thus, Huawei is selected for a longitudinal single-case analysis focused on scenarios. The study combines the data coding approach to conduct an exploratory analysis of Huawei's data, yielding a scenario analysis mainline of "product development—market expansion—technological breakthrough—industrial ecosystem. "(1)The development of digital technology innovation at various stages is achieved through the alternation of different scenario dimensions within a triple helix mechanism. Scenarios are systems formed by the interplay of three dimensions: stakeholders, technological level, and application environment. (2)Through stage-specific scenario transitions such as product development, market expansion , technological breakthrough and industrial ecosystem, the company completed the evolution of digital technology innovation from low-end imitation to coordinated value realization. (3)Due to differences in scenario elements, the paths of digital technology innovation are diverse, including the whole industry path, breakthrough innovation path, and strategic emerging industry path.
The research contributions encompass three aspects. Firstly, it extensively explores the developmental trajectory of digital technology innovation, progressing from initial technological imitation to framework formation, and ultimately achieving ecosystem linkage, offering a new perspective on understanding the patterns of digital technology innovation. Secondly, by redefining the concept of scenarios to include considerations of stakeholders, technological level, and application environment, the study enriches the content of scenario theory, making it more comprehensive and profound. Lastly, it proposes a scenario-driven triple helix innovation mechanism, where the synergy among environment, demand subjects, technology, continuously drives the advancement of digital technology innovation, providing robust theoretical support and practical guidance for future related research.
The study provides insights for enterprises:(1)When formulating digital technology innovation strategies, enterprises should comprehensively consider the needs of stakeholders such as customers and suppliers, promote collaboration among multiple parties, and ensure that the strategy is comprehensive and sustainable. (2)Establishing a flexible digital technology innovation support system is essential, including efficient financial management, platform-based organization, and process control, to address challenges in various scenarios and enhance innovation efficiency and responsiveness. (3)By setting industry standards, establishing industry alliances, and integrating resources across sectors, enterprises can build complex interactive industrial ecosystems. This facilitates continuous innovation and flexible development within the enterprises.

The development of strategic emerging industries is a key approach to accelerating the formation of new-quality productive forces, which are essential in driving technological innovation, economic transformation, and sustainable growth. However, the current research lacks a comprehensive examination of the assessment frameworks for the developmental progress of strategic emerging industries. Furthermore, there is a scarcity of in-depth, scientifically grounded analyses that leverage the new quality productivity theory. Additionally, research utilizing provincial data as a starting point is relatively sparse. This study aims to measure the development levels of strategic emerging industries in China from the perspective of new quality productive forces and to underscore its critical role in the nation's scientific and technological innovation and analyze the regional disparities in their development.

A comprehensive evaluation index system is constructed, covering three dimensions: technological innovation, industrial market scale, and policy environment support. By utilizing the entropy-weight TOPSIS method and spatial autocorrelation models, the development levels and regional disparities of strategic emerging industries across 30 provinces in China are quantitatively assessed.
The results reveal a clear regional concentration pattern, with eastern coastal areas and the Yangtze River regions exhibiting significantly higher development levels than northwestern and border provinces. This indicates substantial disparities in the development of strategic emerging industries across China. Additionally, the Global Moran's Index confirms positive spatial autocorrelation, meaning that regions with higher development levels are often surrounded by similarly advanced regions. This highlights the persistent issue of regional imbalance, with advanced regions continuing to outpace lagging areas in technological and industrial growth.
Several key conclusions emerge from the analysis. First, regions with higher levels of technological innovation and strong policy support—such as Guangdong, Beijing, and Jiangsu—have made significant progress in fostering strategic emerging industries. These regions benefit from well-established innovation ecosystems, substantial government funding, and robust market demand. On the other hand, western and border provinces, such as Xinjiang and Qinghai, face significant challenges due to weaker innovation infrastructures, lower levels of industrial development, and less favorable policy environments. These disparities underscore the need for targeted policy interventions to bridge the development gap.
