In recent years, the breakthrough development of artificial intelligence technology has brought a lot of convenience to human society, but at the same time, it has also brought risks and challenges that can not be underestimated. Therefore, a series of related research on the ethical governance of artificial intelligence have emerged. At present, the main governance strategies include the construction of ethical governance model and the advocacy of ethical service concept. This paper attempts to propose a third strategy as a parallel scheme, that is, to carry out ethical governance in artificial intelligence based on experimental methodology. The importance of carrying out ethical governance in artificial intelligence by experimental method lies in its ability to effectively improve the efficiency of identifying ethical risks, evaluating ethical governance framework and resolving ethical governance conflicts. Experimental approaches to ethical governance in artificial intelligence include computational experiments and social experiments. The former aims to simulate and test scenes with computer simulation technology, while the latter aims to study problems in real scenes through social investigation, social interview and other methods. These two experimental methods have their own implementation process and application scenarios, but there are also difficulties and problems in the actual development process. In general, carrying out ethical governance in artificial intelligence with experimental methods and exploring the risk impact mechanism through pre-designed controllable experiments are conducive to fundamentally improving the effectiveness of ethical governance in artificial intelligence and providing solutions for narrowing the gap from what it is to how to do in ethical governance in artificial intelligence.
Greek science is considered to be the origin of modern science because of its rational and liberal structural features. Greek science mainly adopted a theoretical-formal rational way of thinking, existed purely for its own sake, lacked utilitarian and practical purposes, was poorly institutionalized, and was highly competitive. From the perspective of Politics of Science, city-state politics was a key factor in shaping the structural characteristics of Greek science. On the one hand, civic participation shaped the rational character of Greek science. At the heart of the political process of citizen engagement is persuasion, and the Greek science it nourished is also adept at debate. Considering that pure political debate and persuasion are not powerful enough, Greek science used the method of proof and reasoning to obtain unquestionable, which is conducive to the emergence and development of theory-formal rationality to a large extent. On the other hand, political liberty shaped the liberal character of Greek science. The equality of all citizens in political rights (isonomia) ensured the non-utilitarian nature of Greek science; The freedom of speech (isegoria) of citizens to speak about public affairs made Greek science highly competitive; The ideological power of the city-state was separated from the political power, so that Greek science was less institutionalized.
Science and technology security is an important part of China's national security system, and science and technology elements play a key role in supporting and ensuring national security. From the perspective of national security, this paper analyzes the evolution and connotation characteristics of the concept of science and technology security, analyzes and puts forward the judgment criteria and internal logic of science and technology security issues, and uses the case of " Neck Sticking" problem to prove it. On this basis, this paper uses the method of system element analysis to study and construct the science and technology security system in the New Era. The results show that the science and technology security system consists of four main components, including the subsystem of science and technology security components, the subsystem of science and technology security output, the subsystem of science and technology security environment and the subsystem of science and technology security governance, which together constitute the national science and technology security system.
Provincial laboratories are an important platform for gathering all kinds of innovative resources and building national strategic S&T forces under the new national system. In the process of promoting the construction of provincial laboratories, it is crucial to create an excellent ecology of S&T talents. Taking Zhejiang Laboratory as a case, using literature research method to sort out the background and history of the construction of provincial laboratories, analyzing the process of constructing the ecology of scientific and technological talents in provincial laboratories, proposing five ecological factors such as scientific research facilities, project funding, talent team, organizational culture, institutional mechanism, etc., combining with the field observation of the case site and the interview data to analyze the mechanism of ecological factors on the gathering of S&T talents in the provincial laboratory, and providing empirical support for the high-quality development of the provincial laboratories in China.
As an important production space for the knowledge economy and an instrument of science and technology policy, there has been a lack of understanding of the processes and mechanisms behind the changes that have taken place in the strategic planning of technology parks. By introducing the theoretical perspective of discourse coalition and based on a case study, this paper explains the process of changing the strategic planning of PA Aviation Science and Technology Park and reveals the discourse mechanism behind it. This paper has found that strategic plans for technology parks are not instantaneous, as has been generally presupposed by existing research; rather, they are in a complex and dynamic changing, and are subject to mutual negotiation, gaming, and contestation by different actors in the discourse coalition. This paper also reveals the decisive role of intergovernmental relations in framing the discourse and the complementary role of multiple innovative actors in enriching the discursive elements, thus explaining the mechanisms of different actors in advancing the institutionalization of strategic narratives. Lastly, this paper also provides new insights into research on technology parks and the reality of policy practice.
