Along with the Sino-U.S. trade dispute , the complex geopolitical situation and other variable factors, supply chain friction has become the norm. The risks associated with the flow of capital, information, and logistics in the supply chain have dramatically increased, making it urgent to improve the chain's resilience in order to mitigate disruption risk and maintain the chain's security and stability. At this stage, the importance of data elements in empowering supply chain governance is becoming more and more prominent, and the scale of data assets owned and the ability to transform them into productivity have become important factors in gaining new competitive advantages. From the perspective of supply chain network characteristics, the penetration and application of data elements in the subject and structural elements of the supply chain have significantly revolutionized the operation mode of the supply chain, and become a key driving factor to enhance risk-taking and ensure the continuity of supply and demand.
This study investigates the enabling mechanisms of data elements on the subject and the structural resilience of the supply chain in order to reveal the supply chain resilience enhancement paths in a more thorough and detailed manner. As a result, given the network characteristics of the supply chain, the subject element and structural element may show different resilience mechanisms against risks. By employing the OLS regression model, the study collects data from Chinese listed companies between 2015 and 2022 and uses text analysis to create indicators that show the application level of enterprise data elements. It then uses supply chain subject resilience and structural resilience to characterize the overall resilience of the supply chain and empirically investigates the impact of data elements on resilience.
The research results show that data elements can effectively enhance the level of enterprise risk-taking and the stability of supply-demand relationship, and the findings remain robust after a series of endogeneity and robustness tests, showing that data elements can effectively enhance both supply chain subject resilience and structural resilience. In addition, the application of data elements by enterprises can effectively enhance the innovation effect and the information effect, thus improving the innovation capability of enterprises and obtaining the information advantage to promote the resilience of the supply chain. At the same time, the enabling effect of data elements on supply chain resilience can be differentiated by the internal and external environments of enterprises, that is, the enabling effect is stronger when the enterprise is large, operates in a highly competitive industry, and is situated in an area with a poor supply chain operating environment and high marketization.
Compared with the results of previous studies, this study expands the research perspective of supply chain resilience, constructs enterprise-level supply chain resilience measurement indexes from the perspective of network characteristics, and enriches the research scope of supply chain in the era of digital economy; and it further empirically examines the two indirect empowerment mechanisms of innovation effect and information effect, which provides a useful supplement to the research on the empowerment mechanism of data elements on supply chain resilience. Through the analysis of the research findings, this study proposes to accelerate the construction of data element marketization, further activate the potential of data elements in enhancing supply chain resilience, and formulate targeted data elements application solutions according to the differences in the internal and external environments of enterprises, which will help the government optimize the policies on data elements and supply chain and support the scientific decision-making of enterprises, and have certain theoretical significance for the implementation of the strategic plan of "focusing on enhancing the resilience and security of industrial chain and supply chain".
Future research may integrate the two dimensions of supply chain entity resilience and relationship resilience into a comprehensive index for research, further combine the characteristics of the supply chain to reveal the mechanism path involving more data elements to empower supply chain resilience improvement, and the subsequent economic impacts of data elements empowering supply chain resilience improvement could be predicted.

With the rapid development of the digital economy, massive data has become an important lever to promote the improvement of national governance efficiency. In this process, open access to public data has become an important issue in current national science and technology policy, ethics, and legal research. However, the academic community has paid little attention to its concept definition, internal challenges, and governance paths in the field of ethics.
In light of the research inadequacies, this study first provides a definition of the ethics of open access to public data. In a broad sense, the ethics of open access to public data refer to the values and behavioral norms that all entities with a right to open public data to the community should follow in disclosing various data resources to society; narrowly speaking, the ethics of open access to public data refer to the values and behavioral norms that various public data openness entities should follow in disclosing specific public data to society. In this regard, the study draws on the views of relevant scholars on the two main themes of public data, and summarizes the main characteristics of the ethics of open access to public data from the perspectives of data attributes and public attributes. On the one hand, from the perspective of data attributes, the ethics of open access to public data is characterized by fuzzy classification boundaries and uncertainty in security risks; on the other hand, from the perspective of public attributes, it is featured with overlapping interests and normative public values.
Then the study explores the three main perspectives of material production, economic activity, and source supply based on knowledge production, extending from knowledge production to the three core aspects of the knowledge production process: knowledge field production process, knowledge economy development process, and knowledge innovation supply process, and constructs an integrated analysis model; finally, a comprehensive analysis is conducted on the inherent challenges and governance paths of public data openness ethics based on the integrated analysis model.
The inherent dilemmas of the ethics of open access to public data are summarized. Firstly, the ethical dilemmas in the knowledge field production process, involve platform information privacy, data confidentiality supervision, and the ethical guarantee of the science and technology innovation market. Secondly, the ethical dilemmas of open access to public data in the development of the knowledge economy refer to dilemmas of empowering public data, platform expert technology, and intellectual property infringement. Thirdly, the ethical dilemmas in the process of knowledge innovation supply consist of the ethical awareness dilemma of public participation in data openness, the ethical norms dilemma of data market technology, and the ethical awareness dilemma of online platform public opinion comments. Accordingly, the governance path of the ethics of open access to public data is proposed. First, the governance of ethical dilemmas in open access to public data during the production process of knowledge fields includes ethical governance of platform information privacy, data confidentiality supervision and science and technology innovation markets; second, the governance of ethical dilemmas in open access to public data during the development of the knowledge economy includes ethical governance of public data empowerment, platform expert technology, and intellectual property infringement; third, the governance of ethical dilemmas in open access to public data during the process of knowledge innovation supply involves governance of ethical awareness of public participation in data openness, governance of ethical norms in data market technology, and governance of ethical awareness in public comments on the online platforms.
