The emergence of knowledge broker makes it possible to cross the "Caplan Gap" between academia and politics, which hinders the translation of knowledge into policy. Then, what is knowledge broker? How does it facilitate the transformation of knowledge into policy? The paper first explores the origins, connotations and types of knowledge broker, and then explores the knowledge management function, bridging function, two-way capacity building function, coherence seeking function and knowledge navigation function of knowledge broker in the alignment network linking academia and politics from the perspective of "structural hole" theory. However, knowledge broker also faces three highly challenging and controversial issues, namely, vulnerability, double marginality, and moral hazard. Theoretically clarifying the issue of knowledge broker has important implications for bridging the "last mile" from academic research to public policy in China.

In recent years, a large number of digital platform enterprises with ecological strategies have flourished and many valuable research works have emerged. However, different research fields use their own terms, theories and methods, resulting in theoretical differences on many important issues, which will not only cause ambiguity in practice, but also hinder the further development and integration of digital platform ecosystem researches. Therefore, this study attempts to systematize the researches related to digital platform ecosystem by sorting out the core views of different research schools. On this basis, this study further expounds the possible research directions of digital platform ecosystem in the future, contributes knowledge to the development of platform ecosystem in the face of the digital economy. Some existing studies have confused the concepts of "platform", "platform ecosystem" and "digital platform ecosystem" to a certain extent. This study firstly clarifies the definitions of platform, platform ecosystem and digital platform ecosystem to avoid the ambiguity and confusion of similar concepts. At the same time, this study selects 368 papers that are highly relevant to digital platform ecosystem based on the differences in the concepts and research content of platform, platform ecosystem and digital platform ecosystem, and conducts a statistical analysis of the literature. Secondly, this study compares the research focus of the economic perspective, technical perspective, organizational perspective and strategic perspective by reviewing the literature related to digital platform ecosystem. The economics perspective views platforms primarily as two-sided markets, focuses on the network effects, platform competition and interdependence of different aspects of the market. Technical perspective emphasizes platform as system, focusing on technical architecture design and architecture evaluation of digital platform ecosystem. The organizational perspective explicitly conceptualizes the platform and complementors as a unique form of organization: the meta-organization. The strategic perspective views platforms as a way to find strategic coherence, focuses on the organizational and governance characteristics specific to platform to extend existing strategy theory and examine how complementors use different strategies to influence their value creation activities. Finally, this study proposes directions for more in-depth exploration of future research themes, research content and research design from the perspectives of economics, technology, organization and strategy, integrates the views of various research schools and proposes a theoretical framework, in order to promote the development and integration of future research. This study attempts to break through the isolation between research schools through a systematic literature review to achieve the sorting and integration of cross-disciplinary research. It contributes to the future study of digital platform ecosystem that closely links platform phenomena with classical theories, realize dynamic, richer research scenarios and diverse research methods. The main contributions of this study are as follows. Firstly, drawing on previous researches, we provide definitions and conceptualizations of platform, platform ecosystem and digital platform ecosystem to avoid confusion between these three concepts. Secondly, this study summarizes the core issues of existing research from economic perspective, technical perspective, organizational perspective and strategic perspective, and helps to generate more dialogue across different research schools. Thirdly, we propose possible future research directions for the digital platform ecosystem and hope to make more rapid progress in future research and practice, thus contributing to the study of the digital platform ecosystem.

Abstract:The process of scientific research activities have a progressive, derived feature of complex structure.The scientific research innovation chain-data chain-publishing chain are closely connected and iterative.The evolution of data ecosystem and its model evolution is crucial to promoting scientific research innovation and expanding knowledge dissemination. On the basis of conceptual backtracking, this paper uses the theory of data ecosystem to elaborate the different data-driven logics of scientific research innovation and academic publishing. According to the different data thinking, data institution,data subject relationship, data management structure, data circulation environment and data management methods, the research data ecosystem can be divided into three gradual stages: closed, expanded and collaborative. Summarize the development trend of research data ecosystem from single to ecological, from fragmentation to system, from unilateral to collaborative, from point-to-point to integration, from manual to intelligent. A theoretical model for the evolution of scientific research data ecological model is proposed, and provide a new idea for promoting the overall quality improvement of each element and link of scientific research ecosystem with scientific data ecological governance.

