With the rise of artificial intelligence, AI driven scientific discoveries have become a new paradigm in scientific research. However, whether the research path that relies on data and algorithms can truly constitute "scientific discoveries" still faces fundamental philosophical and methodological questions. Scientific epistemology requires that knowledge claims must undergo falsifiability testing. However, current AI scientific discoveries often appear as "black boxes" due to the lack of interpretability, with outputs mostly statistical predictions rather than logically complete rational claims, resulting in the failure of falsifiability mechanisms: there are no clear theoretical targets to criticize, and scientific debates have become superficial debates on input-output. This reveals a deeper crisis: the traditional scientific cognition based on human intuitive reasoning is difficult to adapt to the complexity patterns revealed by AI. Therefore, resolving this crisis cannot only pursue the transparency of AI, but also requires promoting the expansion of the cognitive boundaries of the scientific community - developing new conceptual systems and formal languages that represent complexity, so as to understand the complex world revealed by AI while maintaining the fundamental mechanisms of scientific theory criticism and evolution.
The artificial intelligence industry is a typical representative of future industries and a strategic emerging industry that leads economic innovation and enhances national competitiveness. As a disruptive technology, generative artificial intelligence has become an important direction for the development of the artificial intelligence industry. Taking 23 provinces and cities in China as the research objects, this paper adopts the TOE theoretical framework and introduces the fsQCA method to explore the high-efficiency development path of China’s generative artificial intelligence industry from a configuration perspective. The research found that: (1) The generative artificial intelligence industry has four typical characteristics: innovation leadership, ecological synergy, radiation empowerment and market explosiveness. (2) There are five paths for the high-efficiency development of China’s generative artificial intelligence industry: organization-environment dual-wheel drive, technology-environment dominant, technology-environment synergy, factor aggregation comprehensive drive, and environment support. (3) Through configuration comparison, it is found that the high-efficiency development of China’s generative artificial intelligence industry requires the coordination of multi-dimensional factors, and the advantage of a single factor is difficult to support its sustainable development. The research conclusions provide policy basis and theoretical guidance for the government to formulate industrial development policies and enterprises to make the next strategic planning.
In recent years, the rapid development of artificial intelligence technology has made intellectual property issues the focus of academic research and judicial decisions. This paper reviews the relevant literature and judicial precedents at home and abroad, focusing on the future development of artificial intelligence technology. From the perspective of stimulating innovation, this study has investigated the basic issues such as the subject qualification, object scope, acquisition standards, rights attribution, implementation and application, and effective regulation of intellectual property protection for works, signs and inventions created by artificial intelligence.It constructs a system of intellectual property protection for artificial intelligence and proposes countermeasures for building an intellectual property protection system for AI-generated works, signs, and inventions.The legal policies regarding intellectual property rights of artificial intelligence should be ly revised and improved. It should be clearly stipulated that works, signs and inventions generated by artificial intelligence can obtain intellectual property protection. The ownership of intellectual property rights of artificial intelligence-generated works, signs and inventions should follow the principle of contract. The qualification of artificial intelligence as the creator of works, the designer of signs and the inventor should be granted. The acquisition standards for intellectual property rights of artificial intelligence-generated works, signs and inventions should be improved. The application of the principles of good faith and creditworthiness, balance of interests and anti-abuse regulations of intellectual property rights should be strengthened in the field of artificial intelligence.
[Purpose/significance] To construct the theoretical system of knowledge fusion in the big data era aims to provide basic theory and practical guidance for knowledge fusion in the big data era. [Method/process] According to the purpose and principle of the theoretical system of knowledge fusion in the era of big data, based on Lakatosian research programme, the theoretical system of knowledge fusion in the era of big data is constructed. [Result/conclusion] The theoretical system of knowledge fusion in the era of big data is composed of basic theory of knowledge fusion, auxiliary hypothesis and application theory of knowledge fusion, and big data environment. Among them, the basic theory of knowledge fusion includes the concept and characteristics of knowledge fusion. The auxiliary hypothesis and application theory of knowledge fusion includes the thinking, supporting theory, demand, object, result, process, technology, method and tool of knowledge fusion. Inspired by the big data environment, the theoretical system of knowledge fusion can be expanded and modified continuously. The theoretical system of knowledge fusion in the era of big data solves the practical problems that the relevant theories of knowledge fusion are scattered and difficult to fully explain and guide the task of knowledge fusion in the environment of big data, and provides a reference for the theoretical research of knowledge fusion in the era of big data.
