With the new generation of technological revolution and the acceleration of industrial transformation, it is increasingly urgent to promote China's high-quality development through new quality productive forces. The innovation network is a more suitable platform for the repeated exchange of tacit and embedded knowledge than market transactions. It is effective in enhancing enterprise innovation capabilities, achieving breakthroughs in key technologies, and forming new quality productive forces. To promote the qualitative leap in the advanced productive forces of innovation network member enterprises and achieve high-quality development, this paper attempts to answer the following key questions: How does core enterprises' knowledge spillover drive network members' new quality productive forces? What roles do network homogenization and relationship capital play in this process?
On the basis of the knowledge-based view and resource-dependence theory, this paper analyzes the relationship between core enterprise's knowledge spillover and network member's new quality productive forces. The research adopts survey data from 392 enterprises and conducts an empirical analysis using SPSS and Amos. The results show that (1) there is a significant positive relationship between core enterprise's knowledge spillover and network member's new quality productive forces. The influence of core enterprises on network members mainly stems from knowledge spillover, and under its continuous influence, the new quality productive forces of network members can be improved. (2) Network homogenization negatively moderates the impact of core enterprise's knowledge spillover on network member's new quality productive forces. Network homogenization implies a lack of resource, skill, and capability complementarity among members, rendering enterprise resources less unique, valuable, and scarce. Consequently, core enterprise's knowledge spillover cannot provide deeper knowledge and technology interaction for network members, reducing the chance for network members to increase their knowledge diversity and ultimately affecting the development of network member's new quality productive forces. (3) Relational capital positively modulates the relationship between core enterprise's knowledge spillover and network member's new quality productive forces. Strong relationships among innovation network members benefit enterprises in obtaining more social capital, which promotes the exchange and sharing of knowledge and information, and fosters the growth of new talents and the accumulation of new labor materials.
Theoretically speaking, this paper firstly supplements the empirical study of new quality productive forces at the enterprise level. Then it constructs a measurement scale of network member's new quality productive forces, which provides ideas and methods for further empirical research related to new qualitative productive forces at the enterprise level. Secondly, from the perspective of the interaction of innovation network members, this paper explores the impact of core enterprise's knowledge spillover on network member's new quality productive forces, enrich the theoretical connotation of existing research and promote the development of knowledge spillover related theoretical research. Thirdly, by integrating the knowledge-based view and resource dependence theory into the research on the knowledge spillover effects of the core enterprise, the applicability of these theories is enhanced, offering a new perspective to understand the knowledge spillover effects of core enterprises. Lastly, it is a valuable addition to the research on the knowledge-based view and resource-dependence theory to incorporate network homogenization and relational capital into the research framework. This expands the scope of research on the knowledge spillover effects of core enterprises and responds to scholars' recognition of the core enterprise's knowledge spillover effects.
The results hold practical significance as follows: (1) The transformation and enhancement of productive forces quality in innovation networks can not be separated from core enterprise's knowledge spillover. If network members aim to develop new quality productive forces, they must realize the importance of core enterprise's knowledge spillover and expand the channels for enterprises to obtain new knowledge, technical information and other resources. (2)The findings affirm the importance of enterprise knowledge heterogeneity, and suggest that enterprises should select partners based on their own existing knowledge, in innovation networks, members should be clear about who to approach in order to gain more reconfigurable knowledge. (3) Strong relationship capital is the effective support to promote new quality productive forces, and the continuous accumulation of relationship capital can ensure that network members have an advantage in choosing partners for core enterprises. (4)In the process of high-quality development of innovation network, it is necessary to adopt tailored measures for different enterprises.

The new quality productive forces are defined by the reliance on the superposition and iteration of data elements. This represents the original driving force behind the maintenance of high-quality economic and social development. Nevertheless, at this juncture, the advancement of novel, new quality productive forces in China is still constrained by institutional impediments, including the absence of a well-defined property rights system, a suboptimal distribution apparatus, and inadequate incentives, particularly a deficient database system and an imperfect data governance apparatus. The insufficient development of economic, educational, scientific and technological, and human resources is regarded as the primary factor contributing to the stagnation in the advancement of new quality productive forces. Some studies have proposed that the development of new quality productive forces should be reinforced through the establishment of a modernized industrial system, the advancement of scientific and educational endeavors, the advancement of scientific and technological innovation and the cultivation of scientific talent. However, a limitation of these studies is that they do not address the institutional constraints that impede the leapfrogging of new quality productive forces, particularly the lack of empirical evidence on whether effective institutional arrangements for data can facilitate the development of new quality productive forces.
By establishing effective institutional frameworks, big data management organizations have been instrumental in removing obstacles, enhancing aggregation, and facilitating circulation. As a result, they have contributed to the development of a robust digital governance ecosystem, enabling the realization of data's full potential. This may prove to be a pivotal factor in facilitating new quality productive forces gains centered on data-driven. Accordingly, this paper considers the establishment of provincial big data management agencies as a prototypical instance of data institutional deregulation. It examines the intrinsic links and pathways of action of institutional deregulation, the digital governance ecosystem, and new quality productive forces from the perspective of institutional change, utilizing provincial panel data from 2010 to 2022 and a double machine learning model.
The findings indicate that the establishment of the big data management organizations, which represents institutional deregulation, has been effective in promoting the development of new quality productive forces. A mechanism analysis indicates that the establishment of big data management organizations can facilitate the creation of a favorable digital governance ecosystem and accelerate the development of new quality productive forces through the exploitation of institutional advantages. Specifically, the establishment of management organizations optimizes the digital policy environment, the digital economic environment, and the digital social environment, thereby contributing to the development of new quality productive forces. Further analysis indicates that the impact of institutional deregulation on new quality productive forces varies across contexts. In regions exhibiting high government efficiency, high human capital, and high levels of information technology, the effect is particularly pronounced.
This paper contributes threefold to the literature. Firstly, it introduces a novel research perspective. From the vantage point of institutional change, the institutional deregulation experiment of establishing a big data management organization reveals that institutional deregulation exerts an upgrading influence on the advancement of new quality productive forces. This not only serves to embed the theoretical interpretation of the institutional change perspective for new quality productive forces, but also provides empirical evidence from China to deepen the institutional theory in the era of digital intelligence. Secondly, this paper presents a novel chain-building path of "institutional deregulation-digital governance ecosystem-new quality productive forces," which can further elucidate the mechanism that is currently opaque between institutional deregulation and the development of new quality productive forces. Thirdly, it methodologically employs double machine learning to address model issues in complex analyses. It can effectively circumvent the issues of model misspecification and the curse of dimensionality that may be encountered by traditional models in the intricate cascade of the topics of new quality productive forces , enhancing conclusion accuracy. The study's findings offer a theoretical interpretation of the institutional change perspective for new quality productive forces and provide a practical basis for policy formulation to promote the development of new quality productive forces through institutional paths and governance systems.

In the face of anti-globalization trends, relying on the static comparative advantage of cheap factors in traditional productivity fails to elevate China's manufacturing industry beyond the lower end of the global value chain. This approach inevitably leads to low-end competition with other developing countries that possess similar factor endowment advantages. In other words, the potential for traditional productivity to sustainably enhance the quality of China's manufacturing industry's productive forces is diminishing. As competition among major manufacturing nations intensifies, leveraging China's institutional and vast market advantages to overcome the low-end lock-in and path dependencies imposed by the dominant rules of Western developed countries becomes crucial. Empowering advanced productivity through innovative factors like big data and artificial intelligence amidst significant changes is key to accelerating the development of the manufacturing industry's new quality productive forces, which is a pressing issue for economists and policymakers.
Qualitative transition is crucial for securing China's manufacturing industry's high-end position in the global value chain under the new development paradigm. It leverages the domestic market's economies of scale and scope to extend the boundaries of innovation possibilities, promote the manufacturing industry to strengthen, supplement, and expand its industrial chain in technology proximity and innovation aggregation areas, and ultimately form a modern manufacturing system with large scale, comprehensive categories, and strong innovation. Most of the existing literature on the relationship between qualitative transition and new quality productive forces of manufacturing industry has examined the impact of factors such as market autonomy of high-end products and domestic demand driven economy on new quality productive forces of manufacturing industry from the perspective of the equilibrium evolution law between productivity and economic development. With the gradual establishment of the basic framework of "zero tariffs, zero barriers, and zero subsidies" in developed Western countries, the trend of regional economic integration is becoming increasingly prominent. That is to say, in the context of major changes, accelerating the construction of advanced productivity quality, improving the diversification and high-end of manufacturing products as endogenous rules, and further integrating into the global economy to enhance its power, it is necessary to consider the empowering effect of advanced productive quality on the new quality productive forces of manufacturing industry with the characteristics of excellent data element vitality, fast iteration, and wide benefits.
On the basis of existing literature, this study attempts to incorporate data element empowerment, qualitative transition, and new quality productive forces of manufacturing industry into a unified analysis framework. Employing panel data from China's manufacturing industry between 2010 and 2022, this study estimates the effects of data element empowerment and qualitative transition on the industry's new quality productive forces. The study reveals that the qualitative transition caused by the biased empowerment of data elements cannot sustain the revolutionary breakthroughs in high-end technologies in the global value chain, hindering the driving force of innovation and development in the manufacturing industry. The improvement effect on the new quality productive forces of manufacturing industry is not significant. The qualitative transition caused by the enhanced empowerment of data elements can significantly increase the complexity of the manufacturing production system, expand the forefront of the manufacturing innovation system, promote the benign evolution of innovation development momentum, and have a significant positive effect on the improvement of new quality productive forces of China's manufacturing industry.
Compared with existing literature, this article contributes to the research in two primary ways. Firstly, considering that the formation of new quality productive forces of manufacturing industry is endogenous to the changes in innovative allocation of production factors caused by different data element empowerment models, this study distinguishes between data element biased empowerment and data element enhanced empowerment, and examines the mechanism by which different data element empowerment models affect new quality productive forces of manufacturing industry. Second, by focusing on unlocking the structural potential and fostering high-quality transformation within the manufacturing industry, this study incorporates qualitative transition into the analysis model to further explore how different data empowerment modes and qualitative transitions influence the industry's new quality productive forces.