To address these challenges, this paper proposes several policy recommendations. First, differentiated regional policies should be developed to support the unique needs of underdeveloped areas, especially in central and western China. These policies could include tax incentives, direct subsidies for innovation, and special funding programs to enhance local technological capabilities and industrial growth. Second, cross-regional collaboration mechanisms should be established to promote resource sharing and technological transfer between more developed and less developed regions. This would facilitate more balanced development across regions and enable the diffusion of innovation to less advantaged areas. Finally, the creation of strategic industry clusters in underdeveloped regions, along with initiatives to attract and retain high-tech talent, would accelerate their integration into the national industrial landscape and foster new quality productive forces.
This study makes several contributions to the literature. First, it extends the theoretical framework of new quality productive forces by applying it to the measurement of strategic emerging industries' development levels. This perspective integrates technological innovation, industrial scalability, and policy support as key factors driving the growth of these industries. Second, it provides a robust empirical analysis of regional disparities in the development of strategic emerging industries across China, offering insights into the spatial patterns of industrial growth and regional innovation ecosystems. Third, the study's findings offer practical implications for policymakers aiming to foster more balanced regional development and to harness the potential of strategic emerging industries in driving national economic transformation.
By fostering innovation, bolstering market capabilities, and intensifying policy backing in regions that are lagging behind, China can achieve more balanced and sustainable growth in these critical industries.

In the era of digital technology, data, as a key and unique production factor, provides a possible opportunity for enterprise innovation to break through the constraints of factor endowment. However, many enterprises have difficulties reaching the digital innovation integration stage and have failed to improve their innovation performance through data resources. Therefore, in order to unravel the contradiction between the potential value of digitalization and its practice and grasp the unique points of digital reforms compared with general reforms, it is of great practical significance to systematically study the impact of digitalization on the innovation performance of enterprises from the microperspective. The conclusions of the existing studies linking digitalization and innovation performance are mixed, and the root of the controversy lies in the inconsistency of the measurement methods of digitalization and innovation performance, the contradictory nature of the action mechanism, and the differences in the contexts in which they work. Also,the controversy raises the question of whether there is a non-linear relationship between digitalization and innovation performance.
Digital proximity is a new integrative concept for capturing the digital condition of action subjects from a result-oriented network perspective.This paper aims to fill in the above-mentioned research gap by verifying that the relationship between digital proximity and innovation performance is U-shaped.Drawing on Hanns et al.’s research template,it builds a theoretical framework that deconstructs the U-shape into two forces,namely the blocking force and the driving force. It argues that the blocking force and driving force are respectively manifested in the two states of "dormant period" and "enabling period" of the digital proximity on the innovation performance of enterprises, and the combination of the two potential states makes the interaction between the two present a kind of strategic paradox, which is reflected in the significant U-shaped relationship.That is, at the early stage of product and service digitalization, the degree of digital proximity is low, and the rigidity of resources and practices in the process of digitalization is strong, at this time, digital proximity is negatively correlated with innovation performance; on the contrary, when the enterprise has a high digital proximity, the innovation spillover and promotion effects are gradually released, and the enhancement of the enterprise's digital proximity reaches the threshold of positive stimulation of enterprise innovation, presenting a negative correlation between the early stage of digital proximity and innovation performance and a negative correlation between the later stage and innovation performance. The trend toward a positive correlation between digital proximity and innovation performance in the later stage. In addition, executives' traits (rational factors such as political connection background, R&D background, and irrational factors such as overconfidence) affecting the strategic choices and target performance of enterprises have become one of the important clues in the study of enterprise performance, and may constitute an important boundary condition for the influence of digital proximity on the innovation performance of enterprises, so it is necessary to include executives' traits in the theoretical framework.