From the perspective of technological evolution, the metaverse is the conceptual expression of the technology bodies combination in the development of digital information technology to a certain stage.From the "internal perspective", it is proposed that the essence of metaverse technology is purposeful programming of information digital phenomena and the core mechanism of technology evolution is "combinatorial evolution".Based on this, following the paradigm of complex economics and technology economy, through the research methods of theoretical application, inductive-inference and analytical speculation, the paper demonstrates that the metaverse technology and its industrial development are the internal logical relationship of circular and mutual promotion.The main conclusions are: the metaverse is an integrated expression of the development of the complex digital economy industry; The metaverse technology can promote the subversive change of the industrial structure of the digital economy.Among them, the key technology component module of the the metaverse, the mechanism and path of technological self creation and innovation, the algorithm of technological aggregation and economic formation, and the technology and economy redomained to promote industrial development were clarified.Studying the internal logical relationship between "technology essence and industrial development" has important thinking direction and practical reference significance for many stakeholders such as government industrial planning departments, technology developers, enterprise manufacturers and investors.

Fintech ethics is the cornerstone of high-quality development of financial services.. In view of the lack of research on systematic governance ， this paper uncovers the intricate hierarchical structure and evolutionary process through an analysis of the meaning of fintech ethics. This includes the hidden nature of technology, the diversity of its applications, the broad range of its social impacts and vertical interactions across various levels, as well as the horizontal phases of Introductory period, technological invasion, and convergence volatility and cyclical iterative growth. Our research proposes a collaborative governance structure that is guided and preventive during the convergence and volatility period. It highlights the role of a triad of government-led collaborative governance agents that connect the market and individuals. This approach emphasizes the cascade of legal intervention, market regulation, and guided ethical embedding to tackle critical issues such as policy failure, uncontrolled risk, and lack of ethical awareness. By presenting a comparative analysis of practical examples in the world's major economies, it provides recommendations for governance in China's present time with implications for promoting financial reform measures.

Does ChatGPT signal an "intelligent revolution"? It is urgent to make a systematic analysis. In this paper, starting from the evaluation of ChatGPT's innovation effects, the comparative analysis found that it belongs to progressive innovation and disruptive innovation in the series of OpenAI products; Compared with similar competitive products, it is indeed a breakthrough innovation and subversive technological innovation. In contrast to AI in China, ChatGPT has become an important part of the "bottleneck" technology system. It is found that ChatGPT, as a "production tool", forms a paradigm revolution in the supply of productivity tools in the field of artificial intelligence. At the same time, it also realizes the paradigm change of AI ethical governance. The organizational structural elements generated for ChatGPT can be traced back to the organizational mission of OpenAI, the flat project-oriented organization, the financing mechanism innovation with limited returns, and the efficient coupling of open source and crowdsourcing R&D organizational solution in the process of AI ModelOps. These findings lay a solid foundation for further research on ChatGPT's political, economic, and social impacts and related technological governance.

Scientific and technological talents (S&T talents) are the key driving forces to accelerate innovation and economic development. The mobility of S&T talents can enhance the spread and diffusion of knowledge, improve resource integration, and lead to technological innovation. China faces challenges in terms of S&T talents such as brain drain, low talent mobility and uneven talent distribution. Therefore, eliminating obstacles to talent mobility and improving the mechanisms for talent allocation have become important policy goals for China. Regional integration is an important policy tool under China’s urban agglomeration development strategy, which helps eliminate barriers to talent mobility. Based on large-scale publication data of more than 1 million talents, this study uses panel data of 41 cities in the Yangtze River Delta from 2000 to 2018, applies a staggered difference-in-differences model, and explores the effect of regional integration policy on S&T talent mobility. Specifically, we propose three research questions: (1) did regional integration policy in the Yangtze River Delta influence S&T talent mobility within the region; (2) what heterogeneities exist in the impact of regional integration policy on S&T talent mobility; (3) how the city-level development and living environment influences the effectiveness of regional integration policy. This study finds a significantly positive impact of regional integration policy on S&T talent mobility within cities and across cities. The positive effect is more prominent among talents in hard sciences, and those who moved between non-neighboring cities, as well as those who moved between cities in different provinces. Moreover, a larger promoting effect of regional integration policy is observed for cities with a population of over 5 million people. Additionally, this study suggests that regional integration policy slightly increased the net inflow of S&T talents in the cities with populations of less than 5 million population. Besides, this study demonstrates that the number of high-quality universities, innovation output, the development of a third industry, and the introduction of high-speed rail in cities strengthened the positive effect of regional integration policy on S&T talent mobility. These findings suggest a clear Matthew effect in terms of the promoting effect of regional integration policy on S&T talent mobility. This is because large-sized cities and cities with better development and living environment for S&T talents benefit more from regional integration policy in terms of S&T talent mobility. The findings of this study have multiple policy implications for optimizing talent distribution and improving regional governance efficiency. Small and medium-sized cities, and the cities with less advantageous environments for S&T talents’ development and living, should take a more active role in regional integration development to mitigate the Matthew effect concerning S&T talent mobility. They can leverage their proximity to major cities, and collaborate closely with talent center cities to enhance the spillover effect of regional integration policy on talent mobility. By creating favorable environments for scientific research, economic development, and living, they can promote the effectiveness of the impact of regional integration policy on S&T talent mobility, and ultimately improve the overall competitiveness of talents in the region.

