To smooth the channels for the commercialization of scientific and technological achievements and convert these achievements into real productive forces, the effective support of fiscal policies is required. The commercialization of scientific and technological achievements is characterized by large capital requirements, long commercialization cycles, complex property rights relations, and high commercialization risks. Market entities such as enterprises often find it difficult to independently bear the huge capital investment and risks involved in the commercialization of scientific and technological achievements, which results in certain constraints on the commercialization of these achievements under the market mechanism. This requires the government to formulate specific fiscal and scientific and technological policies and establish a service platform that connects the supply and demand of technological elements for the transformation of scientific and technological achievements. It should be noted that the effectiveness of fiscal and technological policies is not solely achieved by increasing financial investments. It also requires a systematic examination of the complex characteristics exhibited during the specific implementation of these policies, so that flexible policy formulation and implementation can effectively promote the commercialization of scientific and technological achievements.

From the perspective of policy implementation, this paper explores the implementation characteristics of policies from the aspects of implementation intensity, policy orientation, and policy stability, and further constructs a theoretical framework for analyzing the impact of fiscal science and technology policy implementation characteristics on the commercialization of scientific and technological achievements. Moreover, it constructs a panel data sample covering 174 Chinese cities from 2017 to 2021, and empirically examines the effect of implementation characteristics of fiscal science and technology policies.

The research indicates that the government's strengthening of the implementation intensity of fiscal science and technology policies is conducive to promoting the commercialization of scientific and technological achievements. When the policy is highly targeted and the commercialization of scientific and technological achievements is taken as the goal of policy implementation, it helps promote the construction of services and realize the agglomeration of innovation resources, thus effectively promoting the commercialization of scientific and technological achievements. When the policy is relatively stable and provides a continuous and stable policy environment for market entities, it helps to enhance the expectations of market entities, and then promotes the commercialization of regional scientific and technological achievements more effectively.

The analysis of the effects based on different market conditions shows that when a region has a relatively strong foundation for scientific and technological innovation, strengthening the implementation of fiscal science and technology policies can promote the commercialization of scientific and technological achievements more significantly. When the regional technology market is more active and there is a sufficient demand for technological innovation and commercialization, the promoting effect of the implementation intensity of fiscal science and technology policies on the commercialization of scientific and technological achievements will be more evident.

The research can provide theoretical support for an in-depth understanding of the implementation characteristics of fiscal science and technology policies and their effect on the commercialization of scientific and technological achievements. Meanwhile, the research conclusions can provide important insights for the government to flexibly utilize fiscal science and technology policy tools and adjust the implementation approach based on policy objectives, thereby enhancing policy effectiveness.

The disconnection between innovation chains and industrial chains has internally led to the long-term existence of the "two worlds paradox" between science and industry, and externally, it has exacerbated the economic and political risks associated with supply chain disruptions and the recurring issue of being hindered by key core technologies. Accelerating the integration of the two chains is urgent. Technology standards not only support industrial collaboration but also play a leading role in technological cooperation. Developing and promoting fundamental, universal, and advanced technical standards around key links and critical areas provides a viable and practical approach to achieving double-chain-integration. However, existing research has paid little attention to the driving role of technical standards. Based on its linkage role of technology standards in the integration, we dedicate to elucidating the theoretical logic and mechanisms through which technology standards drive the integration of innovation chains and industrial chains. We aim to answer the following questions. First, why can technology standards drive the integration between the innovation chain and the industrial chain? What are the rational logic and internal mechanisms? Second, how can technology standards drive the integration between the innovation chain and the industrial chain? What are the process and implementation pathways?

This article first takes the connotation and extension of technical standards and double-chain-integration as the premise, and extracts the process mechanism of technology-oriented standard diffusion, demand-driven standard development and two-way synergistic standard bridging. We then analyze the functional realization of dual-chain-integration driven by technology standards from the dimensions of participants, innovation elements and operation space. Finally, we construct multidimensional implementation pathways and operational mechanisms for the integration of both chains driven by technical standards through patent pool formation, strategic knowledge disclosure, and the development of derivative technologies. Based on the strategic needs of China's innovation development and local practical experience, the study reveals the internal law, operation mechanism and realization mode of technology standard-driven integration between the innovation chain and the industrial chain, thus providing a new direction for China to realize scientific and technological self-reliance at a high level.

The theoretical and practical contributions of this article are as follows. First, we construct a theoretical model of the double-chain-integration driven by technology standards, and probes into its integration process and mechanism, which helps to form a theoretical innovation on the double-chain-integration. Second, this article innovatively introduces technology standards into the analytical framework of the double-chain-integration, thus helping to expand the theoretical boundaries of technology standardization. The conclusions do not only help to deepen the rational understanding of the double-chain-integration driven by technology standards, but also offer new analytical ideas, diversified decision-making tools and alternative policy insights for the management practices of enterprises and governments.

