Abstract:The process of scientific research activities have a progressive, derived feature of complex structure.The scientific research innovation chain-data chain-publishing chain are closely connected and iterative.The evolution of data ecosystem and its model evolution is crucial to promoting scientific research innovation and expanding knowledge dissemination. On the basis of conceptual backtracking, this paper uses the theory of data ecosystem to elaborate the different data-driven logics of scientific research innovation and academic publishing. According to the different data thinking, data institution,data subject relationship, data management structure, data circulation environment and data management methods, the research data ecosystem can be divided into three gradual stages: closed, expanded and collaborative. Summarize the development trend of research data ecosystem from single to ecological, from fragmentation to system, from unilateral to collaborative, from point-to-point to integration, from manual to intelligent. A theoretical model for the evolution of scientific research data ecological model is proposed, and provide a new idea for promoting the overall quality improvement of each element and link of scientific research ecosystem with scientific data ecological governance.
At current, China's water environment management is faced with the problem that pollution sources are difficult to be identified quickly and accurately. Aqueous fingerprint traceability through the measurement of three-dimensional fluorescence spectrum of pollutants, the resulting aqueous fingerprint can be compared with the pollution source database, and therefore quickly and accurately identify the discharge source. This paper takes aqueous fingerprint traceability as a case study, through the field investigation of a water environment laboratory, from the perspective of objectivity to open the “black box” of scientific measurement. The pilot application of the technology is essentially a gradual process of the laboratory constructing the objectivity of scientific measurements. Measurement can be regarded as the production of quantitative values, The laboratory constructed the absolute objectivity, local objectivity and interactive objectivity of aqueous fingerprint traceability at three levels: the selection of measurement methods, the development of measurement standards and the interpretation of measurement results. The technology is widely accepted and recognized, with success in pilot applications.
Strategic emerging industries are critical fields for gaining future competitive advantages, set against the backdrop of trade protectionism and economic globalization, vigorously developing strategic emerging industries is an important way to break the US technology blockade and has a long-term leading role in the overall economic and social development. Patents are the crystallization of knowledge and technology. How to compare the patent influence of China and the United States in strategic emerging industries is increasingly attracting the focused attention of academia and government departments.
How to accurately assess the influence of patents has always been a focal point of interest. Numerous studies use various measures such as market value of the patent, citation count, patent scope, or other composite indicators based on patent citations to gauge patent influence. However, these indicators typically present two issues: first, they neglect the quality of the patent initiating the citation; second, patent citations exhibit a lag effect, and a simple citation count often underestimates the value of recently applied patents.
PageRank is an algorithm widely used for web page recommendation. On the internet, important pages are more likely to be linked by other important pages. Taking advantage of this network characteristic, the PageRank algorithm considers the quality of the patent initiating the citation, assessing the influence of nodes within the network. When the PageRank algorithm is applied to a patent citation network, both theory and empirical statistics confirm its superiority; compared to citation counts, it can more effectively identify high-value patents. Moreover, compared to other traditional social network node analysis methods, the PageRank algorithm places more emphasis on the comprehensive influence of a node on other nodes.
To investigate the patent influence of China and the United States in strategic emerging industries, the study utilizes patent application and citation data provided by Google Patent from 1985 to 2019 to construct an international patent citation network to analyze the influence of China and the United States in the patent network and China's core technology based on PageRank algorithm.
The study shows that, firstly, the patent influence of China's strategic emerging industries is exhibiting a growth trend. As strategic emerging industries rise to national industrial policy, particularly after 2010, the number of related patents in China has surged, and international influence has greatly increased. However, compared to the United States, China's high-quality innovative output is still at a relatively low level. The rise in patent quality is not keeping pace with the increase in patent quantity.
Secondly, the level of innovation in China varies across different industries. In terms of national patent influence, the influence of Chinese patents has rapidly increased in new-generation information technology industries and digital creative industries. In terms of core patents, in recent years, the number of core patents held by China in the new materials industry has surpassed that of the United States, becoming the only field among the nine strategic emerging industries where China exceeds the US. However, from the perspectives of both national patent influence and core patents, the gap between China and the United States is most significant in the biotech industry.