Generative artificial intelligence (AIGC) is being integrated into social life and is participating in knowledge production. It also creates new digital inequalities, and scholars are concerned about deepening the digital divide. This article explores the theoretical context of artificial intelligence and its impact on society and tries to answer how AIGC shapes the "AI divide" in the context of the development of Digital China. At the technical level, the "AI divide" involves three dimensions: data, algorithms, and computing power. Data sets serve as the foundation of AIGC, similar to soil. The scale parameters, source channels, content types, and even languages of the data sets invisibly shape the "AI divide". The algorithm model consists of self-supervised learning and human feedback reinforcement learning. It is similar to the roots and stems of a plant, which determines the vitality of AIGC to bloom and bear fruit. Computing power is AIGC's information infrastructure, connecting the real world (chips) and the virtual world (data and algorithms), determining the processing speed of computing operations and the depth of integration in the digital industry. As modern technology becomes increasingly dominant in shaping our understanding of the world and history, social stratification theory can help us understand the impact of the "AI divide". The first level involves the divide among individuals, specifically between ordinary users, in accessing and utilizing AI technology. This includes language barriers, paywalls, practical skills, willingness to use, perception of benefits, and the desire to learn. The second aspect pertains to human-machine differentiation, which, on the surface, refers to the distinction between humans and autonomous AI agents. However, at its core, it represents the divide between the majority who lack technological initiative and the minority who wield it due to their control over digital resources. It refers to using digital resources by countries, regions, or individuals to participate in the development, share knowledge, and overcome differences in capabilities for autonomous growth. To bridge the "AI divide", it is important to establish an independent and self-sufficient technological innovation system. We should also explore and optimize application scenarios to make the most of this system. China needs to take the lead in AI development in the future and promote the construction, transformation, and application of AIGC resources by different enterprises, scientific research institutions, and industry organizations. It must also establish a fair and standardized platform governance ecosystem and create a good technology atmosphere. Equality should be embedded into AIGC's technology process, including algorithm design, training data selection, model generation, and optimization. This will give people of different countries, ethnic groups, and classes the right to participate in scientific development. Finally, China should plan more diverse ecological alliance forms and participate in cooperation platforms under multilateral frameworks such as the United Nations, the World Trade Organization, and Asia-Pacific Economic Cooperation. China should transform games and competitions into consultation and cooperation, connect wider upstream and downstream resources, and try to build a global AI governance community. The article proposes the concept of the "AI divide", which deepens the third-generation digital divide theory in artificial intelligence and has significant practical implications for understanding the development of digital China and the economic and social transformation.

Science and technology ethics is a value criterion and code of conduct, which must be complied in activities of scientific research and technological development. The report of the 20th National Congress of the Communist Party of China proposes to improve the system of scientific and technological innovation. Strengthening the governance of science and technology ethics is an important way to achieve this goal. It is important for sci-tech self-reliance and self-strengthening to strengthen the ethical governance of science and technology. The ethical governance of science and technology in China faces challenges and situations such as enhancing international competitiveness in science and technology, strengthening ethical regulation in emerging technology fields, and balancing scientific and technological innovation with ethical regulation in a reasonable manner. The paper analyzes the following issues exist in the current ethical governance of science and technology in China, that is, policies and regulatory mechanisms are incomplete, ethical review standardization and talents are lacking, scientific and research person and the public and news media are lack of guidance. Finally, the strategies and proposals to strengthen ethical governance of science and technology are advanced. The strategies and proposals can provide some references for formulation of a science-technology ethical governance system which is suitable for Chinese characteristics.