The analysis centered around the ethics of open access to public data provides a certain degree of rational thinking for the governance of ethical issues related to public data openness in the context of Chinese style innovation. However, the limitations of the research lie in the lack of specific case analysis in the exploration process and the lack of exploration of ethical issues in different contexts. Future research can further analyze solutions to this problem by collecting case data, and pay attention to legal regulation and the ethical ecosystem of open access to public data.

Emerging technologies not only signify the cutting edge of technological innovation but also represent a pivotal aspect of international competition, and they are highly valued by nations, international organizations, and leading corporations worldwide. By swiftly and accurately detecting potential emerging technologies in target domains, they can grasp the opportunities of future technological and industrial development, break through the technological barriers in various fields, and thus enhance the competitive advantage of both nations and enterprises in strategic global competitions. In the context of China's aggressive pursuit of its "carbon neutrality and carbon peak" goals, innovation in power grid technology assumes exceptional importance. Power grid companies are compelled to deeply comprehend and master the evolving trends in emerging grid technologies, undertake crucial technological research, and guide precise research and development investments to secure a dominant position in the international arena.
As vital carriers of scientific information, academic papers and patent literature are predominantly used to evaluate the level of scientific research activities and the innovation in industrial technology, and have become the primary sources for detecting emerging technologies. An in-depth study and analysis of these documents, followed by the extraction and selection of innovative information within them, helps to uncover latent technological knowledge. Although single data source methods are operationally effective, they struggle to accurately reflect the complexity of scientific themes. Conversely, research on detecting emerging technologies through multi-source data remains relatively scarce. Currently, there is a lack of academic consensus on the definition of emerging technologies, leading to different indicators for assessing whether a technology topic is an emerging technology. Identifying these technologies accurately and delineating their quintessential characteristics—impact, growth, coherence, novelty, and uncertainty—is crucial. It is noteworthy that quantified research on these features, particularly uncertainty and ambiguity, is still scarce.
This paper introduces a method for integrating multi-source data, aiming to amalgamate academic and patent data to enhance semantic complementarity between varied data types, thereby boosting efficiency in identifying emerging technologies. The study utilizes the Topical N-Grams (TNG) model to extract technological themes from academic papers and patent documents, followed by manual selection to ascertain key technological themes. According to these themes, it computes five primary feature indicators: impact, growth, coherence, novelty, and uncertainty. These indicators are then amalgamated to calculate an emergence score. Subsequently, the study employs a support vector regression machine model for extrapolating these indicators, identifying emerging technologies with potential for future growth. Focusing on the grid sector, the study collects patent literature from the Derwent Innovation database and academic papers from the Web of Science core collection,limiting document types to "Article" and "Review" and setting the timeframe from 2015 to 2022, with a total of 743 344 academic papers and 1 247 235 patents. The analysis of the annual distribution of academic and patent papers published in the grid field reveals a steady increase in research interest; the emerging technologies in the grid sector for 2022 include research on low-carbon planning for new power systems, electric motor drive and control technology, intelligent inspection technology for transmission lines, smart operation and maintenance technology for digital grids, cooperative control technology in multi-unmanned systems, and internal combustion engine power system technology. Notably, research on low-carbon planning for new power systems has consistently ranked high in emergence in recent times. In the deep development strategy of the current power industry, low-carbon transformation and upgrading are deemed vital. Further indicator extrapolation indicates that research on low-carbon planning for new power systems, intelligent inspection technology for transmission lines, cooperative control technology in multi-unmanned systems, and internal combustion engine power system technology maintain their top-five status, while intelligent wind energy power system integration technology and ion battery and energy storage technology are gradually climbing the ranks, suggesting that these emerging technologies are poised for increased attention and development in the future. In addition to academic papers and patent literature, funding programs and policy texts are also very important sources of information. These resources can provide information about the direction of funding and support for S&T research, as well as the level of government attention and policy orientation towards emerging technologies.

With the comprehensive acceleration of the global economic and social digital transformation and the rise of a new round of technological revolution and industrial transformation, the manufacturing industry is developing in the high-end, intelligent, and green trend. However, many underlying and key technologies in industries such as electronic information and advanced manufacturing in China are still confronted with bottlenecks. The competitive advantage of the ICT manufacturing industry is increasingly constrained by the resilience of the supply chain. The various links of the industrial and supply chain are closely interconnected, involving the complex integration of different production factors such as capital, technology, and talent. As society further develops, the connotation of production factors is gradually expanding and deepening. New quality productive forces, including data, knowledge, technology, and management, are important supports. Therefore, accurately grasping the connotation of new production factors, exploring their impact mechanism on the resilience of the supply chain, and cultivating new quality productive forces to maintain the security and stability of the supply chain are of great significance for the ICT manufacturing industry to accumulate competitive advantages with new factors.
This study synthesizes insights from various scholars, and proposes a comprehensive supply chain resilience framework that addresses three critical dimensions: pre-disruption response capabilities, intra-disruption adaptation capabilities, and post-disruption recovery capabilities. It takes 295 listed companies in the computer, communication, and other electronic equipment manufacturing industry on the A-share market from 2018 to 2022 as samples. Numerical values of new production factor variables are obtained based on the data collected through the CSMAR database, CNRDS database, and corporate annual reports to calculate the supply chain resilience of enterprises over a 5-year period for analysis. By defining variables and constructing a multiple linear regression model, the interaction mechanism among the four factors is further explored.
The results show that data and management factors have a significant positive impact on the resilience of the supply chain in the ICT manufacturing industry, while knowledge and technology factors have a significant negative impact. However, when combined, there is a certain substitution effect between the data and knowledge factors, that is, when the level of data elements is generally improved, the negative impact of risks such as the knowledge paradox on the resilience of the supply chain may be partially suppressed. There are differences in the resilience of the supply chain between upstream and downstream enterprises in the ICT manufacturing industry, with downstream enterprises having better resilience than upstream enterprises, and the new factors have different effects on the resilience of the supply chain between upstream and downstream. There is a significant differentiation in the competitive pattern among industrial regions, and there is regional heterogeneity in the impact of new factors on the resilience of the supply chain.
