The intensification of anti-globalization and protectionism has led the world into a new period of turbulent transformation. At this stage, new quality productive forces is a key factor for China's high-quality development. New quality productive forces is characterized by high technology, efficiency, and quality, fundamentally transforming productivity through technology, resource allocation, and industrial transformation. Regional disparities exist in China in terms of economy and industry due to varying development conditions, necessitating tailored development strategies as a primary governmental task. It is of significant theoretical and practical importance to analyze the evolution and disparities in new quality productive forces across regions, study influencing factors, identify obstacles, and explore enhancement paths for driving high-quality development so as to promote industrial upgrading and transformation, and lead global economic development.
A new quality productive forces development level index system is constructed based on data from 30 Chinese provinces between 2011 and 2022. The entropy method is used to measure the current state of new quality productive forces development at the national level, in each province, and within the 8 major economic zones. Markov chains and Dagum's Gini coefficient are employed to analyze the dynamic trends and regional development disparities. The DEMATEL-ISM model is utilized to conduct a structural analysis of the influencing factors of new quality productive forces, identifying intrinsic key factors and the logical relationships and pathways between these factors. Main obstacles hindering the development of new quality productive forces are identified through obstacle degree calculations, followed by targeted path analysis for enhancing new quality productive forces in each region, integrating all analytical indicators.
The results show that (1) in terms of the development of new quality productive forces, China has experienced a consistent upward trajectory from 2011 to 2022. Provinces with high development levels include Guangdong, Beijing, Jiangsu, Zhejiang, and Shandong. When divided by region, the overall level of new quality productive forces is highest in the eastern coastal regions. (2) According to Markov chain and Dagum analysis, significant differences exist in the levels of new quality productive forces development across various regions in China. These differences primarily stem from disparities among the 8 major economic zones. The largest regional disparities are between the northwest region and the eastern coastal, southern coastal, and northern coastal regions, with the lowest disparities between the middle reaches of the Yellow River and the middle reaches of the Yangtze River. Within various regions, the southern coastal areas exhibit the greatest disparities, while the eastern coastal areas show lower and more balanced differences. Additionally, there are spatial spillover effects, where regions with high development levels can drive development in regions with lower levels without hindering the development of higher-level regions. (3) Utilizing the DEMATEL-ISM model and obstacle degree analysis, the study reveals that within the 15 primary indicators of new quality productive forces, 8 indicators are identified as root factors, which include aspects related to the human capital structure, while 7 indicators are classified as outcome factors, encompassing elements such as human capital investment. Root factors affecting the structure include levels of technological cooperation flow, development of emerging industries, and future industrial layout. Intermediate influencing factors include human capital investment, telecommunications infrastructure, and human capital structure, among 7 indicators. Surface influencing factors include human capital assurance, transportation infrastructure, and five other indicators. The main obstacles in most regions are inadequate development in technological cooperation flow, future industrial layout, structure of the digital economy, and level of technological innovation. (4)Through path analysis, the study identifies four strategic development paths to bolster the new quality productive forces. The first path is dedicated to surmounting core barriers and igniting the catalyst for their advancement. The second path is geared towards navigating intermediate obstacles and establishing a systematic framework for growth. The third path underscores the importance of regional collaboration to amplify joint development initiatives. The last path concentrates on the pivotal role of core leadership in fostering balanced development of new quality productive forces.

Digital transformation is a key driver of the current global economy, acting as a catalyst for industrial upgrading and enhancing corporate competitiveness to foster sustainable economic growth, which the Chinese government has prioritized as a core national strategy. By 2022, China’s digital economy reached an impressive scale of 50.2 trillion yuan, accounting for 41.5% of the GDP, underscoring the critical role of digital integration in economic advancement. The interplay between digital transformation and the real economy is profound, with substantial implications for corporate digitalization. This transformation enhances information flow, optimizes resource allocation, and stimulates innovation and productivity, thereby creating a favorable environment for high-quality development. However, the relationship between digital transformation and productivity is complex and multifaceted, warranting further investigation.
This paper centers on new quality productive forces, a concept emphasizing the urgency to enhance total factor productivity through technological innovation and the effective integration of resources. New quality productive forces represent a paradigm shift that not only focuses on quantitative growth but also emphasize qualitative improvements in productivity, reflecting the evolving demands of a modern economy. While existing literature recognizes the positive impacts of digital transformation—such as increased management efficiency, optimized specialization, and enhanced innovation capabilities—significant discrepancies remain regarding its overall effectiveness in different contexts. Some scholars have raised concerns about the multifaceted nature of the transformation process, noting that it is often fraught with complexities, including cultural resistance, inadequate infrastructure, and the need for substantial investment in skills and technologies. These factors can result in delayed effects, preventing the anticipated benefits of digital initiatives from being immediately realized.Consequently, it is essential to delve deeper into how digital transformation influences new quality productivity, as this understanding holds implications for both theoretical exploration and practical application. By analyzing the mechanisms through which digital initiatives contribute to productivity improvements, we can uncover valuable insights that guide policymakers and business leaders in crafting strategies that foster sustainable growth.