On the basis of data from Chinese listed companies, the distance between enterprises and digital industries is used to calculate enterprises' digital proximity, the stochastic frontier model (SFE) is used to measure enterprises' innovation efficiency, the binary variables of executives' political connection background and executives' R&D background are collected and computed, and the composite scores of the executives' personal characteristic indexes are used to assess the executives' overconfidence. Following the organizational inertia theory and the upper echelons theory, the study uses 2 580 observations of 1 044 listed companies from 2010 to 2022 to empirically analyze the influence of enterprises’ digital proximity on innovation performance, and examine the moderating effects of three types of executive traits, namely, executives' political connection background, R&D background, and overconfidence. It is found that, overall, there is a U-shaped relationship between digital proximity and innovation performance, and several robustness tests and endogeneity tests confirm the conclusion. Further, the rational factors in executives' traits (politic connection background, R&D background) positively moderate the U-shaped relationship between digital proximity and innovation performance; while the irrational factor in executives' traits (overconfidence) negatively moderates the U-shaped relationship between digital proximity and innovation performance.

With the integration of digital economy with technological innovation, organizational innovation and industrial innovation, more and more enterprises have been introducing artificial intelligence technology to replace some low-end repetitive work. The emerging workforce, nurtured during the era of AI's swift advancement, is acutely aware of its influence on their professional competitiveness. This rapid technological evolution has instilled a sense of unease among these young professionals regarding potential job displacement and the necessity to master novel technologies. This phenomenon is commonly referred to as artificial intelligence anxiety.
From the perspective of the cognitive evaluation theory of stress, the study analyzes the impact of AI anxiety on the innovative behavior of the new generation of employees. The paper proposes the following hypothesis that, first, AI anxiety can promote innovative behavior of the new generation of employees, and fully tapping the characteristics and potential of the new generation of employees can better stimulate their innovative vitality under the anxiety of AI. Second, job crafting plays a mediating role between AI anxiety and the innovation behavior of the new generation of employees. AI anxiety can stimulate the new generation of employees to actively think about the changes in work content and work mode. Third, organizational attachment not only moderates the relationship between AI anxiety and job crafting, but also moderates the mediating effect of job crafting between AI anxiety and the innovation behavior of the new generation of employees. It is difficult for employees with high organizational attachment to have innovative behaviors in the context of insecurity. On the contrary, employees with low organizational attachment have an attachment style corresponding to secure organizational attachment. Therefore, employees with low organizational attachment are better able to carry out innovative practices and carry out innovative behaviors at work, and AI anxiety has a stronger effect on stimulating their innovative behaviors through job crafting.
The study conducted a survey in two phases with data from November 2023 to February 2024 through a multi-time point survey methodology. The target population consists of employees across various sectors, including the Internet and Technology (IT) industry, manufacturing, catering services, and education. There are 343 valid responses out of 435 questionnaires, which corresponds to a robust response rate of 78. 85%. The study employs SPSS 23. 0 and Mplus 8. 0 software to assess the reliability and validity of the research model. To evaluate the discriminant validity among the four key variables of artificial intelligence anxiety, organizational attachment, work remodeling, and employee innovative behavior, it conducts the confirmatory factor analysis (CFA) using Mplus 8. 0. Additionally, to ensure that common method bias was not a significant concern in this research, Harman's single-factor test was applied to an exploratory factor analysis of the 40 items pertaining to these four variables. It delves into the mediating effect of job crafting, and the moderating effect of organizational attachment; and then it explores the boundary of the relationship among AI anxiety, job crafting and the innovative behavior of the new generation of employees under different levels of organizational attachment.
The results show that artificial intelligence anxiety positively affects the innovation behavior of the new generation of employees through job crafting, and the degree of organizational attachment of employees plays a moderating role in this process. When employees' organizational attachment is low, the positive mediating effect of AI anxiety on the innovation behavior of new generation employees through job crafting is significant. When employees have a high degree of organizational attachment, the mediating effect above is not significant.
Therefore,it is essential for managers to acknowledge the influence of AI anxiety on the new generation of employees, and harness this anxiety constructively to steer, inspire, and energize employees to proactively redefine their roles and to embrace innovation with confidence. While employees should maintain a secure level of organizational attachment, which is characterized by a healthy balance between commitment and autonomy. To facilitate this, managers are tasked with cultivating an organizational environment that serves as both a "safe haven" and a "security island", providing the new generation of employees with a robust sense of security.