Lastly, in recent years, China's patent influence globally has steadily risen. This is primarily attributed to the decline in patent influence of traditional industrial powerhouses in Europe, rather than a weakening of the US influence in the global technology innovation market. The United States continues to dominate global innovation in the biotech industry and related service industries.
Based on the background of possible science and technology decoupling between China and the United States, this study assesses the patent influence of China's strategic emerging industries from a global perspective, and provides theoretical guidance and decision-making reference for industrial policies.
Scientific and technological talents (S&T talents) are the key driving forces to accelerate innovation and economic development. The mobility of S&T talents can enhance the spread and diffusion of knowledge, improve resource integration, and lead to technological innovation. China faces challenges in terms of S&T talents such as brain drain, low talent mobility and uneven talent distribution. Therefore, eliminating obstacles to talent mobility and improving the mechanisms for talent allocation have become important policy goals for China. Regional integration is an important policy tool under China’s urban agglomeration development strategy, which helps eliminate barriers to talent mobility. Based on large-scale publication data of more than 1 million talents, this study uses panel data of 41 cities in the Yangtze River Delta from 2000 to 2018, applies a staggered difference-in-differences model, and explores the effect of regional integration policy on S&T talent mobility. Specifically, we propose three research questions: (1) did regional integration policy in the Yangtze River Delta influence S&T talent mobility within the region; (2) what heterogeneities exist in the impact of regional integration policy on S&T talent mobility; (3) how the city-level development and living environment influences the effectiveness of regional integration policy. This study finds a significantly positive impact of regional integration policy on S&T talent mobility within cities and across cities. The positive effect is more prominent among talents in hard sciences, and those who moved between non-neighboring cities, as well as those who moved between cities in different provinces. Moreover, a larger promoting effect of regional integration policy is observed for cities with a population of over 5 million people. Additionally, this study suggests that regional integration policy slightly increased the net inflow of S&T talents in the cities with populations of less than 5 million population. Besides, this study demonstrates that the number of high-quality universities, innovation output, the development of a third industry, and the introduction of high-speed rail in cities strengthened the positive effect of regional integration policy on S&T talent mobility. These findings suggest a clear Matthew effect in terms of the promoting effect of regional integration policy on S&T talent mobility. This is because large-sized cities and cities with better development and living environment for S&T talents benefit more from regional integration policy in terms of S&T talent mobility. The findings of this study have multiple policy implications for optimizing talent distribution and improving regional governance efficiency. Small and medium-sized cities, and the cities with less advantageous environments for S&T talents’ development and living, should take a more active role in regional integration development to mitigate the Matthew effect concerning S&T talent mobility. They can leverage their proximity to major cities, and collaborate closely with talent center cities to enhance the spillover effect of regional integration policy on talent mobility. By creating favorable environments for scientific research, economic development, and living, they can promote the effectiveness of the impact of regional integration policy on S&T talent mobility, and ultimately improve the overall competitiveness of talents in the region.
Manufacturing intelligentization is an important driving force for building a powerful manufacturing country and cultivating new industrial competitive advantages. How to optimize the doing environment and promote the intelligent development of manufacturing industry is an important issue that needs to be solved at present. Based on the perspective of configuration, the study adopts the research method of combining NCA and QCA, and takes 30 provinces in China as research samples to explore the diversified driving path of ecosystem of doing business to manufacturing intelligentization. It shows that a single doing business condition is not a necessary condition to produce high manufacturing intelligentization. High manufacturing intelligentization is affected by the "multiple concurrent" of six conditions, namely, government environment, market environment, innovation environment, financial services, public services, and human resources, forming three configuration paths, which can be specifically summarized as the financial and resource-driven path, the market-helping path combining resource-driven ,and innovation environment, the innovation-driven path under government-dominant. By further exploring the spatial situation difference of the research samples, it can be seen that the driving path of manufacturing intelligentization in developed and underdeveloped regions is significantly different. Based on the perspective of configuration，the study systematically explores the driving path of doing business to manufacturing intelligentization, providing decision reference and practical guidance for improving the development of manufacturing intelligentization.