To explore this relationship, this paper adopts the Technology-Organization-Environment (TOE) framework, which posits that the success of technological innovation is influenced by three dimensions: technology, organization, and environment. From a technological perspective, the size of a firm and its type of technology dictate its capacity for transformation. Larger enterprises, with their abundant resources, typically exhibit a greater ability to adapt to new technologies, thereby enhancing new quality productivity. In contrast, high-tech firms leverage their technological advantages to achieve breakthroughs through digital transformation. Organizationally, the decision-making capabilities of management are crucial for the success of transformation efforts, as they significantly impact resource integration and efficiency. Additionally, the competitive environment plays a vital role; market pressures compel firms to rapidly adopt new technologies, enhancing resource allocation efficiency and driving productivity growth. This paper constructs a theoretical framework encompassing firm size, technology type, market competition, managerial capabilities, and resource allocation efficiency. This paper proposes hypotheses that will be empirically tested using data derived from A-share listed companies. Utilizing the entropy method, this paper measures new quality productivity through dimensions like innovation leadership, enterprise upgrading, technology-driven growth, and sustainability.
The results show that digital transformation positively impacts new quality productivity in a U-shaped manner. As the level of transformation increases, its beneficial effects amplify. Furthermore, the analysis suggests that larger firms, those in high-tech industries, and enterprises in competitive markets experience more significant advantages from digital transformation. Additionally, this paper identifies that managerial capabilities exert a nonlinear moderating effect, while resource allocation efficiency serves as a significant mediating factor, enhancing capital and labor allocation.
The contributions of this paper are threefold. First, it provides a nuanced examination of new quality productive forces, focusing on innovation leadership, enterprise upgrading, and sustainable development.Second, it enriches the existing body of literature by elucidating the nonlinear relationship between digital transformation and productivity. Lastly, the study explores the nonlinear moderating effect of managerial capability improvement and the mediating effect of resource allocation efficiency, revealing their key roles in digital transformation. It also addresses literature gaps and provides practical insights for businesses to leverage digitalization for enhanced productivity and sustainable growth.

In order to achieve greater self-reliance and strength in science and technology, it is essential to explore the factors that enhance technological self-reliance and self-improvement, this study develops a comprehensive framework using grounded theory and the Delphi method. The conception of technological self-reliance and self-improvement is crucial for the framework of an open system. It calls for a balance between integrating into global innovation networks and maintaining strategic autonomy, and aims to promote active engagement and competitive participation in the global market by leveraging and enhancing local innovative capabilities. The ultimate goal of technological self-reliance and self-improvement is a comprehensive advancement in technology that merges both the manifest and latent capabilities of local entities, propelling them towards greater strategic initiatives, controllability, and competitive advantage on a global scale.
The study begins by defining the concepts of technological self-reliance and self-improvement through a review of existing literature. Technological self-reliance is understood to encompass two interrelated dimensions: technological independence and technological empowerment. Technological independence is about achieving innovation self-sufficiency, emphasizing the development of domestic capabilities to ensure autonomy and security within industrial and supply chains; in contrast, technological empowerment focuses on enhancing the efficiency and effectiveness of technology, advocating for improvements in the quality of technological innovations that can lead to and support high-quality development.
Decision making trial and evaluation laboratory (DEMATEL) is considered an effective method for visualizing complex causal relationships within the system. Using graph theory and matrix calculations, the study assesses the centrality and causality of various factors. The analysis reveals that strategic and governance elements, such as the implementation of innovation-driven strategies and the modernization of governance frameworks, significantly influence the system. These elements are vital in bolstering the national system′s ability to pursue and achieve technological advancements. ISM is employed to create a layered hierarchical structure for these factors, showing how some act as foundational while others operate at intermediate or strategic levels. The identified olive-shaped structure, featuring a robust middle layer filled with intermediary mechanisms, facilitates dynamic interactions across levels. This structural complexity is especially beneficial in areas like national technology sectors, which are characterized by numerous levels of interaction and feedback loops. The MICMAC application was instrumental in classifying these factors based on their roles as drivers or dependents within the system. This classification aids stakeholders in understanding which factors are likely to influence others and which are more susceptible, thus providing a strategic map for policy development and resource allocation. To validate the integrated system model, the study analyzes the development of China′s Circulating Fluidized Bed (CFB) boiler technology. This technology marks a significant progression in energy efficiency and emission reduction. The successful deployment and scaling of CFB technology not only underscore the effectiveness of the strategic factors identified but also demonstrate the model′s validity. This highlights how structured innovation governance and strategic initiatives are crucial in fostering technological self-reliance.
〖HJ*3〗The enriched theoretical framework developed through this study significantly advances the understanding of the determinants fostering technological self-reliance and self-improvement and provides practical guidance for both policymakers and industry leaders. The research underscores the critical role of modernizing governance structures in science and technology innovation as pivotal for achieving technological self-reliance and enhancement, reflecting China′s long-standing endeavors in technological progression. It stresses that refining these governance systems is essential for expediting this advancement. Moreover, the analysis draws attention to the vulnerability of strategic technological initiatives to systemic disturbances, suggesting that the success of such projects hinges on meticulous monitoring of both the initiatives themselves and the contextual factors that influence them. Furthermore, the study reveals that the capacity for innovation leadership in the context of technological catch-up is intricately dependent on a multitude of interconnected factors, highlighting the complexity involved in nurturing such capabilities within a dynamic and integrated system. This comprehensive analysis delivers insightful revelations on the complex nature of building and sustaining technological strength and autonomy, offering a valuable perspective for nations pursuing technological independence and global innovation leadership. These insights are instrumental in shaping strategies that effectively bolster and refine technological ecosystems.

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.