Local governments are an important force in the scientific and technological achievements transformation. Consequently, investigating the intricate interplay between government policy combination and the efficacy of scientific and technological achievements transformation holds paramount significance in the broader context of a national innovation-driven development strategy. This paper centers on an analysis of 881 policy documents pertaining to the advancement of scientific and technological transformation. These documents were issued by 31 provinces, municipalities, and autonomous regions, spanning from the inception of 2016 to the culmination of 2018. The study operationalizes a bimodal network, integrating the dimensions of policy diversity and universality through network calculations. Subsequently, the iterative computation of the policy combination complexity index is conducted to quantify the multifaceted policy intricacies across Chinese local governments. This complexity index is then utilized as a pivotal explanatory variable to scrutinize the comprehensive alignment between diverse regional policy strategies and technological outcomes.
Key findings of the research are as follows: The intricacy of policy combinations exhibits regional variances throughout China. By classifying regions based on the specificity of their policies' diversity and universality, four distinct archetypes emerge: "risk-averse" governments, "follower" governments, "risk-accepting" governments, and "innovative" governments. Intriguingly, there exists a general inverse relationship between the pervasiveness of local government policies and the level of their diversity; in essence, policies of heightened complexity are less ubiquitously employed. This suggests that an excessive complexity of policy combinations may not inherently translate into superior transformational outcomes. Instead, optimal transformational effects tend to manifest within regions boasting a judiciously moderate policy complexity.
A curvilinear relationship, depicted by an inverted U-shape, emerges between the complexity index of policy combinations and scientific and technological achievements transformation. The rationale underscores that heightened policy complexity engenders stricter innovation conditions, thereby accentuating the reliance on regional resource endowments. Should the innovation ecosystem fall short in accommodating the requisites of an intricate policy array, the resultant transformational effects of scientific and technological breakthroughs stand to be attenuated. Thus, while a synergistic relationship between policy combinations and transformative outcomes is observable within a certain range, surpassing a specific threshold precipitates a diminishing trend in the synergistic impact of policy combinations, subsequently leading to a decline in transformative outcomes.
The diversity of local government policies exhibits a distinctly affirmative influence on the scientific and technological achievements transformation. within a given region. Counterintuitively, the universality of policies exerts an opposing, negative influence on the transformation of such achievements. One might infer that heightened policy diversity emanates from local governments strategically harmonizing policies with their indigenous innovation landscapes. This strategic alignment not only amplifies policy implementation but also augments transformative outcomes. Conversely, policy universality gauges the frequency at which policies fostering scientific and technological advancements are invoked by local governments. A lower universality signifies novel policies that evade widespread application, consequently enhancing the transformative outcomes of scientific and technological endeavors. Moreover, the study's robustness is fortified through rigorous verification involving the substitution of explanatory variables and variations in the temporal dimension.
Drawing upon these research conclusions, local governments are advised to bolster their administrative networks, fortify channels of information dissemination, craft innovative policies attuned to their unique circumstances, utilize policy networks to identify novel and impactful policies, foster policy diversity, and ensure that the policy complexity index is upheld at an optimal equilibrium.
Market failure arises in the Integrated Circuits (IC) industry due to high technical barriers and high R&D risk characteristics, providing the theoretical basis for government intervention in the industry. Due to the existence of market failure, however, the effectiveness of policy intervention may not be guaranteed. The National Integrated Circuit Industry Investment Fund (so-called “Big Fund”) established by the China State Council in 2014, allocating fiscal resources in a market-oriented approach, is a policy innovation that aims to target the market failure and government failure in the Chinese IC industry development, which marks the government’s direct intervention in the IC industry in achieving industrial goals. Ten years since its establishment, though a leap-forward has been witnessed in China's IC industry, nevertheless key industrial goals were not achieved and the Big Fund, at the end of the day, rendered the rent-seeking vehicle. Here we deploy the framework of the duality between government interventions and market mechanisms to conduct a systematic analysis on the Big Fund’s duality nature as a policy tool by design and the impacts of such mechanism. We then scrutinized the implementation-level factors that inevitably deviate the Big Fund from its policy design, with policy suggestions being put forward accordingly. Optimizing the Big Fund to leverage the advantages of government intervention and market mechanisms while effectively curbing government and market failures is suggested to be the key to promoting Chinese Integrated Circuit Industry development.