Under the background of major power competition, complex products and systems represented by national heavy equipment are the focus of global technological competition. Breakthroughs in key core technologies face dual challenges across multiple technological levels and fields. It’s very important to enhance the overall efficiency of indigenous innovation. The existing research has identified the dual barriers in complex products and systems innovation, including horizontal integration and vertical collaborative iteration. Case studies of indigenous innovation in complex product systems such as pressurized reactor, heavy-duty gas turbines, and tunnel boring machines reveal that knowledge interaction among innovation actors is the fundamental driving force to overcome above barriers. However, existing research still has several gaps. First, several scholars argue that new knowledge is a critical driver for technological breakthroughs. However, the mechanisms by which new knowledge emerges during the process of breaking through key core technologies remain unclear. Second, existing research tends to regard the innovation consortium as homogeneous entities that uniformly pursue a strategic mission of technological catch-up and indigenous innovation. In reality, the technological bottlenecks faced by different innovation consortia vary significantly in both level and type. This calls for a more nuanced and categorized analysis of the internal mechanisms through which consortia achieve breakthroughs in complex product systems. Third, the emergence of new knowledge results from the joint influence of multiple factors. It is necessary to identify the key influencing factors that shape the evolution of new knowledge during the technological breakthrough process.
In response to above research gaps, we try to do a systematic analysis of the knowledge enhancement mechanisms through which the innovation consortium achieve breakthroughs in key core technologies of complex product systems. First, innovation consortia are classified into four distinct types according to their technological breakthrough objectives and knowledge interaction strategies. Second, the model of knowledge interaction is constructed using the Lotka–Volterra framework to uncover the heterogeneous mechanisms of knowledge enhancement across different types of innovation consortia. Finally, simulation analysis is conducted to examine the influence of key factors on knowledge enhancement outcomes. The results of numerical simulations indicate that both mutually beneficial and partially beneficial symbiotic relationships among innovation agents significantly improve the effect of knowledge enhancement. Only temporary and low-level knowledge enhancement can be achieved under the independent symbiotic relationship. Moreover, the architect’s capability for knowledge orchestration is positively correlated with the effectiveness of knowledge enhancement. Even in the context of an independent symbiotic relationship among members, strong knowledge orchestration efforts by the architect can effectively stimulate knowledge interaction dynamics. In addition, the architect's knowledge breadth is also positively associated with the level of knowledge enhancement. Although extensive knowledge interaction may slow down the speed of enhancement, it ultimately results in a higher overall level of knowledge enhancement.
In this study, several theoretical and practical contributions are proposed. First, it echoes scholarly discussions on collaborative innovation in complex product systems and proposes knowledge enhancement as the intrinsic driving force behind breakthroughs in key core technologies. In doing so, it advances the mechanism research of innovation consortia from a new perspective, offering a more fundamental understanding of how such breakthroughs occur. Second, based on prior research, this study categorizes the differentiated mechanisms of knowledge enhancement within innovation consortia. It moves beyond the conventional view of consortia as homogeneous entities with unified goals. This new perspective broadens the conceptualization of innovation consortia and deepens our understanding of their heterogeneous dynamics. Furthermore, regarding to practical implications, several recommendations are proposed for policy makers and practitioners. First, it is important to promote the establishment of innovation consortia led by enterprises. Giving full play to the role of enterprises as the principal agents of technological innovation, and fostering enterprise-led consortia, can effectively promote the deep integration between scientific innovation and industrial innovation. Second, in light of the characteristics of complex product systems, it is important to build differentiated types of innovation consortia. On the one hand, coordination among upstream and downstream innovation actors should be supported. On the other hand, participation should also be encouraged among actors operating in the same segment of the value chain, even if potential competitive relationships exist. Third, innovation actors should align their strategies with their positions in the industrial chain and resource endowments. Both vertical collaboration and horizontal integration can be used to form innovation consortia that are well-matched to specific technological breakthrough goals and pathways. Internal relationships within innovation consortia should be effectively managed by improving value distribution mechanisms, strengthening trust-based governance, and stimulating partners’ willingness to share knowledge. These efforts are essential for enhancing knowledge sharing and co-creation efficiency within the consortium.