Green technological innovation, the nexus of innovation-driven and green development strategies, plays an increasingly vital role in the national economic green transformation. Meanwhile, high-tech industries, characterized by their technological intensity and environmental friendliness, have emerged as a driving force for accelerating green development and industrial transformation. In this context, high-tech industries have become a prominent area of academic research and a crucial tool for local governments to achieve green development goals. As an efficient and compact spatial development model, industrial agglomeration helps local governments optimize the market-oriented allocation of innovation resources and green transformation development. Given the objective reality of unbalanced regional development in China, are there regional differences in the impact of high-tech industry agglomeration on green technology innovation? Does high-tech industrial agglomeration improve the efficiency of green technology innovation in different regions, and how? These questions are worthy of further research.
Therefore, following the externality theory, this paper constructs a model framework of "high-tech industry agglomeration—knowledge spillover and market competition—green technology innovation efficiency" and discusses it from both theoretical and empirical aspects. Specifically, drawing on provincial data from 2010 to 2022, this study applies spatial Durbin models and mediation effect models to examine the impacts of high-tech industry agglomeration on regional green technological innovation. The findings indicate that high-tech industry agglomeration significantly enhances local green technological innovation efficiency while inhibiting the efficiency in neighboring regions. Furthermore, the green innovation effect of high-tech industrial agglomeration has obvious regional heterogeneity. In the eastern and central regions, high-tech industry agglomeration significantly hinders neighboring regions' green innovation efficiency through the siphon effect. Conversely, in the western region, high-tech industry agglomeration exerts a positive spillover effect, fostering the enhancement of green innovation efficiency in adjacent areas. Mechanism analysis reveals that knowledge spillovers and market competition have partial mediating effects. Specifically, the mediation effect of knowledge spillovers is more pronounced in the eastern region than in the western region, while it is not significant in the central region. Market competition has an insignificant mediating effect in the eastern region, exhibits a masking effect in the central region, and demonstrates a partial mediating role in the western region.
On the basis of the above conclusions, this paper puts forward the following policy recommendations. First of all, governments should objectively recognize the role of high-tech industrial agglomeration. To mitigate the adverse consequences of the siphon effect, differentiated regional policies should be implemented. Secondly, knowledge spillover and market competition should be brought into play to promote green innovation. In the eastern and western regions, policies should encourage the commercialization of knowledge to stimulate the flow of knowledge and technology transfer. In the central region, it is imperative to strengthen market regulation mechanisms and combat unfair competition. In the western region, a moderate relaxation of market entry barriers could incentivize greater enterprise participation in competition, thereby enhancing the dynamism and competitiveness of industrial clusters. Finally, it is necessary to promote high-quality spatial agglomeration of high-tech industries. Establishing stringent entry thresholds for high-tech industries is essential, ensuring that only enterprises with substantial technological prowess and innovation capacity are admitted.
This paper integrates the research results of industrial agglomeration and green technology innovation. It explores the local and spatial effects of high-tech industrial agglomeration on regional green technology innovation across the entire nation and within the eastern, central, and western regions. Additionally, it investigates the mechanisms of these effects through the dual lenses of knowledge spillovers and market competition, aiming to facilitate regional green transformation. The research results provide a theoretical basis and practical support for optimizing regional industrial agglomeration and achieving green development. This study makes several significant contributions to the literature. First, it extends existing research on industrial agglomeration externalities and technological innovation. Second, it responds to previous research on industrial agglomeration and empirically verifies the key role of knowledge spillovers and market competition in improving the efficiency of green technology innovation. Lastly, by considering regional heterogeneity, this study refines its research focus and proposes targeted policy recommendations, thereby providing valuable guidance for local governments aiming to achieve sustainable development

New quality productive forces are the advanced productive forces with innovation playing a leading role and technological innovation as the core element. The approach to developing new quality productive forces is to timely apply technological innovation achievements to specific industries, and transform technology into real productive forces. It cannot be achieved without the cross integration of multiple fields, such as technology and industry. The integration of industrial chain and innovation chain (two-chain integration) can transform abstract theory and technology into advanced productivity. Therefore, identifying the key links that promote the two-chain integration is an important lever for developing new quality productive forces.
In view of this, the idea of "structure-behavior" is introduced to identify the key links of the two-chain integration based on the analytical framework that combines macro-structure and micro-behavior. Firstly, on the basis of the analysis of the connotation, the complex network theory is applied to analyze the macro-structure of the multi-layer network of the two-chain integration. Secondly, in view of network synchronization, the micro-behavior of the two-chain integration is analyzed, and a network dynamics model is constructed from the perspective of R&D elements. Next, by taking the synchronous constraint nodes as the key links, the advantages of random and target constraints are integrated to design an improved control strategy based on the ant colony algorithm. Finally, with the electronic components industry as the research subject, the corresponding industry chain is constructed with the 2020 National Input-output Table of China and the National Economic Industry Classification as references. According to the Patent Retrieval and Analysis Platform of the China National Intellectual Property Administration, the corresponding innovation chain is built. Then the multi-layer complex network of two-chain integration with 72 nodes with strong correlations is established.
The following conclusions are drawn. In general, the results indicate that the synchronous dynamic model and the improved restraint control strategy of the two-chain integration, as designed in this paper, can effectively identify the key links. To be specific, when the industrialization capability of scientific and technological achievements is relatively stable, to ensure the continuity of the two-chain integration, the scope of integration should be expanded. This implies that both industry and innovation entities should be encouraged to participate as extensively as possible. As the scope of integration expands, entities with lower degree values gradually become key links in promoting the two-chain integration. In the field of industrial innovation networks, the degree value directly reflects the scale and impact capacity of the entities. In addition, when the scope of integration is relatively stable, in order to ensure the continuous of the two-chain integration, the industrialization ability of scientific and technological achievements should be improved as much as possible. With the improvement of the industrialization ability of industry technological achievements, entities with higher degree values have gradually become key links in promoting the two-chain integration. In terms of algorithm optimization, the improved constraint strategy designed in this study shows significant advantages over traditional methods in terms of synchronization efficiency and optimization outcomes.