As one of the three pillars supporting national development, intellectual property is a strategic resource for national development and plays an important role in building a new development pattern in China. A unified national market is a key component of the new development pattern, and its construction is the main field in which intellectual property protection plays a role. In April 2022, the Central Committee of the Communist Party of China and the State Council issued the Guidelines for Accelerating the Building of a Unified National Market, emphasizing that it is essential to "improve the intellectual property evaluation and trading mechanism", "promote the innovation of the intellectual property litigation system, improve the cross-regional jurisdiction system of intellectual property courts, and unblock the docking mechanism of intellectual property litigation, arbitration and mediation", which provides guidance for the construction of a unified national market. The State Council executive meeting in May 2023 pointed out that it is necessary to optimize the protection of property rights, improve the system and mechanism to adapt to the construction of a unified national market, further deploy the construction of a unified national market, and put forward compliance development requirements from the construction of the technology market. As a part of the unified national market, the national unified technology market has naturally become an important force for intellectual property protection. By leveraging the functions of constraints, coordination, incentives, and resource allocation, intellectual property protection can unleash the vitality of market transactions, reduce the cost of technology exchange, promote the smooth circulation of resources, and effectively contribute to the construction of a national unified technology market. Moreover, intellectual property protection can further strengthen technological innovation, promote the flow of factors, and create long-term stable development expectations for technology trading entities. Therefore, in order to effectively promote the construction of a national unified technology market, the important role of intellectual property protection should be utilized.
Using the panel data of 290 cities in China from 2013 to 2021, this study empirically examines the impact of intellectual property protection on the construction of a national unified technology market by using fixed-effect and intermediate-effect models. It is found that intellectual property protection plays a significant role in promoting the construction of a national unified technology market, and the conclusion is still valid after the robustness test. The influence of intellectual property protection on the construction of a national unified technology market is heterogeneous, showing that it is weak in the central and western regional cities, Chengdu-Chongqing economic circle, economically underdeveloped cities and resource-based cities. According to the findings of the mechanism test, it is confirmed that intellectual property protection indirectly promotes the construction of a national unified technology market by improving the level of regional innovation and entrepreneurship and increasing the bias of government fiscal expenditure.
Compared with previous literature, the innovation of this study lies in the following three aspects. The first is that it analyzes the enabling effect of intellectual property protection on the construction of a national unified technology market from a theoretical angle, and further improves the theoretical basis of intellectual property protection on the construction of a national unified technology market. Then it provides an empirical basis for the profound implementation of the strategic layout to "accelerate the construction of a unified national market and deepen the market-oriented reform of factors" by analyzing the mechanism of intellectual property protection on the construction of a national unified technology market from the empirical level. Lastly, the study analyzes the heterogeneous impact of intellectual property protection on the construction of a national unified technology market from the perspectives of geographical location, economic development level, and differences in resource-based cities, which provides decision-making reference for accurately implementing the construction strategy of a national unified technology market and achieving high-quality social and economic development.

What kind of government-business relationship could stimulate entrepreneurship has been one of the hot topics in the field of entrepreneurship. In particular, serial entrepreneurship is more concerned with the improvement of the external institutional environment than initial entrepreneurship. A good government-business relationship could optimize the business environment, which is important for the development of serial entrepreneurship. In 2016, General Secretary Xi Jinping first proposed a new type of cordial and clean relationship between government and business, indicating that the government should be friendly and moderate, but also clean and competent. Previous studies on the government-business relationship and entrepreneurial activities have mostly been conducted from the perspective of being "cordial" or "clean". Therefore, following the institutional theory, this paper studies the impact of the joint effect of "cordial" and "clean" on serial entrepreneurship from the perspective of both "cordial and clean" government-business relationship, which helps clarify the mechanism of the impact of a new government-business relationship on serial entrepreneurship.
According to the institutional theory, the government is the most important institutional subject of the external environment of the firm. The construction and implementation of the new government-business relationship provide more resources to support the firm, and the serial entrepreneurs form trust in the government based on this resource information, which in turn influences their choice of whether to engage in entrepreneurial activities again. Therefore, this study hypothesizes that trust in government plays a mediating role between new government-business relationship and serial entrepreneurial behavior. Meanwhile, although the external environment is a key condition that influences serial entrepreneurial behavior, organizations or people in the same institutional environment do not always exhibit similar cognitions or behaviors. Socioeconomic status represents their ability to access economic and social resources for entrepreneurial activities. Therefore, socioeconomic status is considered a key factor influencing entrepreneurs to engage in serial entrepreneurial behavior and may moderate the relationship between the new government-business relationship and serial entrepreneurial behavior.
The government is the most important institutional agent in the external environment of a firm. Serial entrepreneurs form trust in the government based on the resource information released by the government, which in turn influences their choice of whether to engage in entrepreneurial activities again. Thus, trust in government trust may play a mediating role between new government-business relationships and serial entrepreneurial behavior. At the same time, although the external environment is a key condition influencing serial entrepreneurial behavior, organizations or people in the same institutional environment do not always exhibit similar perceptions or behaviors. Socioeconomic status represents their ability to access economic and social resources for entrepreneurial activities. Thus, socioeconomic status is thought to potentially moderate the relationship between new government-firm relations and serial entrepreneurial behavior.
〖HJ*2/5〗The data used in this study consists of two parts: the data related to serial entrepreneurs is from the individual database of the China Family Panel Studies (CFPS) for five consecutive periods from 2012 to 2020, the household economic database in 2018, and the household relationship database in 2018, conducted by the China Social Science Research Center of Peking University. The new government-business relationship is from the "Ranking of Government-Business Relationship in Chinese Cities 2020" published by the Institute of National Development and Strategic Studies of Renmin University of China. Regression tests are conducted based on the above data. The results show that (1) the joint effect of “cordial” and “clean” government-business relationship has a facilitating effect on serial entrepreneurial behavior. (2) The joint effect of “cordial” and “clean” government-business relationship on serial entrepreneurial behavior is mainly achieved through trust in government. (3) Entrepreneurs′ socioeconomic status can weaken the facilitative effect of the joint effect of “cordial” and “clean” government-business relationship on serial entrepreneurial behavior. The above findings indicate that the government needs to develop both “cordial” and “clean” relationship to implement a new type of government-business relationship. It is not only necessary to pay attention to trust in the government, but also to implement the “cordial” and “clean” relationship between government and business according to the different socioeconomic status of entrepreneurs so as to avoid the emergence of absolute equality.

Complex product systems (CoPS) include high-value products, capital goods, control systems, networks and civil engineering constructs. In a more specific way, they refer to over 80 types of one-off projects (or small-batches), including telecommunications exchanges, flight simulators, aircraft engines, avionics systems, train engines, air traffic control units, systems for electricity grids, offshore oil equipment, intelligent buildings, and cellular phone network equipment. CoPS bears the linkage-driven characteristics of technological complexity and engineering intensity. Achieving technological breakthroughs can drive the development of related industries. In recent years, China has successfully developed the C919 mainline passenger aircraft, the "Fuxing" standard electric multiple unit, and the third-generation independent nuclear power technology "Guohe No. 1". These achievements have proven that China has been transformed from a "follower" to a "parallel" or "leader" in some CoPS fields; however, there are bottlenecks in some key technologies and the related CoPS are in a dilemma, such as lithography machines and heavy-duty gas turbines, which are blockaded by the first-mover countries. Therefore, it is necessary to conduct an in-depth exploration of the key driving factors of catch-up so as to formulate effective catch-up strategies.
The catch-up process in the field of CoPS shows that the successful catch-up of latecomers is driven by multiple factors. The existing studies have used case study methods to explore how the CoPS achieve latecomer catch-up and why they can realize catch-up development, but there are still deficiencies. For one thing, the differentiated role of diversity factors in the catch-up process makes it difficult for latecomers to grasp the key driving factors in different catch-up stages; for another, single case studies are unable to make relatively accurate quantitative judgments and reveal the differential effects of these common driving factors at different stages of catching up in CoPS, thereby affecting the formulation and implementation of catch-up strategies.
This study collects second-hand data, including policy data, enterprise data, and literature on the catch-up research of three typical CoPS in China, namely large aircraft, nuclear power, and high-speed rail, from 2013 to 2022 for grounded research on the identification of the driving factors of catch-up in CoPS. Causal relationship analysis can clearly present the connections between different factors, which is the basis of system dynamics simulation. Specifically, technology acquisition strategies and organizational management capabilities directly affect the technological catch-up of CoPS, and the faster the technological catch-up, the larger the institutional market size, thereby accelerating market catch-up, while market catch-up is directly influenced by the size of institutional markets, competition in institutional markets, and the development of institutional markets. On the basis of the above factors, a system dynamics model of the driving factors of catch-up in CoPS is constructed and simulated.
The results show that CoPS in China are in different catch-up stages, and the catch-up process is driven by different key factors. At the follow-up stage, the whole nation system, secondary innovation, and integrated innovation are key driving factors of catch-up. At the parallel stage, institution-driven market explore, individual research, integrated innovation constitute key driving factors for catch-up. At the beyond catch-up stage, institution-driven market size, individual research and the whole nation system constitute key driving factors of catch-up. Thus, it is proposed to comprehensively promote the strategy of independent research and development, expand the advantages of the new system for mobilizing resources nationwide, especially for the CoPS that are in the follow-up and parallel stages, establish project organizations directly led by national agencies and coordinate system integrators, suppliers, universities, and research institutions to carry out joint research and development.
This study integrates programmatic grounded theory and system dynamics methods to explore the driving factors of late catching up in CoPS. On the one hand, it enriches the understanding of the laws of late catch-up in CoPS, and on the other hand, it identifies the key driving factors through quantitative analysis, providing a basis for the formulation of late catch-up strategies.

The "specialized, refined, differential and innovative" (SRDI) enterprises have been focusing on segmented markets for a long time by integrating innovative elements with key links, and mastering the "unique skills". SRDI enterprises are important support for the future industrial chain and the main force to break through the "bottleneck" of key technologies. Industrial collaborative agglomeration is a new trend in the development of modern industries, manifested as the process of vertically related and horizontally complementary industries achieving industrial integration through value chain reconstruction and supply chain integration. It has the characteristics of economies of scale, economies of scope, and external economies, and can provide more cooperation opportunities and development space for small and medium-sized enterprises. The industry generally believes that the industrial ecosystem of agglomeration and symbiosis is the matrix for cultivating SRDI enterprises. Therefore, does industrial collaborative agglomeration have a significant promoting effect on SRDI development in small and medium-sized enterprises?
This article takes small and medium-sized board and ChiNext board enterprises on the Shenzhen Stock Exchange as research samples, matches the urban-level industrial collaborative agglomeration index according to the cities where the enterprises are located, and uses various econometric techniques such as the double fixed effect model, intermediary effect model, instrumental variable method, and propensity score matching method to empirically test the impact of industrial collaborative agglomeration on the SRDI development of small and medium-sized enterprises. It is found that, firstly, multiple robustness tests, including endogeneity tests, show that industrial collaborative agglomeration can significantly promote the SRDI development of small and medium-sized enterprises. Second, there is significant enterprise heterogeneity, city heterogeneity, and industry heterogeneity in the promotion effect of industrial collaborative agglomeration on the SRDI development of small and medium-sized enterprises. Specifically, this promotion effect is more significant in enterprises with low supplier concentration, cities with higher levels of digitalization, and high-end productive service industries. Thirdly, industrial collaborative agglomeration can promote the SRDI development of small and medium-sized enterprises by promoting technological innovation, reducing transaction costs, and reducing operational risks. Moreover, technological innovation, transaction costs, and operational risks all have a partial mediating effect. The research in this article deepens the understanding of the internal relationship between collaborative agglomeration effects and the SRDI path, providing useful references for promoting the transformation and development of small and medium-sized enterprises, constructing a modern industrial chain supply chain system supported by SRDI enterprises, and enhancing the global competitive advantage of China's manufacturing industry.
Compared to existing research, the possible marginal contribution of this study is threefold. (1) From a research perspective, the promotion of industrial collaborative agglomerations as well as the SRDI development of small and medium-sized enterprises, are both key links that support the high-quality development of China's manufacturing industry, which has inherent connections. This study provides a detailed examination of the impact of industrial collaborative agglomeration on the SRDI development of small and medium-sized enterprises, providing a new perspective supplement for research in related fields. (2) In terms of research content, this study analyzes the heterogeneous impact of industrial collaborative agglomeration on the SRDI development of small and medium-sized enterprises from the perspectives of supply chain concentration, digitalization level, and industry heterogeneity. It also explores the path of industrial collaborative agglomeration influencing the SRDI development of small and medium-sized enterprises from three aspects: enterprise technological innovation, transaction costs, and operational risks. (3) The study provides empirical evidence to promote the development of SRDI small and medium-sized enterprises. By matching the urban-level industrial collaborative agglomeration index with the enterprise data of small and medium-sized board and ChiNext board enterprises on the Shenzhen Stock Exchange, the study empirically tests the impact of industrial collaborative agglomeration on the SRDI development of small and medium-sized enterprises, which supplements the empirical evidence that industrial collaborative agglomeration promotes the SRDI development of small and medium-sized enterprises.