In recent years, with the rapid iteration of underlying chips and the rapid development of general technologies, the overall technical architecture of artificial intelligence has gradually become clear, becoming the core driving force for a new round of technological revolution and industrial transformation. National laboratories, technology leading enterprises, research universities, and other types of R & D institutions are the core contributors to AI research and innovation. What role do these organizations play in AI research and development? What are the existing R&D models? How can we achieve catch-up and surpass through R&D system layout? These critical issues urgently need to be addressed, and this paper attempts to conduct systematic research on this from a theoretical level.
Existing research on R&D models focuses on three aspects: first, exploring suitable R&D models for key core technologies/high-tech breakthroughs from the perspective of technical breakthrough; second, analyzing latecomer enterprises' R&D models from the perspective of technological catch-up; third, identifying multinational organizations' R&D models from the perspective of international R&D. However, there are still certain theoretical gaps in these studies: On the one hand, most related studies focus on enterprise R&D organizations or industrial-academic-research cooperation, and have not yet conducted systematic mode analysis on different types of R&D organizations such as national strategic scientific and technological forces, leading to insufficient discussions and applicability of their R&D roles. On the other hand, these R&D models are mostly aimed at traditional technology fields and have limited guiding significance for emerging technologies such as artificial intelligence.
The breakthrough of artificial intelligence technology urgently requires the exploration of new research and development models. This article constructs a theoretical analysis framework for the artificial intelligence research and development model from two dimensions: organizational structure and strategic orientation. Using the multi-case comparative method, this article finds that AI R&D organizations focus on different links of the innovation chain, and have different focuses on theoretical originality, key core technology research, open ecological construction, and industry frontier exploration, forming four types of R&D roles: "innovation explorer", "technology breakthrough leader", "ecological enabler", and "industry leader". Through the analysis of R&D organization’s portraits, research showed that there are differences in the roles of different R&D organizations.
The conclusion provides a theoretical basis and practical basis for China to comprehensively promote the layout of artificial intelligence research and development systems at the level of national innovation system, and achieve high-level technological self-reliance and self-improvement through cohesion. Specifically, the diversified R&D model of artificial intelligence demonstrates that not only do various innovative subjects need to carry out in-depth research based on their own advantages and characteristics, but also different R&D models require mutual coordination, thus connecting the innovation chain and industrial chain of artificial intelligence, achieving a comprehensive layout from theoretical originality, key core technology research, open ecological construction, and industry frontier exploration.
Complex products of offshore equipment are characterized by high market competition and strong periodicity. However, there is still a lack of in-depth analysis on how high-end deep-sea drilling equipment enterprises achieve rapid breakthroughs in key core technologies. This paper analyzes the dynamic evolution process of CIMC offshore drilling platform from late enter to rapid innovation leader from 2008 to 2023. (1) In the stage of strategic merger and acquisition, through technology merger and acquisition, the "structuring" and "competence" of resources are achieved, and the "response speed" of market information is built, and the rapid breakthrough of functional technology is achieved. (2) In the strategic focus stage, through the "integration" of internal and external resources and the "transformation" of the system, improve the "transformation speed" of platform knowledge and achieve a rapid breakthrough in performance technology; (3) In the strategy spillover stage, CIMC utilizes the international market through "leveraging" and "localization" to drive the overall upgrading of domestic offshore industry and improve the "pooling speed" of industrial knowledge. This paper summarizes the important role of resource orchestration in the process of realizing the rapid breakthrough of key core technologies. This paper proposes a theoretical model for accelerating breakthroughs in key core technologies of enterprise resource orchestration for complex product systems, expands the theoretical studies in two fields of resource choreography and absorption rate, and provides useful enlightenment for the policy-making and enterprise practice for accelerating breakthroughs in key core technologies in complex product systems in our country.