This paper expands the empirical research on supply chain resilience, and clarifies the connotation of new production factors and quantifies them in the context of the digital economy and new quality productive forces. It conducts an in-depth analysis of the relationship between new production factors and the resilience of the supply chain of ICT manufacturing enterprises from the perspective of factor combinations, providing support for ICT manufacturing enterprises to better cope with uncertainty shocks and maintain supply chain stability. To enhance the resilience and competitiveness of the ICT manufacturing industry's supply chain, it is imperative to foster the synergistic application of new production factors, including the robust safety management of data, knowledge, and technology. Concurrently, there is a need to bolster communication and collaboration with supply chain partners across the upstream and downstream sectors, ensuring the coordinated development of each link within the supply chain. This approach will facilitate the establishment of stable relationships and lead to the collaborative optimization of the supply chain. Furthermore, to capitalize on regional development opportunities, it is essential to seize the momentum of the central region's rise and the Western Development Strategy. This involves actively encouraging and supporting the growth of ICT manufacturing enterprises in the central and western regions.

Since the 18th National Congress of the Communist Party of China, the Central Committee has prioritized ecological civilization construction, integrating it into the 'five-in-one' overall plan. This construction is imperative, with financial support being pivotal. As an industrial finance sector, Sci-tech Finance plays a crucial role by pooling idle social capital, directing it towards innovative enterprises, and offering financial backing for technological innovation, which is essential for ecological civilization development. Sci-tech Finance contributes to ecological civilization through resource allocation, industrial upgrading and transformation, and ecological cognition. Conversely, ecological civilization fosters the growth of Sci-tech Finance through policy feedback, demand stimulation, and the nurturing of innovative ecosystems. The synergy between Sci-tech Finance and ecological civilization has become a cornerstone of China's sustainable development strategy. Thus, managing their interrelationship and fostering their joint development is a pressing issue in current socio-economic progress and a vital pathway to achieving high-quality economic growth.
Drawing on existing literature, this study selects data from 30 Chinese provinces spanning 2007 to 2021. It employs the entropy value method to calculate the composite scores of Sci-tech Finance and ecological civilization construction. Using a coupling coordination model, it assesses the coupling coordination degrees between the two systems, evaluating their integrated development. Furthermore, it delves into the spatial disparities in their coupling coordination, exploring root causes, spatial correlation, and convergence characteristics through a comprehensive application of the Dagum Gini coefficient, Moran's I index, coefficient of variation, and spatial Dubin model.
The study reveals several key findings regarding the coupling coordination between two systems in China. First, in terms of time trend, the coupling coordination between the two systems in China is steadily rising over time, yet there is considerable scope for enhancing the coordination level in most provinces. Second, in terms of the spatial pattern, the coupling and coordination of the systems exhibit a pronounced east-west gradient, with higher levels of coupling and coordination observed in the eastern regions compared to the western ones. Third, in terms of spatial differences,the differences in coupling coordination between the national level and the eastern, central, and western regions are diminishing annually, as are the disparities within these regions. Notably, regional disparities remain the primary driver of overall differences in system coupling coordination.Fourth, in terms of spatial correlation,the coupling coordination level of the systems exhibits significant spatial autocorrelation, while eastern provinces are characterized by a pattern of high-value clustering, where areas with high levels of coupling coordination tend to be grouped together, demonstrating a "high-high" clustering pattern.Fifth, in terms of convergence characteristics, the coupling coordination of the systems across the nation and within the eastern, central, and western regions displays notable σ convergence and absolute β convergence. The western region is converging at the fastest pace, followed by the central region and the nation as a whole, while the eastern region shows the slowest rate of convergence.
This study stands out by pioneering a new approach: it's the first to bridge the gap between sci-tech finance and ecological civilization construction. It discusses the degrees of coupling and coordination between the two, and provides theoretical basis and data support for the coordinated development of sci-tech innovation and ecological civilization in the new era. Secondly, a variety of models are used to analyze the spatial and temporal evolution characteristics, spatial differences and convergence of the coupling coordination of the two systems. By the end, the paper advocates for the development of synergistic innovation between sci-tech finance and ecological civilization construction by establishing specialized sci-tech finance funds, creating green technology trading platforms, providing customized financial services, and increasing policy support and investment to stimulate innovation and vitality in sci-tech finance, the implementation of regionally differentiated development strategies, the reduction of spatial disparities in coupling coordination, the exploitation of spatial agglomeration effects to foster internal and inter-regional collaborative development mechanisms , and the acceleration of convergence rates to foster balanced progress and competitiveness across provinces.

The construction of the Guangdong-Hong Kong-Macao Greater Bay Area is a major national strategy of China.The Greater Bay Area boasts a solid foundation for collaboration,focused resources for innovation,and robust economic power.However,there are still problems in the collaborative innovation among Guangdong,Hong Kong and Macao,such as the disconnection between industry and academia,the uneven distribution of innovation resources,the obstruction of information flow and the inefficiency of regional innovation.Building a cooperative innovation network is essential since the Greater Bay Area's regional development is uneven and its coordination relationships are complicated.Cross-border university-industry cooperation is an important part of it; one key component of it is cross-border university-industry cooperation; strengthening this relationship between Guangdong,Hong Kong,and Macao would support the region's talent development and technical exchanges.However,cross-border university-industry cooperation in the Greater Bay Area means the interaction between different types of organizations in two regions,which implies dual barriers.One is the macro-level institutional differences between regions.Within the framework of "One Country,Two Systems",Guangdong,Hong Kong and Macao have different social and legal systems.The other one is the micro-level institutional differences between organizations,industry and academia have conflicting logics in values,goals,and interests.Therefore,it is necessary to involve the role of gatekeeper.