Abstract: Accelerating the formation of standards is the key for firms to win competitive opportunities. For example, Tesla has established a significant competitive advantage in the electric vehicle market by rapidly building a network of supercharging stations and formulating efficient charging standards; Kodak, once a giant in the photography industry, gradually lost its dominant position in the market because of its failure to launch digital photography standards in time. From various practical cases, we can see that taking the lead in launching standards has become an important way for firms to demonstrate their innovative strength, formulate technical rules and seize competitive opportunities in specific fields. In this regard, how firms can improve the efficiency of standardization and shorten the standard formation duration is a hot topic of concern for managers.
Existing researches have richly studied the standard formation in the three aspects of firm resource capacity, external environment and standard alliance. Indeed, the research around the influencing factors of standard formation has made some progress, but there are still the following deficiencies that need to be further expanded. Firstly, the existing literature has mainly explored the impact of the size and membership diversity of standard alliance on standard formation from the perspective of individual firms, and lacks research at the alliance level. In fact, standard alliance is the main carrier to promote the process of standard development, and the power structure of alliance is the key factor affecting the operational efficiency of alliance. Secondly, the existing studies mainly take the number of standards developed by focal firms and the cumulative number of patent applications filed by the alliance as the proxy variables of standard formation, and lack the measurement of the efficiency of standard formation at the alliance level, so it is difficult to accurately answer the question of whether and how the standard alliance affects the efficiency of standard development.
In summary, this paper focuses on further expanding the stream of literature along the level of standard alliance, and puts forward the research hypothesis on the power structure of standard alliance and the standard formation duration by using the transaction cost theory, and empirically tests the hypothesis by using 1,672 standard alliances in China's telecommunication industry from 2010 to 2020 as samples. The study finds that: the more decentralized the power structure of standard alliance, the longer the time needed to form the standard, because it limits the information processing efficiency and increases monitoring and coordination cost; the regional marketization gap enhances the positive effect of the power structure of alliance and the length of standard formation; the common partnership of alliance firms weakens the positive effect of the power structure of alliance and the length of technical standard formation. The heterogeneity analysis shows that progressive technical standard and standard alliance with younger members are more likely to be affected by the decentralized power structure of the standard alliance, and the positive effect of the decentralized power structure of the standard alliance on the length of technical standard formation is more significant. The relevant research findings provide theoretical support for firms to form standard alliance and accelerate the formation of standards.
