As the main body of scientific and technological innovation, scientific researchers play an important role in the ethical governance system of science and technology. To carry out scientific research, they need to bear corresponding social ethical responsibilities. Institutional ethical review and supervision system and ethical publicity and education are two important ways of scientific and technological ethical governance, which respectively play the governance functions of "restraint" and "internalization". This paper uses structural equation model to empirically analyze the effectiveness and mechanism of the two paths, and analyzes the impact of the two governance paths on researchers' acceptance of ethical codes, ethical risk perception and research willingness. The results showed that the "constraint" path positively affected the acceptance of ethical codes and ethical risk perception of researchers, indirectly positively affected the positive attitude and research willingness of researchers towards ethical disputes in biotechnology, and the "internalization" path positively affected the risk perception of researchers. The research results provide a reference for scientific research institutions to build an ethical governance path, enhance the ethical risk awareness of researchers and standardize research activities.
At present, AI governance is gradually moving towards the era of legal governance, with obvious "national differences" characteristics. The most representative AI governance models are the EU's centralized governance model guided by ethics priority and the US's decentralized governance model guided by innovation priority. The study of the internal formation logic, characteristics and difficulties of AI governance models in the United States and Europe is of great benefit to the reflection and construction of AI governance systems in line with national conditions. The article compares and analyzes the differences of AI governance system between the United States and the European Union from five aspects: governance concept, governance structure, governance subject, governance intensity and governance dilemma. On this basis, it discusses the general issues and principles that should be paid attention to during the construction of the national AI governance system, such as paying attention to the tension between path dependence and model transplantation, balancing the relationship between "development" and "ethics", etc.
Scientific methodology is an architecture to guide scientific research activities. This paper attempts to explore the influence of scientific methodology on public willingness to participate in citizen science. The methodology of the citizen science project was divided in two dimensions: theoretical deduction and experimental intervention, and the research methods under the two dimensions are summarized as induction and deduction, as well as exploration and exploitation, forming a 2X2 research methodology system. 1,970 citizen science projects were adopted as research corpus, and text mining is employed to classify the narratives. We expanded the keyword dictionary regarding the research methods, resulting in a list of 481 keywords for citizen science research methods, and conduct corpus training to expand keywords based on text similarity. Then we use the constructed keyword dictionary as the corpus for classifying texts. Using stem words and word frequency for text classification. The econometric models with the number of participants and the amount of financing as dependent variables are constructed to estimate the effectiveness of the methodology. The results show that induction method accounts for the largest proportion (33%), while deduction method accounts for the smallest proportion (20%). However, from the effect of methodology, deduction and exploration have significant advantages over induction and exploitation, respectively. From the comparison of the 2X2 quadrant, the deduction has significant advantages over the other three types of methods. Further, researcher identities, disciplinary heterogeneity, funding goals and social engagement play a moderating role. That is, non-professional researchers should focus on the feasibility and scientificity of the methods used in the project, while professional researchers may not have to overly focus on the impact of research methods on project participation. The results indicate that the effectiveness of research methods is mainly caused by graduate students and amateur researchers, and there is no significant correlation with the research methods of university professors and industrial researchers. Relatively speaking, university professors and industry researchers have richer background knowledge, more experience and expertise in matching appropriate research methods for research problems, and stronger professional abilities than the graduate students and amateur researchers. As initiators, professional researchers provide a sense of security to the public participating and are not easily affected by the choice of research methods. Therefore, university professors and industry researchers should not focus primarily on tuning research methods. Also, the project launchers should focus on project attributes. Natural science and high financing target projects should focus on the appropriateness and accuracy of scientific research methods. Furthermore, extensive social participation provides a wider space for information dissemination and resources, easily attracting project enthusiasts. We believe that social participation serves as a "catalyst" between research methods and public participation, and project initiators can gain more public support by increasing social participation. From the comparison of research methods among disciplinary differences, the deductive-exploratory research method has the greatest impact on the willingness of the public to participate under the influence of the social influence of the project initiator. This paper expands citizen science research methods and performance evaluation theory, providing practical reference for citizen science launchers to formulate effective research programs.
