The Low-altitude Economy is an important component of the New Quality Productive Forces, and the sound and sustainable development of the Low-altitude Economy is based on strict safety guarantees. Emerging safety risks derived from Low-altitude Economy activities include aviation safety risks, public safety risks, national information security risks and personal privacy security risks, and are characterized by the plurality of generating and bearing subjects, the arbitrariness of generating time and space, and the asymmetry of risk realization costs and governance costs.
As far as the relationship between safety risks and the development of the Low-altitude Economy is concerned, the complete logical chain of risk evolution suggests an interaction with the development of the Low-altitude Economy itself. First, the development of economic efficiency leads to airspace reform. Secondly, airspace reform leads to changes in the powers (rights) structure. Thirdly, the diversification of powers (rights) leads to the evolution of safety risks. Finally, the emerging safety risks hinder the development of the Low-altitude Economy. However, China’s existing legal system, governance mechanisms, and governance tools cannot effectively regulate and prevent new safety risks caused by the Low-altitude Economy. With regard to the legal system, the existing legal system lags behind practice at the macro level, and some of the rules are characterized by rigidity. In addition, some of the new legal documents are fragmented and even contradictory. In terms of governance mechanisms, there are problems such as chaotic governance institutions, unclear responsibilities and a single structure of governance bodies. In terms of governance tools, there are still problems such as difficulties in law enforcement and high enforcement costs.
The concept of Agile Governance aims to change the way policy operates in the fourth industrial revolution, and it is characterized by more progressive features. First, it is responsive. Agile Governance is more time-sensitive than the traditional plan-based policy-making approach. On the one hand, Agile Governance places more emphasis on rapid response to the object of governance and real-time optimization of governance behaviors, thus achieving the dual efficacy of immediate handling and risk prevention. On the other hand, Agile Governance can also realize the continuous iteration of governance policy and governance itself. Secondly, the multi-stakeholders of governance. Agile Governance advocates the adoption of a new paradigm that goes beyond government governance and allows more stakeholders to participate in governance. As a policymaker, the government should share the “workload” of constructing, monitoring and optimizing the governance system or policy with private entities and citizens’ groups in order to realize the checks and balances among different stakeholders and to make the process of policy-making and the policies formulated more inclusive and human-centered. Agile Governance’s characteristics of rapid response, multi-stakeholders, and continuous iteration reveal its natural interrelationship with emerging safety risks.
In order to promote the high-quality and sustainable development of the Low-altitude Economy on the basis of effective prevention of emerging safety risks, firstly, the construction of “hard law” and “soft law” should be coordinated to help construct a governance legal system that balances economic development and safety protection; secondly, the powers and functions of the main public governance authorities should be clarified and synergy should be strengthened, and the effectiveness of the autonomy of other multi-stakeholders should be emphasized; and thirdly, it is necessary to innovate governance tools by improving infrastructure and promoting the integration of technological tools in order to achieve mutual good governance of emerging safety risks.
In the increasingly tense situation of international relations, national science and technology security, which is closely related to national security and major interests, has been put on the important agenda. Then, how to evaluate national science and technology security, so as to provide a scientific basis for government decision-making? Some existing papers have studied national science and technology security assessment or technology sovereignty assessment, but they have not fully reflected the influence of foreign countries on national science and technology security, which shows that the relativity of security has been ignored. Therefore, the assessment of national science and technology security should be analyzed from the perspective of comparison between countries, so cluster analysis method is introduced to this study. The primary indicators used in this cluster analysis include frontier technology readiness index, patent technology security index in key fields and comparative advantage index of high-tech products, and they all have their own secondary indicators. Generally speaking, countries with more advanced science and technology and deeper participation in globalization have a greater impact on foreign science and technology security, and are also more seriously affected by the scientific and technological competition between China and the United States. Hence, this study selected 19 countries in the G20, which can represent the world's major countries, as the comparison objects.
In this study, the SPSS27 software was used to conduct a statistical analysis of the relevant data of the three indicators in these 19 countries. Then, ANOVA test method was used to determine the minimum number of reliable clusters in the three indicators, and the elbow rule was combined to select the optimal number of clusters. Finally, the results of cluster analysis reveal the state of national science and technology security of each country. Among them, five countries, including China, India, Mexico, South Africa and Turkey, are in the category of less readiness for frontier technology, higher security of patented technologies in key areas, and stronger comparative advantages of high-tech products. The United States alone occupies a category of the best performance in the security of patented technology in key areas and frontier technology readiness, and a middling performance in the comparative advantage of high-tech products. France, Germany, Italy, Japan, South Korea and the United Kingdom are in the category characterized by the strongest comparative advantages of high-tech products, a higher level of frontier technology readiness, and a medium level of patent technology security in key areas. Argentina, Australia, Brazil, Canada, Russia and Saudi Arabia fall into the category of moderate readiness for frontier technology, low security of patented technology in key areas, and the weakest comparative advantage of high-tech products. And Indonesia is the only country in the category of the lowest level of patent technology security in key areas and frontier technology readiness, and relatively weak comparative advantage of high-tech products.