This study contributes to the identification of key links in the integration of industrial chain and innovation chain. By analyzing the essence of the two-chain integration and combining the structural characteristics of industrial and innovation chains, a multi-layer network-based structural model of the two-chain integration is constructed using complex network theory. Furthermore, the dynamic behavior of the two-chain integration is elucidated by examining the network synchronization dynamics and providing quantitative criteria for assessment. Finally, key links that foster the two-chain integration are effectively identified by transforming the problem into a multi-layer network control issue, utilizing constrained control nodes within the network as the key link to promote the two-chain integration. The convergence of the industry chain, innovation chain, capital chain, and talent chain is gaining significant attention. Future studies could adopt the research lens presented in this paper to construct a comprehensive network model that integrates these four critical chains. By examining their dynamic attributes, such research can pinpoint the key links that are vital for the integrated system.

Establishing a military-civilian science and technology collaborative innovation system is crucial for optimizing national resources and integrating military and civilian efforts. The current revolution in military science and technology, marked by unmanned intelligence, demands a new paradigm for innovation to meet evolving needs. Traditional models fall short, as they struggle with dispersed innovation entities, weak synergistic motivation, and unclear innovation node relationships, hindering the efficiency of collaborative innovation. Addressing these issues is key to enhancing the driving force for building digital China and developing a robust national defense science and technology innovation system. However, China is a late-developed country in the digital transformation of the military field. The domestic military intelligence strategy layout is relatively scattered and has not yet formed a global strategy for overall upgrading. Moreover, many domestic enterprises still view digital transformation merely as an extension of internet adoption, treating digital technology as a mere tool for optimizing business processes and enhancing efficiency. This perception limits the full potential of digital technology and results in the underperformance of digital transformation initiatives. Therefore, this paper addresses whether digital transformation can become a sustainable driver of military-civilian science and technology collaborative innovation and a strategic support for enhancing the overall efficiency of the national innovation system at a micro level. Furthermore, at present, the academic community mainly reflects the impact of digital transformation on military-civilian science and technology collaborative innovation from the macro level, but few studies explore the fluctuation, adaptation and stability process of military-civilian science and technology collaborative innovation under the impact of digital transformation from a micro perspective.
Drawing on the sample of listed companies from 2015 to 2022, this paper uses DEA to calculate the efficiency of military-civilian science and technology collaborative innovation, and puts the core variables into the Tobit model for regression. Then the heterogeneous factors of different digital transformation methods, civil-military integration directions and property rights are introduced to further empirically explore the effect and influence mechanism of digital transformation on military-civilian science and technology collaborative innovation.
It is found that the effect of digital transformation on collaborative innovation of military and civilian science and technology shows a significant U-shaped relationship. After endogeneity and robustness tests, this conclusion is still valid. With regard to the heterogeneity problem, compared with the digital transformation mode at the basic technical level, the digital transformation at the practical application level has a stronger driving force for the collaborative innovation of military and civilian science and technology.Compared with non-state-owned and civilian military enterprises, the digital transformation of state-owned enterprises and military-to-civilian enterprises has a more obvious effect on the collaborative innovation of military and civilian science and technology. The mechanism analysis shows that digital transformation mainly accelerates the collaborative innovation of military and civilian science and technology through development innovation, but it does not show a significant incentive effect on exploratory innovation.
Further research finds that the positive moderating effect of market concentration has a threshold effect. When market concentration exceeds a certain limit, the enabling effect of digital transformation begins to weaken or even disappear. The analysis shows that environmental uncertainty hastens the transition from the decline to the rise phase of the digital transformation curve, and alleviates the negative impact of digital transformation on military-civilian science and technology collaborative innovation. The concentration of the supply chain delays the inflection point of digital transformation from the decline to the rise phase and enhances the positive impact of digital transformation on military-civilian science and technology collaborative innovation.
The research conclusions provide empirical evidence and relevant reference for clarifying the dependence relationship between digital transformation and military-civilian science and technology collaborative innovation, and boost the release of innovation vitality under the national defense science and technology innovation system.

Innovation, as the core driving power of promoting the sustainable development of enterprises, has become a key factor for modern enterprises to stand out in the fierce market competition. However, many employees adopt transgressive innovation which includes bootleg innovation (unknown to leaders) and deviant innovation (contrary to leadership′s ideas) to reduce the risk of innovation and pursue higher performance under the wave of digital transformation. In order to understand the influence of digital transformation of enterprises on employee transgressive innovation, there are two questions that deserve attention: (1) Digital transformation not only brings massive heterogeneous resources to the organization, but also makes the decision-making power of the organization more centralized, which affects the enterprise business model and the way of value creation,and redefines the way of work, and even change the nature of work. Then how do these changes affect the employees′ transgressive innovation? (2) How does digital transformation affect bootleg innovation and deviant innovation?
