Technology security has become a key variable that affects China's position in the new international landscape, and is the key to determining the country's future and competitive advantage. How to resolve crises and seize opportunities at the intersection of historic changes in China urgently needs to take the first step in technology security. There is relatively little research in the field of technology security in China, and there is a lack of foreign experience for reference. Research on how to maintain and ensure China technology security has become a sparsely populated "wilderness", and crossing the wilderness requires a directional compass. Therefore, based on a comprehensive study of literature related to technology security, this article combines bibliometric analysis methods to analyze the disciplinary characteristics, trends, and thematic context of technology security research, aiming to present the research landscape , and proposes a technology security research framework that follows the tracing of risk issues, goal and bottom line analysis, governance system and path construction.
First-tier cities (such as Beijing and Shanghai) are currently grappling with the increasingly pressing challenge of talent outflow. Effectively retaining talent, particularly in high-tech fields, has emerged as a critical issue that cities must urgently address. While existing research predominantly focuses on attracting talent inflow, a comprehensive analysis of long-term talent retention strategies remains insufficient. Although some studies have begun exploring the relationship between urban characteristics and individuals’ intention to stay, a systematic theoretical model encompassing various factors has yet to be fully developed. The decision of talent residence involves a complex process of comprehensively considering the multi-dimensional urban factors, including economy, society, culture, and living environment. To gain a deeper understanding of talent retention, it is essential to comprehensively examine the diverse urban attractiveness factors that contribute to talent retention and the mechanisms by which they impact talent.
In order to answer the above questions, this research constructs a research model that links the perceptions of urban attractiveness factors and talents’ intention to stay. Specifically, based on the theory of environmental psychology, this paper introduces well-being as the mediating mechanism to explain how the perception of urban attractiveness factors (including talent policy, economic development, cultural atmosphere, and living environment) affect talents’ intention to stay, because the environment can shape individual psychological well-being and then their attachment to the environment.
To empirically validate this model, this research adopts a mixed-methods approach, combining quantitative surveys with qualitative interviews. In the quantitative phase, we distributed questionnaires to 1200 high-tech employees, utilizing structural equation modeling for analysis. Subsequently, we conducted face-to-face semi-structured interviews with 11 high-tech employees to further validate and interpret the quantitative findings, enhancing the reliability and depth of our conclusions.
This study yields several key findings. Among the four urban attractiveness factors, only the perception of living environment has a significant direct impact on talents’ intention to stay. The higher the individual’s satisfaction with the urban living environment, the stronger their intention to stay. Further investigation of the mediating effect shows that individuals’ perception of urban talent policy, economic development, and living environment indirectly affect talents’ intention to stay by affecting their well-being, where the perception of living environment has stronger explanatory power than other factors. Furthermore, while individuals’ perception of living environment and economic development has a significant positive impact on well-being, the perception of talent policy has a relatively weak impact on well-being, and the perception of cultural atmosphere has no significant impact on well-being. We further explain the differentiated effects of different attractiveness factors based on interview data analysis.
This research makes the following contributions. Theoretically, it interprets urban attractiveness factors from the perspective of individual subjective perception and systematically explores the impact of four key perceived urban attractiveness factors on talent intention to stay. This enriches the theoretical framework for studying retention intentions. Furthermore, the paper introduces well-being as a mediating mechanism, revealing the direct and indirect mechanisms through which the four urban attractiveness factors influence talent intention to stay. Practically, cities can adopt diverse measures to reduce talent outflow, with a particular focus on enhancing the urban living environment. When formulating and implementing policies, policymakers can fully consider the subjective perception and interpretation of policy effects by the audience. Finally, the well-being of talent in the city has become a critical factor influencing their residency decisions, warranting careful attention from city managers.