The above different states of national science and technology security provide directional guidance for these countries to formulate corresponding policies. For example, the United States needs to improve its comparative advantage in high-tech products, and China desperately needs to improve its readiness for frontier technologies.
An orderly mobility of talents in science and technology think tanks helps to enhance the research level and steady development of think tank institutions. This paper analyzes the personal resume information of 551 talents in science and technology think tanks in China based on CV (Curriculum Vitae) analysis method, carrying out a study on the scale, mobility paths and characteristics of science and technology think tank talents with career mobility experiences. Furthermore, Poisson regression and logistic regression are applied to figure out mobility influencing factors. It is found that there exist certain barriers to the mobility between different types, and science and technology think tank talents with career mobility experiences overall show a tendency to flow to public service units; in terms of mobility paths, there show a trend of eastward flow, manifesting as the majority conducting intra-city mobility in the eastern regions while the majority of inter-provincial mobility towards eastern regions in others; in terms of mobility frequency, the younger the career age is at the time of the first mobility, the more career mobility occurs afterwards; 6.72% of the talents in science and technology think tank talents have “Revolving Door” mobility experience, and it is further found that there is a positive correlation between the probability of “Revolving Door” mobility and the number of career mobility.
As the modes of the “Belt and Road” Enterprise Technology Standards Alliance (BRTSA) are diversified and have significant differences, choosing alliance modes according to the context is important for the high-quality development of alliances, and also a significant theoretical issue that needs to be studied urgently. Based on the Technology-Organization-Environment (TOE) framework, the study introduces fuzzy set qualitative comparative analysis method, taking 60 BRTSAs as samples, to explore the matching relationship between specific alliance contexts and modes.
The following important conclusions were obtained from the study. Firstly, single contextual elements at the technical, organizational, and environmental levels do not constitute the necessary conditions for the standard co-consultation and application mode, the standard shared and complementary mode, and the standard iterative upgrading mode. Organizational relevance is a necessary condition for forming the applicability context of the standard co-construction R&D mode. Second, the “organizational similarity alongside standard differences” and “technological similarity in the face of environmental differences” scenarios are applicable to the standard co-consultation application mode; the “strong technological foundation and significant standard differences” scenario is applicable to the standard co-construction R&D mode; the “technological similarity with lacking environmental differences” and “technological similarity and organizational connection” scenarios are applicable to the standard shared complementary mode; the “technological similarity and environmental differences” scenario and “technological similarity, environmental differences and organizational correlation” are applicable to the standard iterative upgrade mode. Third, based on the BRTSA context, the dominant logic is deduced and then matched with the alliance mode. It is found that when technology leading is the dominant logic, it is suitable for the standard co-consultation application mode; when technology innovation, it is suitable for the standard co-construction R&D mode; when technology integration is the dominant logic, it is suitable for the standard shared complementary mode; when technology evolution is the dominant logic, it is suitable for the standard iterative upgrade mode. Fourth, “technology similarity” and “high standard distance” are the most common in the alliance context configurations, and have a wide influence on the choice of BRTSA modes.
This paper has the following theoretical contributions. First, it introduces the TOE framework into the research of BRTSA mode applicable contexts, further expanding the specific connotations and application contexts of the TOE framework. Second, it analyzes and verifies the complex relationship between the alliance context and the alliance mode, refines the applicable context configuration for different modes, and enriches and improves the theoretical connotation and analysis framework of BRTSA modes. Third, it refines the inherent logic of BRTSA's “alliance context - dominant logic - alliance mode”, and promotes the development of alliance dominant logic related research.
This paper puts forward the management suggestions. First, it is necessary to comprehensively and systematically analyze the alliance context and select an adaptive alliance mode to promote the realization of alliance value. Second, focus on the universal role of technology similarity and high standard distance in the alliance context, and actively layout and use various context elements to promote high-quality alliance development. Third, according to changes in specific alliance contexts, we should promote the dynamic evolution of alliance modes ly to enhance the adaptability of alliance modes.