In cross-border university-industry cooperation,universities play a unique role.When universities act as gatekeepers,they can not only regulate the flow of knowledge between regions but also promote the formation of new cross-border university-industry connections.As the key actor in the regional innovation system,the behavior patterns of universities in establishing cooperative relationships can reflect their network roles.With the accelerated development of the Greater Bay Area and the adjustment of universities' own cooperative strategies,the network roles they demonstrate in the innovation system will continue to change.Therefore,a dynamic analysis of the roles of universities is necessary.Using the collaborative patent data of universities in the Guangdong-Hong Kong-Macao Greater Bay Area from 2010 to 2021,this study makes social network analysis and constructs a collaborative innovation network,focusing on the cross-border university-industry connection.According to the location of the focal universities and its bridging industry or academia,the roles of universities are divided into two categories: internal bridging and external bridging,then the roles of universities are further divided in terms of the strength of their connections.The roles of universities are identified with a focus on the gatekeeper,and the distribution and evolution patterns among different roles are discussed by region,providing reference for the governance of the collaborative innovation network in the Greater Bay Area.
The result shows that universities in the Guangdong-Hong Kong-Macao Greater Bay Area play various roles in the collaborative innovation network,and there are differences in the distribution of roles,collaboration tendencies,and role evolution paths among different regions.In terms of role distribution,there are many inactive universities in Guangdong,the number of gatekeepers is relatively small but showing an upward trend.In Hong Kong and Macao,besides inactive universities,gatekeepers are the main part.In terms of collaboration tendencies,universities in Guangdong clearly tend to establish local partnerships,and there are relatively few universities engaged in cross-border collaborations.Hong Kong and Macao universities have interactions with industry or academia both within and beyond the regions,but their connections with Guangdong industry are weak.As for the evolution paths between roles,universities in Guangdong have a relatively simple and clear pattern,mainly evolving from inactive ones to local collaboration-oriented universities,and then further developing into gatekeepers;while with unstable role positioning,the role changes of Hong Kong and Macao universities are more diverse and complex.
Thus,cross-border connection needs to be strengthened; in the management of collaborative innovation in the Greater Bay Area,the role evolution of universities should be guided differentially; local governments need to optimize the network structure and institutional arrangements within the Greater Bay Area,introduce specific collaborative innovation plans,and break interaction barriers to improve the efficiency of gatekeepers in transferring resources and information.

Data, as a derivative element of the digital economy, has injected new impetus into regional innovation and development. In this process, the coupling and coordinated development of human capital and data elements are crucial. In recent years, the vigorous development of the digital economy has sparked widespread discussion in academic circles. To further expand the existing research boundaries, this paper focuses on the perspective of factor combination and uses inter-provincial panel data to explore their impact and mechanism on regional innovation.
In the characteristic fact statement, preliminary discussion is made based on the valid patent authorization information of the five major intellectual property offices from 2010 to 2021. During the statistical period, the total number of patents doubled, indicating that in the process of historical evolution, innovation-driven innovation is still an important engine to promote the progress of the Times. From the perspective of spatial and temporal distribution characteristics, the degree of coupling and coordination between data elements and human capital in China is generally on the rise, but it is still in the immature type, with significant regional differences. Specifically, the degree of coupling coordination between data elements and human capital is still low, and the overall stage is still developing. According to the coupling coordination type, the eight economic regions can be divided into the development pattern of inland regions driven by the growth pole of coastal areas.
Furthermore, the benchmark regression results show that both data factors and human capital as individual factors have significant innovation-driving effects, but as combination factors, innovation empowering effects are stronger. After a series of robustness tests, this conclusion is still valid. Heterogeneity analysis shows that there are significant differences in empowering effects of factor combination innovation in different digital industrialization and industrial digitalization regions. The mechanism test results show that the matching of data elements and human capital can promote regional innovation development through spillover effects, which are mainly reflected in the two paths of technology transfer and R & D personnel flow. From the analysis of the test results of technology transfer, when other factors remain unchanged, the factor coupling degree D increases by 1 unit, resulting in an indirect increase of 0.31 units in regional innovation capability, and the indirect effect accounts for 6.10%. According to the analysis of the test results of R&D personnel flow, the factor coupling degree D increases by 1 unit, the R&D personnel flow level increases by 0.789 points, resulting in an indirect increase of 0.24 units in regional innovation capability, with the indirect effect accounting for 7.68%. The results of three-dimensional spatial fitting show that the transformation and upgrading of industrial structures have differential impacts on the regional innovation development of factor combination, so the threshold model is introduced for further analysis.
Threshold regression results show that, on the whole, the transformation and upgrading level of industrial structure shows a dynamic role of marginal increase before and after crossing the threshold value, which fully indicates that the digital economy is a strong innovation driving force in the stage of high-quality development. However, from the perspective of sub-regions, before and after the transformation and upgrading of industrial structures crossed the threshold value, the eastern region has shown a promoting effect of marginal growth, with the factor coupling coordination coefficient passing the 1% significance test; while the central and western regions have exhibited a non-linear pattern of initial promotion followed by inhibition.
The findings suggest that it is essential to encourage deep coupling between data elements and human capital to create sustainable regional innovation competitive advantages, focus on cultivating development engines centered around the digital industry, and form a positive feedback mechanism that promotes innovation through technology. Moreover, the channel effect of knowledge spillover should be valued to strengthen technological exchange between regions, and it is critical to encourage the free flow of R&D personnel between regions, enhance the level of industrial structure transformation and upgrading, and fully stimulate the "Metcalfe’s power" of the combination of data and human capital formation elements.