Nowadays, the involvement of countries in the global value chain （GVCs） has become a crucial objective for achieving economic upgrading. However, it remains uncertain whether the positive social outcomes of successful economic upgrading can be equally distributed among countries and whether they can be equitably transmitted to various social strata within countries. We explore the mechanisms by which functional upgrading in global value chains affects both inter-country and intra-country inequality. It provides a new empirical assessment of the unequal appropriation of value and social outcomes that stemming from divergent upgrading prospects of the world's global headquarters and peripheries. The results show that, firstly, compared to production functions within GVCs, upstream and downstream functions within GVCs, which are the most intensive in intangible assets, possess the greatest value-adding potential and are more conducive to reducing inter-country inequality. Secondly, the positive economic outcomes resulting from upstream and downstream functional upgrading within GVCs have not translated into more equitable income distribution internally. However, focusing on production functions within GVCs is more beneficial for alleviating intra-country inequality. Finally, from the perspective of impact mechanisms, GVCs power and effective structural change are the respective channels through which functional upgrading within GVCs affects inter-country and intra-country inequality relationships. The existence of knowledge monopoly capitalism in upstream and downstream functions of GVCs, by establishing monopolistic power within GVCs, further creates disproportionate value distribution for actors occupying these functions. Meanwhile, the upgrading of upstream and downstream functions in GVCs negatively impacts income inequality by promoting effective structures changes in domestic and widening skill premiums. Those findings provide empirical evidence for policy recommendations aimed at reducing inter-country inequality and achieving more equitable domestic income equality through the promotion of functional upgrading within GVCs.
Achieving governance at source, systematic governance, governance in accordance with the law, and effectively serving the needs of high-quality economic and social development are important issues for the modernization of the government's data security governance system and governance capacity. Using data life cycle and social capital theories, this study creatively proposes a data security governance theoretical framework that bridges the gap between data life cycle theories with the trust mechanism of "system - organization - society", and then provides an operational mechanism for deconstructing the risks of governmental data governance and realizing effective governance, so as to realize an effective cycle. The research results show that from a horizontal perspective, data life cycle theory provides a systematic logical approach for government data security risk governance and its modernization, which can connect the internal and external governance processes and deconstruct the risks according to the focus of data security at different stages of the whole life cycle. From the perspective of mechanism logic, government data security risk governance is a process of system management "hard power" and trust embedded in "soft power" at the same time, two-pronged process, which requires "both soft and hard". "In order to create a government data security governance system based on "good governance".
New quality productivity is a powerful driving force and supporting force to promote the high-quality development of enterprises. This view has been widely recognized by the community. Accelerating the development of new quality productivity will help enterprises enhance their competitive advantage and realize sustainable development. However, the existing literature focuses on exploring the connotation characteristics and value significance of new quality productivity, and there are few empirical research models to explore its driving forces. Some studies believe that the digital intelligence transformation is the core driving force to lead the innovation and development of enterprises, and whether the digital intelligence transformation can improve the new quality productivity level of enterprises is an urgent topic to be discussed.
Based on the dynamic resource-based view, using the data of China A-share listed companies from 2015 to 2022, this paper empirically analyzes the influence and heterogeneity of digital intelligence transformation on the new quality productivity of enterprises, and tests the mediating role of absorptive capacity and the moderating role of competitive intensity. It is found that: (1) the digital intelligence transformation has a significant impact on the improvement of the new quality productivity level of enterprises, and this conclusion still holds after various robustness tests. (2) the digital intelligence transformation can improve the absorptive capacity and new quality productivity of enterprises, and the absorptive capacity plays a mediating role in the relationship between the digital intelligence transformation and new quality productivity of enterprises. (3) the competitive intensity plays a positive role in moderating the relationship between the digital intelligence transformation and the new quality productivity of enterprises. (4) heterogeneity analysis shows that, compared with state-owned enterprises, enterprises in the central and western regions and in recession, non-state-owned, eastern regions, growing and mature regions can promote the improvement of new quality productivity by implementing digital intelligence transformation.