In the digital era, digital transformation brings a huge amount of heterogeneous resources, and also makes organizational decision-making more centralized and managerial authority strengthened. The perception of overqualification, as one of the most important psychological states of employees, possesses duality and sensitivity, and has a predictive effect on employees′ psychological emotions and innovative behaviors. The Cha-xu atmosphere is bound to have an indirect effect on the resources available to employees and the authority of managers under the influence of the Cha-xu pattern of the Chinese cultural context. Thus, the perception of overqualification and the Cha-xu atmosphere are considered to be two key factors affecting the relationship between enterprise digital transformation and employee transgressive innovation.
Following behavioral decision-making theory and threat rigidity theory, this paper constructs the integrated logic of digital transformation affecting transgressive innovation behavior. Targeting employees engaged in R&D, technology, design, marketing, and other positions that require innovation activities in companies that are undergoing or have undergone digital transformation, this study uses statistical analysis tools such as SPSS 25.0, MPLUS 7.0, and PROCESS 4.1 to organize and empirically analyze the data collected from 1 088 samples.
The results show that (1) digital transformation brings more heterogeneous resources, which positively affects employees′ bootleg innovation; (2) digital transformation makes organizational decision-making more centralized and managerial authority strengthened, which negatively affects employees′ deviant innovation; (3) the perception of overqualification plays a partial mediating role, which can mediate the positive relationship between digital transformation and employees′ bootleg innovation and also the negative relationship between digital transformation and employees′ deviant innovation; (4) the Cha-xu atmosphere positively moderates the impact of perception of overqualification on employees′ bootleg innovation and deviant innovation and also positively moderates the mediating role of perception of overqualification in the relationship between digital transformation and employees′ bootleg and deviant innovation.
This study makes the novelties by placing the two types of transgressive innovation in the same framework; moreover, it reveals the intrinsic influence mechanism of enterprise digital transformation on two types of employee innovation behaviors, and provides ideas for promoting more innovation by introducing a perception of overqualification and a Cha-xu atmosphere; lastly, the analysis of the impact of digital transformation on employee transgressive innovation behavior expands the research on the antecedents of employee transgressive innovation.
There are four managerial insights from this study. First, enterprises should actively provide support for digital transformation resources. Second, the perception of overqualification is malleable and dynamic, and companies should take advantage of employees′ psychological changes to adjust their innovative behaviors. Third, enterprises should actively create a positive Cha-xu atmosphere. Fourth, enterprises need to be fully aware of the two sides of transgressive innovation and guide employees to innovate within the scope of lawfulness and compliance, and promote more innovative achievements. At the same time, the study is subject to a number of limitations, and future research can consider setting up paired questionnaires to collect data to further improve the scientific nature of the study, and also combine experimental methods to make research more accurate in the future.

Integration into the global innovation network is one of the important strategic choices for private enterprises to improve the quality of innovation, which is crucial for the construction of China's open innovation ecosystem. With the development of reverse mixed ownership reform, the participation of state-owned capital in private enterprises is gradually increasing. Studies have already found that the introduction of state-owned equity in private enterprises helps to promote innovation in private enterprises. However, few studies have explored whether state-owned equity helps private enterprises integrate into global innovation networks.
In fact, the pressures and challenges faced by private enterprises in their struggle for survival and growth make it difficult for them to integrate into the global innovation network, and the introduction of state-owned equity is of great significance for private enterprises to cope with the pressure of survival and the challenges of development. On the one hand, private enterprises face an unstable institutional environment at home, irregularities in their own operations, and the risk of being challenged by the host country when operating abroad, and these factors make it difficult to provide a stable survival environment for their integration into the global innovation network. Research has found that the introduction of state-owned equity in private enterprises can serve as an alternative institution, which is conducive to improving the survival environment for their operational environment. On the other hand, the survival pressure on private enterprises also exacerbates their development challenges. The survival instability of private enterprises prevents them from obtaining recognition for resource acquisition through formal channels, increases opportunistic behavior by large shareholders, and has low transparency in information disclosure, which makes it difficult to provide abundant resources for integrating into the global innovation network. The strategic value of state-owned shareholders gives them excess governance influence, which is of great significance for private enterprises to obtain recognition for accessing resources through formal channels, curbing opportunistic behaviors of major shareholders, and improving the transparency of information disclosure. Moreover, differences in the internationalization attention of private enterprises and differences in the competitive environment of technology markets faced by private enterprises may also play an influential role in the way state-owned equity affects the integration of private enterprises into global innovation networks.
To this end, this study summarizes the survival pressure faced by private enterprises as perceived legitimacy and the development challenges as pragmatic legitimacy based on the relevant concepts of institutional theory and legitimacy theory, regards the strategic value and governance role of state-owned equity beyond the proportion of shareholding as shareholder activism based on the theory of shareholder activism, and utilizes the data of A-share-listed private enterprises in Shanghai and Shenzhen between 2007 and 2022 to investigate whether state-owned equity affects the integration of private enterprises into the global innovation network , and it also explores its mechanism, heterogeneity factors and further impact on the quality of innovation are explored.
It is found that state-owned equity has a facilitating effect on the integration of private enterprises into global innovation networks. Mechanism analysis shows that state-owned equity enhances the perceived legitimacy of private enterprises, which is manifested in enhancing the positive effects of private enterprises' operational stability, operational compliance, and host country survival rate on the integration of private enterprises into global innovation networks; state-owned equity enhances the pragmatic legitimacy of private enterprises, which is manifested in the positive effects of enhancing the recognition of private enterprises' formal channels of access to resources and the transparency of information disclosure on their integration into global innovation networks, and inhibits the negative effects of the opportunistic behavior of large shareholders on the integration of private enterprises into the global innovation network. Heterogeneity analysis suggests that state-owned equity is better able to facilitate the integration of private enterprises into the global innovation network when they have a higher internationalization focus and face a competitive domestic technology market environment. The study also finds that state-owned equity improves the quality of private enterprises' innovation after promoting their integration into global innovation networks.