As global fertility rates continue to decline and population aging accelerates, many countries, including China, have introduced pro-natalist policies aimed at encouraging higher birth rates. Childbearing, however, significantly affects women's labor allocation between family responsibilities and professional development, exacerbating gender disparities in the labor market. This study focuses on the academic sector, utilizing data from the Social Science Research Network (SSRN), an open-access platform for rapid publication of preprints. Drawing from a panel dataset covering 14 periods from 2009 to 2022, the study includes 888 female and 2,296 male researchers. Using China’s universal two-child policy as a quasi-natural experiment, we apply difference-in-differences (DID) and difference-in-differences-in-difference (DDD) methodologies to evaluate the policy’s gender-differentiated effects on research productivity among male and female researchers. The findings reveal that the two-child policy exacerbated gender inequality within academia, particularly in terms of research productivity. A heterogeneity analysis further elucidates how the policy's impact varied across different groups of researchers. First, in economically underdeveloped regions, female researchers experienced a more pronounced decline in academic productivity compared to their male counterparts. This effect can be attributed to the dual pressures of traditional cultural expectations and resource scarcity. Women in these regions often face greater constraints, with limited access to both academic resources and support systems, leading to a more significant negative impact on their professional output. Second, researchers without international collaboration were more acutely affected by the policy’s gender-differentiated impacts. In contrast, international collaboration typically brings exposure to diverse cultural perspectives that promote a more inclusive attitude toward work-life balance and childbearing. Moreover, those engaged in international collaborations benefit from richer academic resources and a more favorable publication environment, which can mitigate some of the challenges posed by family responsibilities. Conversely, researchers without international ties face additional challenges due to limited resources and a narrower professional network, further amplifying the negative effects of the two-child policy. Third, compared to researchers at elite universities, female scholars at non-elite institutions were more vulnerable to the policy's negative effects. The resource disadvantages faced by these women made them more sensitive to policy changes, presenting significant barriers to their career development. These women are more likely to be influenced by traditional gender norms, and the added pressure of family responsibilities and societal expectations often leads them to prioritize childbearing decisions, which in turn results in less time and energy for academic competition and career advancement. This exacerbates the productivity gap between male and female researchers in such institutions. The results from the difference-in-differences-in-difference (DDD) model show that the academic environment had a stronger mitigating effect on female researchers compared to male researchers, highlighting the importance of institutional support in addressing gender disparities. Supplementary analyses further demonstrate that the gender gap in research productivity was affected across both the quantity and quality dimensions of academic output. Robustness checks, including continuous treatment analysis of the policy intervention, support these findings. This study provides valuable data and insights for policymakers, offering evidence-based recommendations for future fertility policies and talent management strategies within higher education. By promoting the positive impacts of fertility policies and enhancing overall research productivity, this study contributes to the advancement of gender equality in academia.
Contemporary society is becoming increasingly digitized, with data permeating nearly every aspect of life. The widespread use of data technologies in the knowledge economy and social decision-making has elevated data to a central role in both knowledge production and intelligent decision-making. This transformation reshapes the relationships between humans and machines, humans and knowledge, and humans and intelligence. At the same time, it signals that data is assuming a decisive role within the knowledge system, gradually establishing an authoritative presence in the realm of cognition—one that is often accepted without scrutiny. However, the authority of data fundamentally differs from that of traditional experts. Expert knowledge is grounded in rigorous systems of production and verification, characterized by causal reasoning and repeatability. In contrast, data is often criticized for its reliance on inductive methods and inconsistent quality, which raises concerns about its reliability as a source of knowledge. Furthermore, expert knowledge can bridge the gap between experts and the public through active participation, whereas data-driven knowledge, constrained by technical barriers, often excludes public engagement. As a result, the widespread trust in data may be misplaced, leading to both cognitive and ethical errors. This paper introduces two forms of structural epistemic injustice—“hermeneutical injustice” and “contributory injustice”—to demonstrate how structural biases in data obstruct knowers' understanding of societal and personal experiences. Hermeneutical injustice arises when certain groups lack the necessary conceptual resources to understand and articulate their experiences in social practices, suffering from bias and marginalization in interpretation. Contributive injustice arises when marginalized groups, though capable of developing concepts that reflect their unique social realities, are denied recognition by dominant groups. These suppressions of cognitive diversity result in their exclusion, misunderstanding, and misrepresentation, preventing their full participation in both social and cognitive processes. The digital intelligent society provides new ground for structural epistemic injustice. Data and intelligent technologies significantly expand the cognitive landscape, allowing previously invisible social elements and marginalized voices to emerge through extensive data collection. However, as data is often shaped by specific intentions and biases, it can amplify injustice and discrimination, entrenching and perpetuating inequities. Structural epistemic injustice in the digital intelligent society manifests in three key forms: (1) The invisibility of certain groups in data, resulting from insufficient representation in data collection, excludes marginalized groups from decision-making processes due to a lack of data identity or representation. (2) Bias and discrimination stemming from low-quality data, where issues with data quality and algorithmic processes lead to unjust outcomes for marginalized groups. The opacity and complexity of data-driven decisions hinder understanding and appeal, leaving affected individuals without the means to challenge results. (3) The undue authority granted to data, leading to procedural “justice,” where unjust outcomes are defended as unquestionable due to the perceived infallibility of data, with cognitive inertia causing the dominant group to overlook clear injustices. In data research and practice, data diversity and cognitive pluralism offer potential solutions to structural epistemic injustice. Data diversity improves data quality by incorporating a broader range of perspectives, while cognitive pluralism advocates for the inclusion of diverse non-cognitive values in data-driven decision-making. Together, these approaches can reduce discrimination, promote data justice, and foster social fairness.