In the present fast-paced business world with high uncertainties, open innovation has become an indispensable strategy for firms seeking more heterogeneous information and staying competitive and thriving. However, there is still a critical need for a robust theoretical framework that can accurately predict and explain the realization of open innovation performance, and enlighten firms on how to cooperate and deal with internal and external knowledge partnerships in an open situation. The theory of HeXie (harmonious) management emerges as a promising avenue to address this need, especially the He principle and the two fields offer a conceptual lens that aligns with the complex demands of open innovation systems and provides insights into how firms can unlock their intrinsic value through open innovation initiatives. The purpose of this study is to delve into the mechanisms that underlie the realization of open innovation performance in high-tech manufacturing firms, utilizing the He principle as a guiding framework.
According to the He principle, the research constructs a comprehensive framework to explore the multifaceted pathways to open innovation performance in firms, and figure out how innovation openness exerts a positive influence on open innovation performance under the dual moderation of inclusive organizational culture and intellectual property protection. Empirical tests are made with the panel data from 662 high-tech manufacturing A-share listed firms spanning the period from 2012 to 2021 in China to validate the theoretical framework. Then, the model of fixed panel effects is built for data analysis: the study first examines the direct effect of innovation openness on financial and market performance, and then respectively analyzes the moderating effects of inclusive organizational culture and intellectual property protection policies; finally, it makes robustness analysis and heterogeneity analysis.
　The findings support the fact that the depth and breadth of innovation openness have a significant positive impact on firms' financial performance. However, it's noteworthy that the breadth of innovation openness does not exert a significant influence on firms' market performance, while the depth of innovation openness has a significant negative effect on market performance. This distinction between financial and market performance underscores the nuanced nature of open innovation outcomes. The study also reveals that the presence of an inclusive organizational culture strengthens the positive relationship between the depth of innovation openness and firms' financial performance. This finding underscores the importance of nurturing a work environment where diverse perspectives are valued and integrated into the innovation process. Lastly, it uncovers that the impact of the breadth of innovation openness on firms' financial performance is significantly enhanced in regions with well-developed intellectual property protection policies. This suggests that the interplay between openness and intellectual property protection can be leveraged to optimize financial performance outcomes. What's more, compared with the breadth of innovation openness, inclusive culture has a more significant moderating effect on the depth of innovation openness on financial performance; compared with the depth of innovation openness, the moderating effect of intellectual property policy on the breadth of innovation openness is more significant on financial performance. Intriguingly, the study further explores heterogeneity in the relationship between innovation openness and firms performance and finds that non-state-owned firms and those led by managers with overseas backgrounds experience a more pronounced impact of innovation openness on their performance. This nuanced insight emphasizes the importance of considering organizational characteristics and leadership profiles in the context of open innovation.
In conclusion, the study significantly contributes to the understanding of the pathways through which high-tech manufacturing firms realize open innovation performance. The theoretical framework of this paper is helpful to guide firms to achieve the dual pursuit of short-term and long-term goals and the balance of uniqueness and legitimacy in the context of open innovation. The conclusions provide valuable guidance for firms aiming to maximize the benefits of open innovation and adapt to the challenges in the dynamic business environment. Furthermore, it informs policymakers and practitioners about the significance of fostering inclusive organizational cultures and tailoring intellectual property protection policies to amplify the positive impacts of innovation openness.

With the continuous advancement of globalization and the deepening of technological revolution, the economic development model is undergoing profound changes. On the path of progress,traditional industries are witnessing a gradual decline in their erstwhile vigor. In sharp contrast, innovations in technology, novel business paradigms, and pioneering models are emerging with the vigor of bamboo shoots after a spring rain, growing at a truly remarkable pace. This new trend undoubtedly poses more stringent requirements for the adjustment and optimization of economic structure and the transformation of development mode. In this contemporary epoch, new-quality productivity acts as a catalyst for diverse regions to actively forge innovative trajectories. It encourages the full exploitation of burgeoning technologies and models, bolsters industrial competitiveness, and thereby catalyzes China's economy to progress steadily towards a new epoch of high-quality development. This, in turn, perpetuates a steady influx of impetus into the nation's sustainable development endeavors.