From the perspective of the inherent relationship between nation, nationalism, and techno-nationalism, techno-nationalism is the infiltration and manifestation of nationalist trends in technological activities. Its essential feature is that specific nation-state, in pursuit of maintaining their technological independence or leading position, require their technological activities to follow the principle of putting national interests first, emphasizing the distinction between "self-technology" and "other-technology". Techno-nationalism includes three aspects of emotions, theory and policy. Taking purpose-means as a parameter, the contemporary western techno-nationalism can be divided into four basic types: monopolistic-radical techno-nationalism, monopolistic-moderate techno-nationalism, self-interest-radical techno-nationalism, and self-interest-moderate techno-nationalism, which derive from different theoretical, practical, and institutional foundations.
How to identify the regional governance-driven paths of high concentration of scientific and technological talents in each time period and drive the talent concentration with the improvement of regional governance is an important question to be answered. This study takes 31 Chinese provinces and cities as cases, and combines NCA and multi-temporal QCA methods to explore the linkage effects and path choices of governmental, market and social governance elements on regional technological talent agglomeration. It is found that (1) a single condition does not constitute a necessary condition for high clustering of scientific and technological talents in each time period, but the interaction among governmental, market and social governance conditions in each time period can form a diverse set of conditions driving the clustering of scientific and technological talents. In time period 1, there are several equivalent groups such as finance-enterprise-resident-driven, enterprise-environment-driven and finance-industry-resident-driven. In time period 2, there are multiple paths such as enterprise-environment-resident driven and industry-resident driven. (2) Residents' life plays an important role in each time period, and the political and legal environment only plays a supporting role; enterprise quality and residents' life are mutually enhanced in each time period, and enterprise quality and livable environment are mutually weakened in both time periods; the political and legal environment co-evolves with financial input, enterprise quality and residents' life in each time period, and the relationship pattern among regional governance elements changes and generates inter-stage regional governance group evolution. (3) The relationship pattern between the regional governance elements changes at different levels of governance. (3) There are significant differences in the paths driving the concentration of scientific and technological talents in regions with different levels of governance. This study helps to deepen the understanding of the complex interactions among multiple factors of regional scientific and technological talent concentration in each time period, and brings insights to attract scientific and technological talents in different regional governance areas.
In order to narrow the income gap and improve the distribution pattern, China adheres to the fundamental socialist principle of common prosperity, making economic development achievements more beneficial to low-income groups, and significantly improving the domestic income gap. However, due to the disorderly expansion of capital and other reasons in recent years, the Gini coefficient has rebounded, and the trend of income differentiation has not been fundamentally reversed. At the same time, as a new economic model driven by artificial intelligence, industrial intelligence has changed the distribution pattern of various production factors, and will trigger a profound transformation of the production division and income distribution pattern. In particular, the post creativity and production optimization effects in the middle and late stages of intelligent development can improve the relative income level of low-income groups to a certain extent, providing new ideas for alleviating income distribution conflicts in China. While focusing on rapid economic growth, poverty benefiting growth emphasizes more on whether low - and middle-income groups can benefit from growth, in line with China's development goal of narrowing the gap between rich and poor and achieving common prosperity. However, there is little research in the existing literature on the intertwined impact mechanisms of industrial intelligence and population aging on pro-poor growth. Based on the World Input Output (WIOD) database and the World Bank (WB) database, this article examines the impact mechanism of industrial intelligence on poverty benefiting development in the context of aging, providing empirical support for improving income inequality, narrowing the gap between rich and poor, and stabilizing economic growth. The research results show that population aging has a significant inhibitory effect on poverty beneficial growth, while industrial intelligence has a significant promotion effect on poverty beneficial growth. After considering different estimation methods and indicator measurement methods, this conclusion remains robust. Secondly, heterogeneity analysis shows that in the context of population aging, industrial intelligence has a more significant role in promoting poverty beneficial growth in developed countries, post demographic dividend periods, and labor intensive industries. Finally, further analysis found that industrial intelligence in the context of aging mainly affects poverty based growth through job iteration effects and productivity effects, and analyzed the evolution path through GAM fitting diagrams.Compared to previous studies, this article theoretically incorporates both industrial intelligence and population aging into the model, and studies the joint effects of both on pro-poor development. This enriches research on the influencing factors of pro-poor development, providing empirical support for countries to improve income inequality, narrow the gap between rich and poor, and stabilize economic growth; In terms of research methods, both Generalized Least Squares (FGLS) regression and Maximum Likelihood Estimation (MLE) regression are used to verify the robustness of the test results, and heterogeneity testing is conducted based on factors such as different levels of economic development and different demographic dividend periods. The empirical results have higher reliability; In terms of research content, in addition to exploring the intertwined impact of industrial intelligence and population aging on the quality of enterprises' export products, it also in-depth analyzed and verified the impact path of job iteration effect and productivity effect on industrial intelligence, providing empirical support and policy recommendations for poverty beneficial development. The conclusions of this study have important implications for the transformation and upgrading of industrial intelligence in the context of population aging in China and various economies around the world, as well as for promoting poverty beneficial growth and achieving common prosperity.