Higher education (HE) and science and technology (S&T) are subsystems within the broader framework of economic and social development. HE serves as the primary arena for talent cultivation and human capital output, as well as a key venue for the aggregation of scientific and technological resources. Through activities such as teaching, research, and social services, HE continuously contributes talent, ideas, and outcomes to scientific progress. Simultaneously, the advancement of HE relies on the support of scientific resources and achievements to enhance its capacity, standards, and quality. Consequently, the interactive process between HE and S&T forms an open and complex system in which various elements mutually empower and coordinate with one another. Based on a deconstruction of the mechanisms underlying the coordinated development of HE and S&T, this paper employs a coupling coordination degree model, the Dagum Gini coefficient, and spatial econometric methods to analyze the temporal evolution and spatial distribution of HE–S&T coordination in China from 2010 to 2022. It also examines the spatial effects of driving factors, offering insights to promote coordinated HE–S&T development and providing a reference for global strategies toward sustainable, innovation-driven growth. The study finds that: (1) In terms of temporal evolution, the national HE–S&T coordination in China has transitioned from “moderate imbalance” to “mild imbalance” and finally to “on the verge of imbalance,” with the overall coordination level steadily increasing; (2) At the level of China's four major regions, the spatial disparities in the coordination between HE and S&T are pronounced, exhibiting an overall pattern of “eastern region leading, central region catching up, northeastern region stagnating, and western region lagging,” along with an evolutionary trend marked by “the eastern region transitioning toward high coordination while the western region increasingly departs from a balanced state.” At the provincial level, Beijing, Shanghai, Jiangsu, and Guangdong stand out as exemplary provinces of high coordination; (3) Concerning spatial disparities, the overall differences in the coupling coordination degree between HE and S&T in China are gradually narrowing, with the imbalance mainly attributable to inter-regional differences—most notably between the eastern and western regions, while the gap between the central and northeastern regions remains minimal. Narrowing the disparities between the eastern and western regions is key to addressing the overall imbalance in HE–S&T coordination; (4) In terms of spatial association, HE–S&T coordination exhibits a strong positive spatial correlation with significant positive spillover effects among provinces; (5) Analysis of the driving mechanisms indicates that for direct effects, population density and openness exert a positive influence on regional HE–S&T coordination, whereas the direct effects of economic development, infrastructure, industrial structure, and urbanization are not statistically significant. In contrast, concerning indirect effects, infrastructure and openness generate positive spatial spillovers, while urbanization produces negative spillover effects. Accordingly, it is recommended that: (1) Policies for HE and S&T be coordinated to enhance their integration; (2) Cross-regional development linkages and coordination mechanisms be established to leverage the spatial spillover effects of high-coordination provinces and cities; (3) Regional differences be acknowledged, with HE–S&T coordinated development promoted by local conditions; and (4) A favorable external environment be cultivated to drive the deep integration of HE and S&T.
This study focuses on the innovation practices of specialized, refined, distinctive, and innovative “little giant” enterprises in the era of big science. Based on the theory of knowledge recombination, it delves into the impact of disciplinary diversity in scientific collaboration on radical technological innovation in these enterprises. Through empirical analysis of unbalanced panel data from 2,464 “little giant” enterprises in the new materials field spanning from 2000 to 2018, the study finds that disciplinary diversity in scientific collaboration has a positive effect on radical technological innovation in “little giant” enterprises, with knowledge complementarity partially mediates this relationship. Additionally, the intensity of intellectual property protection negatively moderates the relationship between disciplinary diversity and knowledge complementarity, while technological turbulence positively moderates the relationship between knowledge complementarity and radical technological innovation in enterprises. This study not only elucidates the mechanism through which disciplinary diversity in scientific collaboration influences technological innovation in “little giant” enterprises but also reveals the boundary conditions of this mechanism. The conclusions of this paper contribute to a deeper understanding of the facilitating role of interdisciplinary scientific collaboration in technological innovation among small and medium-sized enterprises.
Accelerating the drive of digital collaborative innovation is the key to solve the problem of externality and complexity of disruptive technology innovation. In view of this, this paper explores the development path of digital collaborative innovation from the perspective of digital labor elements. On the basis of constructing the theoretical analysis framework of digital collaborative innovation, this paper describes the accumulation of regional digital labor factors from the three dimensions of digital knowledge, digital skills and digital consciousness of labor force. The empirical test shows that: 1. The accumulation of digital labor factors makes ' subject collaboration ' and ' interregional collaboration ' an important way of digital collaborative innovation, and knowledge spillover and innovation factor flow are the main channels of ' interregional collaboration '. 2. Digital collaborative innovation is subject to knowledge spillover and innovation factor flow : Beijing, Wuhan, Guangzhou, Shanghai, Tianjin and other regions with strong knowledge enrichment and property rights protection, as well as Wuxi, Wenzhou and other regions with weak intervention in innovation factor flow are more suitable for the cultivation mode of " subject collaboration. 3. The accumulation of digital labor factors has changed the knowledge absorption capacity of knowledge-poor areas, and can reserve power for digital collaborative innovation through imitation innovation. At this time, the role of intellectual property protection is highlighted and becomes the key to the development of independent innovative digital. In addition, excessive intervention in talent and capital flows will damage the connotative innovation path and hinder the development of digital collaborative innovation. The above conclusions provide a theoretical basis and practical direction for formulating digital collaborative innovation policies according to local conditions, echoing the relevant instructions of the 20 major.