Automation, emerging as a significant force under the new technological paradigm, possesses a transformative effect on the direction of global economics. This powerful tool holds the potential to fuel growth; however, it also bears the prospect of negatively influencing employment rates. Therefore, it is essential, both from a theoretical and practical perspective, to delve into the study of automation's impact on employment in an aging context. To gain a comprehensive understanding of this phenomenon, we have conducted an extensive empirical analysis. Our research incorporates cross-country panel data from a diverse range of 65 countries and regions over the span of two decades, from 1999 to 2019. The results gleaned from this analysis reveal that automation considerably contributes to a decline in employment rates. Subsequently, we examined the automation's influence on employment, considering the moderating role of demographic changes, and further explored the specific mechanisms through which automation affects employment rates. The conclusions drawn from our study reveal that automation exerts a negative impact on employment rates, and that this influence is indeed moderated by demographic shifts. Interestingly, the negative effect of automation on employment rates tends to be eased in nations with high levels of aging, attributing to a reduction in labor market competition. This suggests that the impact of automation is not uniformly negative but can be mitigated under certain demographic conditions. Another notable discovery from our study pertains to the displacement effect of automation. It is evident that one of the significant ways automation adversely impacts employment rates is by displishing manufacturing workers. This displacement effect is especially profound among male workers, who are more likely to be engaged in manufacturing jobs. Turning our focus towards China, we have observed that large-scale automation could serve as a viable solution to address labor shortages amidst the aging process. This is while maintaining a stable employment rate. Consequently, automation may emerge as one of the practical means to tackle the current issue of rapid aging. Therefore, understanding the dynamics of automation and its relationship with employment is critical, not only for its potential to drive growth but also for its capacity to reshape the employment landscape in an aging world. In conclusion, our study deepens the understanding of the intricate relationship between automation and employment and helps policymakers navigate the challenges and opportunities brought about by technological advancements.
The digital transformation of small and medium-sized enterprises is an important part of China's digital construction. Although the existing research has made great breakthroughs in the test of efficiency and performance improvement of SMEs' digital transformation, but neglected the exploration of its transformation antecedents, especially the comprehensive impact of various antecedent factors on the selection of SMEs' digital transformation mode is still unclear. Based on the important characteristics of relatively limited resources and capabilities of SMEs, this study explores what kind of digital transformation mode SMEs will build under different factor endowment combinations from the perspective of matching resources and capabilities. Through the questionnaire survey of 128 small and medium-sized enterprises and the configuration analysis of antecedents with the help of fsQCA method, the research results show that: (1) there is a "multiple concurrent" effect between enterprise resources and dynamic capabilities, and the transformation and development of seven digital models can be realized through different combination paths;(2) further cluster seven types of models and propose three types of digital transformation models for small and medium-sized enterprises. One is the resource-driven auxiliary value chain transformation with strong resource strength and weak dynamic capability. When small and medium-sized enterprises have strong resource strength and their dynamic capabilities cannot further transform resources into competitive advantages, they can choose to rely on existing resources to carry out the digital transformation of corresponding functions. At the same time, the lack of dynamic capabilities is not conducive to the digital transformation of value-added links with strong interaction with the outside. Therefore, small and medium-sized enterprises with such combination of resources and capabilities can choose to support the digital transformation of value chain modules. Second model is the transformation of value-added value chain derived by capacity, which has balanced resource strength and outstanding dynamic capabilities. For enterprises with outstanding dynamic capabilities, even if they do not have relatively outstanding resource strength, they can reorganize their internal and external resources by virtue of their perception, integration and reconstruction capabilities, and carry out more complex digital transformation of value-added value chain links. Especially for enterprises with digital transformation experience, it is easier to use dynamic capabilities for digital transformation of value-added value chain. The third one is the parallel digital transformation option which applicables to small and micro enterprises with small scale and digital transformation just starting. For small and micro enterprises with relatively weak resource strength and dynamic capability, they can try to carry out parallel digital transformation on the auxiliary and value-added value chain with their own flexibility. However, it should be noted that the parallel digital transformation is relatively simple and belongs to the transformation mode of low cost and low complexity. This research enriches the research on antecedents of SMEs' digital transformation, which focuses on the internal resources and capabilities of enterprises, and explores the antecedents of the choice of digital transformation mode of SMEs. Based on the resource-based view and dynamic capability theory, this paper explores the combination of factors that may affect the digital transformation model from the perspective of resource and capability configuration, and provides a reference for SMEs' digital transformation practice.