Under the new normal of the current global economy, big data and information technology are developing rapidly and are gradually changing the forms of traditional industries and economic development models. The national big data comprehensive pilot zone (referred to as the "big data pilot zone") plays an important role. It is not only the forefront of technological innovation but also an important support for promoting new industrialization, informatization, urbanization, and agricultural modernization. Current literature predominantly focuses on the impact of big data pilot zones on regional economic growth, green development, enterprise total factor productivity, technological innovation, and the digital transformation of enterprises, yielding largely positive outcomes. However, the influence of these zones on regional new-quality productivity has been less explored. In reality, big data pilot zones invigorate regional economies and revitalize traditional industries by seamlessly integrating extensive data resources and fostering innovative applications. Concurrently, they nurture and enhance the development of new quality productive forces, which is not only catalysts for economic growth but also a crucial lever for economic transformation and upgrading, offering robust support for sustainable economic development.
New quality productive forces embody the internal momentum for growth and is instrumental in driving economic transformation and upgrading. Using panel data from 30 Chinese provinces, autonomous regions, and municipalities from 2012 to 2022, this study constructs an evaluation index system of regional new quality productive forces across three dimensions: laborers, means of labor, and objects of labor. It then empirically examines the impact of national big data comprehensive pilot zones on regional new-quality productivity.The results show that the big data pilot zone can significantly improve the level of regional new-quality productivity. From the differences in regional geographical location, industrial structure, scientific and technological level, and financial environment, the improvement effect of regional new-quality productivity brought by the big data pilot zone is more obvious in the central and eastern regions, regions with good industrial structures, high-tech regions, and regions with well-developed financial environments.
The significance of data elements is increasingly being recognized with the vigorous development of the Internet and big data technology. The findings offer provide a solid empirical basis for understanding the effectiveness of China's frontier digital infrastructure construction policies. The study concludes that the establishment of big data pilot zones actively stimulates economic growth and illuminates a clear path for enhancing regional new quality productive forces. In future economic development, it is imperative for governmental bodies to prioritize the optimization of big data pilot zones' potential. This should be achieved by fostering the transformation of traditional regional economic drivers and by nurturing new quality productive forces through the strategic integration of big data resources and the advancement of innovative applications. By effectively bolstering regional new quality productive forces, China can steer its economy towards a trajectory of higher-quality development, thereby establishing a robust foundation for the nation's enduring prosperity and strength.

Over the past forty years of reform and opening up, mechanization and factory-based production have intensified the damage to the natural environment and the excessive consumption of resources. The extensive growth model that comes at the expense of resources and the environment can no longer meet the requirements of sustainable economic development, and there is an urgent need to transform traditional economic growth methods. Innovating in an ecologically symbiotic manner is the driving force for promoting green, low-carbon innovation and sustainable innovation, and it is also a crucial measure for achieving high-quality development in a low-carbon economy. Existing research has mostly used traditional regression methods, focusing on the net effects of individual dimensions of innovation ecosystems and their constituent conditions on low-carbon transformation, with limited exploration of the phenomenon of synergistic integration among innovation ecosystems. The coupling relationships among the various dimensions of innovative ecological symbiosis and the ways in which they drive low-carbon transformation are unclear, and the interactions between multiple innovation dimensions are overlooked, making it difficult to fully explore the nature of complex systems.