At present, technological innovation has entered an unprecedentedly intensive and active period. The uncertainty of technological development, the complexity of cross-border integration, international scientific and technological cooperation and competition, and other factors have brought more challenges to government decision-making and technological governance. As a policy consulting tool, technology assessment can provide high-quality knowledge and strategic intelligence with scientific and forward-looking characteristics. It plays an increasingly important role in government science and technology policy formulation and management decision-making, and has become an important means to support technology development layout, respond to crises, and tackle challenges. The OECD document emphasizes that technology assessment is a key source of strategic intelligence and points out that constantly changing decision-making needs are driving the development of technology assessment. NSF expects to begin building the knowledge base, data, and analytical tools required for critical technology assessment through a one-year National Key Technology Assessment Pilot Network. In the current era of increasingly fierce international competition, it is timely to strengthen technology evaluation for government decision-making. The research team found through a literature review that Chinese scholars only began to explore technology assessment in the early 1980s. Early research mainly focused on international experience analysis, and there was generally less research on technology assessment tools and methods. Therefore, the aim is to explore the connotation, characteristics, evaluation objects, purposes, content, methods, results, and applications of technology evaluation for government decision-making. Based on a comprehensive review of relevant research and cases on technology evaluation, the research team analyzed the connotation of technology evaluation for government decision-making and summarized its four characteristics: comprehensiveness and systematicity, objectivity and accuracy, policy orientation and foresight, and emphasis on stakeholder participation. The research team analyzed and summarized the experience and practices of relevant evaluation practices at home and abroad from three dimensions: evaluation objects and purposes, evaluation methods, evaluation results and usage. This research team also proposed a general technical evaluation methodology framework applicable to government decision-making, including five key stages of evaluation implementation: disassembly of evaluation objects, determination of evaluation dimensions, collection of evidence information, analysis of evidence information, and reporting. Furthermore, within the framework of evaluation methodology, the research team has assembled a series of methods, tools, and techniques discovered in case studies to construct an evaluation methodology system. Based on the practice of evaluating brain computer interface technology, the application of the technology evaluation methodology system has been explained through typical cases. This study fills the gap in relevant research fields in China and provides a methodological and theoretical basis for decision-makers and technology evaluation practitioners to more effectively utilize technology team believes that there is still room for further development and formation of relevant technology evaluation products, methods, tools, and models, as well as the development of technology evaluation talent teams and basic databases for government decision-making. Theory and practice promote each other to enhance the overall capability level of technology evaluation in China.
New R&D institutions, as the testing ground for China's science and technology system reform, have become an important regional innovation force in the bustling construction at the local level. However, the core question of where exactly the 'newness' of these institutions lies remains to be further studied. Grounded in the national innovation system and from the perspective of institutional economics, the article conducts theoretical analysis on new R&D institutions using the concept of transaction costs, and summarizes the institutional models of these institutions in practice through multiple case studies. The research indicates that new R&D institutions innovate through institutional integration, reducing the institutional transaction costs of innovation activities, and increasing the incentive levels for science and technology personnel, thus supporting integrated functional innovation with common technology services and technology transfer incubation as its core. Based on the classification of institutional models, new R&D institutions in local practices exhibit four types: basic research type, technology service type, technology incubation type, and product development type, among which basic research type and product development type institutions deviate significantly from the standard model. This research provides important reference for clarifying the conceptual positioning and functional boundaries of new R&D institutions, and offers important experiential insights for the optimization management of future new R&D institutions.
Realizing the deep integration of the talent chain, innovation chain, and industry chain (referred to as "three-chain deep integration") is a prerequisite and inevitable path for the deep integration of the innovation chain, industry chain, capital chain, and talent chain. It is also an effective means to smooth the virtuous cycle of education, technology, and talent. At present, the degree of integration between the talent chain, innovation chain, and industry chain is insufficient, which cannot effectively play a supporting role in the "deep integration of innovation chain and industry chain". Exploring the theoretical logic, integration status, and improvement path behind the "three-chain deep integration" is of great significance for the construction of a modern industrial system and the development of new quality productivity.