The theoretical contributions of this study are as follows: first, the existing literature focuses on the connotation characteristics and value significance of new quality productivity, while there are few empirical research models to explore its driving factors. This study examines the influence of digital intelligence transformation on the new quality productivity level of enterprises through empirical research, which not only provides theoretical reference for promoting the transformation of digital intelligence and improving the new quality productivity level of enterprises, but also enriches the empirical research on the relationship between digital intelligence transformation and new quality productivity of enterprises. Second, based on the dynamic resource-based view, the theoretical model of "digital intelligence transformation-absorptive capacity-new quality productivity of enterprises" is constructed, and the intermediate transmission mechanism of absorptive capacity is deeply analyzed, which opens the "black box" in the process of digital intelligence transformation and empowerment of new quality productivity of enterprises. Thirdly, by including the industry competitive intensity at the macro level as a moderating variable, the boundary conditions of the impact of digital intelligence transformation on the new quality productivity of enterprises are further clarified, which is helpful to clarify the complex and diverse relationship between them and enrich the relevant research on the dynamic resource-based view.
In the face of complex and uncertain scientific research activities, the wide application of generative AI tools is leading to a new scientific research paradigm – “AI for Science”.
By inquiring into the scientific research paradigm driven by artificial intelligence, this paper discusses the difference between the scientific research paradigm here and Kuhn’s “paradigm”. According to the current discussion of AI-driven scientific research paradigms, most of the findings are based on the evolution of Gray’s scientific research paradigms. But when we delve into the practice and application of the AI-driven scientific research paradigm, we find that it may not be evolving along the lines that Gray delineates. In addition, Gray’s division is mainly based on the change of scientific research means or methods, but according to the view of scientific practicalism, scientific research activities are composed of three main influencing factors: scientific research subject, scientific research means and scientific research object. Therefore, Gray’ s division has certain limitations, and it is necessary to further clarify the limitations of this classical division.
Then, it further combs the existing historical forms of scientific research paradigm. After sorting out the different historical forms of the four groups of scientific research paradigms, it can be found that the development process from simple science to complex science, and the transformation process from philosophy to natural science, all the elements of scientific research activities have undergone transformative changes. But between physics and chemistry, only scientific methods have changed. On the other hand, natural history and mathematical experimental science have changed the means and objects of scientific research. When reviewing these different scientific traditions in history, it is found that the division of the historical form of scientific research is varied, and different subject positioning, vision and concern will form different division results. Whether it is the change of scientific tradition in a grand perspective or the change of scientific model in a specific field, it provides historical and forward-looking experience for the division of scientific research paradigm in the era of artificial intelligence. The rise of AI for Science has brought about the thinking of the revolution of scientific research paradigm, which provides a new perspective for the division of scientific research paradigm based on the uniqueness of the change of scientific research subjects.
Based on this, two conclusions can be drawn. Firstly, the division of scientific research paradigms has many forms in history, which cannot be confined to the Gray’s division. Second, when sorting out the different historical traditions of scientific research paradigms, it is found that compared with traditional scientific research activities, there are some great differences in research subjects and other aspects of AI-driven scientific research activities, which is a significant change compared with previous scientific research paradigms. Therefore, the scientific research paradigm driven by artificial intelligence can be regarded as a new scientific research paradigm. Therefore, the truly revolutionary division is not only based on the change of scientific research tools, but also on the organic change of various elements in scientific research activities, the most important of which is the change of scientific research subjects, of course, there are also changes in scientific research objects, and artificial intelligence from Artificial Intelligence Generated Content (AIGC) to Artificial Intelligence Generated Science (AIGS).
In the future, with the extensive and deep application of artificial intelligence in scientific research activities, it will likely contribute to a major revolution in the paradigm shift of human scientific research, and it will also more closely interpret the depth and breadth of scientific problems and social phenomena.