“SRDI” small and medium-sized enterprises (S-SMEs) are an important vehicle for implementing innovation-driven strategies. In view of the lack of research on the micro-level of S-SMEs' innovation performance in academic circles, this paper examines the significant key factors and configuration effect that influence S-SMEs' innovation performance from the perspective of complex causal effect analysis, mixing NCA, empirical regression and QCA methods, and refines the corresponding improvement paths. It is found that (1) R&D capability, financing environment and market competitiveness significantly affect the innovation performance of S-SMEs; (2) there are five configuration paths that enhance the innovation performance of different types of S-SMEs; (3) when financing is blocked, either small-scale production or improving their own market competitiveness can enable S-SMEs to maintain a high level of innovation performance target. This paper attempts a new way of thinking of complex causal effect analysis, which provides some theoretical and practical references for the study of S-SMEs' innovation performance in the future.

Based on the analysis of the thinking essence and methodology program of the new paradigm of scientific knowledge production in the era of big data, this paper points out that the big data-driven knowledge production mode has brought about some social problems, such as causing new social justice problems, strengthening the new monopoly of academic resources, shaping the new path dependence of knowledge production, and bringing new scientific research ethics disputes. Then, based on STS perspective, this paper deeply reflects on the root cause and nature of these social problems from data science and the new perspective of studies in science of science, new academic power in data capital construction, new interest distribution and balance relationship in new knowledge production mode, and value load of data science laws.

Under the guidance of the strategic objective of "carbon emission peak and carbon neutrality", green innovation has become the key for heavy polluting enterprises to achieve high-quality development. As a mean of market-driven environmental regulation, environmental subsidies provide economic basis and material guarantee for corporate green innovation. However, in reality, local governments have discretion in choosing the objects of subsidies, which is related to both the supporting effect of environmental subsidies and the resource allocation of the national green development strategy. In addition, enterprises can freely choose whether to use environmental subsidies for direct environmental pollution control or green technology research and development innovation. Among them, there are problems to be further explored: in which kind of firms are the supporting effect of environmental subsidies on corporate green innovation better? Based on Porter's hypothesis, stakeholder theory and institutional theory, the panel threshold regression model was adopted to examine and validate the differential impact of environmental protection subsidies on corporate green innovation as well as the internal mechanism among 337 listed companies operating in heavily polluting industries over the period spanning from 2010 to 2019. The results show that: (1) The incentive effect of environmental protection subsidies on corporate green innovation is mainly effective for firms that cross the threshold of corporate social responsibility. Firms with high CSR level have green development consciousness and need to upgrade their products and technologies through green innovation; On the other hand, firms with high CSR level have abundant external resources, such as green resource integration and talent introduction, while environmental subsidies ease the financial pressure and resource constraints within firms, providing favorable conditions for firms to make better use of environmental subsidies for green innovation. (2) When the firms cross the threshold of CSR, the incentive effect of environmental protection subsidy on corporate green innovation is better in state-owned enterprises. The status of state-owned firms can escort the incentive mechanism of environmental subsidies for green innovation, which can better play the role of environmental subsidies in promoting corporate green innovation. This paper contributes to the literature from the four perspectives. Firstly, this paper extends the theoretical extension of Porter's hypothesis. The traditional Porter hypothesis focuses on the influence of environmental regulation policy mix and optimal interval on enterprises' green innovation. On this basis, this paper expands the hypothesis to the perspective of stakeholder status and institutional foundation to explore the micro-mechanism of environmental subsidies affecting enterprises' green innovation mechanism. Secondly, according to the stakeholder theory, it is proposed that there is a threshold of CSR in the process of promoting enterprise green innovation with environmental protection subsidies. The level of CSR means the resource guarantee, attention pressure and innovation coordination from stakeholders, which expands the theoretical connotation of stakeholder theory in the field of green innovation. Thirdly, based on the institutional theory, this paper proposes that the state-owned firm identity will promote the mechanism of green innovation driven by environmental protection subsidies after CSR crosses the minimum threshold, enriching the research perspective of institutional theory and extending it to the research on the related mechanism of the anthems of green innovation. Finally, based on threshold effect, this paper constructs the micro-mechanism of environmental protection subsidies driving corporate green innovation with threshold of CSR. Previous studies focus on the optimal interval of environmental regulation intensity based on Porter's hypothesis. This paper endeavors to investigate the threshold mechanism and expand the research on the micro-mechanism of the antecedent variables that lead to corporate green innovation.