The open competition mechanism for selecting the best candidates is an important booster for key technology research, with the dual advantages of concentrating efforts on major issues and cross-regional selection. It helps to attract talents within and outside the regions to select the best candidates for research and development, and promotes the flow and concentration of innovative resources in the region. However, the policy practice is mostly focused on how to clarify the key projects in the competition mechanism, and fails to give effective play to the advantages of the mechanism.The studies on the open competition mechanism have mainly focused on the institutional model, and some scholars have analyzed the characteristics of the chief technology officers, however, few studies have dealt with the effectiveness of the "assuming the best candidates" in inter-regional practice, Therefore, this paper focuses on the inter-regional open competition mechanism and examines the current status of its operation.
In order to gain an in-depth insight into the national practice of open competition mechanism of core technologies at the micro subject level and macro regional level, this paper analyzes the characteristics of subjects who issue project demands and subjects who make successful bidding in cross-regional open competition mechanism based on the public information collected from the websites of the municipal governments of 31 provinces and through the matching of subject information by official websites of various units, Baidu, and the State Intellectual Property Office. Then, by taking the provinces where project demands are issued as the source, the provinces that make successful bidding as the target, and successful bidding frequencies as the weight, the study constructs the cross-regional successful competition network to explore the distribution characteristics of the nodes of each province and the characteristics of the network as a whole, and reveal the current situation of the operation of the cross-regional open competition mechanism.
It is found that China's successful cross-regional bidding rate varies greatly from region to region, but the overall rate is relatively low; the subjects who issue their technology demands are dominated by medium- and large-sized manufacturing enterprises less than 30 years old, and their counterparts are mainly from comprehensive and scientific and technological "985" and "211" colleges and universities, small- and medium-sized scientific research and technological service enterprises less than 10 years old, and scientific research institutions with excellent scientific research foundations and rich innovation outputs, as well as the "internal and external cooperation" consortia led by enterprises and universities. The overall participation of the provincial and municipal nodes in the cross-regional open competition mechanism is high, but the depth and breadth of participation are poor, and the strength of the links between the provinces and municipalities is generally weak; the cross-regional network presents the characteristics of "flat hierarchy + circle interaction". Specifically, the provinces in the core circle show the strength of "single nucleus radiation", the provinces in the middle circle "bring the weak with the strong", and the provinces in the peripheral circle lack initiative and enthusiasm.
In order to better implement the open competition mechanism to promote the flow and agglomeration of science and technology innovation resources, this paper suggests that it is necessary to (1) establish a nationwide platform for open competition mechanism to break down the information access barriers ; (2) improve the financial system of science and technology to ensure that the selection of talents is not subject to geographical constraints, and improve the selection mechanism to ensure fair competition; (3) establish incentive mechanisms and government support measures to release the vitality of the more developed regions in the cross-regional open competition mechanism and give full play to the leading and radiating role of the more developed regions; (4) and encourage the less developed regions on the periphery to take the initiative to establish contact with the provinces and cities that are in the structural holes in the cross-regional bidding network.

China′s digital economy industry has been expanding in scale and depth, with a strong promotion effect on economic growth. However, due to practical differences in economic foundation, factor endowment, geographical location, and other aspects, China′s digital economy during its high-speed growth,implies the development of an uneven, homogenized path of structural problems. The trend of a "digital divide" between regions, industries and groups is becoming more and more obvious. Uneven regional development of the digital economy has a negative impact on the coordinated development of the regional economy, and the relationship between regional disparities and the "digital divide" has an accelerating tendency to fall into a "vicious circle" under the effect of the siphon effect, resulting in widening the economic gap and deepening the old irrational contradictions of the original pattern of regional economic development. These issues raise the questions of how the spatial and temporal distribution pattern and evolution trend of China′s digital economy industry and its subsectors are evolving at this stage, and what kind of spatial convergence characteristics exist. The scientific answers to the above questions are of great practical significance for the comprehensive understanding of the spatial differences and regional connections in the development of China′s digital economy industry.
Using the EG index, standard deviation ellipse method, and σ-convergence and β-convergence models, this study examines the spatio-temporal pattern and evolutionary trend of China′s digital economy industry using sub-industry data of China′s digital economy industry for the period of 2013-2021, and tests the convergence characteristics in conjunction with spatial effects. The research finds that China′s digital economy industry as a whole is in multi-polar distribution, the spatial trend is decreasing step by step from the coast to the inland , the spatial agglomeration degree is medium and shows a weak trend of dispersion, the center of gravity of the distribution tends to move to the south; digital economy industry segments coexist in both agglomeration and dispersion trend, in which the digital product manufacturing industry is mainly manifested in the migration to the southwestern provinces of Sichuan-Chongqing and Guizhou, while the digital product service industry, the digital technology application industry, and other capital and technology-intensive industries are further clustered to the southeast coast; there is no obvious σ-convergence in the development of digital economy industry nationwide, but it is characterized by significant absolute β-convergence and conditional β-convergence, i.e., the less developed regions show a stronger growth trend. Factors such as the level of economic development, technological innovation, economic openness, and digital infrastructure have different degrees of facilitating effects on the convergence of China′s digital economy industry, and can amplify the spatial spillover effect of digital economy industry development on neighboring regions.
Compared with the existing literature that mostly measure the level of the digital economy through the construction of the indicator system, and fail to comprehensively reflect the connotation of the digital economy industry, this paper defines the scope of digital economy industries based on the "Statistical Classification of the Digital Economy and its Core Industries (2021)", which profoundly responds to the connotation of digital industrialization and industrial digitization, enriches the relevant research on the quantitative assessment of the digital economy industries, and also provides a useful supplement to the in-depth understanding of the characteristics of the internal differences of China′s digital economy industries; besides, existing studies usually ignore the potential impact of spatial effects on the dynamic evolution of China′s digital economy industry development, and lack a systematic exploration of the spatial convergence characteristics of China′s digital economy industry development and its influencing factors. This paper, however, introduces a variety of spatial analytical methods, such as the EG index, standard deviation ellipse, spatial autocorrelation and other spatial analytical methods, to explore the spatio-temporal pattern and the law of evolution of China′s digital economy industry; its spatial convergence characteristics are analyzed by the σ-convergence and β-convergence models, which provides empirical reference for revealing the trend of the dynamic evolution of the development of China′s digital economy industry and its intrinsic laws and promoting the regional coordination development of the digital economy.