Talents are the primary resource for innovation, and scientific and technological talents are the core driving force for national innovation and economic growth. This study delves into the intricate landscape of scientific and technological talents research, utilizing the Web of Science database as a foundation. By integrating bibliometric analysis with the insights from scientific knowledge mapping, the study examines the distribution characteristics, interdisciplinary dynamics, and development trends within the realm of scientific and technological talents research. The results show that the number of related research papers has increased significantly since 2005, highlighting the global emphasis on Scientific and technological talents. The United States dominates the field, while China and other countries also show a positive development trend. Disciplines such as education, information science and librarianship, and multidisciplinary sciences have made significant contributions to Scientific and technological talents research, and emerging topics such as the new crown epidemic, early career education, trust in Scientific and technological talents, citizen scientists, measurement of Scientific and technological talents, social media, and anxiety and stress are becoming hot topics for research. Based on the above research conclusions, four suggestions are proposed. First, it is necessary to build a scientific and complete research paradigm to promote the high-quality development of the theory and practice of scientific and technological talents. The concept lacks a precise definition and measurable standards, and the research itself has not yet formed a systematic and complete theoretical framework. It is suggested to draw on methodologies from disciplines such as education, sociology, management, economics to innovate and standardize the field, thereby constructing a scientific research system that fosters high-quality development in both theory and practice. Second, strengthen interdisciplinary cooperation and innovation in the field of scientific and technological talents research, establish interdisciplinary research platforms, and promote communication and cooperation between different disciplines. Encouraging interdisciplinary academic exchanges through conferences, seminars, and workshops will help focus experts from different fields on issues related to scientific and technological talents. Third, continue to monitor and evaluate the research trends of scientific and technological talents. Bibliometric and informetric methods, such as citation analysis, co-word analysis, and trend analysis, should be employed to quantitatively evaluate hot topics, key authors, institutions, and interdisciplinary collaboration patterns in the field. International comparative studies should be conducted to analyze the similarities and differences in the cultivation and development of scientific and technological talents across different countries and regions, learning from international experiences to propose strategies and measures suitable for each nation's context. Finally, pay attention to the mental health of scientific and technological talents, conduct related research, implement work-life balance policies, and improve the working environment to cope with the challenges brought by global events. Improving the work environment for these talents by reducing excessive competition and work pressure, and offering more career development opportunities and flexibility, is also advised.
There have been two attempts to quantify risk in the history of major risk research in science and technology. The first attempt occurred in the early 1980s, when constructivists represented by B.Fischhoff defined risk as the probability of occurrence of non-preference events through probability theory. The second attempt came in the early 2000s, when the hybridists, notably Martin Peterson, advanced Rasmussen quantification, which defined risk as the statistical expectation of a dangerous event. Unfortunately, the defect of these two attempts is that they focus on the quantitative statement form of major risks of science and technology at the scientific level, but ignore the ethical appeal to the constitutionality of risks. Therefore, the most urgent issue in the current research on Mega-risk in science and technology is to adjust ethical standards on the basis of determining the problem domain of Mega-risk in science and technology, respect the development law of science and technology itself, attach importance to the forward-looking philosophy, break the paradigm barrier, guide scientific and technological innovation under the interdisciplinary paradigm, and thus apply humanistic value and symbiotic value to scientific and technological innovation, strengthen strategies for managing and controlling Mega-risk in science and technology.
In this paper, first of all, we sort out the history of research on Mega-risk in science and technology. By comparing the concept of risk with the West, we find that the connotation of risk is not only the expression of danger and harm, but more importantly, risk represents the reality that things are constantly changing and people's desire to control things is difficult to achieve. The former form quantitative risk research in previous research on risk. The lack of the latter leads to the absence of the qualitative view of risk for a long time.
Secondly, the deficiencies of quantitative research on Mega-risk of science and technology show that the quantitative view of risk has the advantages of simplicity and strong operability, but such a division is easy to ignore or exclude other factors from risk research. In addition, Mega-risk in science and technology gradually show a series of philosophical issues related to human beings. Technological progress, the meaning of nature, and unquantifiable value issues relating to human well-being and sustainability, such as equity, benefits and risks, and ethics of value, are inherently controversial and cannot be agreed upon. The separation and prominence of these value issues positively promoted the formation of qualitative research on risk in the early 21st century.