Enterprises are the main force of scientific and technological innovation, and leading technology enterprises can promote the industry to realize overall technological progress by virtue of their technical, scale, and market advantages. Giving full play to the industry linkage of technological innovation capability of leading technology enterprises is an effective way for China to realize scientific and technological self-reliance and self-improvement. Therefore, it is of practical significance to study the industry linkage of technological innovation capability of leading technology enterprises.
Existing research has made useful explorations of the linkage role of technological innovation capability in leading technology enterprises, but the linkage objects of concern are mainly industrial chains and industrial clusters. There is a lack of discussion on the linkage of technological innovation capability within the industry of leading technology enterprises. Thus, this paper focuses on the intra-industry linkage effect of technological innovation capability of leading technology enterprises under the influence of the technology gap within the industry. It utilizes the data of A-share listed companies in Shanghai and Shenzhen from 2012 to 2022, and empirically examines the manifestation of the intra-industry linkage effect of the technological innovation capability of leading technology enterprises from the perspective of technology gap based on the model of productivity catch-up and the effects of the degree of competition, uncertainty of the industry environment, and intensity of production factors on the technological innovation capability of leading technology enterprises under the viewpoint of technology gap and the moderating effect of the degree of industry competition, industry environmental uncertainty and industry factor intensity on the intra-industry linkage of technological innovation capability of leading technology enterprises, and further identify the characteristics of intra-industry linkage of technological innovation capability of leading technology enterprises.
The results of the study show that (1) leading technology enterprises have linkage effects on the technological innovation capability of enterprises in the industry, which is manifested in technological innovation diffusion and technological innovation following; (2) compared with enterprises with a low degree of industry competition, enterprises with a high degree of industry competition have a stronger following effect of technological innovation and a weaker diffusion effect; (3) the higher the degree of competition and environmental uncertainty in the industry, the stronger the following effect and the weaker the diffusion effect of technological innovation of enterprises in the industry; (4) the following effect of technological innovation of enterprises in technology-intensive industries is the strongest, the strongest diffusion effect of technological innovation of enterprises lies in labor-intensive industries, and the following effect and diffusion effect of technological innovation of enterprises in capital-intensive industries is at the intermediate level;(5) the behavior of enterprise technological innovation industry linkage is manifested in the active catch-up rather than passive imitation of enterprises in the same industry, showing the Matthew effect and significant proximity effect.
The contribution of this paper mainly lies in three areas. (1) It explores the manifestation and internal mechanism of the linkage effect of leading technology enterprises on the technological innovation ability of enterprises in the industry from the perspective of technology gaps within the industry, which expands the research perspective of enterprise technological innovation. (2) It clarifies the specific manifestations of the linkage effect of technological innovation capability of leading technology enterprises in the industry, which is a useful supplement to the existing research. (3) By identifying the characteristics and industry differences of intra-industry linkage of technological innovation capability of leading technology enterprises, the study confirms the Matthew effect and the proximity effect, expanding the research perspective on the technology innovation linkage of leading technology enterprises;it further reveals the micro-mechanism of the intra-industry linkage effect of technology innovation capability of leading technology enterprises, and thus the study is of reference significance for promoting the intra-industry linkage of leading technology enterprises.

With the digital economy still in its infancy, there is still a lack of academic research focusing on the complex antecedent configurations of enterprise digital transformation and their temporal evolution. Drawing on the theoretical perspective of strategy tripod, this study uses the data from 2014–2019 of A-share listed companies and employs the dynamic fsQCA approach to identify the "causal recipes" for achieving a high-level digital transformation. From the perspective of the strategic tripod, the conceptual framework is composed of three sets of causal conditions: including institutional conditions (i. e. , level of marketization as a formal institution; regional Guanxi culture as an informal institution), industrial conditions (i.e., industry munificence, industry dynamism, and industry complexity), and dynamic capabilities (sensing capability, absorptive capability, and reconfiguration capability).
The analysis confirms that all conditions consisting of the strategic tripod are significant to enterprise digital transformation. Institutional conditions ensure legitimacy for digital transformation, industrial conditions influence enterprises' willingness to implement digital transformation, and conditions related to firm dynamic capabilities determine the effectiveness of digital transformation. Notably, enterprise digital transformation is not solely driven by any single factor. Instead, all these three kinds of conditions play significant roles in influencing the digital transformation of enterprises. Then the coexistence of multiple antecedent configurations for high-level digital transformation is identified, which is consistent with the strategic tripod. The qualitative comparative analysis reveals that there are four typical patterns of high-level digital transformation in the three phases of 2014-2015, 2016-2017, and 2018-2019, including "emphasis on institutions", being "institutional-industrial driven", "industrial utilization", and "the synergy among the three dimensions of the strategy tripod". Additionally, it is found that there are three typical patterns in each phase. The diversity of digital transformation configurations apparently reflects the strategic and managerial wisdom of enterprises which constantly explore the potential of digital transformation and gradually open up various transformation paths. Consistent with the development characteristics of the emerging economy, enterprise digital transformation has undergone a transition process that has been dominated by macro-, meso- and micro-level factors, respectively, across three time periods. Specifically, in the early stage of digital transformation development, it was led by institutions, followed by industrial policy stimulation, and finally deepened and developed through enterprise innovation. That is, institution-related conditions were the main drivers of digital transformation from 2014-2015. Then from 2016-2017, the incentive role of industry factors in digital transformation became more important; and from 2018-2019, digital transformation focused on leveraging the enterprises' own dynamic capabilities. Thus, the key drivers of enterprise digital transformation have been shifting from being institution-oriented (at the macro-level), to industry factor-driven (at the meso-level) and recently towards enterprise internal factor-driven (at the micro-level).
Moreover, the analysis results of regional heterogeneity show that the role of the industry-related conditions is more pronounced for enterprises undergoing a relatively high-level digital transformation in the eastern region, while the institutional background matters more for enterprises in the central region, and all three aspects of the strategy tripod (i. e. , institutional factors, industry conditions and enterprises' internal capabilities) are indispensable for enterprises in the western region to enhance their digital transformation.
This study makes threefold contributions as follows. First, it extends the extant research on the antecedents to enterprise digital transformation by simultaneously considering the institution- industry and enterprise-related causal conditions in an integrative framework with solid support from the strategy tripod perspective. Second, it applies the fsQCA approach to identify the equivalent configurations of high-level digital transformation, providing a finer-grained understanding of the causal conditions under which high-level digital transformation occurs and thus producing insights more closely aligned with the complex realities of how enterprises can improve the effectiveness of digital transformation than conventional research approaches. Third, the findings provide the recipe for managers to make good use of institutional factors, industrial conditions, and dynamic capabilities to succeed via digital transformation. They also provide both theoretical and practical insights for policymakers who are dedicated to driving enterprise digital transformation.

The use of digital technology such as the Internet,cloud computing,and big data has resulted in an influx of digital startups. These digital startups have not only generated many new professions,but have also aided in the transformation and upgrading of traditional industries,promoting economic and social progress. The ongoing innovation and breakthrough of their business models is the key to the vitality of digital startups. For example,digital startups such as Amazon and Alibaba have changed the traditional retail industry through platform-based business model innovation. However,even with innovation in their business models,not all digital startups are successful,and many companies become bogged in the mud and,regrettably,depart the market. Thus,digital startups are facing the practical challenge of how to innovate business models to promote performance. Existing research on this topic has focused on the positive effects of business model innovation,while disregarding the negative implications,which may result in increased R&D expenses,a larger likelihood of product failure,and more employee turnover. Digital startups,in particular,are pronouncedly service-oriented,and higher cost investment and increased revenue risk amplify the negative impact of business model innovation. Simultaneously,digital startups are clearly digital-oriented,and digital technology influences the process of business model innovation,but previous research has not focused on the role of technological innovativeness. The aforementioned lack of focus on the distinctiveness of business model innovation in digital startups is not favorable to in-depth examination of new laws of innovation and entrepreneurship in the digital economy.
Drawing on the data from 760 firms in the Chinese Panel Study of Entrepreneurial Development (CPSED II) database,this study investigates the different mechanisms of the impact of efficiency-centered and novelty-centered business model innovation on the performance of digital startups,as well as the moderating role of technological innovativeness. The results show that in digital startups,efficiency-centered business model innovation has a positive impact on firm performance,while novelty-centered business model innovation has a negative impact on firm performance,and technological innovativeness negatively moderates the positive impact of efficiency-centered business model innovation on firm performance and the negative impact of novelty-centered business model innovation on firm performance. This is because digital startups that adopt efficiency-centered business model innovations facilitate value creation and capture by restructuring transactions and controlling key resources,whereas firms that adopt novelty-centered business model innovations face the challenge of attracting new transactional players and continuously locking in stakeholders,which is detrimental to firm performance. When technological innovativeness is high,however,digital startups must develop novel value propositions to maximize the unique features of their products,which contradicts the value claim of cost minimization pursued by efficiency-centered business model innovations and is thus detrimental to firm performance; adopting novelty-centered business model innovations,on the other hand,makes it easier to attract new trading entities to build a new trading system and sustainably lock in users,investors,and other stakeholders,thus positively affecting firm performance.
This paper investigates the "black box" of negative effects in the cost-value structure of business model innovation in digital startups. It confirms that the service-oriented character of digital startups increases the potential risk of business model innovation. This risk is reflected in novelty-centered model innovations in the context of low technological innovation,and in efficiency-centered business model innovations in the context of high technological innovation. Second,the paper emphasizes the importance of matching business models and technological innovation in digital startups. When technological innovation is low,digital startups are more conducive to firm performance through efficiency-centered business model innovation,whereas when technological innovation is high,digital startups are more conducive to firm performance through novelty-centered business model innovation. Finally,this paper emphasizes the dual role of value creation and value capture in digital startup business model innovation,providing a novel theoretical perspective for the discussion of business model innovation concerns. Overall,the findings are enlightening for digital startups in implementing business model innovations that are compatible with technical innovations,thereby promoting the digital economy's growth.