High-tech enterprises' involvement in shaping technical standards is pivotal for their innovation endeavors and securing a competitive edge in both domestic and global markets. The contemporary corporate rivalry transcends the realm of products and services, encompassing the entire supply chain. Suppliers and customers, as key external stakeholders, significantly influence a company's operational decisions and serve as vital sources of external knowledge. The existing studies have extensively discussed technical standardization capabilities of enterprises from the perspective of external networks, but they have reached unanimous conclusions. As an important part of the external network of enterprises, the supply chain network has been neglected by existing research. This paper aims to address this gap by exploring the influence of the supply chain network on the technical standardization capabilities of enterprises, including how their network positions may affect these capabilities. Furthermore, digital technology, as a key driver of technological innovation, has profoundly altered the operational dynamics of corporate external networks. It has introduced new challenges to established theories like network embedding and structural hole theory. Given the rapid evolution of digital technology, the impact of digital technologies on the external networks of enterprises has not been fully discussed. Therefore, this paper further explores the moderating role that the level of digital application may play in the relationship between the supply chain network and the technical standardization capabilities of enterprises.
Drawing on the social network theory and the resource dependence theory, this paper takes the listed companies in China's A-share automobile industry from 2013 to 2022 as the research object, constructs a supply chain network based on the top five suppliers and customer data disclosed by the enterprises, examining the influence of supply chain network positioning on technology standardization capability at both the technological and market levels and the moderating effect of enterprise digital application level, and further discusses the impact of supply chain network location on different types of technology standardization capabilities and technological innovation capabilities.
The study finds that enterprises in the advantageous position within the supply chain network have strong technical standardization capabilities. Enterprises located at the center of the supply chain network exhibit stronger technical standardization capabilities than those at the periphery. Mechanism testing reveals that technological innovation capabilities and market dominance act as mediators between supply chain network positioning and enterprises' technical standardization capabilities. The level of enterprise digital application positively moderates the relationship between centrality and both technological innovation ability and market power. However, the adjustment of structural holes is not significant. Further analysis shows that the degree centrality has a stronger positive impact on the technical standardization ability and technological innovation ability of different types of enterprises compared to the structural hole. The positive impact of independent innovation capabilities on enterprise technology standardization capabilities is stronger than that of collaborative innovation capabilities.
The possible contributions of this paper are as follows: Firstly, it discusses the impact of supply chain network location on enterprise technology standardization capabilities for the first time, and analyzes the difference in the influence of centrality and structure hole on enterprise technology standardization capabilities, which expands the research scope of supply chain network and enterprise technology standardization capabilities, and provides reference for enterprises to improve enterprise technology standardization capability by building advantageous supply chain network location. Secondly, from the dual channels of technology and market, this paper reveals the influence mechanism of supply chain network location on the technology standardization capability of enterprises, and analyzes the impact of enterprise digital application level. This helps enterprises choose appropriate technology standardization strategies based on different network environments and their own digital level, and maximize the advantages of enterprise network location. Finally, this paper analyzes the differences between the influence of independent innovation capability and collaborative innovation capability on the technology standardization capability of enterprises, and reveals the influencing factors of technology standardization capabilities more comprehensively.

The Chinese government has placed scientific and technological innovation at the core of national development. The strategic position and role of science and technology(S&T) in overall national security have gradually increased.Along with the increasing complexity and severity of national security, S&T security, as an important component of national security, is a crucial guarantee for national security. Therefore, in order to optimize the structure of China's S&T security system, it is necessary to analyze the level of coupling coordination development between the internal subsystems of China's S&T security system, explore the main driving factors affecting the development coordination of China's S&T system, and propose countermeasures to promote the improvement of China's S&T security level.
At present, research on the evaluation of technological security mainly involves constructing comprehensive technological security assessment or risk assessment models to evaluate the overall technological security in China. However, these approaches do not explain the internal interactions and couplings within the technological security system. Therefore, this paper introduces a coupling coordination model to assess the coupling relationships and coordination levels among the subsystems within China's S&T security system. The coupling coordination model can evaluate the balance between subsystems by measuring the interactions and development trends among multiple subsystems within the system. Although domestic and foreign scholars have applied coupling coordination evaluation models in different fields, there has been almost no application in the field of S&T security systems. Thus, this study aims to provide recommendations for promoting positive interactions within China's S&T security system, thereby enhancing the country's technological security level by using machine learning methods to evaluate the driving factors of coupling coordination in S&T security systems and the relative importance of these factors.
This study constructs an evaluation index system of the national S&T security system from four subsystems: science and technology achievement security, talent security, environment security, and activity security. It first employs the game theory combination weighting model to integrate the hierarchical analysis method and entropy weight method to get the comprehensive weights, which can avoid the single weighting method being overly subjective or objective, and thus improve the scientificity and reasonableness of the weights of the assessment indexes. Then it combines the simulated annealing algorithm with the projection pursuit evaluation method to build an evaluation model, and then a coupling coordination degree model is constructed to analyze the comprehensive development level of the national S&T security system and the coupling coordination level among the four subsystems. Finally, five machine learning algorithms, namely random forest, ExtRaTrees, gradient boosting tree, AdaBoost, and CatBoost, are deployed to further identify the driving factors of the coupling coordination degree of the S&T security system. The research results show that the development level of the national S&T security system and the coupling coordination development level of the four subsystems have increased year by year. The number of science and technology human resources per ten thousand population is the most significant driving factor for the coupling coordination level of China's S&T security system.