The present paper constructs an evaluation index system to measure the development level of the digital economy, and then measures the provincial manufacturing carbon emission efficiency based on the MinDS model of global benchmark technology. Then, the present paper empirically tests the impact of the digital economy on China's manufacturing carbon emission efficiency, and conducts a comparative analysis of the action paths. The present paper found that the development level of China's digital economy tends to rise during the survey period. But there is a significant digital divide, which is reflected in the high development level of the eastern region, while the development of the central and western regions is relatively low. The carbon emission efficiency of China's manufacturing shows a upward trend, and presents a spatial pattern of gradual decline from east to west. The digital economy has a significant U-shaped nonlinear impact on the carbon emission efficiency of manufacturing, supporting the hypothesis of EKC. The path test results show that the labor efficiency enhancement effect and the energy factor saving effect are two feasible paths to play the digital carbon reduction effect, and the latter has a relatively greater carbon reduction effect.

High-level talents are the source of strength for building world power of science and technology, but how to retain and attract world-class scientific and technological talents(WSTT) has not been explored by the academic community. Currently, most researches on the influencing factors of scientific and technological talents flow adopt methods such as questionnaire surveys and econometric models. However, due to the objective shortcomings of the research methods, only a few factors can be discussed on the flow of talents such as academicians, and a comprehensive and systematic theoretical model has not yet been formed. And there are not many analyses on WSTT. To this end, the paper regards the winners of international famous academic awards in the field of natural science as WSTT. Based on the qualitative data such as the biographies of the research objects, the paper uses grounded theory method to construct an influencing factor model of WSTT, and comprehensively and systematically reveals the key factors and mechanisms that affect talent flow. Grounded analysis, which is based on detailed qualitative information, is widely used to explore and summarize the influencing factors of a phenomenon, and has a good research utility for this study. Specifically, first of all, 227 winners with relatively sufficient information are selected as research samples, who have flow experience between the production of significant achievements and the awarding of awards. Secondly, through the grounded analysis processes such as open coding, axial coding, and selective coding, it is found that: (1)Livelihood security (medical conditions, salary and treatment, work stability, living environment), working atmosphere (colleague relationships, partners, academic exchanges, institutional management, regional academic environment), research support (team building, research conditions, research fields, research autonomy, and external support) and research strength (institutional reputation and research team) are the external environmental factors affecting talent flow; family life (family reunion, family health, and comfortable life) and personal emotions (academic inheritance, homeland complex, research mission, and changing environment) are the internal drivers of talent flow. (2)There are indirect mechanisms between internal and external factors, as well as external factors themselves, that affect talent flow, including team building→colleague relationships→talent flow, medical conditions→family health→talent flow, academic exchanges→comfortable life→talent flow, academic exchanges→changing environment→talent flow, research conditions→changing environment→talent flow, and other indirect pathways. (3)There are certain disciplinary differences in the main influencing factors of talent flow, which are reflected in the industry-research interaction and experimental setup in the field of biology, academic exchanges in the field of mathematics, institutional characteristics and experimental setup in the field of chemistry and physics, and mandatory retirement system for government departments in the field of earth sciences. Finally, the following suggestions are put forward on how to better retain and attract talents: encouraging diverse forms of academic exchanges; providing sufficient but moderate research support; paying attention to the "self-realization" needs of scientific and technological talents; paying attention to family care for scientific and technological talents.