Innovation can help SMEs reduce costs, improve efficiency, and enhance the quality of their products and services, bringing long-term growth. However, due to their own financial and technological constraints, SMEs generally have certain barriers to innovation. How to help SMEs ease financing constraints and enhance technological innovation capability has become an urgent issue to be addressed. Supply chain finance plays an important role in stimulating the innovation activities of SMEs. On the one hand, the adoption of supply chain finance can make it easier for SMEs to obtain lower-cost funds, thus alleviating their financing constraints. On the other hand, close partnerships based on supply chain finance ecological networks can promote business dealing and core technology sharing in the chain, thus accelerating the formation of collaborative innovation networks, which is conducive to improving the innovation capability of SMEs. Existing studies have verified that supply chain finance can alleviate financing constraints, while financing constraints can affect firms' R&D investment efficiency. However, the logical link between supply chain finance, financing constraints, and R&D investment efficiency has not yet been established.
Given the above research deficiencies, this paper aims to explore the effect of supply chain finance on the R&D investment efficiency of SMEs. It focuses on the external influence mechanism as well as the internal conduction path and verifies the role that financing constraints play between supply chain finance and R&D investment efficiency. The data of 109 GEM-listed SMEs from 2016 to 2022 is selected for empirical analysis. Firstly, the original data are subjected to descriptive analysis, a correlation test, and a variance inflation factor test to eliminate interfering factors. Subsequently, the data is analyzed based on three-stage DEA analysis, binary logistic regression, multiple linear model regression, and panel Tobit model regression to verify the suppressing effect and moderating effect among the variables. Finally, key variables were replaced for robustness testing to ensure the accuracy of the findings. The results show that supply chain finance can significantly enhance the R&D investment efficiency of SMEs, and financing constraints play a suppressing effect between the two (i. e. , by controlling for the factor of financing constraints, the effect of supply chain finance on the R&D investment efficiency will be more enhanced). Further, in firms with higher supplier concentration and customer concentration, the enhancement effect of supply chain finance on R&D investment efficiency is more significant.
This study makes a contribution in two ways. First, it introduces the concept of "efficiency" in measuring firms' innovation performance. Through the three-stage DEA method, the whole process of "injection of innovation resources", "incubation of innovation results", "realization and commercialization" is tracked, which is more comprehensive than other innovation performance measurement methods. In addition, three-phase DEA overcomes the disadvantages of traditional DEA, which ignores the environmental impact and cannot be adjusted. It is able to measure more realistic R&D investment efficiency, which provides a basis and guidance for the comprehensive assessment of SMEs' innovation performance and the long-term development of innovation activities. Secondly, it confirms the direct effect between supply chain finance and R&D investment efficiency, and verifies the suppressing effect of financing constraints and the moderating effect of supply chain concentration. This lays the foundation for further exploring the internal mediating variables and external moderating variables of the relationship between supply chain finance and R&D investment efficiency. The financing constraints and supply chain concentration variables selected in this paper can highly correspond to two important directions for the development of supply chain finance business: one is to continue to strengthen the role of support for SMEs' financing, and the other is to build a supply chain finance ecosystem that promotes SMEs to be embedded in the synergistic system of value co-creating and risk-sharing with supplier firms and customer firms. The research on suppressing and moderating effects in this study responds to the call of reality, and the conclusions are conducive to giving full play to the advantages of supply chain financing and collaborative innovation, so as to provide dual support for SMEs' innovation activities in terms of both finance and technology.

ESG information disclosure is regarded as a systematic and comprehensive way of releasing corporate non-financial responsibilities such as ecological environmental responsibilities,social responsibilities,and corporate governance responsibilities to the stakeholders. More and more listed companies have taken ESG information disclosure as an important means of establishing their green corporate image and gaining momentum for achieving high green innovation performance,and how the companies can improve green innovation performance through ESG information disclosure motivation has attracted attention from the research field. Many scholars have found that internal factors such as corporate financial performance,values,risks,and investment evaluation,and external factors like pressure from governmental environment regulation,public environmental concern,and consumers' green consumption intentions,have a great impact on the corporate motivation to disclose ESG information to outsiders. ESG information disclosure is beneficial for corporate reputation management,exerting green spillover effects and value transmission effects to generate altruistic social value. However,there is still controversy about whether ESG information disclosure motivation can positively affect green innovation. Some scholars argue that corporate ESG information disclosure motivation is restricted by macro policy and institutional factors and may have no significant impact on green innovation performance; besides,the impact mechanism of ESG report information disclosure motivation upon corporate green image is still unclear and remains an unsolved “black box” for the present researchers. Therefore,it is of significance to have a comprehensive understanding on the correlation between ESG information disclosure motivation,green image and green innovation and thus know how to help companies promote green development.
Following the motivation theory,the signal transmission theory and the environmental psychological value-belief-norm theory,this study constructs a conceptual model of the relationship among the dual motivations of corporate ESG report information disclosure,green image,green value cognition,and green innovation performance,taking green image as a mediating variable and green value cognition as a moderating variable,to explore the impact mechanism of ESG information disclosure motivation upon green innovation performance. It divides the motivators of corporate ESG information disclosure into egoistic ones and altruistic ones,in which the egoistic motivators mainly refer to those generated by the corporates to meet the needs of self-growth reputation,resource needs,etc. ,while the altruistic motivators mean those generated by the corporates to meet the needs of social responsibility and social value realization. The study adopts the questionnaire survey method of 254 samples from the listed companies that have released ESG reports between 2018 and 2022 and finds that ESG information disclosure motivators,no matter egoistic ones or altruistic ones,both have a significant positive impact upon corporate green innovation performance; green image plays a mediating role in the relationship between ESG information disclosure motivation and green innovation performance; and the top managers' green value cognition positively adjusts ESG information disclosure motivation and green innovation performance. This study also discovers that ESG information disclosure motivation can help companies solve the problems of information asymmetry and agency conflicts,convey environmental,social and governance information to stakeholders,and meet the corporate green development needs. The more attention corporates have paid to ESG information disclosure motivation,the higher the green innovation performance they are likely to achieve.
In summary,by adopting the environmental psychological value-belief-norm theory,this study expands the field of interdisciplinary theoretical research and enriches theoretical research perspectives; it uncovers the impact mechanism “black box” of ESG information disclosure upon green innovation performance,discusses the role and significance of green image construction from multiple dimensions,and provides basic theoretical support for improving the self-utility and social utility of corporate green image,enhancing the top managers' green image awareness,and thus improving the corporate green innovation performance.
In order to gain continuous momentum for improving green innovation performance,the companies should actively promote ESG information disclosure motivation,improve corporate green image and the top managers' green value awareness. Besides,in the current context of China's comprehensive green transformation of economic and social development,the government should strongly enforce the corporate ESG information disclosure laws,insistently strengthen the supervision and technical guidance on ESG information disclosure,and stimulate corporates' enthusiasm for their ESG information disclosure by providing green subsidies and other preferable policies.

Entrepreneurs are at the helm of the enterprise-based technological innovation system. Without a high-quality team of entrepreneurs, it is difficult to build high-quality enterprises and a modernized industrial system. Thus, it is necessary and critical to comprehensively promote the construction of high-quality entrepreneur group, and build a team of entrepreneurs with high standing and strong leadership that the Communist Party and the public are satisfied with. It is of strategic and supportive significance for the goal of 'making breakthroughs in promoting high-quality economic development, achieving greater self-reliance and strength in science and technology, and making major progress in creating a new pattern of development and building a modernized economy'. It also is a profound response to the 'accelerated construction of a national strategic human resources force' in the new era. It can be seen that in the process of promoting high-level scientific and technological self-reliance and self-improvement, the value and role effect of different types of entrepreneurs, especially strategic entrepreneurs, have become a major issue of talent to support innovation and development in the new era.
Strategic entrepreneurs are an important component of the national strategic talents, and have irreplaceable value in promoting high-level scientific and technological self-reliance and self-improvement. Strategic entrepreneurs are not only a breakthrough in the development boundary of entrepreneurs, but also a future direction for the construction of entrepreneurial teams. Following the entrepreneurial theory, this study dwells upon the practice foundation of excellent entrepreneurs and enterprises in China and innovatively defines the connotation of strategic entrepreneurs in the Chinese context from the perspective of role expectation; it further portrays the typical characteristics of strategic entrepreneurs, explores the differences and similarities between strategic entrepreneurs and general entrepreneurs, and forms a new cognition of strategic entrepreneurs on the whole. On this basis, it analyzes the strategic talent value and innovative talent value of strategic entrepreneurs in the process of achieving high-level scientific and technological self-reliance and self-improvement, and finds that strategic entrepreneurs play an important role in enterprises, industrial chains, innovation consortia, and other fields through the trickle-down effect, peer effect, and bridge effect. The research systematically answers the questions of who the strategic entrepreneurs are, what value they have, and how to realize the value of the strategic entrepreneurs.
The study makes a comprehensive theoretical analysis of the mechanism of strategic entrepreneurs to promote high-level scientific and technological self-reliance and self-improvement. It is concluded that strategic entrepreneurs play important roles in enterprises, industrial chains, and innovation consortia through trickle-down effect, peer effect, and bridge effect. The trickle-down effect refers to the trickle-down process of enterprise technological innovation from top (strategic entrepreneur) to bottom (subordinate employees), including trickle-down environment, trickle-down subject, trickle-down strategies, and trickle-down results, and it is mainly achieved through the mechanisms of purification, infiltration, and transformation. As for the peer effect, it is argued that the demonstration, leadership, and appeal demonstrated by strategic entrepreneurs have a positive impact on the overall industry chain, all parties on the chain (general entrepreneurs, entrepreneurs, strategic scientists, etc. ), and the integration of the dual chain through the peer effect. In the innovation consortium, the bridging role of strategic entrepreneurs is mainly achieved through the circulation of innovative elements and the scenario based application of scientific and technological achievements.
The theoretical contribution and innovation of the research are mainly reflected in three aspects. Firstly, the interpretation of the connotation of strategic entrepreneurs reflects the higher requirements of the state, society, industry and enterprises for entrepreneurs, and also reflects the important value of strategic entrepreneurs. Strategic entrepreneurs are not only the title or honor of entrepreneurs, but also a higher expectation for the role of entrepreneurs. Secondly, the role value and mechanism of strategic entrepreneurs in promoting high-level scientific and technological self-reliance are discussed. Thirdly, the findings provide theoretical support and practical guidance for strategic entrepreneurs to promote the self-reliance and self-improvement of high-level science and technology in the new era.

With the integration of digital economy with technological innovation, organizational innovation and industrial innovation, more and more enterprises have been introducing artificial intelligence technology to replace some low-end repetitive work. The emerging workforce, nurtured during the era of AI's swift advancement, is acutely aware of its influence on their professional competitiveness. This rapid technological evolution has instilled a sense of unease among these young professionals regarding potential job displacement and the necessity to master novel technologies. This phenomenon is commonly referred to as artificial intelligence anxiety.
From the perspective of the cognitive evaluation theory of stress, the study analyzes the impact of AI anxiety on the innovative behavior of the new generation of employees. The paper proposes the following hypothesis that, first, AI anxiety can promote innovative behavior of the new generation of employees, and fully tapping the characteristics and potential of the new generation of employees can better stimulate their innovative vitality under the anxiety of AI. Second, job crafting plays a mediating role between AI anxiety and the innovation behavior of the new generation of employees. AI anxiety can stimulate the new generation of employees to actively think about the changes in work content and work mode. Third, organizational attachment not only moderates the relationship between AI anxiety and job crafting, but also moderates the mediating effect of job crafting between AI anxiety and the innovation behavior of the new generation of employees. It is difficult for employees with high organizational attachment to have innovative behaviors in the context of insecurity. On the contrary, employees with low organizational attachment have an attachment style corresponding to secure organizational attachment. Therefore, employees with low organizational attachment are better able to carry out innovative practices and carry out innovative behaviors at work, and AI anxiety has a stronger effect on stimulating their innovative behaviors through job crafting.
The study conducted a survey in two phases with data from November 2023 to February 2024 through a multi-time point survey methodology. The target population consists of employees across various sectors, including the Internet and Technology (IT) industry, manufacturing, catering services, and education. There are 343 valid responses out of 435 questionnaires, which corresponds to a robust response rate of 78. 85%. The study employs SPSS 23. 0 and Mplus 8. 0 software to assess the reliability and validity of the research model. To evaluate the discriminant validity among the four key variables of artificial intelligence anxiety, organizational attachment, work remodeling, and employee innovative behavior, it conducts the confirmatory factor analysis (CFA) using Mplus 8. 0. Additionally, to ensure that common method bias was not a significant concern in this research, Harman's single-factor test was applied to an exploratory factor analysis of the 40 items pertaining to these four variables. It delves into the mediating effect of job crafting, and the moderating effect of organizational attachment; and then it explores the boundary of the relationship among AI anxiety, job crafting and the innovative behavior of the new generation of employees under different levels of organizational attachment.
The results show that artificial intelligence anxiety positively affects the innovation behavior of the new generation of employees through job crafting, and the degree of organizational attachment of employees plays a moderating role in this process. When employees' organizational attachment is low, the positive mediating effect of AI anxiety on the innovation behavior of new generation employees through job crafting is significant. When employees have a high degree of organizational attachment, the mediating effect above is not significant.
Therefore,it is essential for managers to acknowledge the influence of AI anxiety on the new generation of employees, and harness this anxiety constructively to steer, inspire, and energize employees to proactively redefine their roles and to embrace innovation with confidence. While employees should maintain a secure level of organizational attachment, which is characterized by a healthy balance between commitment and autonomy. To facilitate this, managers are tasked with cultivating an organizational environment that serves as both a "safe haven" and a "security island", providing the new generation of employees with a robust sense of security.