Corresponding countermeasures and suggestions are put forward, which can provide new ideas and methods for national S&T security management. First, the cultivation and introduction of scientific and technological talents should be stressed, and the government should establish a flexible mechanism for the introduction and mobility of talents, encourage exchanges of talents at home and abroad, and improve the overall quality and competence level of scientific and technological talents, so as to meet the needs of the national scientific and technological development. Second, the evaluation and transformation of scientific and technological achievements should be strengthened, as should the rewards and support for important scientific and technological achievements. Meanwhile, it is necessary to improve the incentive mechanism for scientific and technological innovation and create a fair and just environment for scientific and technological innovation.

As technology convergence among strategic emerging industries deepens, the boundaries among technologies are increasingly blurred and redefined. Understanding the interconnections between technologies and grasping the structural dynamics and innovative trends within technology clusters from a global perspective are of significant value for efficiently allocating technological resources and enhancing innovation output. Currently, the studies related to technology convergence and innovation situation assessment mostly use small-sample patent data from specific industries or specific regions, which may lead to biased results. However, due to the difficulty of data acquisition and analysis, few scholars have conducted relevant research on technology integration and innovation situation assessment based on global patent big data. The importance of relevant research data in supporting the formulation of macro-innovation guidance policies is self-evident.
Therefore, this study utilizes global PCT (Patent Cooperation Treaty) big data to develop models for identifying key core technology clusters and assessing innovation trends. It first collects 4 611 149 PCT applications, 14 887 452 records of IPC categories, and 23 961 143 PCT citations.The RIT index is constructed to classify all technology domains into four technology categories, and this paper unfolds along two logical lines: "patent big data + technology convergence + technology clusters" and "PCT patents + RIT index + h-strength index." In details, IPC co-occurrence relationships of all domains are extracted to construct a global technology convergence network map; the core structure of the network map is extracted by using h-strength; and the results are carefully interpreted by combining the algorithmic identification of the network communities with the interpretation of technical experts. A total of 2 mega, 8 large, 30 medium and 34 smaller-sized key technology communities are identified in this study for global and domain-wide.
This research framework aims to provide data support for understanding global technological innovation hotspots and assisting in the formulation of macro-industrial innovation policies. In terms of theoretical innovation, this paper integrates three research topics: innovation measurement, technology convergence, and technology clusters. For instance, in the analysis of IPC co-occurrence network graphs, the paper combines the classification of key technology innovation trends with the analysis of the characteristics of key technology convergence clusters.
According to a new indicator, the relative impact of technology (RIT), its two-dimensional scatter chart and IPC co-occurrence core network, 76 core technology integration communities around the world and in all fields are identified, and their innovation trends are evaluated. The study finds that pharmaceuticals and the transmission of digital information and wireless communication networks are the main driving forces for global technological innovation. Optical elements, systems, and apparatus show strong characteristics on the whole, and semiconductor devices, new energy vehicles and autonomous driving present four different innovation situations, namely strong, emerging, recessionary and sleeping characteristics, which present obvious technological iteration. In addition, technical fields such as medium-scale catalysts, layered products, additive manufacturing, copolymers and copolymerization processes, semipermeable membranes and preparation, and surface liquid coatings also show distinctive characteristics.
In the conclusion section, the paper emphasizes technical interpretations, along with policy recommendations and future research prospects. In subsequent studies, it is suggested to systematically compare China's technological development context with international mainstream trends based on current technology community divisions. This would help clarify China's structural characteristics and directions of innovation, analyze China's technological advantages and disparities, identify potential technological development risks, and propose innovative governance strategies for China's cutting-edge technologies. Moreover, the paper provides policy suggestions for enhancing China's discourse power in global innovation strength evaluation and integrating into the global innovation ecosystem. Overall, this study contributes to a comprehensive understanding of global technology convergence and innovation dynamics, offering valuable insights for policymakers and researchers alike.As for the research deficiencies: on the one hand, h-strength is used to intercept the core network mapping of co-occurring relationships among IPCs, which makes isolated and smaller technologies excluded from the core network; on the other hand, the data sources and analysis indicators of this study are more limited, mainly relying on PCT patents, IPC classification numbers and citation indicators. Future research could incorporate more diverse data sources and analytical indicators, such as tripartite patent datasets, natural language processing models, and non-patent citations.

In the modern era, scientific and technological innovation serves as a crucial driving force for economic and social development. In the digital age, research paradigms are leaping towards data-intensive type, with national strategies placing a greater emphasis on the development and utilization of scientific data resources. However, the vast and complex nature of scientific data presents fundamental differences in value, type, and form; scientific research imposes multifaceted requisites on scientific data utilization, encompassing accuracy, sharing, and security. The extant scientific data governance mechanisms struggle to effectively manage the supply-demand dynamics of scientific data, failing to mitigate the negative externalities of data breaches that threaten national security, public interest, and private rights. Moreover, these frameworks are falling short in leveraging the beneficial externalities that could arise from the open and collaborative use of scientific data, which is crucial for driving national progress, bolstering economic growth, and fostering technological advancement.