With the acceleration of the global technological and industrial transformation, future industries have become a new track in international competition, and the construction and improvement of the future industry innovation ecosystems are crucial to a country’s long-term competitiveness. China has repeatedly proposed to plan ahead and actively cultivate future industries, and the Report to the 20th National Congress of the Communist Party of China proposed to “improve the scientific and technological innovation system and form an open innovation ecosystem with global competitiveness”. Under the New System for Nationwide Resource Mobilization, the government is the architect of the future industry innovation ecosystems, and giving full play to the role of the government is an important strategic support and institutional guarantee for promoting industrial innovation relying on disruptive technologies. As a key instrument and carrier for the government, policy plays a vital role. According to the policy synergy theory, the internal friction within the system caused by policy conflicts and the offset of effectiveness will reduce the overall implementation effect, and single or partial policies are difficult to provide a complete policy blueprint for the construction of an efficiently integrated the future industry innovation ecosystems. Policy coupling and synergy help to break down barriers and restrictions and rapidly improve innovation performance. Insufficient coupling and synergy will restrict the systematic nature of policy formulation and the efficiency of implementation, and become a potential obstacle to China’s construction of a global competitive advantage in future industries, urgently requiring systematic research to provide theoretical basis and practical guidance. Therefore, the structural coupling and synergy of policies are crucial for the cultivation of a multi-dimensional future industry innovation ecosystem.
This paper aims to answer the question of how the core network affects innovation performance through what kind of policy coupling and synergy transmission path. Taking China's hydrogen energy industry as an example, this paper quantifies policies based on the research framework of “knowledge-entrepreneurship-business”, constructs a theoretical model of the policy coupling and synergy path of the multi-dimensional innovation ecosystem, uses the Partial Least Squares Structural Equation Modeling(PLS-SEM) to construct and verify the transmission path of hydrogen energy policies from 1995 to 2023 that affect innovation performance through coupling and synergy, and uses social network analysis to study the relationships among government departments. The research finds that the coupling and synergy among policies at all levels have a positive impact on innovation performance, the coupling degree remains stable at an intermediate coordination state, and the synergy degree improves slowly with an overall poor performance; in the transmission path of “policy formulation→coupling and synergy→innovation performance”, the influence coefficients in descending order are the business-driven business-innovation coupling and synergy, the business-leading business-knowledge coupling and synergy, the knowledge-dominated knowledge-business coupling and synergy, the entrepreneurship-catalyzing entrepreneurship-business coupling and synergy, the entrepreneurship-boosting entrepreneurship-knowledge coupling and synergy, and the knowledge-supporting knowledge-entrepreneurship coupling and synergy; the policy network presents a “core-middle-edge” structure, playing the roles of leading and guiding, supporting and coordinating, and serving and supervising respectively in policy formulation. This paper provides a reference for the hierarchical structure quantification research of future industry policies, makes up for the deficiencies in the research on the transmission path of policy coupling and synergy, and contributes to government decision-making and industrial practice.
Existing studies focus on whether cross-border M&A can improve innovation quality, but lack of attention to how cross-border M&A has differentiated impact on innovation quality. This paper divides cross-border M&A into exploratory M&A and exploitative M&A based on the perspective of exploratory and exploitative learning, divides innovation quality into technology quality and market quality based on technology and market dimension, empirically tests the differentiated effects of two cross-border M&A behaviors on different dimensions of innovation quality, and explores the moderating effects of integration depth and knowledge depth based on knowledge management theory. It is found that exploratory M&A helps to improve technology quality, exploitative M&A helps to improve market quality, and the impact of cross-border M&A on innovation quality depends on the post M&A knowledge management process. Firms with deep integration (high knowledge acquisition degree) and deep field knowledge (strong knowledge exploitation ability) can benefit more from cross-border M&A.