This paper takes Shanghai and Shenzhen A-share listed during 2010 to 2020 as samples, investigate the internal mechanism and the influence of returnee executives on the digital transformation of enterprises and its mechanism. The results show that: (1) Returnee executives are helpful to promote the digital transformation of enterprises, and this conclusion is still valid after considering endogeneity and various robustness tests; (2) The mechanism shows that the returnee executives mainly promote the digital transformation of enterprises by improving enterprise human capital level, learning and absorption ability and ESG responsibility; (3) Heterogeneity analysis shows that the promotion effect is more significant in SME and enterprises with low financial asset allocation efficiency. The conclusion of this paper not only enriches and expands the upper echelons theory and the related research on the influencing factors of digital transformation of enterprises, but also helps to provide empirical evidence for enterprises to adapt to the trend of digital development and speed up the process of digital transformation of enterprises.
The normalization of VUCA environments puts forward higher requirements for enterprise resilience, digital and intelligent empowerment is an important means to promote the enterprise resilience and push the creations in new?ventures. Based on the data of small?and?medium-sized IC new?ventures in the Yangtze River Delta, this?paper?uses multiple linear regression analysis method to empirically test the influential mechanism of digital intelligence to enterprise resilience on the network of inter-personal-relationship.The results show that:digital intelligence has multi-effect on enterprise resilience in new?ventures, digital intelligence and network embeddedness promote enterprise resilience;among the two dimensions of network embeddedness, local network embeddedness and extra-local network embeddedness all play a partial mediating role;environmental dynamics positively moderates the relationship between network embeddedness and enterprise resilience. The research results not only open the "black box" on the influence of digital intelligence on enterprise resilience, but also provide theoretical guidance and empirical evidence for new?ventures implementing digital intelligence to respond the uncertainty risks.
As the leader of the market segment in the future, SRCN enterprises (Small and medium-sized enterprises with the characteristics of specialization, refinement, characterization and novelty) play an important role in breaking through the key technological bottlenecks and maintaining the stability of the global industrial chain. However, in the highly uncertain market environment, especially in the context of epidemic and anti-globalization, how to smoothly survive the crisis and achieve sustainable development for SRCN enterprises has become the focus of current managers. Based on the resource-based view and the perspective of dynamic capabilities, this paper constructs a chain intermediary model to explore the impact mechanism of entrepreneurial orientation on the performance of SRCN enterprises, and further uses the data of 372 SRCN enterprises for empirical analysis. The research finds that: (1) entrepreneurial orientation has a significant positive impact on the performance of SRCN enterprises; (2) entrepreneurial bricolage and organizational resilience play a synchronous and chain intermediary role between entrepreneurial orientation and the performance of SRCN enterprises. The research conclusion is of great theoretical significance for the success of SRCN enterprises, as well as practical significance for the survival and development of SRCN enterprises under the domestic and international double cycle background.