The rapid development of digital technology has blurring industry boundaries, and the boundary-spanning innovation has become a common innovation mode for the rapid development of new ventures under circumstances of industrial transformation. The automotive industry is undergoing the intersection of the digital economy and the energy revolution. The knowledge system required by automobile enterprises has far exceeded the boundaries of the mechanical engineering disciplines, showing the characteristics of deep cross-integration between vehicles and knowledges from various other fields such as energy, computers, big data and so on. The mainly advantage of boundary-spanning innovation is rooted in the effective connection of cross-domain heterogeneous knowledge and capabilities of team members to generate new value based on a specific combination. Therefore, it is necessary to explore the characteristics of team combination in the context of boundary-spanning innovation. Scholars have explored the impact of single feature factors such as demographic characteristics, skills and experience, and cognitive diversity on team performance, while lack of holism and set theory perspectives to explore the interaction between numerous features and multiple concurrent causal relationships. Based on the imprinting theory, this paper adopts the research method of fsQCA, and takes 40 emerging automakers in China as research samples to explore the multiple concurrency causality and multiple realization paths that affect the entrepreneurial performance, and answer the question of what types of combinations of entrepreneurial team characteristics will enable firms to achieve high levels of entrepreneurial performance in new energy vehicle industry. The results show that the characteristics of a single entrepreneurial team of emerging automakers do not constitute a necessary condition for high entrepreneurial performance. There are three types of entrepreneurial team characteristics that can produce high entrepreneurial performance, namely heterogeneous team supported by the "automotive + finance" industry imprint, "strong heterogeneous-weak compound" team supported by the "automotive + ICT + finance" industry imprint, and composite team supported by the "automotive + service + finance" industry imprint. These three types of configuration of the anthems are different, but can make the emerging automakers produce high entrepreneurial performance, reflecting the high entrepreneurial performance of multiple ways to achieve. What is noteworthy is that, the automotive industry experience and financial industry experience appear as the core conditions in the three configurations. This paper also finds that three entrepreneurial team configurations lead to non-high entrepreneurial performance, all of which are caused by lack of high functional background heterogeneity and high experience in automotive manufacturing and business services industries. Based on the above research conclusions, this paper mainly proposes two suggestions. First, enterprises should consciously make adaptive adjustments to the combination of entrepreneurial teams. The entrepreneurial team should have the experience and ability of various industries required to boundary-spanning innovation, and improve the entrepreneurial performance through the combination of adaptive experience and ability. Second, enterprises should pay attention to identifying the core industry capabilities required for boundary-spanning innovation. Although boundary-spanning innovation breaks down the barriers between industries and promotes the recombination of cross-domain resources, it does not mean that all industry resources are equally important, and enterprises need to identify the key industry experience and capabilities required for their own development. This research sheds light on an imprtance issue in entrepreneurial team management, what kind of commbination of team members is good for new firms to develope high level performance in the circumstance of boundary-spanning innovation. The research conclusion provides decision reference and practical guidance for new firms on how to allocate entrepreneurial teams to improve entrepreneurial performance.
Global Innovation Hubs are centers that emerge as a result of the extensive development and geographical diffusion of science and technology innovation activities, serving as crucial nodes within the global innovation network. The development modes of these hubs represent abstract summaries of the historical evolution and practical implementation of regional science and technology innovation systems. Identifying and comparing these modes is an essential starting point for uncovering regional innovation patterns and formulating targeted development strategies. Previous studies have primarily examined Global Innovation Hubs from the perspective of their temporal dynamics in historical evolution and spatial positioning within the global innovation network. This study aims to further enhance our understanding by exploring the diversity of regional innovation modes, thereby unraveling various developmental paths embedded within different points across the global innovation network.
Through more than 10 rounds of expert deliberation spanning three years, this paper selects 31 characteristic indicators to assess regional scientific research capability, innovative economy, and innovative ecology. Using the two-stage K-means clustering method, this study identifies and systematically compares the development patterns of 100 global cities (metropolitan areas). The findings reveal that Global Innovation Hubs exhibit ten distinct types of differentiated development modes: all-around champion hub, international financial hub, ecological hub, knowledge hub, data-driven hub, innovation highland hub, developing hub, international communication hub, growing hub, and quality hub. Notably among them are Chinese cities which predominantly fall into three modes: Beijing and the Guangdong-Hong Kong-Macao Greater Bay Area are the all-around champion hubs; Shanghai is the innovation highland hub; while 15 other cities (metropolitan areas) including Hangzhou, Nanjing and Wuhan are the growing hubs.
This study primarily focuses on analyzing these three types of Global Innovation Hubs including China cities. It is observed that they possess distinctive characteristics as follows: Firstly, all-around champion hubs attract top scientific talents worldwide along with leading institutions and facilities. They dominate global frontier technological innovations as well as cooperation networks while connecting with a global technology ecosystem subsystem. Moreover they gather high-tech enterprises globally with outstanding entrepreneurial ecological advantages. Secondly, innovation highland hubs emerge as prominent hubs for emerging technologies and industries at a global level, by fostering strong industry-university-research alliances alongside industrial parks formation where government plays an instrumental role in shaping regional industrial clusters. Thirdly, growing hubs are regional economic growth poles, driving and radiating science and technology innovation activities in the region and its surrounding small satellite cities. However, due to limited scientific knowledge accumulation and technological history, these hubs still function as secondary nodes within the global innovation network.