At present,the security and stability of the global manufacturing industry chain are facing unprecedented challenges.How to improve the resilience of the industry chain and strengthen the construction of the industry chain has become an urgent problem to be solved.Based on the balanced panel data of 30 provinces and cities in China from 2007 to 2017,from the perspective of industrial transformation and upgrading and innovation chain construction,this paper studies the impact of collaborative agglomeration of manufacturing industry and science and technology service industry (hereinafter referred to as collaborative agglomeration of two industries) on the resilience of manufacturing industry chain,and discusses how the collaborative agglomeration of two industries affects the resilience of manufacturing industry chain by influencing technological innovation,On this basis,we further explore the regulatory role of innovation ecosystem symbiosis in this mechanism.The research finds that: the collaborative agglomeration of two industries can significantly promote the resilience of the manufacturing industry chain by influencing technological innovation.The symbiosis of innovation ecosystem can effectively adjust the impact of the collaborative agglomeration of two industries on the resilience of the manufacturing industry chain.The collaborative agglomeration of two industries can not only directly affect the toughness of the manufacturing industry chain,but also effectively adjust the impact of technological innovation on the toughness of the manufacturing industry chain.Based on the above research conclusions,relevant suggestions are put forward to enhance the resilience of the manufacturing industry chain.
Abstract：With the development of digital economy, big data, cloud computing, block chain, artificial intelligence and other digital technology system gradually mature, China's industrial chain gradually towards digitalization, networking and intelligence, digital economy has changed the traditional industrial chain model, effectively improved the industrial chain including various links of R & D, production, transportation and sales. Through big data and cloud computing simulation, digital economy has reduced R & D costs to improve production. Therefore, can the development of digital economy empower the key links of the industry chain, finding out the path of promoting the breakthrough of core "neck" technology to enhance the control ability of key links of the industry chain? Along this line of thought, this paper focuses on two aspects of digital industrialization and industrial digitization, and compares to study the function of digital economy to the control ability of key links in the industrial chain.
The digital economy relies on digital technology and uses big data as a key production factor, changing the traditional industrial chain model. This paper combines input-output tables and Guotaian database to statistically measure the data of digital economy, industry chain centrality and intermediation from 2016-2022, and comparatively study the issue of digital industrialization and industry digitization to enhance the control ability of key links of industry chain, and conclude that: First, digital economy, digital industrialization and industry digitization significantly enhance the control ability of key links of industry chain, and the intensity of the role decreases in turn Second, there is regional heterogeneity in the digital economy to enhance the control ability of key links in the industry chain, with the eastern coast to the comprehensive economic zone in the northwest weakening in turn; Third, there is industry heterogeneity in the digital economy to enhance the control ability of key links in the industry chain, with the special equipment to transportation equipment, storage and postal services weakening in turn; Fourth, digital technology innovation takes the mediating effect of the digital economy, digital industrialization, industry digitization and key links in the industry chain. The intensity of intermediary effect of digital economy for industry chain centrality and intermediary degree are 0.4452 and 0.3635 respectively, accounting for 76.36% and 64.45% of the total effect ratio respectively. Accordingly, targeted countermeasure suggestions are proposed.