New product development (NPD) has been an effective mean for firms to survive and develop in the increasingly complex market environments. Therefore, a growing number of firms are striving to enhance their competitive advantages in the product markets by improving the NPD advantages (i.e. speeding up NPD and improving new product creativity). Accordingly, enhancing NPD advantages has become an important strategic activity for firms, and should be considered with their own strategic orientation. As a management philosophy that guides business activities, strategic orientation reflects firms' strategic positioning and is a type of potential resources of firms. In the process of NPD, the impacts of strategic orientation on NPD advantages needs to be realized through specific organizational actions. As the process of knowledge input and output, NPD can be regarded as the result of the integrating knowledge. Through organizational learning, firms can acquire new external knowledge, discover new uses for existing knowledge, or discard obsolete knowledge to update it quickly, thus laying a solid knowledge foundation for improving NPD advantages. However, organizational learning is a complex decision-making and behavioral process, which needs to be analyzed in the context of an organization's overall strategy. Unfortunately, existing research lacks in-depth discussion on the role of different strategic orientations on enhancing NPD advantages, how strategic orientations influence the choice or implementation of specific learning behaviors, and how different strategic orientations promote NPD advantages.
To fill the research gaps mentioned above, this study subdivides firms’ strategic orientations into two types (i.e. market orientation and technology orientation) from the perspective of the reality of "market pull" and "technology push" faced by firms in the process of NPD, as well as existing related research. Based on this, the differentiated roles of these two strategic orientations in improving firms’ NPD advantages are discussed and their relative effects on firm’s NPD advantages are investigated based on resources-based view. To reveal the mechanisms by which strategic orientations affect firm’s NPD advantages, this study introduces organizational learning theory to explore the mediating role of knowledge integration and organizational unlearning on the above relationships. Empirical data from 254 Chinese manufacture firms reveal that both market orientation and technology orientation can effectively enhance firm’s NPD advantages (i.e. NPD speed, NPD innovativeness), and the effect of market orientation on the speed of NPD is stronger than that of technology orientation, while the effect of technology orientation on new product innovation is stronger than market orientation. Both market orientation and technology orientation have positive effects on two different organizational learning behaviors (i.e. knowledge integration, organizational unlearning), but market orientation has a stronger effect on knowledge integration than technology orientation, and technology orientation has a stronger effect on organizational unlearning than market orientation. Two different learning behaviors play different roles in enhancing the advantages of NPD. Specifically, knowledge integration has a stronger effect on the speed of NPD than organizational unlearning, while organizational unlearning has a stronger effect on new product innovation than knowledge integration. Furthermore, this study also found that market orientation affects the speed of NPD through knowledge integration, while technology orientation affects new product innovation through organizational forgetting.
The contributions of this study reflected in the following three aspects. First, by revealing the comparative impacts of market orientation and technology orientation on firms’ NPD advantages, this study broadens the understanding of the complex relationship between strategic orientation and NPD advantages. Second, this study subdivides organizational learning behaviors into two types (i.e. knowledge integration, organizational unlearning), and investigates their differential impacts on NPD speed and creativity, which not only deepens the understanding that different learning behaviors bring heterogeneous NPD advantages to firms, but also breaks through the limitations of the existing studies that mainly split organizational learning from the perspective of knowledge intake, and provides a promising avenue for further study on organizational learning. Third, this study reveals that there are different paths of choice between strategic orientations and NPD advantages, which helps to deepen the understanding of how strategic orientations impact firm’s innovation performance from a new perspective.
The development power of China's economy in the new era has gradually shifted to be driven by science and technology innovation, which has become the main engine of China's economic and social development. At present, the pilot policy has become a superior public policymaking mechanism with Chinese characteristics, and science and technology innovation pilots have played a leading role in deepening the reform of China's science and technology system.
In the process of improving the theory from "growth pole" to "innovation pole", "innovation growth pole" has become a development direction in line with China's reality. In order to realize science and technology innovation-driven development, China has deployed a series of pilot policies in the field of science and technology. However, there is still a lack of systematic analysis on the effectiveness of the implementation of pilot policies on science and technology innovation, and whether the pilots can become innovation growth poles. The study defines the concept and connotation of "innovation growth poles", builds a theoretical framework by combining the political operation logic of STI pilots. Identify and select representative pilot policies on science, technology and innovation, and evaluate and analyze 15 typical pilot policies based on panel data of 274 cities from 2003 to 2020.