Thirdly, by examining the Technology Acceptance Model (TAM), we find that for human beings, the main impact of Mega-risk in science and technology is that we cannot predict what harm the new technology will produce, that is, the risk is more destructive than we know. Although risk assessment can alleviate public perception of risk to a certain extent, it is actually a more subjective, valuable and pragmatic process, and managers need to use the results of risk analysis to formulate policies after taking into account public perceptions and attitudes (risk acceptability), legal and political constraints, and value tradeoffs. Therefore, decisions about scientific and technological activities are based on facts in the stage of risk assessment and value in the stage of risk management, which leads to the possibility of bias in the decision-making of major scientific and technological risks.
Finally, the shrinking time required for the evolution of science and technology means that human cognition of technology is facing increasingly severe challenges, such as global warming, nuclear pollution, genetic engineering and artificial intelligence ethical irregularities and other issues put forward higher ethical construction requirements for human beings. Therefore, on the one hand, technology, as an applied science, should be given enough time in the process of its occurrence and development in the stage of scientific and technological innovation to fully demonstrate and test the value contained in science and technology and the facts, so as to avoid the possibility of increasing the negative consequences of technology for users and others due to the rapid completion of the design process; On the other hand, if the goal of technological innovation is the common progress of society and science and technology, then we need to return to Marxism, which is oriented towards the free and universal development of human beings, but at the same time has to recognize the shortcomings and negative phenomena associated with the current scientific and technological progress.
This study investigates how academic-industry collaboration experiences influence scientists' generation of outlier innovations. By analyzing patent data from 1993 to 2018 in China and employing a panel negative binomial random effects regression model, this research examines the impact of academic-industry collaboration on scientists' production of outlier innovations and its boundary conditions. The results indicate that academic-industry collaboration experiences significantly enhance the likelihood of scientists discovering outlier innovations, possibly because such collaboration improves scientists' understanding of industry goals and thinking patterns while also stimulating their attention to the commercialization of research outcomes. Furthermore, scientists' organizational search resources, such as individual innovation experience and collaboration networks, moderate the effect of academic-industry collaboration experiences on the possibility of outlier innovation’s origination. Specifically, the wider the scientists' breadth of innovation experience, the weaker the positive impact of academic-industry collaboration experiences; similarly, the larger the number of indirect collaborators within the organization, the weaker the positive influence of academic-industry collaboration. This study provides a new perspective for understanding the role of scientists in the innovation ecosystem and offers managerial implications for facilitating the transformation of scientific research into technological innovation.
Advancing the green transformation and balancing the economic and social development with ecological environment protection are the essential requirements for Chinese path to modernization. In this process, we need to reveal the principle of innovation system, and analyze the path of green technology innovation, understanding the impact of knowledge elements and capital elements on the green technology innovation in the complex environment. Theoretically, various elements in the innovation system are interconnected to form a network. Therefore, exploring the aforementioned issue from the perspective of complex networks is an effective method. We connect the two dimensions of knowledge elements and capital elements, use the companies listed on Growth Enterprise Market (GEM) of the Shenzhen Stock Exchange as a sample, and collects the data related to venture capital, green patents, financial and operational from 2010 to 2021. We construct a coupling network of knowledge element-venture capital to examine the potential "mobility barrier" and "siphon effect" that enterprises may face in green innovation. The study also explores strategies to overcome these challenges.
The research results show that (1) "mobility barrier" in the green innovation impedes the positive influence of knowledge spillovers on the patent outputs. The industry leaders tend to blockade knowledge, triggering a "siphon effect" that hinders the collaborative R&D in patents; (2) to break through the "mobility barrier" and "siphon effect", introducing the external channels for knowledge resource spillover is crucial. The venture capital network emerges as an effective pathway for the knowledge spillovers, focusing on the investments in SMEs across various industries; and (3) embedding the enterprises within a knowledge-venture capital coupling network can effectively break through the barriers of "mobility barrier" and "siphon effect". On one hand, the venture capital aids in connecting the innovative enterprises in multiple industries, thereby breaking the "mobility barrier". On the other hand, the coupling network decentralizes the industry-leading enterprises, reducing the "siphon effect".