There are two varieties of the platform: consumer Internet platform and industrial Internet platform. The two platforms are different in terms of structure and functionality. Consumer Internet platforms, often known as B2C or C2C commerce platforms, are primarily used to facilitate trade services and connection information between bilateral suppliers and consumers. The industrial Internet platform involves many links in the industrial chain, such as production, supply, and sales. It provides basic support services through technical empowerment, realizes the synergy of the whole industrial chain through online and offline integration, and plays a huge role in industry resource integration cost reduction and efficiency improvement. Scholars have made rich achievements in studying the evolution of consumer internet platforms, but the theory and practice of industrial Internet platforms are still lagging behind.
Prior research has demonstrated that two critical viewpoints for examining the evolution of platforms are dynamic capability and business model innovation, both of which are mutually reinforcing and collaborative. However, they are rarely combined by researchers to examine their synergistic effect in the evolution of industrial Internet platforms. The organic combination of dynamic capability and business model innovation can make enterprises form an isolation mechanism that hinders competitors from imitating, which is very important for platform evolution. Therefore, from the perspective of integration of dynamic capability and business model innovation, this paper studies how to realize the evolution of industrial Internet platform through the mutual drive and co-operation of dynamic capability and business model innovation in the logic of "factor-process-result", so as to provide reference for other enterprises to build and develop industrial Internet platforms.
This study uses the exploratory single case study approach and chooses Zhijing Technology as the case based on the theoretical sampling. The "triangle verification" approach is used in this paper's data collection, which gathers information from multiple sources. The data of this study are mainly second-hand materials collected through open channels, and the sources mainly include the official information released by Zhijing Technology, high-quality academic papers and teaching cases with Zhijing Technology as the research object, and authoritative news media reports. In addition, it also includes the researchers' direct observation experience of various APP business modules of Zhijing Technology.
Firstly, the important influencing factors of the evolution of industrial Internet platforms include the internal and external environment of enterprises, and the internal environment mainly includes managers' knowledge and experience, managers' cognition, corporate resources and ability, etc. The external environment is mainly composed of market demand, location advantage, market competition, technological change and policy support. The evolution process of industrial Internet platforms must fully consider the influence of the internal and external environment. Secondly, in the evolution of industrial Internet platforms, dynamic capability, and business model innovation are mutually driven and co-performed. Dynamic capability drives value proposition and value creation innovation respectively by enhancing the keenness of internal and external opportunities and the overall planning of internal and external resources, thus driving business model innovation; the experience and resources accumulated by enterprises in the process of business model innovation also drive the upgrading of dynamic capabilities. In this process, the dynamic capability has experienced the upgrading of the cognitive dimension "opportunity perception capability, opportunity exploration capability and opportunity development capability" and the behavioral dimension "resource patchwork capability, resource integration capability and resource reconstruction capability", and the attributes of business model innovation have experienced the process of "efficient business model innovation, novel business model innovation, and locked business model innovation". Finally, the evolution of industrial Internet platforms presents a path of "platform construction, vertical extension, and vertical and horizontal expansion". Enterprises first build a B2B trading platform connecting bilateral users, then use digital technology to empower some industrial chain enterprises, and finally integrate industrial chain resources through horizontal and vertical business expansion to realize data interconnection between upstream and downstream of the industrial chain, and help the whole industry to reduce costs and increase efficiency, and achieve transformation and upgrading.
The study reveals the evolution mechanism of industrial Internet platforms, and enriches the research on the evolution of industrial Internet platforms and the relationship between dynamic capabilities and business model innovation.

In the new wave of industrial digital transformation, Chinese enterprises are facing multiple challenges including accelerated technological innovation, constantly changing consumer preferences, and the volatility and restructuring of global supply chains. Therefore, enterprises need to re-examine their digital transformation vision and strategy, focusing on how to enhance and reshape their digital capabilities. As the dynamic capability foundation for enterprise digital transformation and upgrading, digital capability is the ability of enterprises to widely integrate digital resources and other organizational resources in the value network using digital technology to promote systematic digital transformation and achieve digital value creation. This enables enterprises to break free from traditional resource dependencies during the digital transformation wave, thereby achieving a sustainable competitive advantage. However, building and enhancing a company's digital capability is a complex system process, and existing research on the factors that affect a company's digital capability is relatively scattered. Previous studies mainly focus on the independent effects of a limited number of factors on digital capability, and the identification of key factors is not comprehensive enough, nor does it consider the possible interrelationships between various influencing factors.
To answer the fundamental question of how enterprises possess digital capabilities, this study adopts the Technology-Organization-Environment (TOE) framework and the ISM-MICMAC system dynamics approach to explore and clarify the hierarchical path of multiple factors affecting the digital capability of enterprises. This study uses literature research method and TOE framework to screen out 19 effective English articles and 23 articles in Chinese, and preliminarily identifies the influencing factors of technology, organization, and environment on the digital capabilities of enterprises. Then, through expert group consultation and opinion summary, it identifies the main 19 influencing factors of enterprise digital capability. Secondly, the ISM method is used to clarify the hierarchical relationship and correlation path between various influencing factors, and converges to enhance the digital capability of enterprises, constructing a multi-level hierarchical explanatory structure model of the influencing factors of digital capability. Finally, this study combines the MICMAC method to identify strong driving force and strong dependent force factors, revealing the importance and role of each influencing factor in the system.