Disruptive research achievements in basic research are not only the core drivers of advancing new productivity but also an essential component of achieving high-level scientific and technological self-reliance and self-strengthening. These breakthroughs often serve as the cornerstone for groundbreaking discoveries and technological innovations that can transform industries and societies. In the context of scientific research, disruptive achievements are those that fundamentally alter existing paradigms, challenge conventional wisdom, and lead to paradigm shifts across various scientific fields. In this study, the focus is placed on the field of astronomy, where such research achievements have historically played a pivotal role in expanding the boundaries of human knowledge and shaping technological progress.
The research adopts a Grounded Theory approach, a qualitative research methodology that emphasizes the systematic collection and analysis of case data to develop theoretical insights grounded in empirical evidence. By examining a diverse set of case studies in the field of astronomy, the study seeks to uncover the underlying patterns and mechanisms that contribute to the generation of disruptive research achievements. The findings of this study suggest that the generation of disruptive research achievements is influenced by a combination of three primary dimensions: (1) the researchers themselves, (2) scientific research activities, and (3) the scientific research results. Each dimension includes multiple sub-factors that contribute to the overall process. Firstly, the dimension of researchers, as the core subject of scientific research, plays a decisive role in the production of disruptive research achievements. This dimension can be categorized into three main aspects: internal factors, environmental factors, and scientific research capabilities. Internal factors refer to those characteristics that reflect an individual's inherent traits and motivations, such as scientific interests, personality traits, and a broad range of interests. Environmental factors encompass the external conditions and influences that shape a researcher’s development, including family background, access to research platforms, and the influence of key mentors or collaborators. Scientific research capabilities, on the other hand, refer to the comprehensive qualities and skills that enable a researcher to conduct innovative work within their field, including formal education, early career recognition, engineering experience, leadership in projects, and strategic foresight. Researchers who are able to integrate interdisciplinary approaches and draw insights from various scientific domains are more likely to contribute to groundbreaking innovations that disrupt existing paradigms. Secondly, in the process of generating disruptive research achievements, various critical factors influence each stage of the research lifecycle, from the proposal of the project to its execution and eventual outcomes. During the project formulation phase, the selection of cutting-edge topics, the orientation of the research, and the integration of interdisciplinary approaches are key factors that shape the potential for groundbreaking discoveries. In the project implementation phase, factors such as clear research objectives, the composition of the research team, the availability of scientific instruments, and funding support play crucial roles in driving the production of disruptive results. Lastly, in the stage of achieving results, scientific collaboration and academic exchanges significantly influence the sharing and dissemination of research findings. Finally, many groundbreaking scientific discoveries arise from serendipity—unexpected observations or occurrences that were not initially anticipated. Serendipitous scientific discoveries, or "Serendipity," refer to phenomena that scientists stumble upon while investigating something else. In the case studies presented in this paper, serendipitous discoveries can be categorized into two types: first, chance encounters, such as the unexpected recording of neutrinos from a supernova during proton decay detection; and second, accidental results, such as unintended discovery of the radio signals from the center of the Milky Way while attempting to solve short-wave communication interference. These serendipitous discoveries, while often highly uncertain, can lead to disruptive research achievements with profound implications. The question of whether scientific policies can effectively plan for or cultivate such serendipitous findings remains an open topic for further exploration in the academic community.
Based on these findings, the paper offers several recommendations aimed at promoting the generation of disruptive research achievements. One key suggestion is to provide young researchers with more opportunities to engage with cutting-edge scientific endeavors from an early age. This could be achieved through dedicated programs that spark their interest in scientific research and cultivate the spirit of scientific inquiry. Additionally, fostering an environment where young scientists are given leadership roles, enabling them to develop critical skills in engineering practice and organizational leadership, is crucial for nurturing the next generation of innovators. Encouraging more scientific collaboration and academic exchange is another key recommendation. By promoting interdisciplinary research and facilitating the sharing of research outcomes, the scientific community can accelerate the development and dissemination of disruptive innovations.