Firstly, this study focuses on the talent chain as a key variable and proposes the scientific connotation of the talent chain, which includes the dimensions of "classification + growth process". From the perspective of talent classification, the talent chain includes different types of talents such as basic scientific talents, skilled talents, management talents, entrepreneurial talents, compound talents, and leading talents. From the perspective of the talent growth process, the talent chain includes three chain structures: First, the education stage: the entire chain of talent cultivation that runs from basic education to higher education; Second, the social work stage: runs through the entire chain of talent identification, cultivation, introduction, utilization, guarantee, motivation, evaluation, and mobility; Third, career development stage: runs through the entire chain of basic skilled talents, advanced professional talents, and leading top talents. Secondly, this study clarifies the theoretical logic of "three-chain deep integration". To better achieve "deep integration of the three chains", special attention should be paid to: the talent chain matches specialized talents for the innovation chain and the industrial chain, the flow and optimization of talent elements in different chains, the promotion of talent growth by the innovation chain and the industrial chain, and the coordinated development of the talent chain, innovation chain, and the industrial chain with external chains. Then, this paper analyzes the existing issues in China's practical implementation of this integration, including insufficient policy coordination and collaboration, the integration of science, education, industry, and education is "not deep enough", the circulation of innovative elements in industry-university research and application being hindered, and the lack of sound talent evaluation and incentive mechanisms. Finally, this study proposes improvement paths and strategic recommendations for the "three-chain deep integration": (1) Strengthen the top-level planning and institutional innovation for promoting the integration of talent innovation and industry. (2) Establish a mechanism for condensing talent training objectives for the key needs of deep integration of the innovation chain and industrial chain. (3) Promote the cross-chain flow of scientific and technological talent resources, and form a new pattern of co-education, sharing, and sharing. (4) Build a talent evaluation system and dynamic monitoring platform that meets the requirements for the development of new quality productivity. (5) Create a healthy ecosystem conducive to the deep integration of talent chain, innovation chain, and industry chain.
Under the background of the accelerating evolution of the once-in-a-century changes, the increasingly frequent adversity events and the unpredictable business environment have posed great challenges and threats to the digital innovation practice of enterprises. In order to effectively resist the uncertainty and disruptive impact from the outside world, many enterprises have shaped the ability to flexibly cope with decline crises in the process of digital innovation and recover, develop and evolve rapidly from the risk of failure. This paper proposes the concept of digital innovation resilience to represent this phenomenon. On this basis, clarifying the specific connotation of digital innovation resilience, and clarifying the measurement method and evolution model of digital innovation resilience are the internal requirements for building a self-reliant digital innovation system and realizing the goal of Chinese-style modernization. Firstly, the paper starts with organizational resilience, and on the basis of revealing the connotation of innovation resilience, it extends the concept of digital innovation resilience and points out the basic characteristics of it. Secondly, the time series data of digital technology patent application is used to replace the immediate response of digital innovation to external shocks, and the core variable method is used to measure enterprises’ digital innovation resilience. Finally, statistical indicators were extracted and dimensionality was reduced for the time series data of enterprise digital innovation resilience by using time series feature engineering. In combination with K-means clustering algorithm, enterprises with similar evolutionary trends of digital innovation resilience during the sample period were divided into groups, so as to identify four evolution modes: random oscillating type, weak growth type, late catch-up type and core leading type. The above research can not only provide a scientific basis for correctly evaluating the level of enterprises' digital innovation resilience, but also provide useful inspiration for the academic community to explore the differentiated improvement path of enterprises' digital innovation resilience based on different types of evolution models.
With economic growth and industrial upgrading, scientific and technological innovation is a key driving force in addressing global challenges and enhancing international competitiveness. Technology leading enterprises promote the transformation of scientific and technological achievements into real productivity, and have become the main force to realize technological breakthroughs and help innovation-driven development. It is not only important to focus on the direct path of enterprises' breakthroughs in key core technologies, but it is even more important to clarify the process of building enterprise innovation ecosystems behind the technological breakthroughs. And the enabling role of the national innovation system in this process needs to be explored.
This study is a longitudinal single-case study of a Chinese medical device company, Myriad Medical, and collects primary and secondary data from over 30 years since its establishment. Based on the theories of ecosystem evolution and dynamic capability theory, this study constructs an evolutionary path of corporate innovation ecosystems and explores the evolution and interaction between the national innovation system and corporate innovation ecosystems at different stages. The study will integrate the existing innovation ecosystem related theories and explore the evolution of the innovation ecosystem in the key core technology breakthrough of the leading science and technology enterprises according to the analytical framework of "resource allocation situation - innovation body structure - value proposition change", which enriches the research on innovation ecosystem theory. It enriches the theoretical research on innovation ecosystem. At the same time, it clarifies the enabling role of the national innovation system from the dynamic capability dimension of "identification-integration-reconstruction" of enterprises.
In the process of technological breakthroughs, the innovation ecosystem of enterprises has undergone an evolution path of "demand-driven independent production model - open innovation network for technological breakthroughs - multi-agent innovation network for brand building - collaborative innovation ecology with new quality agents for sustainable development". The state enhances the improvement of the enterprise innovation ecosystem through a top-down path of "traction - driving - empowerment - co-creation", while enterprises respond to the national innovation system from the bottom up with a logical process of "identification - integration - reconstruction". The key to this coupling lies in the "people-centered" approach.