It is concluded that, firstly, in terms of element categories, there are 4 technological factors, 10 organizational factors, and 5 environmental factors that affect the digital capability of enterprises. Secondly, in terms of hierarchical structure, the explanatory structure model of this study consists of eight levels, among which the root factors affecting the digital capabilities of enterprises include six factors such as demand transformation and digital economy level. The intermediate factors include 11 factors such as executive digital cognition and digital human capital, and the surface factors are digital organizational preparation and digital technology application and diffusion. Thirdly, in terms of factor correlation, there are six factors with high driving force and low dependence, among which the deep driving factors are demand transformation, policy orientation, digital economy level, and executive digital background. There are four factors that contribute to high dependence and low driving force. The intermediate factors are digital human capital and technology management, while the superficial factors are digital organizational preparation and digital technology application and diffusion.
The theoretical contributions of this study are threefold. Firstly, by sorting out multiple factors that affect the digital capabilities of enterprises within the theoretical framework of TOE, it advances the systematic understanding of how to enhance the digital capability of enterprises, and makes up for the lack of fragmented discussions on a limited number of antecedents in empirical research. Secondly, it uncovers the hierarchy and interplay of elements in building digital capabilities, offering a new lens on their formation and key components. Thirdly, this study expands the application of system dynamics in the field of enterprise digital research by constructing an explanatory structural model that affects the digital capabilities of enterprises. The exploration of multiple research paradigms to enhance the theoretical framework of enterprise digital capability is beneficial and provides valuable insights for enterprises on building and enhancing their digital capability during digital transformation.

The decision-making experience and practical evidence on how to enhance enterprises' core technology innovation performance in key fields are relatively scarce and have not been fully studied. At present, most of the studies have only explored the influence of antecedent variables on the core technology innovation performance in key fields, but have not conducted in-depth investigation on the basic conditions of the role of each influencing factor as well as the specific context, and an integrated analytical framework on the antecedent factors of enterprises' core technology innovation performance in key fields is missing.
Therefore, within the TOE theoretical framework, this study takes 80 Chinese high-tech manufacturing enterprises as sample cases, collects and normalizes sample data during the 3-year period from 2018 to 2020, in which R&D investment and other data are from the Cathay Pacific database (CSMAR), invention patent data are from the Wisdom Sprout Global Patent Database (PatSnap), and data related to digital technology are from the annual reports of listed companies. It uses fuzzy-set qualitative comparative analysis (fsQCA) to explore the influencing factors of core technology innovation performance in key fields and their enhancement strategies.
It is found that, first, individual antecedent factors do not constitute a necessary condition for the generation of high innovation performance, but the level of digital technology and firms' research and development (R&D) investment play an important role in generating high innovation performance. Second, there are four different combinations of antecedent conditions, namely digital-integrated innovation strategy, digital-perceived innovation strategy, digital-collaborative innovation strategy, and digital-R&D innovation strategy. Core technology innovation in key fields is not only limited by the influence of knowledge innovation, but also constrained by the enterprise's R&D, innovation resources, etc. Digital technology helps enterprises generate high levels of key core technology innovation performance by effectively improving the enterprise's resource allocation methods, changing technology innovation model. Third, in the grouping of enterprises to achieve high-level core technology innovation performance, when the level of digital technology and the environmental characteristics of enterprises are the same, knowledge integration ability and knowledge perception ability can be effective substitutes for each other. In addition, the knowledge integration capability and knowledge perception capability of an enterprise can effectively complement each other.
The practical implications of this study are threefold. First, enterprises should start from a holistic perspective, and not only focus on the impact of a single factor on their innovation performance. As a complex innovation decision, the R&D of core technology innovation is difficult, and the risk of R&D is high. Enterprises need to fully combine the research foundation of enterprise technology, organizational ability and the external environment. Second, enterprises should combine their own technical conditions and organizational capabilities to build new advantages in technology research and development. In a highly dynamic environment, enterprises with strong knowledge integration capabilities can adopt a digital-integrated innovation strategy and rely on digital technology to assist enterprises in utilizing innovation. Enterprises with strong knowledge-perception capabilities can adopt a digital-perception innovation strategy and use digital technology to assist enterprises in exploratory innovation. When enterprises lack perception or integration capabilities, they can also adopt a digital-R&D innovation strategy to optimize the allocation of innovation resources, adjust the R&D model and change the business model through the deep embedding of digital technology. In addition, in a non-highly dynamic environment, enterprises can adopt a digital-collaborative innovation strategy to empower enterprises to carry out dual innovation activities through digital technology. Third, enterprises should continue to improve their own digital technology level and increase R&D investment to provide new impetus for core technology innovation. Government departments should further improve the optimization mechanism of R&D subsidies, and continue to formulate scientific and effective incentive policies for the layout of digital technology for enterprises, so as to encourage enterprises to adopt digital technology to empower research and innovation in core technologies. While enterprises need to continuously improve and optimize R&D investment, make full use of digital technology effects for R&D, constantly explore new paradigms for R&D, and expand new boundaries of knowledge, so as to achieve core technology innovation in key fields.

In recent years, with the development of emerging technologies, the "pragmatism" tendency of patent authorization examination has become more and more prominent, which leads to a lack of ethical rationality in patent authorization examination, and even breaks through the moral bottom line in some cases, seriously threatening the most basic ethical value requirements of safety and order in patent authorization examination. Although the intellectual property chapters of international treaties, regional patent treaties, and free trade agreements (FTA) all contain authorization requirements for refusing inventions that disturb public order, violate public morality, and that are harmful to the life and health of humans, animals, or the environment, and many countries have already paid attention to the ethics of patents, the existing rules actually only pay attention to the ethical issues of the technology itself, and do not pay attention to the ethical requirements in the R&D process of patented technology which aims at excluding technologies with significant ethical defects. The purpose of constructing a perfect scientific and technological ethics review system is to ensure that the activities are conducive to enhancing human well-being and realizing the sustainable development of scientific research. Therefore, it is of great significance and innovation to take the technical ethical review in patent application as the research theme.