Background and Research Questions
Since 2018, the United States has adopted means such as "decoupling", "breaking supply chains", and "de-Sinicization" to block and suppress China's industrial technology upgrading, especially in the high-end chip manufacturing field. This has put China in a "chokepoint" dilemma. Against this backdrop, China has still achieved key technological breakthroughs in the chip field, as demonstrated by the release of the Huawei Mate60 series of mobile phones. Although previous studies have focused on tackling core and key technologies, most of them concentrated on problem definition and approaches, lacking empirical research on digital-enabled technological innovation. This study focuses on issues that urgently need to be explored, such as how enterprises can use digital technologies to achieve technological breakthroughs in an environment where "broken supply chains" coexist with the digital economy, what open-innovation measures to take, the specific role of digital technologies in this process, and the extent to which they promote technological breakthroughs.
Methodology
Taking A-share listed companies as samples, 20 cases were structurally sampled from chip and semiconductor component concept stocks according to the requirements of theoretical saturation. In-depth research was conducted on 12 enterprises significantly affected by "broken supply chains", and based on the logic of replicative co-occurrence, 4 typical cases with similar chip-manufacturing links were determined, covering enterprises in fields such as integrated circuit manufacturing, chip processing equipment, fiber lasers, and radio-frequency integrated circuits, to highlight the causal relationship between "broken supply chains" and technological breakthroughs.
Data was collected by analyzing second-hand data such as annual reports, official websites, and public reports of typical case enterprises, as well as through interviews from multiple parties. The data analysis followed a process of dialogue with theory. First, the theoretical fields of systematic emergence theory, open innovation, and digital technology/platform were determined. Then, key information was extracted from the cases and summarized into first-order codes, which were verified through multiple channels. Subsequently, the first-order codes were clustered into second-order codes in combination with the theory. The authors independently coded and discussed to ensure theoretical consistency. Finally, the relationship between the codes and the theory was reviewed and iteratively adjusted, and discussions were also held with industry managers to ensure compliance with the original intention of the theory. Ultimately, nine first-order code categories and four second-order codes were obtained to reflect the open-innovation and digital-enabling mechanisms.
Main Findings
Discovery of Open-Innovation Approaches under the Impact of "Broken Supply Chains": "Decoupling" has ed enterprises to respond actively, with active open innovation. Vertical resource integration is manifested in standardizing supplier management, expanding the business chain, and strengthening cooperative relationships to achieve close technological cooperation. Horizontal resource integration includes strategic cooperation with universities, participation in industry standard-setting, and cooperation with internationally advantageous enterprises. For example, Company C rebuilt its supply chain, and Company B collaborated with universities to tackle key etching machine technologies, indicating that "decoupling" breaks the restrictions on knowledge flow and promotes technological innovation and the reconstruction of the supply-chain system.
Discovery of the Digital-Enabling Mechanism in Open Innovation: The digital-enabling of digital technology is reflected in the advantages of information processing and the trust-strengthening mechanism, promoting information sharing and collaboration across the entire industrial chain. For example, Company A participated in standard-setting, and Company B used blockchain to share knowledge. The digital-enabling of digital platforms depends on technological enabling and has advantages such as low cost, achieving information connectivity and resource integration and expansion. For example, the platform of Company A connected the industrial chain to improve efficiency. Digital technology also accurately matches the flow of knowledge. For example, the platform of Company B provides diversified services to promote systematic emergence.
Discovery of the Impact of Enterprise Heterogeneity: Relative technological advantages and enterprise size significantly affect enterprise performance. Companies A and B, with advanced technologies, are outstanding in platform ecosystems and standard alliances. Technology affects the improvement of the platform and the right to speak. The large-scale Company A uses digital technology to improve efficiency, reflecting the moderating role of scale in systematic emergence. Companies C and D are small-scale and have less advanced technologies, but Company C's horizontal integration and Company D's vertical integration have both promoted innovation, indicating that different relationship paths have a positive impact on systematic emergence.