The study finds that Science, technology and innovation pilot can promote the agglomeration of funds in innovation resources, compared with the systematic assessment, the evaluation of the agglomeration effect of a single pilot policy will exist about 7%-19% overestimation; science and technology innovation pilot can produce significant economic effects in the pilot area, the net effect of a single policy evaluation will still appear about 8%-26% overestimation, while the enhancement of the innovation capacity is the pilot to promote the economic and social development of the region's key path; science and technology innovation pilot has a significant spatial spillover effect, can radiate and drive the economic and social development of neighboring areas. At the same time, the improvement of innovation capacity is the key path for the pilot to promote the economic and social development of the region; the science and technology innovation pilot has a significant spatial spillover effect, which can radiate and drive the economic and social development of neighboring regions. Pilot STI projects implemented in China can become innovation growth poles, and both theoretical and empirical analyses support this view. Pilot S&T innovation projects become innovation growth poles by strengthening their comprehensive advantages through the development mechanism of "gathering innovation resources - innovation-driven economic development - radiation-driven development of neighboring regions".
Based on the findings of the study, this paper proposes the idea of science and technology innovation pilots becoming an innovation growth pole, aiming to provide policy insights for improving the policy of science and technology innovation pilots, accelerating the realization of high-level scientific and technological self-reliance, and realizing Chinese-style modernization.
Catch-up innovation policy is a type of task-oriented innovation policy, which provides a new policy scheme for improving enterprises' technological capability. However, the existing research has not given sufficient theoretical explanation on how catch-up innovation policy affects enterprises' technological capability. Based on the theory of industrial innovation system and China's policy practice, this paper constructs an analytical framework for the transmission path of catch-up innovation policy, and carries out an empirical test . The results show that :(1) the catch-up oriented innovation policy can promote the industry chain related enterprises, innovation chain related institutions, and service chain related institutions to form an incentive and compatible actor network around the focus enterprises and promotes the improvement of enterprise’s technological capability. （2）The innovation participation of service chain related institutions is the core node of the influence transmission path of catch-up oriented innovation policy and can play a role in connecting the government and the market.（3）Innovation participation of innovation chain related institutions and the industry chain related enterprise are effective paths for the transmission of catch-up oriented innovation policy, their synergistic coupling relation can significantly improve the R&D investment behavior of enterprises.（4）Innovation expectation and R&D investment are the decisive factors for the improvement of enterprise’s technological capability, and also is firm internal path of the transmission of catch-up innovation policy.
The U.S. has long employed technology export controls to hinder the progress and competitive edge of Chinese high-tech enterprises. In recent years, the U.S. has intensified these efforts through the use of Entity List Sanctions, a highly precise and targeted export control mechanism. Between 2018 and March 2023, it imposed 24 Entity List Sanctions on Chinese entities, impacting over 680 Chinese high-tech companies and entities operating in the computer, communications, defense and military, aerospace and aviation industries. By employing this technology blockade, the U.S. aims to impede the progress of independent innovation within Chinese high-tech enterprises. As a result, the impact of U.S. Entity List Sanctions has garnered significant attention and discussion within Chinese academia and industry. However, existing research on these sanctions is primarily theoretical, lacking sufficient empirical findings based on large samples. Moreover, the results from theoretical studies and infrequent empirical analyses often diverge. Therefore, a comprehensive analysis is necessary to examine how U.S. Entity List Sanctions affect Chinese enterprises’ independent innovation, considering both theoretical and empirical perspectives. To address this research gap, our study analyzes the short- and long-term effects of U.S. Entity List Sanctions on Chinese companies’ independent innovation. We also explore the boundary conditions of these effects, examining risk perception, diversification, and resource constraints. Our research primarily focuses on A-share computer and communication industry listed companies from 2013 to 2021. The findings of our study indicate that U.S. Entity List Sanctions have a negative impact on Chinese firms’ independent innovation, primarily driven by short-term effects that diminish over time. Furthermore, our analysis reveals that firms exhibiting positive risk perception, high diversification, and ample resources are better equipped to resist and overcome the constraints imposed by U.S. Entity List Sanctions on their innovation efforts. This study offers practical contributions in several areas. Firstly, it highlights the importance of Chinese confidence in overcoming the challenges posed by U.S. Entity List Sanctions. Secondly, it emphasizes the significance of a positive mindset among Chinese enterprises when approaching these sanctions, encouraging a rational assessment of associated risks while fostering enthusiasm and initiative for team-based innovation. Thirdly, the study advocates for proactive exploration of diversified business models by Chinese companies, facilitating cross-field, cross-business, and cross-product transformations to drive technological evolution and continuous innovation. Lastly, it underscores the need for increased government support for corporate innovation and the alleviation of resource constraints faced by enterprises.