This paper puts forward "two dimensions of patent ethics", namely "institutional ethics" and "technical ethics". Institutional ethics of patent refers to whether the design of patent rules conforms to ethical norms, whether it is beneficial to the survival and development of human beings and whether it is fair;the technical ethics of patent is closely related to the invention, and it is a dimension closely related to the governance of scientific and technological ethics in patent ethics. Technical ethics also has two meanings: one is whether the process of invention conforms to ethical norms; the second is whether the technology or invention itself has potential ethical risks. In fact, whether technology itself violates ethics is not a simple legal issue, but an issue of value judgment. Therefore, the study focuses on the ethical issues in the R&D process of technology that applies for patent authorization, and the construction of relevant mechanisms for reviewing the ethical issues in the stage of patent application and authorization. Subsequently, combined with the current legislation and practice, it is pointed out that the lack of patent ethics review mechanism in China leads to some unavoidable practical problems. Then it demonstrates the necessity and significance of an ethical review of patent application. In the last part, it puts forward the method and path to construct the technology ethical review mechanism for patents in China.
It concludes that the lack of a special patent ethics review mechanism will not only lead to a poor connection between patent law and scientific and technological ethics norms within the framework of scientific and technological law, but it will also be difficult to regulate the ethical risks of independent research activities outside science institutes. Constructing a patent ethics review mechanism is helpful to realize the effective connection between science and technology law and patent law, enforce the compliance of scientific research procedures, and protect the interests of vulnerable groups. Therefore, firstly, the Patent Law should be revised to effectively link it with the science and technology law. Secondly, the principle of ethical review of patent application should be established; the ethical review of patent should not be at the expense of the efficiency of patent examination and approval; the ethical examination of patent should not excessively increase the burden of examiners and exceed their professional ability.Thirdly, a list of patent ethics review should be formulated. Classified and graded supervision procedures should also be implemented. Classified supervision means distinguishing between applications that need to accept ethical review and those that do not need to spend relevant resources to conduct review. Graded supervision is to distinguish between the strictness of ethics review and its applicable standards. It is necessary to set up "general procedures" and "summary procedures" for patent applications with technological ethical risks, and improve the self-discipline management of researchers and their awareness of ethical compliance.

The government's support for corporates to carry out applied basic research through the funding of science funds is an important measure for corporates in China to enhance their independent innovation capability,master key core technologies and deeply integrate industry,academia and research. This study selects five countries—China, the United States, the United Kingdom, Japan, and South Korea—and examines their respective government-supported R&D innovation funding initiatives for corporates. It provides a comprehensive analysis by comparing the objectives of establishment, eligibility criteria for funding recipients, funding sources, and the mechanisms and scales of R&D funding programs across these nations.
In terms of the purpose of establishment,the government-supported corporate R&D funding programs of the five countries have clear targets. The funding programs in the United States and the United Kingdom are primarily aimed at enhancing the innovation capabilities of small and medium-sized corporates, encouraging their participation in scientific and technological R&D to improve their research and innovation levels. Additionally, the United States is dedicated to fostering collaboration between industry, academia, and research institutions, thereby propelling the advancement of corporate technology R&D and the commercialization of research outcomes. China, Japan and South Korea provide funding in accordance with national strategic priorities. China pays more attention to the urgent needs and cutting-edge research of key technologies. Japan focuses on major technological breakthroughs,aiming to address the forefront technological issues that are urgent at regional,national,or even global levels. South Korea,on the other hand,centers on resolving current technological bottlenecks,offering categorized funding according to different technological fields.
The five countries have varying eligibility criteria for corporate funding. China is stringent, favoring strong or partnered corporates. The US offers the broadest funding scope, targeting small businesses and promoting industry-academia-research collaboration, where corporates share R&D outcomes on a membership basis. Japan emphasizes tri-partite cooperation and requires joint university applications for funding. The United Kingdom and South Korea do not have explicit requirements for the types of corporates eligible for funding,with South Korea focusing on encouraging deep cooperation among various innovation institutions,allowing corporates to apply individually or in conjunction with research organizations.
　In terms of funding sources,China has been developing a multi-subject input mechanism. The United States' government-supported corporate R&D funding programs encompass a mix of government,corporate,and other institutional contributions,with many programs adopting a corporate membership fee model for corporate participation in funding. Other countries primarily rely on government grants or procurement. In terms of funding models and scales,the United States sees significant variations in the amounts of R&D funding programs,with corporates eligible for funding ranging from $100,000 to $9 million,over periods of 2.5 to 5 years. Japan and South Korea adopt a natural-year format for their funding,with a broader span of funding periods ranging from 1 to 10 years. This approach of longer natural-year funding cycles enables many original innovation and core technology areas in Japan and South Korea to receive long-term,stable support.
Regarding funding evaluation,China's corporate-funded projects usually carry out strict evaluation on the mid-term and final assessment. Both the United States and the United Kingdom conduct reviews at various stages of funded projects. The United States performs performance evaluations at the completion of each phase,with continuation to the next phase contingent upon passing these assessments. The United Kingdom establishes formal evaluation and auditing processes during the funding period and upon submission of project results.
In light of the current challenges and opportunities to strengthen basic research support for Chinese businesses, this paper first suggests aligning strategic funding goals with market needs to enhance the dual-drive strategy. Second, it recommends developing a differentiated funding system to specifically encourage corporate innovation and expansion. Third, it advises creating an industry-academia-research cooperation funding structure to promote mutual benefits through a variety of partnerships. Finally, it calls for the refinement of the classified and layered funding model to progressively increase the effectiveness of financial assistance.