The possible contributions of our study are primarily reflected in three aspects. First, we broaden the perspective on green technology innovation. The current research focus on the output of green technology innovation, and do not thoroughly analyze the innovation strategy as collaborative R&D. In order to incorporate it into the research framework, we also investigate the "siphoning effect" while exploring the "homogeneity barrier". Second, we enrich the scene of exploring the influencing factors of technological innovation. The existing research on constructing networks often focuses on the internal relational networks among the firms, such as cooperative networks and knowledge element networks. These networks typically emphasize the reorganization of existing knowledge without truly incorporating external knowledge. We introduce the venture capital network to investigate the role of external networks in firm knowledge spillovers. Third, we deepen the understanding of how enterprises integrate resources to promote the green technology innovation from the perspective of complex networks. The previous literature often isolates the impact on green technology innovation embedding in a specific network, which are disconnect from reality. Firms need embed in various networks, and integrate the diversified resources in the green technology innovation. Our research eliminates the gap between the green technology innovation and venture capital market, examining the synergistic interaction between the finance and knowledge.
Abstract: R&D innovation is considered an effective means to address climate change. The Beijing-Tianjin-Hebei urban agglomeration plays a critical leading and exemplary role in promoting R&D innovation and reducing regional carbon emissions, especially with industrial enterprises playing a dominant role in R&D innovation. Based on panel data from industrial enterprises in various prefecture-level cities in the Beijing-Tianjin-Hebei urban agglomeration from 2010 to 2020, this study decomposes R&D innovation into two dimensions: efficiency and scale. Through indicator measurement, econometric modeling, and spatiotemporal analysis, this paper empirically investigates the spatiotemporal impact of R&D innovation by industrial enterprises on carbon emission intensity in the Beijing-Tianjin-Hebei urban agglomeration. The research results show that: (1) There are significant differences between R&D scale and innovation efficiency. During the study period, the R&D scale of industrial enterprises in various regions steadily increased, while innovation efficiency fluctuated relatively. (2) The spatial impact of R&D innovation on carbon emission intensity exhibits a two-stage characteristic, with 2016 being the most significant turning point, shifting the significant spatial weight matrix from geographical distance to economic distance. (3) From the scale dimension, there is a time lag effect in reducing carbon emission intensity by expanding the R&D scale. (4) From the efficiency dimension, the short-term impact of innovation efficiency on carbon emission intensity is not obvious; long-term accumulation is required to effectively reduce carbon emission intensity. The study innovatively analyzes the spatiotemporal impact of R&D innovation on carbon emission intensity of industrial enterprises in the Beijing-Tianjin-Hebei urban agglomeration from both scale and efficiency dimensions, exploring their differentiated impact paths. The research results will provide important references for the rational layout of R&D scale and efficiency within China's urban agglomerations and promote regional collaborative carbon reduction.
University scientific researchers are the fundamental drivers of fostering new productive forces and facilitating high-quality development, playing a pivotal role in integrating education, science, and technology while nurturing talents. Since the implementation of the "Double First-Class" initiative, inter-institutional mobility among university scientific researchers has become increasingly frequent and disorderly due to various contributing factors. Instead of solely attributing it to external environmental factors, it is more meaningful and valuable to analyze the impact of individual characteristics on their intention to switch institutions from the perspective of scientific researchers themselves. Consequently, effective measures can be implemented to optimize this situation. This study randomly selected 878 representative scientific researchers from 13 provinces in eastern, central, western and northeastern China to conduct a questionnaire survey on how individual characteristics influence mobility willingness, and conducted descriptive, differential and regression analysis of statistical data. The study found that the overall mobility willingness of university scientific researchers in China is relatively strong, but there are differences in mobility willingness among different individual characteristics. Among them, gender, age, seniority, title, school type, discipline field, and marital status show significant differences in mobility willingness, while education, region, and children's situation do not show significant differences in mobility willingness. Further regression analysis results show the correlation between gender, age, title, school type, discipline field, and marital status with scientific researchers' mobility willingness. Based on this, the study conducted exploratory analysis of the relationship between individual characteristics and mobility willingness in different dimensions, proposed a multi-dimensional and coordinated guiding strategy, and provided targeted suggestions from the government, universities, and scientific researchers to promote the scientific, reasonable, orderly mobility, and sustainable development of scientific researchers.