This paper proposes the following countermeasures: First, digital industrialization and industrial digitalization synergistic symbiotic system should be established. China should strengthen the promotion of digital industrialization and industrial digitalization in the same frequency linkage, establish a symbiotic system of synergistic development, effectively drive the key links of the industry chain to improve control capabilities, bridge the digital divide, and share digital achievements. Second, Taking the New National Mechanism advantage to promote the "neck" technology precision breakthrough. China should take advantage of system advantage to promote the digital economy to empower the "neck" industry chain of the core technology, to achieve a safe and stable industry chain, independent and controllable. Third, designing the digital technology innovation targeting target system. China should clearly locate the digital technology innovation target with development strategy, increase the "neck" industry linkage in different industries and regions, promote regional coordinated development, precisely enhance the independent R&D and innovation capability of digital technology, and further enhance the control capability of key links in the industry chain. Accordingly, China should increase support for the digital economy industry, build a production network with a smooth domestic and international cycle to achieve high-quality growth in the whole industrial chain.
Abstract: Exploring the use of blockchain technology to improve the level of government services has become a hot topic of common concern in the current practical circles and academia. Based on the thinking of the difference between the mechanism of blockchain technology and the efficacy of practical applications, this paper combines the research basis of technology adoption and adaptive structuring theory, and relies on the interaction relationship of actors, technology, and organizational structure characteristics to understand the adoption mechanism of blockchain technology in the field of government services, and uses the reform case of the Blockchain Plus Government Services initiative on the District L of Y City to verify and supplement. It is found that the bounded interaction between reform actors and government organizational structure characteristics affects the application effect of blockchain technology, and the adoption of blockchain technology presents the characteristics of "adaptive and bounded adoption". Based on this, this paper innovatively proposes a bounded technology adoption model to explain the degree of technology adoption and the bounded application effect. The study further proposes that in the process of technology adoption, the corresponding technical structure can be matched and embedded based on the actual situation of the organization, and the organizational change that is compatible with the technical structure can be completed, so as to better improve the application effect of the technology.
As a new organizational model of R&D, innovative R&D institutions are gradually becoming a new force for innovation driven development. This paper analyzes the realization mechanism of the functions of innovative R&D institutions through multiple cases, namely, Beijing Institute of Collaborative Innovation, Beijing Academy of Quantum Information Sciences and Beijing academy of Artificial Intelligence, and finds that innovative R&D institutions break through the barriers of knowledge flow in innovation collaboration through a series of internal governance mechanism innovations, and support the realization of their functions from basic research, application research to achievement transformation.
The research conclusions are as follows: (1) The goal of the internal governance mechanism of innovative R&D institutions is still focused on the realization of research functions. There is still a lack of innovative and breakthrough institutional mechanisms in the transfer and transformation of scientific and technological achievements, and the functional blending of innovative R&D institutions needs to be further explored; (2) Innovative R&D institutions effectively promote the integration of multiple agents by establishing a diversified input mechanism and a decision-making mechanism of the board of directors, laying a foundation for implementing application oriented R&D activities and solving the problems of resource coordination and strategic coordination; (3) Innovative R&D institutions promote the coordination of science and market system logics through flexible scientific research fund use system and innovative intellectual property system, and solve the multiple institutional logic barriers between different subjects faced by achievements transformation; (4) Innovative R&D institutions provide the possibility to cross the "fence" between organizations and promote the integration of multi-source knowledge by establishing diversified professional talent teams.The research conclusion has certain theoretical significance for the functional design and implementation of innovative R&D institutions.
Convergence science has triggered a new wave of scientific and technological innovation, which is of great value for the realization of key core technologies from "Lagging Behind and Catching Up" to "Leading and Surpassing". However, there is still a gap in the research on the R&D characteristics and breakthrough paths of key core technologies. Facing traditional manufacturing and emerging industry, this paper selects two typical technologies, namely, industrial robot bearing and brain computer interface, and explores the R&D characteristics and breakthrough paths of key core technologies by using the Derwent patent network analysis method. This paper finds that: (1) There are significant differences in the R&D characteristics of key core technologies from the perspective of technology convergence. The basic technologies represented by industrial robot bearings are mainly the intersection of similar disciplines and the intersection of internal categories of technologies, emphasizing the integration of technology networks; Brain computer interface is a cutting-edge technology represented by a wide range of disciplines and cross technology departments, emphasizing the diversity of technology clusters. (2) On the basis of the analysis of the R&D characteristics of key core technologies, we explore two breakthrough paths, namely, "Scenario Demand Traction + Technology Internal Category Integration + Leading Enterprises Driving Industrial Chain", "Technology Innovation Driving + Cross Technology Department Integration + Industry-University-Institute Innovation Consortium". This paper has further improved and developed the theoretical research on the breakthrough of key core technologies, which has a certain practical guiding significance for realizing the self-reliance of China's high-level science and technology.