The study recommends, first, that policy making should increase support for science and technology leading enterprises. The government should support the development of science and technology leading enterprises through policy guidance and resource allocation, enhance their technological innovation and market guidance capabilities, and promote synergistic cooperation among multiple actors. Second, in the construction of the national innovation system, it is necessary to play the role of top-down leadership and emphasize the bottom-up innovation drive of leading enterprises, so as to form a top-down interactive innovation ecology. Third, the national innovation strategy and the innovation activities of enterprises should always pay attention to the needs of the people, focusing on improving the quality of products and services to meet the needs of social development and people's lives. Fourth, while realizing the transformation of technological achievements, leading science and technology enterprises should pay more attention to the construction of a data-driven innovation ecology, so as to enhance the sustainable development capability of the enterprises themselves and the industry.
As a complex product system, new energy vehicles have brought disruptive changes to existing transportation modes and energy consumption structures, especially in the context of addressing climate change and promoting green development trends, playing a crucial role in continuously leading the transformation and upgrading of China's automotive industry. However, despite the significant achievements in the development of the new energy vehicle industry, a retrospective analysis reveals that its technological level has been constrained by multiple factors, such as the absence of core technologies, low-end production capacity, and fraudulent subsidy claims by enterprises. These factors have long maintained a fixed gap with cutting-edge technologies, positioning the industry as a follower struggling to achieve a leap forward and deeply mired in a "middle-technology trap." This not only results in the idle waste of government fiscal funds but also further dampens the enthusiasm of market entities and end-consumer participation, ultimately hindering the healthy development of the new energy vehicle industry. Based on this, analyzing the theoretical mechanism for the new energy vehicle industry to bridge the technological gap and achieve technological catch-up in the short term becomes an important issue that drives China to transition from a major automotive country to a powerful one and inspires other industries stuck in late-developer traps to pursue technological catch-up.
Addressing this issue, this paper first systematically argues the characteristic facts of the new energy vehicle industry falling into the "middle-technology trap" in its early stages by combining aspects of government regulation, market development, and industrial chain support. It identifies that non-unified technical standards, pervasive local protectionism in the institutional environment, insufficient competitive mechanisms, and outdated market environments, along with an industry chain system that only masters low-end technological processes, are the main reasons why new energy vehicles face low levels of core technology R&D, an extensive but not strong industrial chain, and a lack of autonomy. Considering that mainstream technology catch-up theories like reverse A-U cannot effectively explain the phenomenon of rapid industrial catch-up, this paper, based on the existing literature on industrial technology transcendence paths and focusing on the phenomenon of rapid development in the new energy vehicle industry in the short term, attempts to reveal the mechanism of technological catch-up for new energy vehicles as a complex product system from the perspective of dynamic stage evolution based on the logical chain of "goal-action-outcome." Specifically, facing the predicament of being stuck in the "middle-technology trap," this paper, in conjunction with industry-relevant background information, finds that the technological catch-up process of the industry undergoes three stages and forms a new catch-up model: core component industrialization achieved through alliance-led entity coordination by integrating elements and constructing standards; application scenario diversification achieved through policy-empowered process coordination by establishing and optimizing processes; and ecosystem maturation achieved through market-led strategic coordination by leading competition and extending value. Throughout the catch-up process, the government, market, and industry chain as the boundary conditions of industrial development, jointly drive the industry to bridge the technological gap by leveraging institutional advantages, scale benefits, and support advantages.
The new innovation catch-up model proposed in this paper differs from existing technology catch-up theories formed in strongly administratively controlled and monopolistic market areas, providing a robust theoretical supplement to the literature on bridging technology gaps in open market environments. It further expands the innovative evolutionary path for late-developer industries to achieve technological catch-up, providing a theoretical basis for revealing the basic mechanisms and principles of complex product systems to achieve rapid catch-up.
The process of enterprise digital transformation is the reconstruction of production modes, business models, and industrial forms, as well as the promotion of enterprise core values. How to better implement digital transformation and enable high-quality development in traditional manufacturing industries has always been a challenging issue in both practice and theoretical research of Chinese manufacturing enterprises' transformation. Based on theoretical review and practical induction, this research classifies feasible paths of enterprise digital transformation into three orientations: technological production, business models, and organizational structure. Using text mining methods, this research classifies Chinese manufacturing enterprises.Using the entropy weight-TOPSIS comprehensive evaluation method, this research evaluates the performance increments brought by different transformation paths, and explores the impact of different transformation paths on comprehensive enterprise performance based on the Bayesian linear regression model. The research findings show that the digital transformation path most favored by sample manufacturing enterprises is business model-oriented; however, the technological production-oriented digital transformation path has the most significant positive impact on comprehensive enterprise performance growth, being the source of long-term competitive advantage for manufacturing enterprises. This research expands the technical methods and theoretical achievements in the field of digital transformation research, providing theoretical support and path references for the digital transformation and upgrading of manufacturing enterprises in China.
