Diffusion capacity is a crucial component of a great power’s technological capabilities, and civil-military technology fusion is a representative phenomenon of such diffusion. In the context of great power competition, the United States is actively promoting civil-military technology fusion through its spin-on policy. This policy aims to leverage technologies developed by the commercial sector to enhance U.S. military competitiveness, particularly against the backdrop of declining innovation capabilities within its military R&D departments. The underlying logic of the U.S. spin-on policy includes: prioritizing small businesses and non-traditional defense suppliers as key partners, employing a mix of policy tools as the primary means of implementation, and fostering a risk-taking culture as an intrinsic guiding principle. The U.S. spin-on policy has not only facilitated the entry of commercial technologies into the defense sector but has also driven profound developments within the U.S. defense system. Specific impacts include: enhancing the diversity, vitality, and resilience of the U.S. defense industrial base; strengthening U.S. defense innovation capabilities; accelerating the digital and intelligent transformation of the U.S. military; initiating preliminary shifts in U.S. defense technology philosophy and reshaping its defense technology system; and bolstering U.S. military competitiveness against China. The spin-on policy is expected to continue in the future and may exert an even more significant impact on the strategic competition between the U.S. and China. Additionally, the U.S. approach offers insights for China on how to further advance civil-military technology fusion and deepen its own spin-on effort.

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. 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. 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 product 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 product 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.

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 examines the innovation practices of specialized and sophisticated “little giant” firms in the era of big science, investigating how disciplinary diversity in scientific collaboration influences breakthrough technological innovation through the lens of knowledge recombination theory. Analyzing unbalanced panel data from 2,464 “little giant” firms in China's new materials sector from 2000 to 2018, we uncover significant findings regarding the mechanisms and boundary conditions of interdisciplinary scientific collaboration. Our empirical results demonstrate that disciplinary diversity in scientific collaboration positively affects breakthrough technological innovation in these specialized SMEs. This relationship is partially mediated by knowledge complementarity, suggesting that the integration of diverse yet complementary knowledge domains facilitate the recombination of existing ideas into novel technological solutions. The study further reveals two critical boundary conditions that shape this relationship. First, we find that intellectual property protection strength negatively moderates the relationship between disciplinary diversity and knowledge complementarity. Stronger IP protection appears to create barriers to effective knowledge sharing across disciplines, potentially limiting the synergistic benefits of interdisciplinary collaboration. Second, technological turbulence emerges as a positive moderator between knowledge complementarity and breakthrough innovation, indicating that rapidly changing technological environments enhance the value of integrating diverse knowledge streams. These findings contribute to multiple theoretical domains. The study advances knowledge recombination theory by elucidating how interdisciplinary scientific collaborations operate differently in specialized SMEs compared to larger firms or research institutions. We provide empirical evidence for the micro-level mechanisms through which diverse collaborations translate into innovation outcomes, particularly highlighting the pivotal yet partial mediating role of knowledge complementarity. Furthermore, our identification of IP protection and technological turbulence as opposing moderators offers new insights into the contextual factors that enable or constrain the innovation benefits of interdisciplinary collaboration. Methodologically, the research employs rigorous econometric techniques to analyze longitudinal data while controlling firm-level characteristics and environmental factors. We utilize multiple indicators of breakthrough innovation, including patent originality and technological impact measures, to ensure comprehensive assessment of innovation outcomes. The practical implications are significant for both policy and management. Policymakers should consider developing balanced IP frameworks that protect innovation incentives while facilitating cross-disciplinary knowledge flows. Targeted initiatives like interdisciplinary research platforms and public-private partnerships could enhance collaborative innovation for specialized SMEs. For “little giant” firms’ managers, the findings underscore the importance of strategically cultivating scientific partnerships across complementary disciplines while remaining responsive to technological changes that may amplify the value of knowledge integration. This study opens several promising research directions. Future work could explore optimal levels of disciplinary diversity, potential sector-specific variations beyond materials science, and the organizational processes that facilitate effective knowledge recombination in specialized SMEs. By integrating theoretical insights with empirical evidence from China's innovative firms, this research provides a nuanced understanding of how interdisciplinary scientific collaboration drives breakthrough innovation in the big science era. The findings highlight the complex interplay between knowledge diversity, institutional environments, and technological contexts in shaping innovative outcomes. They contribute to ongoing discussions about fostering innovation in specialized SMEs through scientific collaboration while accounting for the practical constraints imposed by IP regimes and technological dynamics. This research ultimately enhances our understanding of how “little giant” firms can leverage interdisciplinary scientific partnerships to achieve technological breakthroughs.

A comprehensive review of previous literature on digital technology innovation predominantly posits that expediting the agglomeration of capital and talent yields positive externalities. However, shortages in these resources often precipitate systemic disruptions, such as talent poaching competitions and detrimental tax rate races among regions. These phenomena impede the efficient allocation of resources and obstruct the advancement of regional digital collaborative innovation. In contrast, data, as a novel production factor, can manifest agglomeration effects within virtualized environments, thereby propelling urban digital innovation. Lacking a tangible physical form, data factors necessitate integration with traditional elements, such as labor, to generate amplified, synergistic, and multiplicative impacts in production processes. This unique characteristic of data implies that digital labor, by inheriting data-factor attributes, may reconfigure the dynamics of traditional factor mobility, thereby influencing regional digital collaborative innovation.