This study employs hypergraph modeling to examine how research content novelty and team background diversity influence scientific impact and research disruptiveness in projects funded by the Management Science Department of China's National Natural Science Foundation (NSFC). We focus specifically on youth funding projects to understand how these key dimensions of scientific research affect knowledge production and paradigm shifts in different career stages. Through constructing two distinct types of hypergraphs - content hypergraphs reflecting research content novelty and team context hypergraphs capturing team background diversity - we analyze 8,100 English publications by NSFC-funded researchers from 2008 to 2023, including 2,812 Young Scientists, 44 Outstanding Young Scientists, and 55 Distinguished Young Scientists. The content hypergraphs are built based on the Web of Science categories of each paper, while team context hypergraphs are constructed using the historical publication records (203,191 papers in total) of team members, allowing us to comprehensively capture both the novelty of knowledge combinations and the diversity of team academic backgrounds. Our analysis reveals complex relationships between these dimensions and research outcomes. Research content novelty shows a significant positive correlation with citation counts but, surprisingly, demonstrates a generally negative relationship with disruptiveness indices. This finding challenges conventional assumptions about novel research and breakthrough innovations, suggesting that while novel knowledge combinations may attract scholarly attention, they don't necessarily lead to paradigm-shifting discoveries. Team background diversity exhibits non-linear relationships with both citation impact and disruptiveness. The analysis indicates that moderate levels of knowledge diversity among team members may be optimal for producing both high-impact and disruptive research outcomes. This "sweet spot" in team composition suggests that while diversity brings fresh perspectives and innovative approaches, some degree of common knowledge foundation remains essential for effective collaboration and knowledge integration. Examining these relationships across different career stages reveals distinct patterns of innovation. Young Scientists tend to produce more disruptive findings despite receiving fewer citations, suggesting a greater propensity to challenge existing paradigms. In contrast, Distinguished Young Scientists generate research with higher content novelty and team diversity, resulting in more citations. This pattern demonstrates the complementary roles that researchers at different career stages play in scientific advancement. The distribution analysis of our indicators shows that while most research concentrates in low-novelty regions, there exists a significant peak in high-novelty areas, reflecting researchers' strategic choices between incremental advances and radical innovation. Team background diversity shows a right-skewed distribution, indicating that while most research teams maintain relatively homogeneous backgrounds, there is a growing trend toward more diverse team compositions, particularly among senior researchers. These findings have important implications for science funding policies and talent development strategies. First, evaluation criteria should be redesigned to better support potentially disruptive research, particularly from early-career scientists, whose innovative contributions might be undervalued by traditional metrics. Second, differentiated support mechanisms should be developed for researchers at various career stages, recognizing their distinct approaches to innovation. Third, funding programs should actively promote interdisciplinary collaboration while maintaining domain expertise. Our results suggest that current evaluation metrics focusing primarily on citation counts might systematically undervalue young researchers' contributions to scientific disruption. This indicates a need to develop more sophisticated assessment systems that can capture different dimensions of scientific impact. These insights contribute to our understanding of how research novelty and team diversity influence scientific outcomes in China's research funding system, offering practical guidance for optimizing funding mechanisms to foster both steady knowledge advancement and breakthrough discoveries.

As the main body of China's national scientific and technological innovation institutions, universities play a vital role in the national innovation system. China’s university should be based on the forefront of scientific research and adapt to the new paradigm of scientific research characterized by data intensive computing; effectively manage scientific data from the perspective of data assets, ensuring that scientific data meets current and future research needs, and maximizing the value of institutional data assets. The United Kingdom is one of the earliest countries in the world to put forward the concept of "data as assets". As a problem-oriented scientific data management tool, the UK’s university Data Audit Framework has important reference value for China's university scientific data management.

This paper introduces the background of the Data Audit Framework (DAF) project in UK universities, and analyzes the scope, content, procedures and methods of the implementation of the framework, as well as the main practices in Warwick University, Bath University, and Emory University. On this basis, this paper summarizes the applicability characteristics of DAF. The first is overall planning, which set up a data management committee composed of university managers and senior professors, formulate a unified data audit plan, rationally define the scope of audit, and coordinate the audit schedule. The second is classification and grading, according to the value and importance of data, important, secondary and unimportant data assets are divided to provide a basis for the adoption of targeted resource allocation and management strategies. The third is problem-orientation; the purpose of DAF is to assist institutions to assess the risk areas faced by the current environment, and to raise the awareness of managers and researchers on the best practices of scientific data management. The fourth is continuous improving. DAF designs two main lines of identifying problems and solving problems. As a closed loop, its ultimate goal is to solve problems and serve the self-improvement process of scientific data management.

This paper also discusses the enlightenment of DAF to the management of data assets in China. First, establish the awareness of data assets and optimize the audit environment. Universities should strengthen top-level design, regard data asset audit as an important scientific data management tool, and promote the excellent management of data assets while carrying out excellent research. Second, make sound management systems and improve audit basis. Universities should clearly define data assets management objectives, management methods and codes of conduct to ensure that data assets audit has good grounds. Third, promote standardized management and conduct management audit. The audit of data assets in universities should be positioned as management audit, focusing on three aspects. (1) The status of establishment and maintenance of data assets catalogue, understanding the scientific research resource base of the university. (2) The status of classification management of data assets, evaluating the value of scientific research resources of the university. (3) The status of utilization of data assets, grasping the contribution of scientific research resources of the university. Fourth, strengthen professional training and consolidate audit conditions. Universities should strengthen the training of researchers and auditors, popularize and improve data literacy to adapt to the arrival of data intensive research paradigms.