The research findings contribute a novel empirical approach and data foundation for the systematic identification and comparison of Global Innovation Hubs. Moreover, the inclusion of emerging cities (metropolitan areas) such as Beijing and the Guangdong-Hong Kong-Macao Greater Bay Area provides compelling evidence to elucidate the evolution of global innovation geography, particularly highlighting China's ascent as an emerging scientific and technological powerhouse. Furthermore, this study enhances the understanding of Global Innovation Hubs by exploring diverse regional innovation modes. The conclusion reveals ten distinct development models that further substantiate how regions can formulate their own "regional formula" for science, technology, innovation, and industrial advancement based on their unique knowledge base and innovation resources. Identifying development modes can assist China's Global Innovation Hubs in accurately positioning their niche and benchmark city within the global innovation network, providing empirical support and decision-making references for establishing Global Innovation Hubs in China.
Under the circumstances of major changes unseen in a century, the scientific and technological revolution is accelerating, anti-globalization is resurging, local conflicts and turmoil are frequent, and the COVID-19 epidemic is pandemic, and the global innovation ecology is facing major challenges. Based on the systematic review of the concept, structure, theoretical basis and practical challenges of the globally open innovation ecology, this paper takes the IC industry as the research object, clarifies its globally competitive situation and innovation layout, focuses on the two major Chip Acts of the Europe and the United States, analyzes the motivation and key contents of its enactment, and further elaborates on its constituent entities, construction elements and openness. Then the trend of global opening of innovation ecology is analyzed, and the difficulties in its development process are clarified. Finally, the countermeasures and suggestions are put forward to promote China to build an open innovation ecology with global competitiveness.
Accelerating the high-level building of an innovation ecosystem is the path for building an innovative country. In this study, 30 Chinese provinces (excluding Hong Kong, Macao, Taiwan, and Tibet) are used as examples of case studies. To start with, This article expands the "energy level theory" and comprehensively considers the openness, dynamism, and regionality of regional innovation ecosystems, and builds an indicator system from two dimensions："energy level structure" and "energy level effect" to gauge the energy level of local innovation ecosystems. Secondly, this work applies the resource orchestration theory to the study of innovation ecosystems, and distinguishes two new digital production elements (digital platforms, data resources) and four traditional innovation resources and capabilities (technological talents, R&D capital, industrial diversification agglomeration, and industrial specialization agglomeration) of the innovation ecosystem in the digital context. Finally, the fsQCA technique is utilized to investigate the configuration paths that influence the energy level of regional innovation ecosystems. As a result, it makes clear the guidelines for resource orchestration in regional innovation ecosystems within the brand-new framework of empowered "digital intelligence".
The findings show that: Firstly, many contemporaneous causal links are shown in the innovation ecosystem's resource orchestration. Causal asymmetry and "various routes" characterize the configuration paths driving regional innovation ecosystem energy level. The concentration of R&D capital performs a pretty universal role in assisting high-capacity innovation ecosystems. Secondly, there are two new paths for enhancing the innovation ecosystem's energy level in the new scenario of "digital intelligence" empowerment: "capital-digital platform- driven " and "talent-capital-digital platform- driven," as well as a typical road: "talent-capital-driven". Thirdly, the primary reason why the regional innovation ecosystem cannot operate at a high energy level is that the region is focused on the creation of industrial agglomerations, lacks the ability to attract traditional innovation resources like talent and capital, and is less sensitive to the application of new production factors like the development of digital platforms and the use of data resources.
Therefore, this paper offers the following three recommendations: initially, it's essential to guarantee a sufficient supply of regional R&D funding and emphasize the function that research funding plays as an incentive. Simultaneously, the government should increase oversight of the use of scientific research funds while increasing autonomy in the use of scientific research funding. Moreover, different areas should deepen the application of data innovation, unlock the value of data elements, improve the enabling effect of "data" and "intelligence," and create a regional innovation ecosystem powered by "data intelligence". Last but not least, backward regions should learn from other innovation ecosystems' resource arrangement templates for high-energy operation. For them, it's critical to boost the vitality of innovation resources, rebuild regional innovation capacities and resources, overcome the "lock in effect" of industrial agglomeration, and therefore raise the energy level of the innovation ecosystem.