Enterprise operations tend to be platform-oriented in the platform economy, and employees become intrapreneurs. Platform leadership provides development opportunities for employees by building a career platform. Can platform leadership actively influence intrapreneurial behavior? What is the impact mechanism? A thorough study on this issue can help enterprises find effective ways to promote the development of “company platformization” and "employee-maker orientation". However,there is inadequate research in the existing studies.
Hence, to further research on the impact mechanism of platform leadership on intrapreneurial behavior, this study proposes the relationship model of platform leadership and employee intrapreneurial behavior with psychological ownership and job crafting as the mediating variables and entrepreneurial culture as the moderating variable based on the proactive motivation model and job-environment matching model. It uses first-hand survey data from 354 employees from enterprises in high-tech manufacturing, communication and IT industries, internet industries, new energy and new materials industries as samples, and conducts empirical research on the mediating effects of psychological ownership and job crafting and moderating effect of entrepreneurial culture on the relationship between platform leadership and intrapreneurial behavior. Then it measures “platform leadership” “intrapreneurial behavior” “psychological ownership” “job crafting” and “entrepreneurial culture” on existing mature scales by the Likert’s five-point scoring method, and conducts validity tests, aggregation tests, descriptive statistics, correlation analysis, and hypothesis tests on the data by SPSS.
The conclusions are as presented. Firstly, platform leadership has positive effects on employee intrapreneurial behavior, indicating that platform leadership can effectively promote intrapreneurship and achieve "employee-maker orientation". The career platform created by platform leaders creates opportunities for employees to start new businesses internally and provides guarantees and resources for the success of intrapreneurship. At the same time, the value concept of platform leaders' shared growth and their tolerance for entrepreneurial failure make employees willing and dare to engage in intrapreneurial activities. Secondly, psychological ownership and job crafting have partial mediating effects between platform leadership and employee intrapreneurial behavior, respectively, and psychological ownership has positive effects on job crafting; the two play a chain mediating role between platform leadership and employee intrapreneurial behavior. That is, platform leadership influences intrapreneurial behavior through a dual path, namely the psychological path of psychological ownership and the behavioral path of job crafting. This means that broad job design provides employees with more work autonomy, allowing them to discover entrepreneurial opportunities through job crafting, and can better promote the role of platform leadership in influencing employees’ intrapreneurship. Thirdly, entrepreneurial culture has positive moderating effects on the relationship between platform leadership and employee intrapreneurial behavior, which means that the higher the level of entrepreneurial culture, the greater the direct influence of platform leadership on employee intrapreneurial behavior. Organizational situational factors are important because they influence employee motivation for proactive behavior, and the improvement of intrapreneurial initiative among employees requires a good entrepreneurial culture to provide support. This conclusion indicates that shaping a good entrepreneurial culture helps platform leadership exert its influence on employees' intrapreneurship.
In summary, this study explores the positive impact of platform leadership on the intrapreneurial behavior of employees based on the proactive motivation model. By introducing psychological ownership and job crafting, it further analyzes the psychological and behavioral pathways of the impact of platform leadership on employee intrapreneurial behavior, and confirms the dual mediating effects of psychological ownership and job crafting between platform leadership and intrapreneurial behavior. In addition, the study clarifies the boundary role of organizational contextual factors in the impact of platform leadership on employee intrapreneurial behavior; with entrepreneurial culture as a moderating variable. it explores the boundary conditions of the influence of platform leadership, and the research results show that organizational situational factors can affect the effectiveness of platform leadership on employee intrapreneurial behavior. Future research can compare the impact of platform leadership and other leadership styles on employee intrapreneurship, explore other impact paths, reveal the underlying mechanisms, and choose individual characteristic factors such as entrepreneurial ability and entrepreneurial attributes for further exploration.

Manufacturing upgrade is a crucial component of national economic development strategies, with the sources of competitive advantage evolving from traditional products and technology to data-driven, algorithmic, and service-oriented paradigms. Currently, the study of how Digital Intelligence Services (DIS) influence manufacturing upgrades is in its nascent phase, particularly within the Chinese context, where the integration of these elements trails behind advanced enterprise intelligence practices. The mechanisms through which DIS can enhance competitive advantages are yet to be fully explored and articulated. Given these issues, this study focuses on the following aspects: (1) the definition of DIS and the relationship between "digital" and "intelligence"; (2) the impact of DIS on manufacturing upgrades from various perspectives, including its driving motivations, mechanisms, outcomes, and underlying knowledge framework; and (3) the future development directions of DIS in the context of manufacturing upgrades.
This study delves into the multifaceted domain of DIS and their influence on the manufacturing industry's transformation. To achieve this, it selects the core collection of the Web of Science (WoS) database as the primary sample source. Through a meticulous literature review, the study identified and clustered foreign scholarly works, ultimately narrowing down the focus to two pivotal research topics: "digital intelligence services" and "manufacturing industry upgrading. " The analysis began with the earliest relevant literature, dating back to 1996, and encompassed a comprehensive collection of 542 non-duplicative literature data. Utilizing CiteSpace, this study maps the developmental trajectory, frontier hotspots, and changing trends of DIS's impact on manufacturing upgrades. Through latent semantic analysis (LSI) of keywords, a visual map was created. This approach integrates the individual "S-B-O" model with the product-service system-focused "S-B-O" model, resulting in a comprehensive framework of DIS’s impact on manufacturing upgrades across four dimensions: motivation, mechanism, performance, and knowledge system.
The study reveals several key findings: In terms of motivation, the trend in research indicates that DIS influences manufacturing upgrades by addressing "user demand responses. " Mechanistically, clustering analysis shows that DIS promotes manufacturing upgrades through a parallel process, achieved via the coordination of manufacturing and service systems. In terms of performance, the primary pathways for DIS-driven manufacturing upgrades are efficiency enhancement and model innovation, which are the focus of most studies. Regarding knowledge concepts, the DIS concept and theoretical focus evolve from technology-driven services to personalized services and, ultimately, human-machine interaction services.
The research introduces several innovative contributions. First, it delineates the distinctions and interconnections between "digital" and "intelligence" within existing literature, establishing a theoretical groundwork for comprehending the intrinsic mechanisms that underpin DIS's role in advancing manufacturing upgrades. Second, it examines the impact of DIS on manufacturing upgrades from multifaceted perspectives, including user demand and industrial development, extracting coherent, progressive themes from the literature, and formulating a theoretical framework that elucidates causal relationships. Third, diverging from conventional technology-driven perspectives on industrial structural changes, this study highlights the role of DIS in manufacturing upgrades through inter-industry dynamics. This offers invaluable insights into understanding theoretical development trajectories and frontier issues.
Future studies should delve into the synergies between new-generation manufacturing and artificial intelligence technologies. This exploration necessitates the development of diverse channels for securing key resources and a deeper comprehension of the multifaceted motivations that drive the impact of services on manufacturing. Moreover, research should aim to expand the application of knowledge domains based on ontology theory. Efforts should be directed towards advancing the standardization of knowledge systems, considering the perspectives of the Internet of Things, platform ecosystems, and service ecosystems. Subsequently, on the one hand, there is a need to construct data-driven AI large models that facilitate autonomous learning and intelligent decision-making in service contexts. This development will broaden the range of manufacturing realization methods and operational models. On the other hand, future research should harness blockchain technology to establish open cooperative networks. This will involve creating a management system designed to identify, assess, and mitigate risks to user data security, thereby enhancing the quality and reliability of manufacturing digital intelligence services.

The wave of digitization has swept in, and new breakthroughs have been made in digital technology innovation, represented by emerging technologies such as big data and artificial intelligence. The Chinese government is determined to build a number of new growth engines, such as new-generation information technology and artificial intelligence, and to create digital industry clusters with international competitiveness. Digital technology innovation is the key for countries to competing for a new round of competitive advantages in science and technology and the commanding heights of industrial development, and it also provides a key impetus for the high-quality development of China's digital economy under the new development pattern.
However, in the process of digital technology research and development, the inefficiency (or inefficiency) of individual digital technology innovation of an organization may cause the organization to rely on backward technology and form a digital technology reverse lock. Digital technology locking hinders the survival and high-quality development of the digital economy, and in-depth exploration of the unlocking mechanism of digital technology locking will be the key to leading enterprises to improve the quality and efficiency of digital technology innovation against the technology bottlenecks in the field of scientific and technological innovation. Thus, this paper identifies the digital technology invention patent application data of Chinese listed companies through the IPC classification number, measures the reverse locking effect of China's digital technology based on the input and output of digital technology, examines the "erosion effect" of the locking of digital technology on the development of the digital economy, and specifically analyzes the digital unlocking strategy in different situations. It also analyzes the digital unlocking strategy under different circumstances, providing experience and reference for understanding the connotation of digital technology reverse locking and breaking through the "digital locking cage".
Specifically, following technology path dependence theory , this study uses the digital technology patent application data of Chinese listed companies from 2011—2021,and adopts the non-radial super-efficient SBM method to measure China's digital technology lock-in.It then examines the erosion effect of digital technology locking on the development of the digital economy and analyzes feasible unlocking strategies under different circumstances. It is found that there is a significant erosion effect of digital technology locking on the development of the digital economy, and the effect follows the nonlinear trajectory of "significant erosion—convergence of erosion effect—strengthening of erosion effect". Influenced by the spatial diffusion of technology, digital technology locking on the development of the digital economy shows the phenomenon of "neighborhood erosion". The analysis of unlocking strategy shows that compared with internal technology introduction, external technology introduction significantly breaks the fixed evolution track of reverse digital technology lock-in, and regions in weak institutional innovation environments have higher marginal benefits by curbing digital technology lock-in through technology imitation and transformation. In addition, the curbing effect of technology digestion and absorption on digital technology lock-in is characterized by asymmetry between regions, and intellectual property protection provides a solid institutional guarantee for the absorption of knowledge and the quality transformation of digital technology achievements.
This study makes some novelties in two ways. First, considering the potential risk of technology reverse lock-in caused by the continuous self strengthening of digital technology in a backward framework,it measures the reverse lock-in effect of digital technology in China and examines its "erosion effect" from multiple perspectives. Compared to previous research on technology lock-in, the study enriches the new connotations generated by technology lock-in in China in the digital era and deepens the literature related to the development of digital technology. Second, the study explores the feasible paths for unlocking digital technology in China's realistic context, and specifically analyzes the diversified strategies for unlocking digital technology in different scenarios, expanding and deepening the relevant research content of technology unlocking, providing policy reference and empirical reference for China to shake off the shackles of digital locking.