What factors determine the attention allocation of think tanks? The policy knowledge market in China is currently experiencing rapid development. Think tanks are witnessing substantial growth in terms of institutional size and research output, accompanied by a noticeable surge in knowledge demands from both the government and the public. The widespread adoption of social media has also further bridged the information gap between the supply and demand sides. In this evolving market landscape, the allocation of attention to policy issues has become a pivotal decision-making process for think tanks. Efficiently distributing limited resources across a spectrum of policy issues has a profound impact on the sustainability of think tanks. This article introduces a supply-demand framework to elucidate how think tanks allocate attention to policy issues. In a market environment, think tanks determine the policy issues they focus on, not solely based on their supply-side characteristics but, more importantly, by being responsive to dynamic shifts in external policy knowledge demands. The government and the public, as core actors within the policy system, directly influence think tanks' allocation of attention through their demand signals. We have constructed a novel database to measure think tanks' issue attention in China from 2016 to 2020 by utilizing social media data and text classification algorithms. Leveraging the vast amount of objective data from think tanks on social media platforms in China, we have conducted data collection, cleansing, and analysis over a five-year period. This has resulted in a comprehensive dataset comprising over 230,000 posts published by 204 Chinese think tanks between 2016 and 2020, with a total character count exceeding 250 million. To identify the policy issues that think tanks pay attention to, we have employed the unsupervised topic model, Latent Dirichlet Allocation (LDA), effectively capturing the changes in attention across 25 policy topics within the Chinese think tank community from 2016 to 2020. Subsequently, we have developed an innovative empirical framework that integrates multiple data sources to test the theoretical framework and research hypotheses outlined above. This study collects and combines diverse data sources, including State Council executive meetings and Baidu Index. This research reveals the multifaceted factors influencing think tanks' issue attention, stemming from both supply and demand dynamics. The rapid emergence and growth of the policy knowledge market not only drive think tanks towards professionalization but also underscore the importance of their ability to sense external environmental changes and optimize resource allocation across various policy issues. Think tanks in China are increasingly recognizing the importance of being agile in responding to evolving policy knowledge demands to maintain their relevance and effectiveness. The theoretical contribution of this study primarily lies in several aspects. Concerning think tank research, this paper systematically discusses the driving factors in the policy knowledge production process of think tanks. In the context of issue attention research, this paper expands the scope of issue attention. Last but not least, this study's findings provide valuable insights for policymakers, think tanks, and researchers seeking to understand the evolving dynamics of the policy knowledge market in China.