Theoretical Significance
Regarding the issue of systematic technological breakthroughs, by integrating the characteristics of the digital economy era, this study deeply analyzes the technological breakthrough and digital-enabling mechanisms under the impact of "broken supply chains", differentiates the moderating effects of characteristic variables such as enterprise technological advantages and scale, combines open innovation, digital enabling, and enterprise characteristics to construct a theoretical model, filling the gaps in previous research on the internal mechanisms of digital enabling and the role of enterprise characteristics, and providing a new perspective and theoretical support for related research.
Practical Implications
At the industrial level, efforts should be made to strengthen the construction of digital infrastructure and the application of general digital technologies, promote policies to support information sharing and collaborative innovation in the industrial chain, and create a good industrial digital ecosystem to help enterprises achieve technological breakthroughs. At the enterprise level, enterprises should be encouraged to strengthen the construction of digital platforms. Large enterprises should play a demonstrative and leading role in exploring digital transformation paths, drive the coordinated development of small and medium-sized enterprises, use digital technologies to optimize supply-chain and knowledge-base management, improve innovation capabilities and efficiency, and respond to external shocks to achieve technological upgrading.
Quantum computing, based on the fundamental principles of quantum superposition, entanglement, interference, and quantum supremacy, features characteristics such as computational power leaps, uncertainty and probabilistic nature, and reversible computation. It demonstrates enormous potential in fields like cryptography breaking, large-scale data analysis, military simulation, and critical infrastructure protection. Starting from the basic principles and technical attributes of quantum computing, this paper systematically analyzes its multidimensional impacts on information security, national security, and market order: on one hand, the capability of large number factorization and quantum search algorithms threatens existing encryption systems and data privacy, potentially leading to retrospective privacy breaches and critical facility paralysis; on the other hand, the quantum computing power race and its dual-use nature trigger dual risks of international competition and arms control dysfunction, while also creating potential crises of market monopoly and unbalanced fair competition. In response, a comprehensive governance framework can be constructed from three levels: legislative regulation, regulatory innovation, and international coordination. This includes revising existing security legislation and establishing specialized quantum technology laws to form hierarchical security control benchmarks; combining risk assessment, quantum technology review, and multi-level collaborative regulatory mechanisms to refine market entry, in-process supervision, and emergency response procedures; and advocating unified standards and multilateral cooperation at the international level to prevent quantum hegemony and computing power monopoly. Meanwhile, the development of quantum ethics norms and talent cultivation systems should be promoted to balance technological innovation with social responsibility, thereby laying a solid legal foundation for the healthy and sustainable development of quantum computing while safeguarding national security and public interests.
With the widespread adoption of artificial intelligence (AI) technology, ensuring the privacy of user data has become a significant research concern. Enterprises establish privacy policies to safeguard user data privacy. However, most of these policies exhibit several weaknesses, such as lack of transparency, opacity, unfairness, low practicality, and timeliness. Furthermore, they often overlook predictive private information provided by users. Consequently, these privacy policies are ineffective in protecting acquired privacy and may inadvertently violate predictive privacy, contradictory to their original intent, creating a privacy policy paradox. Drawing upon the human-centric AI framework, we suggest the development of Human-Centered privacy policies to address the challenges posed by current privacy policies effectively and ensure the data privacy security of users.
Based on the agenda setting theory and technology acceptance model, this research utilizes deep learning and text analysis method to explore the state, causes and effective road to construct meta-universe public cognition from the two levels of information transmission and reception. By analyzing the meta-universe news and user’s comments data from 2021-2023, this research reveals the meta-cosmic agenda communication is a game involving multiple agents, and the secondary communication of information by opinion leaders dominates the formation of public emotional cognition. The content of the media agenda does not coincide with the focus of public comment and contrary to the news, the sentiment of user comments is negative, which is due to the interaction of multiple external variables such as policy culture, which affect the perception of technological usefulness and ease of use. This paper analyzes the “user element” of meta-universe from multiple angles and at a deep level, which provides reference for the new quality productivity forces integration of meta-universe innovation and development, meta-universe policy formulation, product innovation and content publicity.