Since the issue of the overall strategy of building a strong manufacturing country formulated in 2015, China has been endeavoring to promote the intelligent manufacturing equipment industry as the main development direction so as to improve the efficiency of collaborative innovation in China's intelligent manufacturing equipment industry and optimize the network structure urgently. Therefore, it is of theoretical and practical significance to explore the evolution trend and influence mechanism of cooperative innovation network for improving the allocation of innovation resources in China's intelligent manufacturing equipment industry.
In light of this context, this study takes China's intelligent manufacturing equipment industry as an example to analyze the impact of multi-dimensional proximity and interactivity on the evolution of cooperative innovation networks. It first analyzes the impact of multidimensional proximity and its interactivity on the evolution of collaborative innovation networks from a theoretical perspective and proposes corresponding hypotheses. Then it constructs a theoretical model to explore the dynamic influence mechanism of knowledge proximity, social proximity and institutional proximity and the interaction among them on the evolution of cooperative innovation network. Specifically, this study selects data of China's intelligent manufacturing equipment industry from 2001 to 2020 for empirical research, analyzes the spatiotemporal characteristics of the evolution of collaborative innovation networks at each stage by using social network analysis method from a lifecycle perspective, and uses the negative binomial regression to test the proposed research hypotheses.
The results show that the evolution of the collaborative innovation network in China's intelligent manufacturing equipment industry is characterized by a phased expansion. The intra-regional cooperative innovation network has evolved from the "single-core marginal type" to the "dual-core multi-key - marginal type", and the cross-regional cooperative innovation network has evolved from a "one axis and two points" pattern to a "diamond" pattern. It is found that there is an inverted U-shaped relationship between knowledge proximity and the evolution of cooperative innovation network. In the three stages divided, social proximity has a significant promoting effect on the evolution of collaborative innovation networks, while the impact of institutional proximity is not significant. Social proximity and institutional proximity have significant substitution effects. The interaction between knowledge proximity and institutional proximity, as well as between knowledge proximity and social proximity, has no significant impacts on the performance of collaborative innovation.
Corresponding suggestions are expounded in three ways. Firstly, in terms of network evolution, the government should actively guide innovation resources to concentrate in regions and central cities such as Beijing, Shanghai and Guangdong to form hubs of innovation. The government should actively guide and encourage deep cooperation between advantageous regions and regions with lower technological levels to optimize the overall allocation of innovative resources by formulating tax incentives and research achievement reward policies. In addition, Fujian, Sichuan, Hubei, Liaoning, Tianjin and other regions should make full use of the radiating driving role of collaborative innovation in Beijing, Shanghai and Guangdong, actively promote the development of the current diamond pattern of multi-core and multi-node, and constantly expand and improve their driving roles in the corresponding economic circle. Finally, for Gansu, Xinjiang, Hainan and other regions, it is necessary to adopt new technologies to improve the knowledge spillover absorption capacity of innovative enterprises, and give full play to their own characteristics to coordinate with regional core cities.Secondly, the protection and management of intellectual property rights are worthy of effort. Innovation subjects generally tend to limit the existence of opportunism when choosing partners to avoid the loss caused by the unconscious spillover of their own knowledge. Therefore, the government should refine and improve the laws and regulations on intellectual property protection,increase the cost of violating the law, and improve intellectual property protection and management from all angles.
Finally, because social proximity based on trust and a good history of cooperation plays a significant role in promoting cooperative innovation performance, the government should make full use of big data information technology to build a nationwide online platform for promoting industry cooperation and industrial alliances to broaden the communication channels of innovation entities and improve the efficiency of cooperation and innovation.

Scientific research funding is an important source of scientific and technological innovation activities, and in recent years, the Chinese government has continuously optimized the policy of scientific research funding with a focus on following the laws of science and improving the effectiveness of its use. However, in practice, problems such as rigid management mode and tedious expense reimbursement procedures seriously reduce the efficiency of research fund utilization. In response to these problems, China has introduced the contract system for scientific research funding, but the management of scientific research funding is a complex and systematic process. Furthermore, the contract system for scientific research funding is a trust-based funding management model. The above reasons have led to difficulties in system implementation in practice.
Centering around the contract system for scientific research funding, this study obtains textual data by interviewing policy implementation subjects and target groups. After that, it utilizes the grounded theory analysis method and conducts three levels of coding, including "open coding, axial coding, and selective coding". Then it extracts the factors affecting policy implementation and constructs a model of the factors affecting the implementation of the contract system. The model consists of four main categories, including top-level design, willingness to implement, values, and policy environment, and nine subcategories, including policy definition, supporting policies, policy tools, departmental management, implementation attitudes, policy acceptance, cognitive ability, cultural environment, and technological environment.
It is found that, foremost, the policy design of the contract system for scientific research funding can affect the willingness to implement relevant policies and the acceptance of the policies by the main body of policy implementation and the target group. Therefore, the government needs to further improve the policy design of the contract system for scientific research funding so as to clarify the system's content and coverage. Second, the management needs and implementation attitudes of policy implementation subjects affect policy implementation behavioral choices. Thus, there is a need to establish a mechanism for monitoring and incentivizing policy implementation. Third, the target group's sense of access and trust in the policy practice have a great influence on their cooperation in the contract system. The study suggests that the government can apply the contract system to a wider range of programs. At the same time, it is also very important for the government to improve the feedback mechanism for further improvement. Last but not least, the cultural and technological environments of scientific research integrity provide the environmental guarantee for the effective implementation of the contract system. Consequently, the study concludes that the government needs to accelerate the digital transformation of the contract system for scientific research funding. It can promote the circulation and sharing of policy information, while it is also necessary to improve the integrity mechanism of the contract system and to shape a cultural environment of integrity.
The novelties of this study are manifested in the following two aspects. First, at the theoretical level, this study utilizes the case of the implementation of the policy of contract system for scientific research funding. It further reinforces the conclusion of existing research that the relevant factors in public policy implementation and their interactions can influence policy implementation. Unlike the previous literature, this paper starts from the perspective of influencing factor analysis. The results of this study not only make up for the inadequacy of the analysis of the factors influencing the implementation of the contract system in existing studies, but also respond more deeply to the implementation dilemmas in the contract system. Secondly, the research results provide management reference for further promoting the effective implementation of the contract system of scientific research funding, effectively utilizing the "leverage effect" of scientific research funding, and enhancing the effectiveness of the policy at the practical level.

Enabled by digital technology, innovation ecology can efficiently realize the transfer, interaction, expansion and evolution of knowledge, and form the core competitiveness of the digital age. At present, China has initially explored an innovation ecosystem supported by "new infrastructure" such as 5G, Internet of Things, industrial Internet and artificial intelligence, with industry leading enterprises as the main body and "platform + a large number of small and medium-sized enterprises" as the main structure, which has become a prototype of the integration of China's digital economy and the real economy, and can meet the needs of future scenarios better. The long-term development of the innovation ecosystem led by the industrial Internet platform is the key to the integration of China's digital economy and the real economy.
However, the current academic research on industrial Internet platform dwells on connotation analysis, exploration and application, and business model analysis, and there is a lack of research on industrial Internet clusters and their ecology. In addition, current studies on the value co-creation of innovation ecosystems are mainly conducted from the perspectives of the innovation ecosystem subjects, and the network relationship formed between the subjects and the external innovation environment, but less attention is paid to the co-creation relationship between the platform and manufacturing enterprises, between intelligent devices and humans, and between machines and data to explain the value co-creation process mechanism of the innovation ecosystem led by the industrial Internet platform. The value co-creation mechanism of the innovation ecosystem led by the industrial Internet platform is yet to be revealed.
The innovation ecosystem led by the industrial Internet platform takes digital resources and digital infrastructure as key production factors, reshaping the win-win cooperation logic in the industrial value network, and reflecting unique characteristics different from the general innovation ecosystem. Therefore, drawing on the value co-creation theory of the innovation ecosystem, this study explores three mechanisms, including modularity, scenario, and complementarity from the intrinsic attributes, and analyzes their interactive utility. This paper selects the COSMOPlat Industrial Internet platform as the case study object; it adopts a structured data analysis method to analyze the case, encodes and abstracts the original data, realizes the analysis and induction of the theme, and finally extracts a rigorous theoretical theme, forming a data structure composed of first-order constructs, second-order themes and third-order categories.
It is found that (1) the innovation ecosystem led by the industrial Internet platform is a value creation and value acquisition system composed of multiple participants in different fields. It is an open, supply-and-demand-driven, loosely coupled innovation system based on a multi-platform interactive architecture, and the innovation system can improve the initiative of each subject to participate and the digital ability and innovation diffusion ability through the sharing and symbiosis of technology, resources and scenes, so as to achieve the goal of system innovation. (2) The innovation ecosystem led by the industrial Internet platform achieves a win-win situation of efficiency and collaboration within the ecosystem on the supply side through modularity and complementarity, and integrates the demand side into the ecosystem through the scenario mechanism to form a future-oriented co-creation system. The modularity mechanism effectively integrates information technology infrastructure, big data technology, blockchain technology, and artificial intelligence technology, and builds a multi-platform interactive architecture to promote the integration of data and reality. The scenario-based mechanism accesses the scalable new generation of intelligent technology to construct the user scenario-based experience, and activates multiple subjects to actively embed the ecology through the governance scene to create a win-win situation. The complementary mechanism and modular technology are nested in multiple layers to complete the industry technology complementarity and digital technology complementarity, match scenarios to iterate the solution covering the whole life cycle of users, optimize collaborative innovation among various entities in the ecosystem through the platform enabling process complementarity. (3) The innovation ecosystem led by the industrial Internet platform integrates resources efficiently to achieve value co-creation through the modular mechanism, scenario mechanism, and complementary mechanism, improves the ecological digitization ability, and forms the same side network effect, cross-side network effect and cross-domain network effect of the innovation ecosystem.