The nationwide system is a task-oriented system that is independent of the socialist or capitalist system, as well as the planned or market economic system. Research on the foreign experience in implementing the “nationwide” system for technological breakthroughs provides a reference for further improving China’s “nationwide” system in this regard. National strategies best reflect the top-level phased goals and core development needs of a country. Through the construction of Japan’s “nationwide” system and the national strategic evolution relationship analysis framework, specific investigation at different stages of Japan’s “nationwide” system research target, technology, organization mode, summarizes the dynamic development characteristics of Japan’s “nationwide” system, analyze the relationship between the market and the government, the implementation of subject diversified changes, for China's technical research “new nationwide system” to provide reference experience.With Japan’s national strategies in different periods as defining standards, this study delved into the goals, technological fields, and organizational models of Japan’s “nationwide” system for technological breakthroughs during various strategic periods, and summarized the adaptive characteristics between its “nationwide” system for technological breakthroughs and national strategies. Based on the research on the traceability and historical evolution of the term “Nationwide System”in Japan, this paper summarizes its basic characteristics: Matching of technical research models with national strategic goals; Dynamically adjusting the direction of technical research fields; Improving the overall deployment level of the“Nationwide System”for technical research. Moreover, the analysis focused on its specific manifestations in the adjustment of the relationship between the government and the market, the functional positioning of diversified entities, and the models of collaboration among entities: In terms of government-industry coordination, the government’s role in aligning national strategies with industry-led technological breakthroughs is crucial. Regarding industry collaboration, establishing an innovation ecosystem led by major enterprises is essential. In terms of industry-academia cooperation, national research institutions and universities play a significant foundational and supportive role. This aimed to provide some foreign cases for reference to improve China’s “new nationwide system” for technological breakthroughs. Japan’s “nationwide” system for technological breakthroughs after World War II showed the following characteristics: First, it was obviously characterized by a national strategic orientation and dynamic development; second, it was one of its key features to emphasize the development of corporate research and development capabilities in its implementation; third, Japan’s national research institutions played the dual roles of “research” and “administration” during its implementation. Based on the research findings, three policy suggestions were made for further improving China’s “new nationwide system” for scientific and technological breakthroughs: First, in terms of top-level design, we should enhance scientific decision-making and give better play to the leading and guiding role of national strategies in scientific and technological breakthroughs; second, for planning and coordination, we should facilitate the effective collaboration of diversified entities and better harness the auxiliary management and coordination capabilities of national research institutions in scientific and technological breakthroughs; third, to adjust its relationship with the market, the government should understand the needs and deficiencies of industrial development to create a favorable policy environment for business innovation.
Moral enhancement refers to the use of technologies, such as biomedical interventions or artificial intelligence (AI), to improve an individual’s moral motivation or cognitive capacities, thereby fostering moral development and addressing humanity’s existential crises like ecological degradation and terrorism. This topic has become one of the most popular in contemporary applied ethics. In contrast to applied ethics, a significant trend in normative ethics is the study of moral progress, which examines how society as a whole can improve morally. Although closely related, research on social moral progress and individual moral enhancement rarely cross-reference each other. However, the goal of moral enhancement can only be achieved through the moral progress of society as a whole, and social moral progress, in turn, depends on individuals developing relevant motivations and cognitive capacities. This article aims to bridge these two areas, arguing that only by promoting overall moral progress in society – establishing moral principles and distribution systems that place greater emphasis on equality – can humanity’s existential crises be alleviated, and moral enhancement has a unique role within this framework.
While technological advancements have brought unprecedented benefits to human society, they have also led to unique ethical dilemmas of our time. Excessive consumerism has resulted in climate degradation and resource depletion, and high-tech terrorism poses an existential threat to humanity. This article argues that these ethical challenges, at its core, stem from the growing socioeconomic inequality created by the market economy in the context of the technological revolution. To address these ethical issues at their root, we argue, there is an urgent need for societal reforms to establish a more equitable distribution system. The success of such reforms depends on transforming moral principles. Therefore, we argue that it is necessary to envision and advocate for new moral ideals that place a higher value on equality, driving improvements in prevailing ethical standards. Social moral progress requires the support of individual moral advancement. Only when a sufficient number of individuals make decisions based on these new moral ideals and act consistently can a new moral system be established and sustained. Consequently, we argue that moral enhancement, as an efficient means of promoting individual moral progress through technological support, may not independently resolve the ethical dilemmas of our era, but it can play a crucial role in this process.
The article first reviews the ultimate goals and methods of various types of moral enhancement, briefly assessing their limitations in terms of effectiveness and morality. Next, it argues that the root cause of humanity’s existential crises lies in the extreme economic and social inequality in the technological era, and that without a more equitable distribution system, moral enhancement – even if it overcomes its current flaws – cannot independently resolve this structural issue. The third section advocates for establishing moral ideals that prioritize equality to guide society toward greater fairness. Finally, the article argues that while moral enhancement has unique value in mitigating existential crises, it must be guided by moral ideals, selecting and refining enhancement methods that support a moral system of equal and fair distribution.