Academic entrepreneurship has become one of the most prevalent forms of science and technology transformation. In order to clarify the impact mechanism of academic entrepreneurship, individual information of 7641 faculty members affiliated with five universities in Shanghai was collected, which included research achievements and academic entrepreneurship activities. The Poisson and Tobit regression models were constructed to analyze the effect of academic entrepreneurship on faculty members' research output. The internal transmission mechanism of the effect of academic entrepreneurship was explored with knowledge exploration as the mediator. According to the study, faculty members' real status of academic entrepreneurship significantly promoted knowledge exploration in new disciplines. A direct effect of knowledge exploration on faculty members' basic research output and the quality of applied research was observed, while it played a mediating role for the impact of academic entrepreneurship on the impact of basic research and the quantity of applied research. There should be careful consideration of both the mutual benefits and clog-out effects associated with academic entrepreneurship and reasonable guidance of faculty members' entrepreneurial behavior in accordance with an organization's vision. Several supporting policies are needed to support academic entrepreneurship, improve the multi-goal performance evaluation system for faculty, and encourage the synergistic and orderly development of scientific research and academic entrepreneurship.
Cities and enterprises are important carriers of resource elements, and are key levers for achieving green and high-quality development. As a new engine for economic growth, the digital economy provides opportunities for green and high-quality de-velopment in cities and opportunities for promoting the green transformation of en-terprises. The existing research has demonstrated the impact of digital economy on the green and high-quality development of cities. However, most of these studies have focused on the macro or meso level, without taking into account the interactive development mode between cities and enterprises. The ESG performance of a company provides a good perspective for analyzing its impact on the city. ESG stands for environmental, social, and corporate governance, which are three key aspects of a company's sustainable development. A company's good ESG perfor-mance indicates that it performs well in areas such as environmental protection, so-cial responsibility, and corporate governance. by analyzing a company's ESG per-formance, we can understand its commitment to the city's environmental and social responsibility, as well as the rationality of its governance structure, and evaluate its impact on the city. This study, therefore, focuses on the symbiotic structure of "city-business" and examines the impact, mechanism, and heterogeneity of the de-velopment of the digital economy in cities on the ESG performance of enterprises aiming to construct a new path for green and high-quality development.
Specifically, based on the resource-based theory and using financial report data from A-share listed companies in China from 2011 to 2019 and statistical data from major cities and towns, this study employs a difference-in-differences model to test the resource effect and path of the impact of the development of the digital economy in cities on the ESG performance of enterprises, using the comprehensive trial policy of the national big data experimental zone. The study employed various methods, such as parallel trend test, placebo effect, PSM-DID, and lag analysis, to examine the robustness of the findings. The results of the study are as follows: (1) The devel-opment of the digital economy in cities has a significant positive effect on the ESG performance of enterprises, and this effect varies with property rights, technological attributes, and industry pollution levels. The state-owned enterprises, non-high-tech enterprises, and non-heavy-polluting industries are more able to leverage the re-source effects brought about by the development of the city's digital economy; (2) At the city level, the development of the digital economy in cities can empower sus-tainable development of enterprises through the aggregation of digital talents and the construction of digital finance; (3) At the enterprise level, the development of the digital economy in cities can promote the digital transformation and green innovation of enterprises, thereby enhancing their ESG performance. The marginal contributions of this paper are as follows: (1) exploring the causal relationship between urban digital economy and corporate ESG performance from the perspective of digital economy; (2) interpreting the resource effect of urban digital economy on corporate ESG performance from the perspective of resource-based theory.
This study places cities and enterprises within the framework of green and high-quality development. Based on theoretical analysis and empirical testing using multiple econometric methods, it provides a new path for the collaboration of cities and enterprises to achieve green and high-quality economic development.