In order to make up for the deficiencies of the existing research, specific research questions arise: Is the symbiosis of single dimension of innovation ecosystems and their constituent conditions a necessary condition for low-carbon transformation? What kind of configuration of innovative ecological symbiosis is conducive to promoting low-carbon transformation? What are the complex impact mechanisms among these configurations? This study uses the fuzzy set qualitative comparative analysis method, and employs the total factor productivity index to measure the level of low-carbon transformation, and draws on the data envelopment analysis method used by He Weijun et al. for calculation to comprehensively analyze the complex causal relationships between innovative ecological symbiosis and low-carbon transformation and explore a diversified development path for low-carbon transformation that suits China's national conditions. To ensure the adequacy and availability of sample data, this paper selects panel data from 30 provinces in China (excluding Xizang, Hong Kong, Macao and Taiwan) from 2014 to 2020 as sample cases to analyze the complex mechanism between innovation ecosystem symbiosis and low-carbon transformation. The indicator data is sourced from the China High-tech Industry Statistical Yearbook, China Science and Technology Statistical Yearbook, China Regional Innovation Capability Evaluation Report, and provincial statistical yearbooks.
The research results show that,firstly, the single dimensions of the innovation ecosystem and their constituent conditions do not possess the necessary conditions for low-carbon transformation. Secondly, there are two configurations that can promote low-carbon transformation, namely, institutional logic configuration and platform logic configuration. These two configurations represent multiple pathways for achieving low-carbon transformation under different governance mechanisms in the innovation ecosystem. Furthermore, by observing the consistency among provinces during the panel period, it is found that there are certain group differences between the two configurations, which may be due to differences in infrastructure development, technological foundations, and industrial structures. Finally, among the two configurations that promote low-carbon transformation, there is a complementary relationship between subject coordination, knowledge development and creation, and knowledge flow and diffusion, and these three prerequisites have a universal role in low-carbon transformation. There is a substitutive relationship between institutional logic and platform logic, but this relationship is not singular but depends on specific stages and needs.
The marginal contributions of this paper are reflected in two aspects: on the one hand, it constructs a theoretical model of low-carbon transformation from the perspective of innovative ecosystem symbiosis, enriching and refining the existing research results on innovative ecosystem symbiosis; on the other hand, it explores the necessary and sufficient dual causal relationship between innovative ecological symbiosis at the provincial level in China and the emergence of low-carbon transformation paths. It reveals the diverse development paths that promote and hinder low-carbon transformation of economic development modes through innovative ecological symbiosis, providing a theoretical basis for dynamic research on the impact of innovative ecological symbiosis on low-carbon transformation trajectories.

The deep integration of civil-military resources is the internal requirement of enhancing the degree of civil-military integration and realizing the dynamic balance between civil-military demand as well as supply from the perspective of supply side. As civil-military integration enters the stage of deep development, advanced defense industries with Chinese characteristics that match to civil science technology and social economic development are also adjusting and optimizing their layout and deployment in key areas of construction. Therefore, how to scientifically and effectively integrate civil-military resources and build the integrated sharing system of civil-military resource elements has become urgent. Building docking platforms, setting up demonstration zones and setting up new types of organizations are important ways for our national governments to realize the sharing of civil-military resources. At present, many provinces in China have set up the civil-military integration sharing service platform one after another. On the whole, although the construction of civil-military resource sharing and integration has crossed the preliminary stage of platform building, it has presented the practical characteristics of diversified allocation modes, miscellaneous resource systems, multiple participants and many involved factors, and thus it is necessary to sort out and reconstruct the typical characteristics of the existing civil-military resource integration system, summarize and condense the model of civil-military resource integration and allocation, and analyze the mechanism of the influencing factors of the resource sharing and allocation to provide support for the deep integration of civil-military resources at the theoretical level.#br#In this study, the research paradigm of grounded theory is applied in the construction of element system for deep integration of civil-military resources. The study takes 15 civil-military integration public service platforms, civil-military science and technology industrial parks, and the construction of national defense science and technology industry alliance as the case units of grounded research.The contents of modules reflecting resource sharing are conceptualized and categorized, such as "resource sharing", "demand docking" and "supply and demand information" on the official websites of each service platform, resulting in 239 conceptual contents and 27 initial categories. Meaning clustering is carried out in the initial category, and four main categories including substantive elements, connecting elements, penetrating elements and preparatory elements are obtained. On the above basis, the framework of element system for deep integration of civil-military resources is constructed, and the internal correlation of different elements in the system is analyzed.