With the continuous advancement of the digital revolution, digitalization has become the core force for innovation and transformation and the important engine for building new competitive advantages at the national level around the world. It has been widely recognized that digitalization promotes regional development; however, there is still a lack of research on the impact of digitalization on regional innovation from the perspective of innovation efficiency, and the influence of digitalization on regional innovation efficiency has not been tapped from multiple dimensions. In the context of digitalization, the spatial and temporal boundaries of regional innovation are increasingly blurred, and the importance of synergy innovation is more emphasized. As the basic carrier of regional synergy innovation, the innovation network plays a significant role in promoting the deep integration of the digital economy and the real economy and the improvement of digitalization in regional innovation. However, there is still a lack of research that integrates innovation network, digitalization and regional innovation efficiency into the same framework. Therefore, exploring the impact of digitalization on regional innovation efficiency and the mechanism of innovation network between digitalization and innovation efficiency have become important issues to be studied urgently.
Following the regional digitalization and synergy innovation theory, this paper empirically analyzes the impact of digitalization on regional innovation efficiency based on the panel data of 30 provinces in China from 2009 to 2020, and tests the mechanism of innovation network between digitalization and regional innovation efficiency. On the one hand, based on the theoretical connotation and structural characteristics of regional digitalization, this paper analyzes the impact of digitalization on regional innovation efficiency from three aspects: digital infrastructure, digital service and digital application. The individual fixed effects model is used for panel regression analysis. On the other hand, the mechanism of the innovation network between digitalization and regional innovation efficiency is discussed from two aspects: the comprehensive level of the innovation network that represents the overall development of innovation network, and the innovation network link that represents the cooperation between the actors in the innovation network. Then the sequential test method is used for analysis.　
The results show that digitalization can significantly improve regional innovation efficiency and the regional heterogeneity in the center, west, and east is growing greater and greater. All three digitalization sub-indicators can significantly promote the improvement of innovation efficiency, and the effect size shows the differentiated characteristics of “digital infrastructure > digital application > digital service”, and the results are still valid after a series of robustness tests. Digitalization and its three sub-indicators can indirectly improve regional innovation efficiency by promoting the innovation network comprehensive level and innovation network link. The innovation network comprehensive level and innovation network link play a significant mediating role between digitalization and regional innovation efficiency, and the robustness of the mediating effect has been further verified. In addition to digital application, the joint development of digitalization comprehensive level, digital infrastructure, and digital service with the innovation network comprehensive level can significantly contribute to the improvement of regional innovation efficiency, and the joint development of digitalization and its three sub-indicators with the innovation network link can significantly promote the improvement of regional innovation efficiency.
This paper discusses the impact of digitalization on regional innovation efficiency from the three dimensions of digital infrastructure, digital service and digital application, and puts forward corresponding policy recommendations, including accelerating the construction of regional digitalization and building a provincial digital powerhouses, optimizing the construction of regional innovation network and strengthening synergy innovation in the digital context, and promoting the joint development of digitalization with innovation network to foster a sound ecology where digitalization interacts frequently with innovation network. For future research, on the one hand, regional spatial correlation can be considered in the study, and the spatial econometric model is recommended to explore the impact of spatial spillover effect of digitalization on the other regions’ innovation efficiency. On the other hand, innovation efficiency may be decomposed according to different stages of regional innovation activities, and the differentiated impact of digitalization on regional innovation efficiency could be explored at different stages.

Innovation is the first driving force for high-quality economic development. Cities, as carriers of innovation, are the gathering place of all kinds of innovation factors and resources, and releasing urban innovation vitality and improving urban innovation capability are important grips for the implementation of the national innovation strategy. Today, economic globalization has encountered a countercurrent, the global industrial and supply chains have undergone important structural changes, and China's economic development is facing many challenges. The Chinese government has made timely adjustments to its strategic plan, proposed the construction of a new development pattern, and emphasized that "around the construction of a new development pattern, we will enhance the endogenous power and reliability of the domestic macro-cycle, and improve the quality and level of the international cycle". Hence, it can be seen that upgrading the level of international circulation is an important part of the construction of the new development pattern. Existing research shows that upgrading the level of international circulation is conducive to the large-scale agglomeration of global innovation factors in China, the free flow of commodities and factors, and the improvement of attractiveness to foreign investment. So will upgrading the level of international circulation affect the innovation capability of cities? What is its mechanism of action? Exploring and answering these questions will provide support for upgrading the quality of international circulation and implementing the innovation-driven strategy, which is of great theoretical and practical significance.
Thus, this paper constructs an index system from four dimensions, namely, trade level, investment level, technology level, and international exchange and cooperation, uses the entropy weight method to measure the level of international circulation and explore the influence of the level of international circulation on the city's innovation capability, and empirically tests it by using the data of 296 prefecture-level and above cities in China from 2001 to 2021.
The results show that the level of international circulation can significantly promote the enhancement of urban innovation capability, and the conclusions are still valid through a series of robustness tests such as replacing the explanatory variables, shrinking the tails, and regressing the samples according to different regions, different administrative levels and different sizes of cities. The effect of international circulation level on the enhancement of urban innovation capability varies according to regions, administrative levels and city sizes, and it has a greater effect on the promotion of innovation in cities in the eastern region, provincial capitals and large cities. The mechanism test shows that an increase in the level of international circulation can significantly promote the agglomeration of R&D factors and significantly increase the attractiveness of cities to foreign investment. Meanwhile, the level of international circulation contributes to the agglomeration effect of R&D factors and improves the attractiveness of foreign investment, which effectively enhances urban innovation capability.
The main marginal contributions of this paper include four aspects. (1) This paper explores the impact of the level of international circulation on urban innovation capability in the context of the new development pattern, expanding the research boundaries of the factors influencing innovation. Existing literature seldom deals with the impact of the improvement of the international circulation level on the innovation capability of cities, and this paper has done some exploration in this regard. (2) From the perspectives of R&D factor agglomeration and attracting foreign investment, this paper explores and opens the potential mechanisms and paths of the international circulation level affecting urban innovation capability. (3) Existing literature mainly qualitatively examines the historical origin, scientific connotation, internal logic and realization path of the economic cycle from the macro level, focusing on exploring the economic cycle theoretically, while this paper cuts in from the perspective of the international cycle level, providing empirical evidence for the economic cycle theory from the meso-level empirical evidence. (4) The findings of this paper also have important theoretical significance. The study finds that the international circulation level can promote urban innovation capability, which provides theoretical basis and empirical evidence for the correct understanding of the significance and role of the international circulation level on urban innovation capability, and gives theoretical support for the international circulation level to help improve urban innovation capability.

The development of the new energy vehicle industry and its technological innovation have received widespread attention in the context of the ongoing global technology revolution and the growing importance of sustainable development as a strategic focus. New energy vehicles are a technology-intensive emergent industry, and their basic technologies cannot be developed and implemented without the combined efforts and cooperative innovation of businesses, academic institutions, and research centers. However, the existing literature still lacks empirical studies on the long-term collaborative innovation behaviors of various innovation agents in the collaborative innovation network of the new energy vehicle industry. Using the exponential random graph model (ERGM), this study empirically examines the variables influencing the dynamic relationship changes in the collaborative innovation network of the new energy automobile industry.
Using the collaborative invention patent data of the new energy vehicle industry from 2017 to 2021 in China, during which the new energy vehicle industry developed rapidly, this study generates collaborative innovation networks year by year. The networks show obvious core-edge features, that is, a small number of members in the center of the network are closely connected, while the connections between edge nodes and other nodes are sparse. Specifically, the networks exhibit a spatial trend of decentralization and certain agglomeration, indicating that some innovation entities form some small-scale innovation clusters, and the innovation cooperation within the clusters is relatively close. The large number of star structures and closed triangle structures in these clusters indicate that the network structure variable plays an important role in the formation of the network. Through the analysis of the network nodes, the study finds that the core of this kind of cohesive sub-group is dominated by the leading enterprises, such as the leading automobile enterprises and large state-owned enterprises. This phenomenon is consistent with the overall situation of the new energy vehicle industry. The new energy vehicle industry has entered a stage of rapid development, and the capital and manpower invested by enterprises far exceed those of universities or research institutes. As a result, enterprises occupy a dominant role in technology research and development. Meanwhile, enterprises also need the research capabilities of universities and research institutes to support research and high-tech development; thus, with the leading enterprises as the core, a group of universities, research institutes, and small enterprises have gathered to form a collaborative innovation sub-group.
The study further applies ERGM to the networks generated by collaborative patents. It is found that in the development of the current network, organizations with different types of cooperation, such as university-industry cooperation, are more likely to generate invention patent creation, for the new energy vehicle industry is an emerging technology-intensive industry in need of diversified kinds of resources. In addition, it is found that organizations with high-level innovation capability would attract more collaboration, and organizations are willing to seek cooperation with others with similar innovation capabilities. As for the network structure, star structures are more likely to be formed in the current networks. According to the dynamic network analysis, the comparison results reveal that the effects mentioned above hold as time goes by, while the effects of differences in innovation capabilities between entities become weaker over time. The robustness checks, including TERGM analysis and analysis with alternative samples, also show consistency with the main analysis. Besides, the results of heterogeneous analysis based on organizational type indicate that, compared with enterprises, universities, and research institutes are more willing to generate collaboration within the network.
This study explores the collaborative innovation network in the new energy vehicle industry from a dynamic network perspective. It offers an overview of the development of collaborative innovation in the new energy vehicle industry in China, which contributes to the knowledge and provides insights into the development of the new energy vehicle industry in China. Additionally, the study has limitations. While several key influential factors to the network are identified, there are still more features that might be explored from a network analysis using larger datasets to advance the understanding of collaborative innovation.

With its high-end technological comparative advantage, China's manufacturing industry has been striving to reach the top of the global value chain. However, the traditional channels of using the international cycle to continue maintaining the technological comparative advantage of the manufacturing industry have been walled off because of some Western countries' "decoupling" or "de-risking" strategies. There is an urgent need to confirm if China's industrial sector will be able to innovate more effectively as a result of the recycling model's change. In light of the current development pattern, what strategies can China's manufacturing industry employ to leverage its technological edge to remove barriers and clear the way for new ideas to flow, ultimately bringing a long-term boost in innovation performance? The cyclic mode is a potent engine that can be used to improve China’s status in the global value chain, and it can also be used to cultivate the international competitive advantage of the manufacturing industry under the new development pattern. The dividends for China's manufacturing to realize high-quality development by utilizing the global cycle are becoming increasingly limited as the manufacturing sector is refuring to western developed nations.That is to say, new opportunities for the upgrading and transformation of China's manufacturing industry and the cultivation of international competitive advantage can only be created by changing the cyclic mode to achieve external promotion of the internal and then seize the initiative of China's high-quality development of the manufacturing industry.
It is important to note that most of the existing research has examined endogenous sources of technological comparative advantage under various cyclic modes from the perspectives of supply and demand equilibrium, independent innovation, the digital economy, and opening up to the outside world. Some researchers have also examined the significance of the dynamic comparative advantage during the transformation of cyclic modes in the process of improving the manufacturing industry's innovation performance from various angles. The imitation dividends of the international cycle's marginal contribution to the improvement of China's manufacturing sector's innovation performance are diminishing as China's manufacturing industry has been gaining its technological comparative advantage and moves from being an imitator in the international cycle to an innovator in the domestic and international double cycle. Thus, consideration must be given to the deciding influence of heterogeneous technological competitive advantage on the structure of factor endowments at various stages of manufacturing development when assessing the impact of recycling model transition on manufacturing innovation performance.
This paper uses panel data from China's manufacturing sector from 2001 to 2021 to estimate the impacts of various circular modes and technological comparative advantage on manufacturing innovation performance. It aims to integrate circular mode transformation, manufacturing innovation performance, and technological comparative advantage into a unified analytical framework. The labor-intensive manufacturing sector, which is characterized by an adaptive competitive selection mechanism, is able to significantly improve the manufacturing industry's innovative performance. It is also found that the labor-intensive manufacturing sector's technological comparative advantage brought by the large-calibre international cycle greatly optimizes the efficiency of factor allocation in the manufacturing sector. The manufacturing sector is compelled by the domestic and global double cycles to leverage capital-intensive technological advancements in order to significantly strengthen its technological advantage and achieve high-quality development through the closing of the technological potential gap. This has a positive impact on the manufacturing sector's innovation performance.
This study contributes to the literature by investigating the mechanism by which the domestic and international circulations affect the total factor productivity of the manufacturing industry based on differentiating between different circulation patterns, given that the improvement of manufacturing innovation performance is endogenous to the high fitting degree between the transformation of the circulation pattern and the structure of factor endowment.Moreover, it integrates the technological advantage induced by various factors into the model and further investigates the influencing mechanism of the recycling model transformation and the technological comparative advantage on the innovation performance of the manufacturing industry, which enhances the technological comparative advantage and cultivates new growth poles in the manufacturing industry.