Zombie firms are those firms that have poor profitability and rely on government support or external financing to survive and not exit the market, which crowd out normal firms, slower economic growth and reduce tax sources. Zombie firms have a large number of bank loans, which bring financial risks to banks, or create pressure on local governments by enjoying financial resources. The disposal of zombie firms is an important part of supply-side structural reform to achieve industrial restructuring and upgrading, and promote the high-quality development of China's economy. Special Economic Zones (SEZs) is an important place-based policy of the Chinese government to promote economic growth, attract foreign investment, and promote scientific and technological innovation. The impact of SEZs on firms' productivity and growth has received widespread attention from scholars, and a natural question is whether SEZs can inhibit the formation of zombie firms? Different from previous studies, which mainly focus on the zombie firms in manufacturing industry, this paper explores the effect of SEZs on the formation of zombie firms in high-tech industry. We use an unbalanced panel dataset of Shanghai science and technology firms from 2008 to 2018, and after removing outliers and missing values, the dataset included a total of 54,629 firms, 160,165 observations. We use real profit method, amended real profit method, amended excessive loan method, and branch method to identify whether a firm was a zombie. We find that the proportion of zombie firms in our sample is 12.8%. After adding the control variables, industry and time fixed effects, the coefficient of dummy variable (SEZ) was -0.006 and passed the significance test at the 1% level. So SEZs inhibit the formation of zombie firms, which reduce the probability of firms becoming zombies by 0.6%. The results are still robust after replacing the dependent variables, using propensity score matching method, and controlling the location of firms. We also test two mechanisms to baseline results. First, SEZs restrain firms from becoming zombies by promoting innovation. SEZs provide a good business environment for firms to operate and innovate, and firms improve their production efficiency and reverse losses through the agglomeration economy, close cooperation network and active innovation activities of SEZs, so the probability of firms becoming zombies is reduced. Second, government subsidies from SEZs increase the probability of firms becoming zombies. SEZs provide a variety of preferential policies for firms, including tax preferences and subsidies. Some firms can continue to survive for the purpose of obtaining policy rent, not filing for bankruptcy and exiting the market. Based on the findings, this paper makes the following policy implications. First, science and technology firms, as the main body of innovation, represent the direction of innovation-driven development, so they are favored and cared for by local governments. But there are also zombie firms surviving in high-tech industry, which suggests governments to adopt reasonable methods to identify them and try to avoid them occupying or rent-seeking valuable policy resources. Second, due to weak operating ability and poor profitability, some zombie firms may have more opportunistic tendencies and put more energy into seeking policy rent. Therefore, SEZs should adopt more inclusive policies and cut down direct subsidies. Third, SEZs should not rely on tax preferences and financial subsidies to achieve short-term effects. The real advantage of SEZs is to create a good environment for firm innovation agglomeration and strong positive externalities, and achieve a virtuous circle of sustainable development.
There is already an extensive discussion in the literature on the government-led supply mode for core technologies in the new national system. However, there still needs to be more discussion on the supply of core technologies in market-oriented industries. This research analyzes how the lithography equipment manufacturer ASML in the Netherlands achieves breakthroughs in the core technology of the lithography industry through an innovative ecosystem, serving as a typical case study. The study finds that companies should build dynamic and long-term value propositions in developing core technology in the industry and play a leading role in technology selection and layout. When constructing market-oriented innovation ecosystems, core companies need to focus on non-mainstream user needs, deeply integrate with mainstream users, drive the growth of complementary parties, participate in non-profit alliance organizations, and create an excellent competitive and cooperative environment. This research proposes an innovative mode of market-oriented core technology in the industry based on the innovation ecosystem, which provides practical experience for companies to play the role of innovation leaders and provides a reference for constructing a government-market collaborative supply mode.
Under the impact of major public health events, the current speed and direction of scientific and technological development have burst out with new characteristics. Based on the theory and empirical basis of disaster economics, this paper selects multiple groups of panel and time series data, and uses the composite control method, breakpoint regression and vector autoregressive model to investigate the inducement and reverse effect of modern disasters on technological innovation from two aspects of medical technology and digital technology. The research findings are as follows: (1) The COVID-19 not only induced technological progress in medical related fields, but also forced the application and innovation of digital technology; (2) In the short term, the negative impact of the increase in epidemic intensity on innovation will reach its peak within one and a half months, but the significance of the impact will decrease rapidly after that, and the negative impact will gradually converge to the zero level; (3) At the international level, compared with the United States, Europe, Japan and South Korea, the induced effect and anti-driving effect of the epidemic on scientific and technological innovation are more significant in China, showing the resilience of China's scientific and technological development in the context of the epidemic. The research conclusion reveals the conditional impact of modern epidemic on scientific and technological innovation, and also provides reference value for the construction of China's emergency innovation system, social digital transformation and international scientific and technological competition in the post-epidemic era.