“SRDI” small and medium-sized enterprises (S-SMEs) are an important vehicle for implementing innovation-driven strategies. In view of the lack of research on the micro-level of S-SMEs' innovation performance in academic circles, this paper examines the significant key factors and configuration effect that influence S-SMEs' innovation performance from the perspective of complex causal effect analysis, mixing NCA, empirical regression and QCA methods, and refines the corresponding improvement paths. It is found that (1) R&D capability, financing environment and market competitiveness significantly affect the innovation performance of S-SMEs; (2) there are five configuration paths that enhance the innovation performance of different types of S-SMEs; (3) when financing is blocked, either small-scale production or improving their own market competitiveness can enable S-SMEs to maintain a high level of innovation performance target. This paper attempts a new way of thinking of complex causal effect analysis, which provides some theoretical and practical references for the study of S-SMEs' innovation performance in the future.
In the national strategic scientific and technological forces, China's leading technology enterprises and high-level research universities play a leading role in promoting the high-quality development of China's innovation industry, helping to drive more universities and enterprises to innovate and ultimately bring about overall scientific and technological progress in China. It is necessary to study the coupling and coordination of innovation in strategic scientific and technological forces between universities and enterprises, in order to take targeted measures to improve the innovation indicators of high-level research universities and technology leading enterprises, promote innovation cooperation and coordinated development between the two, and enable them to jointly shoulder the innovation mission of national strategic scientific and technological forces. This is of great significance for improving the international competitiveness of China's innovation industry and enhancing the effectiveness of the national innovation system. Using the data of key universities and large and medium-sized high-tech enterprises, the comprehensive measurement index system of scientific and technological innovation level of China's high-level research universities and science and technology leading enterprises is constructed respectively, and the principal component analysis method is used to measure the comprehensive innovation level scores of the two. Then, the macro-level coupling and coordination relationship of the binary system is analyzed by using the coupling and coordination degree model. And further use the grey correlation method to examine the mutual influence between the innovation indicators of key universities and the innovation indicators of leading enterprises in science and technology in detail at the micro index level, namely the impact of various innovation indicators of key universities on the innovation level of technology leading enterprises, as well as the impact of various indicators of the innovation system of technology leading enterprises on the innovation level of high-level research universities, so as to reveal the micro coupling mechanism of the two systems at the index level. The findings of the study are as follows: first, the comprehensive innovation level of China's leading science and technology enterprises and high-level research universities is continuously improving. Second, the two innovation systems of China's leading science and technology enterprises and high-level research universities have gradually transitioned from low-level equilibrium to high-level equilibrium, from extremely uncoordinated to highly coordinated. Third, among the indicators that universities affect enterprises, the impact of scientific research projects, R&D achievements and scientific and technological services is mostly higher; Scientific and technological manpower has less impact than scientific and technological investment. Fourth, among the indicators that enterprises influence universities, foreign trade export has the greatest impact, and technology import has the smallest impact; Human factors and enterprise scale have a greater impact than capital factors. Suggestions: All sectors of society should take measures to promote innovative cooperation between strategic scientific and technological forces of universities and enterprises, and increase the investment in research and development funds of high-level research universities. Science and technology leading enterprises should strengthen cooperation with high-level research universities in scientific research projects, promote the transformation and implementation of scientific research achievements, appropriately expand the size of their own personnel and institutions, and increase foreign trade exports. High-level research universities need to adhere to the strategy of independent innovation.