Abstract: [Purpose/significance] The value of patents is an important manifestation of AI patents' competitiveness. A comparative analysis of the value of AI patents between China and the United States is of great significance for understanding the current situation and status of China's industrial development and determining the future strategic planning and development direction. [Method/process] This study uses Himmpat database as the retrieval system, uses AHP-entropy weight method to calculate the weight of each index, analyzes the development status of artificial intelligence in China and the United States through the comparison of patent value, and analyzes the development path of China's AI industry. [Results/conclusion] The results show that in recent years, both China and the United States are in a rapid development stage in the field of artificial intelligence, but the United States has certain advantages at all levels with the help of "first mover advantage"; China has developed rapidly in the application layer, but there are still some weaknesses in the research and development of high-value patents. In the face of the gap between the industrial development of the two countries, China should give full play to the "advantage of backwardness" and solve the "stranglehold" problem in accordance with the existing problems. While paying attention to the application of technology, China should adopt the development strategy of "paying equal attention to both inside and outside", encourage the research and development of related patents at the basic and technical levels, promote interdisciplinary cooperation in the research and development of new technologies, "fan out from point to area", give play to the "head goose effect", and through cooperation between the dominant subjects, form a "preponderant polymer" to ensure the development of China's AI industry along a correct and efficient path.

Under the dual influences of an aging population and low fertility, China will face a long-term declining trend in the labor force . Therefore, the outline of the 14th Five-Year Plan of China emphasizes that the population quality dividend should be expanded to improve the level of human capital .One could “plant sycamore trees and attract phoenixes”. However, it is more important to retain “phoenixes” and produce economic benefits. The introduction of talent is only a means but not a terminus. Whether talent can be retained ultimately depends on whether there is an environment suitable for their development and whether a good ecosystem appropriate for the long-term development of talent can be established to effectively form "talent stickiness". Diverse institutional advantages, market size and talent policies affect the flow, competition and development of human capital, ultimately determining the economic benefits of talent. Hence, what type of institution can enable talent to yield a high human capital economic effect? Optimizing institutional arrangements to improve human capital's economic growth effect is essential for the Chinese local government to attract talented people. Through literature review and analysis, this paper puts forward the institutional framework for influencing the economic growth of human capital, namely the "Accumulation-Allocation-Innovation" (AAI) institutional framework. Utilizing the dynamic pooled fsQCA method and inter-provincial data from 2001 to 2017, the study analyzes the institutional configuration pattern of the human capital's economic growth effect. The study found that (1) either accumulation institutions, allocation institutions, or innovation institutions are not necessary for the high economic growth effect of human capital, which a single condition cannot guarantee. (2) Four institutional configuration patterns promote the economic growth effect of human capital: the institutional configuration of allocation-innovation, the institutional configuration of accumulation-innovation, the institutional configuration of innovation, and the balanced institutional configuration. (3) The improvement of innovation institutions boosts the economic growth effect of human capital despite the absence of allocation and accumulation institutions. (4) Multiple paths are found in the multi-period comparative analysis: the "dominant path" (The institutional path of innovation), the "buffering dominant path" (the institutional path of allocation), and the "turning path" (the institutional path of accumulation and innovation). Some suggestions are put forward to promote the human capital economic growth effect in China based on the research results. First, an interactive federation among the accumulation institution, allocation institution and innovation institution should be strengthened. Second, even when accumulation institutions and allocation institutions are restricted, improving innovation institutions is also a way to increase the human capital economic contribution rate. Third, measures should be adjusted to local conditions and according to circumstances, and the driving path should be reasonably chosen. Finally, we attach importance to the effect of allocation institutions on human capital economic growth.Different from the static configuration perspective, this paper starts from the complex dynamic perspective, which not only expands the research field of high economic growth effect of human capital, but also provides new thinking for how to improve the institutional environment of high economic effect of human capital.

This paper takes Shanghai and Shenzhen A-share listed during 2010 to 2020 as samples, investigate the internal mechanism and the influence of returnee executives on the digital transformation of enterprises and its mechanism. The results show that: (1) Returnee executives are helpful to promote the digital transformation of enterprises, and this conclusion is still valid after considering endogeneity and various robustness tests; (2) The mechanism shows that the returnee executives mainly promote the digital transformation of enterprises by improving enterprise human capital level, learning and absorption ability and ESG responsibility; (3) Heterogeneity analysis shows that the promotion effect is more significant in SME and enterprises with low financial asset allocation efficiency. The conclusion of this paper not only enriches and expands the upper echelons theory and the related research on the influencing factors of digital transformation of enterprises, but also helps to provide empirical evidence for enterprises to adapt to the trend of digital development and speed up the process of digital transformation of enterprises.