This paper uses geographic distance and transportation convenience to test its impact on collaborative innovation. The spatial distance is included in the dynamic optimization model to analyze the mechanism of university-enterprise cooperation. Different from using the distance between cities which has commonly been seen in existing related research, this paper examines the impact of distance between a university and an enterprise on their collaboration by mining the geographic information of universities and enterprises and collecting micro-data on patents cooperated by universities and enterprises. And the distance has a significant negative impact on the probability and frequency of cooperation on patents between university and enterprise. The heterogeneity of enterprises and universities also leads to differences in the impact of distance: the influence of distance is more significant in the cooperation between smaller enterprises and universities, in the cooperation between enterprises and "985" universities, and in the cooperation in industries with higher substitution elasities. Further analysis shows that the opening of the high-speed railway and subway has increased the probability and frequency of university-enterprise cooperation, and decreased the negative impact of spatial distance on university-enterprise cooperation. The discussion of robustness testing and endogeneity issues confirms the robustness of the results. The conclusion of the article has certain significance for further improving university-enterprise cooperation.
Existing research emphasizes the important role of data resources, but lacks a discussion on how to integrate data resources to enable product innovation performance. Following the analysis logic of “condition-behavior-outcome”, this paper explores how calculative and relational inter-organizational trust enable product innovation performance through the two ways of data resources integration including stabilizing and pioneering. Using the questionnaire data of 222 manufacturing enterprises in the two-time survey in South China areas, we use PLS-SEM (Partial Least Squares-Structural Equation Modeling) tool to conduct the empirical test, and draw the following conclusions: (1) Calculative inter-organizational trust can enable product innovation performance through the two ways of data resources integration including stabilizing and pioneering; (2) Relational inter-organizational trust has a nonlinear mediating relationship with product innovation performance through two data resource integration ways, stabilizing and pioneering, that is, moderate relational trust can improve product innovation performance through two data resource integration ways, but too high relational trust cannot improve product innovation performance via two data resource integration ways; (3) There is an interactive effect between the two ways of integrating data resources (stabilizing and pioneering) on product innovation performance. When enterprises improve the two ways of data resources integration simultaneously affected by calculative and relational inter-organizational trust, they can better enable product innovation performance. The study responds to the important question that how manufacturing enterprises integrate data resources and exert the value of data elements, providing important enlightenment for emphasizing data resources integration to enable the high-quality development of enterprises.
Based on the theoretical studies of national innovation system, national innovation (system) governance system and national innovation (system) capability, this study first constructs three evaluation systems for the development level of national innovation governance system, national innovation capacity and the adaptability between the both; secondly, measures the development level of innovation governance system in China and OECD countries by using entropy value method, mean squared difference method subjective evaluation G1 method and fuzzy Borda method; again, adopts LightGBM machine learning is used to identify the key elements of the governance system driving national innovation capacity enhancement; finally, gray correlation is used to explore the overall adaptability of governance system and innovation capacity. It is found that: firstly, the level of development of innovation governance systems varies significantly across countries, and uneven development of the dimensions of governance systems reduces the level of governance; the uneven development of each dimension of governance system will reduce the level of governance; China is a low level country; improving policy tools and institutional rules will help to improve the development level of governance system. Second, the ratio of government R&D funding allocation, the number of policies, and the proportion of R&D talents in the whole society are the three key factors of the national innovation governance system driving the improvement of national innovation capacity. Third, when the level of national innovation governance system and national innovation capability are comparable, both show adaptability, and China belongs to high adaptability, and the high reason is the roughly homogeneous development of innovation governance system and national innovation capability. The research results help to improve the national innovation governance system and enhance the national innovation capacity, and provide a basis for decision-making on the reform of the national science and technology innovation system and mechanism to make up for the shortcomings.