Existing research on scientists’ trust not only neglect to pay attention to the transformation of scientists’ trust from normal society to abnormal society, but also fail to categorize the objects of scientists’ trust clearly. Based on the existing research, this paper divides scientists’ trust into two dimensions: moral character and ability. This article using a multi-year cross-sectional survey data to analyze the changes of scientists’ trust and its influencing factors under different social conditions. This paper found that, people’s trust in the competence of scientists is higher in both social conditions; public trust in the competence and moral character of scientists has increased significantly compared to normal society. Third, however, this increase is highly heterogeneous and comes mainly from increased trust in scientists among people with scientific interest and high scientific literacy. The research findings of this paper have effectively enriched the research of scientists’ trust issues.
This study delves into the intricate interplay between managers’ overconfidence, varying degrees of managerial discretion, and corporate investment efficiency within the context of global economic transformation and a progressively complex market environment. Drawing on a comprehensive dataset spanning 2010 to 2019 from Chinese A-share listed companies on the Shanghai and Shenzhen stock exchanges, our research sheds light on several pivotal findings.
Firstly, the study underscores the detrimental impact of managers’ overconfidence on corporate investment efficiency, manifesting as either overinvestment or underinvestment. This finding underscores the crucial role of psychological traits in shaping corporate decision-making processes, challenging the assumption of complete rationality often assumed in traditional economic models. Specifically, the research reveals that overconfident managers tend to overestimate their abilities and project success rates, leading to distorted investment decisions.
Secondly, we uncover significant variations in the negative consequences of managerial overconfidence across different types of managerial discretion environments. In settings characterized by high external environmental discretion, notably in resource-rich market conditions, the adverse effects of overconfidence are mitigated in overinvested firms. Conversely, in firms exhibiting underinvestment, the moderating effect of the market environment remains insignificant. This observation underscores the mitigating influence of a favorable market environment on the decision-making biases of overconfident managers. On the other hand, when internal organizational discretion is constrained, the overall negative impact of managerial overconfidence diminishes, highlighting the constraining effects of organizational structures and internal norms on managerial behavior. Notably, special situational discretion, such as enterprise ownership and regional institutional environments, fails to exhibit a pronounced moderating effect, potentially attributed to the intricate interplay of multiple factors and the increasing convergence of market conditions.
Thirdly, our analysis underscores the pivotal mediating role of risk-taking behavior in the relationship between managerial overconfidence and investment efficiency. Overconfident managers, driven by their inflated self-assurance, tend to undertake higher levels of risk in pursuit of greater returns. This enhanced risk-taking, while potentially fostering innovation and competitiveness, can also lead to suboptimal investment decisions and a subsequent decline in investment efficiency. Our empirical results robustly support the transmission mechanism of “overconfidence - risk-taking - corporate investment efficiency,” elucidating the indirect pathways through which psychological biases manifest in corporate financial outcomes.
Collectively, this study contributes to the growing body of literature examining the intricate relationship between managers’ psychological traits and corporate investment behaviors. By integrating managerial discretion as a critical moderating factor, our research offers novel insights into how firms can optimize their investment decisions amidst a complex and dynamic economic landscape. Practical implications include emphasizing the importance of assessing managerial psychological profiles during the hiring process, integrating psychological trait development into training programs, and establishing robust decision-making, evaluation, and monitoring mechanisms to mitigate the risks associated with managerial biases. Furthermore, our findings underscore the significance of tailoring managerial discretion frameworks to balance creativity and risk management, ultimately facilitating high-quality economic development and corporate sustainability.