To empirically validate this theoretical conjecture, this study operationalizes digital collaborative innovation along two dimensions (intra-regional and inter-regional) cooperationwithin the theoretical framework of innovation systems. Utilizing a panel dataset encompassing 283 prefecture - level cities from 2011 to 2023, the research undertakes a rigorous econometric analysis to examine the effects and underlying mechanisms of digital labor factors on digital collaborative innovation. Additionally, it explores the optimal trajectories of digital collaborative innovation across cities, contingent upon the cumulative development of digital labor factors.

The study's principal findings are as follows:(1) Digital labor factors demonstrably accelerate holistic regional digital collaborative innovation.;(2)Knowledge spillovers and the circulation of innovation factors remain pivotal mechanisms through which digital labor drives regional digital collaborative innovation;(3)Under the constraints of knowledge diffusion and factor mobility, the modus operandi of digital labor-driven digital collaborative innovation exhibits distinct spatial heterogeneity. Regions characterized by abundant knowledge reserves (e.g., Beijing and Wuhan), robust intellectual property protection (e.g., Shanghai and Tianjin), or limited innovation-factor competition (e.g., Wuxi and Foshan) are better suited to pursue inter-regional collaborative innovation models. Conversely, cities with proactive policy interventions in innovation-factor circulation (e.g., Guangzhou, Ningbo, and Shenzhen) tend to foster more effective intra-regional digital collaboration;(4)The accumulation of digital labor factors enhances the knowledge absorption capacity of regions with limited knowledge endowments, enabling them to build innovation capabilities through imitative innovation. In this context, intellectual property protection emerges as a critical determinant for transitioning from collaborative to independent innovation. Furthermore, excessive regulatory interventions in talent and capital flows are found to undermine the path of endogenous innovation, thereby impeding the full realization of digital collaborative innovation potential. These findings not only enrich the theoretical understanding of digital labor factor cultivation but also offer a robust foundation for harnessing digital dividends, invigorating digital economic innovation, and formulating evidence - based strategies for regional coordinated development.

This research contributes to the extant literature in three significant ways. First, by integrating the unique characteristics of digital labor, it elucidates the micro-foundations of regional digital collaborative innovation, thereby advancing the theoretical discourse on digital labor valuation. Second, it adopts a dual-dimensional analytical approach, examining both intra and inter-regional collaborative dynamics, which mitigates the potential exacerbation of regional disparities inherent in single-entity or single-city innovation studies. Third, by analyzing the evolving patterns of knowledge spillovers and factor mobility in the context of digital labor accumulation, it identifies region-specific optimal pathways for digital collaborative innovation, providing policymakers with tailored recommendations for formulating effective digital technology cooperation strategies.

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. The deconstruction of the relationship between cross-border M&A and innovation quality in innovation management literature still remains at the issue of whether cross-border M&A can improve innovation quality, and no consensus has been reached. The sharp contrast between the contradictory research conclusion and the hot wave of cross-border M&A in the industry indicates that the academic community urgently needs to shift its research focus from “whether to improve” to “how to improve”, that is, to clarify the internal mechanism of cross-border M&A affecting innovation quality.

The narrow research perspective leads to theoretical deficiencies in existing literature in revealing the impact of cross-border M&A on innovation quality. Firstly, existing research regards cross-border M&A as homogeneous and neglects exploring the differential innovation effects of different types of cross-border M&A. The existing literature that measures cross-border M&A based on transaction quantity is too simplified and cannot present the heterogeneity of M&A transactions, which hinders a deeper analysis of the impact of cross-border M&A innovation quality. Secondly, existing research focuses on analyzing whether cross-border M&A can affect the technology dimension of innovation quality, while neglecting the exploration of the market dimension. Looking at the literature on innovation quality, it is found that the characterization of innovation quality should be based on both technology and market dimensions, and there are differences in connotation and measurement between the two dimensions. Thirdly, existing research has focused on testing whether “can be improved”, resulting in a lack of interpretation for boundary conditions. Only a few literature have revealed the moderating effects of technological relevance, institutional distance, and intellectual property protection from the perspective of pre-merger factors, and have not addressed the contingency scenarios that affect the acquisition and exploitation of knowledge in the process of M&A integration.

This paper divides cross-border M&A into exploratory M&A and exploitative M&A based on the perspective of ambidextrous 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. Exploratory M&A aims to establish new competitive advantages, which is a long-distance, out of domain knowledge search characterized by exploration, change, experimentation, and innovation; exploitative M&A aims to leverage own technological advantages, which is a local, domain specific knowledge search characterized by refinement, execution, efficiency, and selection. Technology quality represents the technological value or impact of innovation achievements, while market quality represents the market value or impact of innovation achievements.

This article collects conceptual data on exploratory M&A, exploitative M&A, technological quality, market quality, etc. through a questionnaire survey. The sample comes from the global M&A transaction analysis database (Orbis M&A) in the BvD series from 2010 to 2023. 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.