This paper aims to enhance the scientific data governance system to balance data security with efficient data flow. It highlights the benefits of a data classification and grading system for managing heterogeneous data, aligning with the complex nature of scientific data. However, current research often overlooks the system's role in data circulation and sharing, focusing instead on security. The paper points out a significant gap in the literature regarding the impact of scientific data centers' classification and grading systems on overall governance. To address this, the paper conducts empirical research on China's national scientific data centers, applying contextual integrity theory and policy analysis to assess how data flow supports freedom, security, and value within specific contexts.
This paper utilizes the publicly accessible texts related to classification and grading from 20 national scientific data centers as research samples, and sets up seven observational points, namely normative categories, resource support, policy synergy, management model, liability allocation, openness degree, and normative value, to evaluate the supply, effectiveness, and value balance of the classification and grading system norms of scientific data centers in China. The breadth and depth of the research perspectives are sufficient to ensure the scientificity and reliability of the research results. The results indicate three cardinal issues within the classification and grading system of national scientific data centers. Firstly, the classification and grading system norms of the 20 national scientific data centers are inadequately formulated and have weak cooperativity among norm groups. Secondly, the positive list management and imbalance of liability allocation diminish incentives for the open sharing of scientific data. Thirdly, the existing classification and grading system overemphasizes data security to the ignorance of circulation, failing to achieve an appropriate equilibrium between security protection and open sharing values.
Drawing on the research findings, this paper offers several recommendations for improvement. It advocates for the augmentation of formal regulations that adhere to the principles of openness, rationality, and non-discrimination, while also reinforcing the harmonization of norms across various governance bodies. Subsequently, the paper suggests transitioning from a positive list to a negative list approach, thereby fostering a more permissive atmosphere for the dissemination of scientific data. Additionally, the establishment of an accountability and incentive framework is proposed to encourage the sharing of scientific data. Furthermore, it calls for the refinement of scientific data classification and grading protocols, integrating considerations of security and sharing value, and accounting for the positive and negative externalities associated with data utilization. Lastly, the paper endorses the application of the Principle of Proportionality, encompassing appropriateness, necessity, and balance, in the valuation and categorization of scientific data.
This paper integrates research findings from the domains of Contextual Integrity theory, data classification and grading system, and scientific data governance. It innovatively introduces the Contextual Integrity theory into the fields of scientific data governance and the classification and grading system, filling the empirical gaps in the scientific data classification and grading system. Moreover, it constructs a novel model for classification and grading system model that balances both openness and sharing, and puts forward new approaches to optimizing scientific data governance. The results of this paper are expected to provide valuable guidance for researchers in their data management activities.

As a new type of production factor, data has become a key driving force for high-quality economic and social development. In order to expedite the establishment of data foundation system and fully release the value of data elements, China's central and local levels have issued relevant policies, proposing to explore the construction of data intellectual property protection systems and registration systems. Before examining the practice pattern of data intellectual property registration system, we must first clarify the connotation of the system to provide theoretical reference for the analysis of registration pilot practice. Data, data sets and data products have different connotations and characteristics. Data property registration, data product registration and data intellectual property registration show some differences in theoretical basis, system structure and protection objects. Moreover, due to the compatibility between data and intellectual property objects, the inclusiveness of intellectual property protection, data judicial cases mainly apply intellectual property rights protection rules, which makes it legitimate to use intellectual property rights to protect data.
By summarizing and comparing the published data IP registration specifications of various provinces and cities,the study concludes that the work has been steadily advancing, but there are still challenges in practice. For example, the definition of registration scope has not been unified, the allocation of rights and responsibilities of registration institutions needs to be refined, and the application scenarios for registration certificates still need to be expanded. First of all, the restrictions on the scope of objects differ greatly among the pilot local rules, as well as the value consideration of whether the data holder can become the registration subject, and how the definition of the scope of the rights content can better fit the objectives of rights protection and transaction circulation. Secondly, the legal compliance review standards of data sources are not clear, and the adoption of formal review or substantive review by each pilot province and city will have a certain impact on the results of subsequent registrations. At the same time, the division of responsibilities and collaborative supervision of various departments have yet to be strengthened. Finally, it is unclear whether the registration of data intellectual property rights is subject to registration effectiveness or registration antagonism at the legal level, and the social level of acceptance of registration certificates is not high, which, in addition to the need to enrich the application scenarios of registration certificates, is also manifested in the lack of access norms for the application of registration certificates and the security guarantee system.
To sum up, in order to solve the difficulties in data intellectual property protection and release the potential value of data elements, this paper makes concerted efforts from the institutional, practical and technical levels: First, from the institutional level, it is clear that the object of the data intellectual property registration system is a data set with commercial value and intellectual achievement attributes that is obtained according to law and processed by certain rules or algorithms, and it is also clear that the data processors who have endowed the data with the attributes of commercial value and intellectual achievement are the subjects of registration, and the data processors are granted limited exclusive rights, Second, from the practical level, it is necessary to strengthen the synergy of the competent authorities and enhance the examination ability of registration agencies by implementing dual audit mechanism and unified registration work service guidelines, and registration agencies can also strengthen business cooperation with investment and financing institutions to help enrich the application scenarios of registration certificates. Third, from the technical level, combine the characteristics of blockchain technology to realize the interconnection among various platforms, and build an intelligent audit system for data intellectual property registration with the help of a blockchain optimization algorithm model, which vigorously enhances the effectiveness of data intellectual property registration and the operation efficiency of data intellectual property trading market, while taking into account data security and transaction convenience.