#br#Furthermore, on the basis of the content of resource elements, the main body of organization and deployment, and the system coordination mechanism, as well as the existing typical civil-military integration development mode, the study summarizes the classification of the subject structure, namely centralized precision collaboration structure, distributed autonomous collaboration structure and collaborative multi-chain collaboration structure, which are inherent in deep integration of civil-military resources. The centralized precision collaboration structure is characterized by high frequency of resource circulation and intensive information interaction, which is often influenced by information docking, qualification recognition, construction and management standards, sharing barriers and other factors. The distributed autonomous collaboration structure has the characteristics of flexible constraints and autonomous participation, and is greatly influenced by the participation willingness of the subject, the division of rights and responsibilities, the distribution of interests and other factors. The collaborative multi-chain collaboration structure is manifested by the integration of information chain, value chain, innovation chain, governance chain, which depends on the shaping of inter-subject value and organizational management as well as the further improvement of system and market environment.#br#Finally, according to the element system and the classification of the subject structure of the deep integration of civil-military resources, the main factors that affect the deep integration of civil-military resources are sorted out. The attributes, importance and interaction of the influencing factors are analyzed by using the DEMATEL analysis method. According to the attribute combination, the influencing factors are divided as being key-driving, supporting-driving, supporting-oriented and key-oriented, and the strategies of various factors in the adjustment of resource allocation mode are given. According to the research results, policy suggestions are put forward from three aspects: the operation of civil-military public service platform, exploration of civil-military resource sharing modes in different regions, and establishment of policy supply system based on influencing factors.#br#

The Chinese modern industrial system is a new industrial system supported by the real economy and led by scientific and technological innovation; however, issues such as the financial industry's transition from real to virtual, the imbalance in the industrial supply and demand structure, and the lack of incentive for enterprises to engage in the transformation of scientific and technological achievements have created bottlenecks in the construction of a modern industrial system with Chinese characteristics. These challenges hinder the effective advancement of China's modernization efforts. The rapid optimization and allocation of resource elements by the digital economy breaks the time-space restriction of the circulation of resource elements under the traditional industrial development mode, and further optimizes the industrial structure and promotes the high-quality development of the industrial system through the development of industrial digitalization and digital industrialization, which is conducive to the construction of a Chinese modern industrial system. In addition, the new quality productive forces can take advantage of the transformation efficiency of the digital economy to further build an industrial upgrading path with scientific and technological innovation as the engine, emerging industries as the leading and industrial optimization as the direction, and provide strong support for the construction of a Chinese modern industrial system. Therefore, this study aims to explore the possible internal relationship among the digital economy, new quality productive forces and a Chinese modern industrial system. It aims to address the following questions: How does the digital economy affect Chinese modern industrial system, and does this impact have a spatial spillover effect? What is the mechanism of the new quality productive forces in the relationship between the two under the conditions of different resource enrichment, digital economy development level and regional location?What is the heterogeneity of the relationship between them?#br#The current studies on the single dimension of digital economy, new quality productive forces and modern industrial system are relatively sufficient, but few scholars have conducted extensive discussion on the driving mechanism and influencing factors of the Chinese-style modern industrial system, and there is a lack of systematic analysis incorporating the three into the same framework. Thus, this study first establishes the theoretical analysis framework of digital economy, new quality productive forces and Chinese modern industrial system. Then, it takes 31 provinces from 2012 to 2022 as the research object, screens and analyzes the relevant data of digital economy, new quality productive forces, and Chinese modern industrial system, and finally obtains 341 sample data. Finally, the study uses the benchmark regression model, the mediating effect model and the spatial Dubin model to analyze the influence of the digital economy on the Chinese modern industrial system and the mediating effect of the new quality productive forces. The results show that the digital economy has a significant promoting effect on the Chinese modern industrial system, and this impact is more significant in resource-based provinces, high-level groups of digital economy and the eastern region. The digital economy can promote the formation and development of new quality productive forces and drive the construction of Chinese modern industrial system, that is, the role path of "digital economy—new quality productive forces—Chinese modern industrial system" is established. Further analysis reveals that the digital economy has a significant positive spatial spillover effect on the Chinese modern industrial system.