The research contributions of this research are as follows: ① This study extends the application of "energy level theory" to clarify the concept of innovation ecosystem energy levels from two dimensions: "energy level structure" and "energy level effect," enriching the theoretical connotation of "energy level theory" in the field of innovation ecology. ② This paper identifies the driving path configuration that leads to the improvement of regional innovation ecosystem energy levels, analyzes the linkage effect of "traditional + new" resources and capabilities on the improvement of innovation ecosystem energy levels, and expands the application of resource arrangement theory in the field of innovation ecosystem. ③ This research explores the resource allocation patterns of innovation ecosystems in the context of digital intelligence, providing theoretical guidance and reference templates for innovation ecosystems with "insufficient resource utilization" and "not knowing how to allocate resources".
Chinese outward investment is particularly focused on the science and technology sector, and multinational companies (MNCs) have innovatively advanced the practice by extensively establishing multinational R&D centers. Multinational R&D centers are able to transfer advanced knowledge back to the parent company, a process known as reverse knowledge transfer (RKT) in the field of academic research.
Throughout the academic research on RKT, there is little literature on whether RKT contributes to long-term innovation performance, and most studies focus on the host country context from the subsidiary's perspective, ignoring the importance of the home country context element. Innovation is an important development strategy for MNCs, and whether Chinese MNCs can effectively utilize RKT to enhance long-term innovation performance has attracted much attention.
Based on the knowledge base theory and institutional theory, we construct a theoretical framework. A sample of 190 Chinese MNCs questionnaire survey data is used to match relevant indicators from the World Bank's 2006 report Government Governance, Investment Environment and Harmonious Society: A Report on the Competitiveness of 120 Chinese Cities. The variable relationships are revealed through partial least squares structural equation modeling (PLS-SEM).
It is found that RKT by Chinese MNCs can promote long-term innovation performance, dual unions play an intermediary role, and a favorable institutional environment is conducive to the development of the process. The more RKT, the more frequent interaction and communication between multinational R&D centers and parent companies, and the more opportunities for parent companies to carry out knowledge sharing in the long run. This rich source of knowledge across borders creates a future-oriented innovation environment for the parent company. In this process, dual association plays a mediating role between RKT and long-term innovation performance, while the mediating role of dual balance is not significant. This suggests that organizational learning can lay the foundation for enhancing long-term innovation performance and that Chinese MNCs place more emphasis on the overall effect of exploitative and exploratory learning rather than on the balanced development of different learning styles. The exploration of the institutional context in the home country suggests that Chinese MNCs located in regions with a better institutional environment and institutional efficiency can have legitimacy and policy support for RKT and are more willing to innovate in the long run. Not only the positive effect on dual association is more pronounced, but also further contributes to long-term innovation performance.
The paper reveals the positive role of RKT in enhancing long-term innovation performance and the importance of institutional context in it, deepening innovation research and institutional theory in MNC management. This study clarifies the positive role of RKT in enhancing long-term innovation performance, while discovering the mediating effect of dual association in it, and illustrates that the aggregate utility of exploitative and exploratory learning is particularly important for achieving long-term innovation performance of RKT. Consideration of the home country's institutional context highlights the importance of a favorable institutional environment for Chinese MNCs to cultivate long-term competitive advantage. Not only does it complement research on the use of external knowledge for innovation in developing countries, but it also further expands the application of institutional theory in international business.
Innovation consortium is the strategic linchpin of the new national system, and the leadership of enterprises is an important way to form innovation consortium. How to build an innovation consortium with "fusion of interests, integration of elements and convergence of capabilities" to promote the deep coupling of innovation and industrial chains is an important research topic in the process of building an innovative country under the new situation. In this paper, we analyzed the characteristics of five management linkages and mechanisms of enterprise-led innovation consortia through case studies, and constructed a three-stage dynamic evolution model accordingly. It was found that: (1) corporate strategy renewal is the driving force of the innovation consortium; (2) binary organizational structure is the fulcrum of the relationship between the two chains; (3) real option thinking is conducive to incentive-compatible interest integration; (4) interactive learning mechanism is the key to the process of factor integration; (5) digital empowerment is the important support of capability integration. This paper constructs a three-stage evolutionary model of innovation consortium, analyzes the dynamic process and management ideas of deep coupling of innovation and industrial chains. Then aims to provide stable solutions for traditional enterprises in deep red sea competition, so as to comprehensively and safely promote S&T self-sufficiency and industrial autonomy.