With the escalating uncertainty of the entrepreneurial environment, the importance of recovering from setbacks and the significance of entrepreneurial team resilience has become increasingly prominent. Entrepreneurial team resilience refers to the collective capacity of a team to positively respond to adversity, effectively recover, and sustain its operations when its members encounter entrepreneurial difficulties together. In today’s rapidly changing business landscape, where risks and challenges abound, the resilience of an entrepreneurial team is crucial. It not only determines how well the team can adapt to unexpected obstacles but also shapes its long-term success and sustainability. When faced with setbacks, a resilient team is able to maintain morale, adjust strategies, and find new opportunities for growth. According to the team interaction perspective, combined with the research question of "how to build entrepreneurial team resilience and how it affects entrepreneurial growth", this study constructs a theoretical process model of entrepreneurial team resilience development in entrepreneurial project failure context. The findings of the study reveal a nuanced understanding of the development of entrepreneurial team resilience and its impact on entrepreneurial growth. In the initial stage, it becomes evident that situational utility plays a pivotal role in shaping the team’s resilience. As external situational factors and internal team dynamics intersect, they jointly facilitate the interactive evolution of entrepreneurial team resilience. This interplay highlights the importance of aligning external conditions with internal capabilities to foster resilience. In the second phase, the transformation of entrepreneurial team resilience into practical utility takes place. Specifically, the resilience of the team triggers a collective cognitive reappraisal, encouraging members to reassess challenges and opportunities from a new perspective. This cognitive shift, in turn, s collaborative action revolution, where the team works together to devise innovative solutions and strategies to drive entrepreneurial growth. Finally, in the third stage, the impact of entrepreneurial team resilience on entrepreneurial growth is manifested in two distinct outcomes: coordinated adaptation and jump development. Coordinated adaptation refers to the team’s ability to adjust its operations and strategies in response to changing market conditions and environmental pressures. On the other hand, jump development signifies a significant leap forward in the company’s growth, often achieved through the successful implementation of innovative ideas and strategies facilitated by the team’s resilience. Collectively, these findings provide a comprehensive framework for understanding how entrepreneurial team resilience evolves and how it can drive positive outcomes for the business. By fostering resilience, entrepreneurs can empower their teams to navigate challenges, seize opportunities, and ultimately achieve sustainable growth. Findings show the specific path of entrepreneurial team resilience from construction to utility transformation and then generate impact mechanism, enriching the research level of resilience in entrepreneurship field, providing inspiring references for crisis response of entrepreneurial teams. Our findings contribute to the understanding of how entrepreneurial team resilience is built from the perspective of team interaction, and clarify the specific process by which entrepreneurial team resilience translates the effectiveness of resilience into entrepreneurial growth through collective cognition and team action. This finding fully demonstrates the nature of team interaction underlying entrepreneurial team resilience and provides a comprehensive perspective for understanding the holistic development process of entrepreneurial team resilience.
Based on the analytical framework of the expansion of technological prospects, two-dimensional structural transformation of economic complexity, and breakthrough of the "stagnation trap" of middle-income countries, this paper constructs a set of network indicators reflecting the evolution characteristics of product space structure. Using the export products data of 133 countries from 1962 to 2019 obtaining: (1) Measuring the " Prospect coefficient for technological upgrading of Potential Advantageous Products" yields information on the national capability accumulation, which is correlated with the country's economic complexity to obtain a visualization of the non-linear evolution of technological prospects. The "S" curve formed shows that middle-income countries are facing a jump in capability from irrelevance to relevance between the expansion of technological prospects and economic complexity, and only very few countries can cross the sparse zone in the middle part of the curve, climbing from the bottom to the top of the curve, and ranking among developed countries. China, like Japan and South Korea, is one of the few countries that have caught up and moved out of the sparse zone in the middle of the curve. (2) On the basis of measuring the two-dimensional structural indicators of product diversity and heterogeneity in the economic complexity of 133 countries, a comparison between China, Japan, and South Korea reveals that China is currently undergoing a two-dimensional structural transformation of economic complexity, similar to what happened in Japan and South Korea when they broke through the "stagnation trap" and entered the high-income countries, and the product heterogeneity index has been greatly improved during the deep structural adjustment, but the two-dimensional transformation from product diversity to heterogeneity has not been completed yet. (3) By visualizing the four-phase evolutionary characteristics of China, Japan and South Korea's product space and targeting the progressive capacity of government policies behind it, we can provide a decision-making basis for China to successfully complete the two-dimensional structural transformation, expand its technological prospects and break through the "stagnation trap" to realize high-quality development under the conditions of the new round of technological revolution and industrial change by drawing on the experience of Japan and South Korea in grasping the "second window of opportunity" for the digital economy and green development technology.
China's female scientific and technological personnel support the "half of the sky" of scientific and technological innovation, but they face difficulties in career development, such as limited upward space and difficulty in balancing career and family. Based on the biographies of 99 winners of the "Young Chinese Female Scientist Award", this paper uses the resume analysis method to construct a multi-factor analysis model that affects the career development of young female scientific and technological talents, and deeply excavates the career development characteristics of outstanding female scientific and technological talents from the data level. The results show that although the scientific research environment of female scientific and technological workers has improved, the gender differences in the scientific research field, the discipline and geographical distribution of talents still exist. The diversity of academic qualifications, academic structure and career experience is conducive to the career development of young female scientific and technological talents. It is suggested that the government and universities should establish social capital to support female scientific and technological talents, break down disciplinary and geographical barriers, adopt a diversified training model, and create a more inclusive and diversified scientific research ecology. Female scientific and technological workers should grasp the critical period of career development and balance deep accumulation and moderate mobility to promote career development.