#br#Different from previous studies, this paper explores the impact of digital economy on Chinese modern industrial system from three perspectives: industrial integration, sustainable development and innovation empowerment. Then, guided by Schumpeter's innovation theory, it upgrades the three elements of traditional productive forces with "new quality". Furthermore, the paper systematically analyzes the concrete action path of new quality productive forces in the process of digital economy affecting the construction of Chinese modern industrial system. Finally, research deficiencies are presented, and the possible moderating effect of external environmental factors on the relationship between the digital economy and the Chinese path to modernization of the industrial system is warranted for future study .#br#

Under the guidance of the "innovation-driven strategy", innovation has increasingly become an important support for empowering high-quality development. With the rapid development of the digital economy, digital industrialization and industrial digitalization are promoted together, and the rapid progress of digital-related technologies makes the digital economy an important driving force to promote innovation. Therefore, it is a key issue to peep at the innovation effect brought by the development of the digital economy from the perspective of enterprises as the micro-subject of innovation. However, it is worth noting that the development of the digital economy at the macro level has a relatively indirect impact on the innovation performance of micro-enterprises and contains many confusing factors, while the digital transformation of enterprises driven by the digital economy provides a sound framework for exploring the innovation effect of enterprises against the background of digital economy development. Therefore, this paper aims to analyze how the digital transformation of enterprises affects the innovation behavior of enterprises with the help of the related theories and literature of digital economy and enterprise development, and further investigate the innovation effect of the digital transformation of enterprises from the perspective of efficiency.#br#This paper uses the data of A-share listed companies in Shanghai and Shenzhen from 2011 to 2021, and constructs an index system to measure the digital transformation of enterprises from five dimensions: goal orientation, technology drive, organizational empowerment, environmental support, and results and applications. It also examines the innovation effect of enterprises from the perspective of innovation input, output and efficiency. Then the innovation effect of enterprise digital transformation is empirically tested by the three-dimensional fixed effect model; with the investor's emotion as a moderating variable in the model, the moderating effect of investors' emotion is investigated. Furthermore, heterogeneity is analyzed from the perspectives of enterprise property rights and location factors. After clarifying the channels and sources of innovation efficiency loss caused by digital transformation of enterprises, this paper evaluates the improvement effect of digital industry policy on innovation efficiency.#br#The results show that during the sample inspection period, the digital transformation of enterprises has both incentive effects on innovation input and output and characteristics of innovation efficiency loss. This conclusion is still valid after selecting instrumental variables at the enterprise and city levels for endogenous processing and using substitution variables for robustness testing. As an irrational factor in the market, investor sentiment positively moderates the innovation incentive effect of enterprise digital transformation and negatively moderates the loss of innovation efficiency; the property right attribute and location of an enterprise are also important sources of its innovation efficiency loss; and digital industry policy can effectively improve the inhibition of enterprise digital transformation on innovation efficiency. Therefore, this paper holds that enterprises should explore the digital transformation path in line with their own development status and avoid the inefficiency of innovation caused by blind obedience; government policy orientation should further deepen the reform of state-owned enterprises, pay special attention to regional coordinated development, and explore the implementation of diversified digital industry policies.#br#This paper contributes to the study on enterprise digital transformation in several directions. Firstly, the innovation effect of enterprise digital transformation is comprehensively investigated by bringing it into the same analytical framework as the input, output and efficiency of enterprise innovation, and the characteristic facts of the loss of innovation efficiency in the initial stage of enterprise digital transformation in China are confirmed, and its sources and possible countermeasures are further analyzed. Secondly, a more complete evaluation system for enterprise digital transformation is constructed. Different from the previous practice that most literature measures the digital transformation of enterprises through a single index, it divides the digital transformation of enterprises into five dimensions and constructs a comprehensive evaluation system. The conclusions provide path support for the digital transformation of enterprises in the future and empirical evidence for promoting an innovation-driven development strategy based on the development of the digital economy from the perspective of enterprises.#br#