Resource depletion, climate change and excessive pollutant emissions have led to the deterioration of the natural environment, seriously constraining high-quality economic development. Heavily polluting enterprises are an important source of environmental pollution, and improving the sustainable performance of heavily polluting enterprises is not only an intrinsic requirement to follow the high-quality development of the economy, but also a responsibility to actively address environmental challenges. Digital transformation has become the core driving force behind the development of enterprises. Therefore, it is necessary to study whether digital transformation can positively affect the sustainable performance of heavily polluting enterprises. However, few studies have explored the impact of digital transformation on sustainable performance from the perspective of heavily polluting enterprises. Then digital transformation empowers businesses to swiftly adapt their resources and competencies to the ever-shifting competitive landscape. It facilitates a dynamic alignment between a company's internal assets and the external environment, optimizing the allocation of existing resources and enhancing the efficiency of resource distribution. However, few existing studies have focused on the mediating role of resource allocation efficiency between digital transformation and enterprise sustainable performance from the integrated perspective of resources and capabilities. Finally, absorptive capacity is an important variable that affects the ability of firms to transform and utilize resources, but few studies have focused on the moderating role of absorptive capacity between digital transformation and sustainable performance of heavily polluting enterprises.
Therefore, this study examines the impact of digital transformation on the sustainable performance of heavily polluting enterprises based on the resource base view and dynamic capability theory, using data from A-share heavily polluting listed companies from 2008 to 2022. The results of the study show that digital transformation can enhance the sustainable performance of heavily polluting enterprises; digital transformation will promote the sustainable performance of heavily polluting enterprises through improving resource allocation efficiency, but resource allocation efficiency does not play a mediating role between digital transformation and the environmental performance of heavily polluting enterprises; absorptive capacity does not play a positive moderating role between digital transformation and the sustainable performance of heavily polluting enterprises; the state-owned nature as well as the positive effect of digital transformation on sustainable performance improvement is more significant for heavy polluters in the growth period.
This study has three theoretical contributions. First, this study further expands the theoretical logic of digital transformation for non-economic value creation. It verifies the key role of digital transformation in achieving sustainable performance of heavily polluting enterprises, and further proves the importance of digital transformation in high-quality economic development. Second, this study further expands the scope of application of dynamic capabilities theory between digital transformation and sustainable performance of heavily polluting enterprises. By identifying the mediating role of resource allocation efficiency in the relationship between digital transformation and sustainable performance of HIPCs, this study further refines dynamic capabilities and opens the "black box" of the process of digital transformation affecting the sustainable performance of HIPCs. Third, it expands the boundary conditions for the impact of digital transformation on the sustainable performance of heavy pollution enterprises. By identifying the weighted role of absorptive capacity in the relationship between digital transformation and sustainable performance of heavily polluting enterprises and regressing it into groups according to the nature of the enterprise and the life cycle of the enterprise, this study enriches the contextualized research from the perspective of resources and capabilities.
Future research could explore if there is a nonlinear relationship between digital transformation and sustainable performance of heavily polluting enterprises. Then, the mechanisms of other factors, such as green innovation and business model innovation are worthy of further analysis, for it will generate valuable insights into the mechanism linking digital transformation and sustainable performance of heavily polluting enterprises under different circumstances. Furthermore, there may be differences in the impact of digital transformation on the sustainable performance of heavily polluting enterprises with the same cultural characteristics, so future research could use data from other countries to determine the applicability of the findings.

Over the past 40 years of reform and opening up, the mixed ownership reform of state-owned enterprises (SOEs) has complemented the reform of state-owned enterprises and the development process of private enterprises, made positive progress and remarkable achievements in the scale, scope, mode and speed of mixed reform, and also made great breakthroughs in institutional integration and mechanism construction. With the development of productivity and social changes, new problems have inevitably appeared in the practice of state-owned enterprise reform, and the mixed reform still needs to be further promoted, and how to develop a higher level of mixed reform is still worthy of further study. Mixed-ownership reform is not a one-way road for SOEs to accelerate their development, but a two-way rush between SOEs and private enterprises. The advantages of private enterprises in terms of market mechanism, efficiency and scientific and technological innovation are organically integrated with the capital, resources, technology and management advantages of SOEs, and the mixed-ownership reform enterprises burst out with vigor and strong development momentum. The complementary advantages of state-owned capital and private capital have effectively enhanced the superimposed value of their advantages in the mixed-ownership reform. When SOEs choose to carry out mixed ownership reform in what proportion and in what way, they should first clarify their own development demands, combine the characteristics of non-state-owned capital, and skillfully combine them to achieve a win-win situation.
Most of the existing literature on mixed reform and innovation focuses on the impact of changes in ownership structure on innovation. However, the mixed reform is not a simple diversification of equity, but the introduction of non-state capital with a high shareholding ratio and giving play to the governance role of non-state-owned shareholders. Previous studies on the mixed-ownership reform and innovation investment of SOEs?have mainly focused on the impact of changes in shareholding structure on innovation investment, but the proportion of shares held by non-state-owned shareholders introduced by the mixed-ownership reform to promote innovation investment has been seldom considered. In addition, the mechanism through which the deep mixed-ownership reform of SOEs will increase the innovation investment of SOEs in high-tech industries, and the differences in the role of mixed-ownership reform of SOEs in different regions on innovation investment are all worthy of in-depth exploration.
Using the data of listed SOEs in the A-share high-tech industry from 2010 to 2019, this paper adopts a multi-point DID to test the effect of mixed ownership reform on the innovation input of SOEs in China. Empirical results show that, compared with unmixed and deep mixed reform, it can promote the innovation investment level of SOEs in high-tech industries. The results hold valid after a series of robustness tests, such as predisposition score matching and overlapping DID. On this basis, it is found that the mixed innovation effect of SOEs is more obvious in the eastern region and the highly market-oriented region. The mechanism test confirms that by strengthening supervision and mitigating agency problems, the deep mixed-ownership reform can promote the innovation input of SOEs in high-tech industries. Therefore, more attention should be paid to the depth of substantive reform rather than form in the new round of SOE reform.
Compared with previous studies, this paper has made breakthroughs in three aspects. First, it carefully arranges the shareholding ratio of non-state-owned shareholders among the top ten shareholders of enterprises, divides the mixed reform into non-deep and deep mixed reform, and studies the impact of mixed reform on innovation investment by category, enriching the related research on mixed reform. Second, combined with the multi-stage DID model and multiple robustness tests, it analyzes the influence of the mixed reform of SOEs in the high-tech industry on the enterprise's innovation investment, and expands the boundaries of previous research. Thirdly, this paper not only pays attention to the impact of the internal deep mixed reform on innovation investment but also studies the impact of regional and marketization degree on the depth mixed reform of SOEs from the external environment of enterprises, which broadens the research ideas of the mixed reform of SOEs.

The rapid development of digital technologies such as big data, artificial intelligence, cloud computing, etc., has brought profound changes to the economy and society, and has given rise to the emergence and growth of the digital economy. The digital economy has become an important driving force for China's economic development in the new era, and its scale has ranked second in the world, accounting for more than 40% of the GDP. To develop the digital economy and achieve high-quality economic development, it is necessary to promote the digital transformation of enterprises and enhance their innovation capabilities. However, the digital transformation of enterprises is not only affected by the market mechanism, but also influenced by government policies and incentives. Therefore, it is of great theoretical and practical significance to explore the impact of government digital incentives on firm innovation and its underlying mechanism.
In order to examine the effect of government digital incentives on firm innovation and the mediating role of enterprise digitalization level in this process, the study adopts the theory of enterprise growth as the theoretical framework, and selects high-tech listed companies in China's information transmission, software and information technology service industry from 2013 to 2020 as the research sample, for these sample enterprises are an important part of China's high-tech industry, and play an important role in promoting China's scientific and technological innovation and economic transformation; while they are the main beneficiaries of China's digitalization policy, which is of great significance for assessing the implementation effect and improvement direction of China's policy. Then the study uses the seemingly unrelated regression (SUR) method to conduct systematic estimation. It measures firm innovation from two dimensions: innovation input and output, using the natural logarithm of R&D expenditure and the natural logarithm of the number of effective invention patents as the proxy variables, respectively, and the natural logarithm of the total amount of digitization support provided by the government as the proxy variable for digitization incentives and the ratio of digitization technology intangible assets to total assets as the proxy variable for enterprise digitization level. The paper sets control variables such as enterprise size, the number of years the enterprise has been on the market, the company's annual capital expenditures, etc.
The main findings of the paper are as follows.(1) Government digital incentives have a significant positive impact on both firm innovation input and output, indicating that digital incentives can enhance firm innovation level and thus supporting hypothesis H1. (2) Enterprise digitization level plays a significant positive mediating role between digital incentives and firm innovation, suggesting that government incentives can promote firm innovation by improving enterprise digitization level and thus supporting hypothesis H2. (3) The effect of government digital incentives on firm innovation varies according to the equity nature and growth period of enterprises. Specifically, government digital incentives have a more effective promoting effect on state-owned enterprises and innovation level, while for GEM-listed companies, government digital incentives stimulate their R&D investment levels more effectively than other listed companies.
The paper extends previous research on the impact of government incentives on firm innovation by focusing on the digital incentives, which are different from traditional subsidies and tax incentives, and examines their effect on both innovation input and output. Then, it reveals the mechanism by which government digital incentives affect firm innovation by introducing and testing the mediating role of enterprise digitization level. Moreover, it conducts heterogeneity analysis based on the equity nature and growth period of enterprises, and provides more nuanced and specific insights for policy design and implementation.
Hence, the study argues that it is essential for enterprises to actively respond to the national strategy of developing the digital economy, seize the opportunities brought by government digital incentives, and enhance their digitization level and innovation capabilities; and it is imperative for government departments to improve the digital-related policies, optimize the allocation of resources, promote the flow of data elements, and balance the trade-offs between incentives and market discipline.

Against the current backdrop of low-carbon governance and high-quality development, manufacturing enterprises with heavy and chemical industry structures have been confronted with the problems of "high energy consumption, high emissions, and high pollution", and there are still many key industries in urgent need of green transformation. At the same time, some manufacturing enterprises, including some large enterprises, have a vague understanding of the long-term, systematic, and complex evolution trend of environmental evolution and green transformation and the phenomenon of copying peer enterprises’ transformation mode under the guidance of passive thinking prevails. One important reason why it is difficult to form an appropriate transformation path is that under the current dynamic situation, the green transformation process of manufacturing enterprises is affected by the interaction of multiple network relationships formed of macro- to micro-multidimensional factors, and the internal mechanism and path of its transformation are more complex. Therefore, how to clarify the interactive mechanism of multi-dimensional factors in this complex network and then explore the different configuration paths is increasingly important for the continuous acquisition of heterogeneous resources embedded in the network, for it is essential for the promotion of the sustainable green transformation process.
From the perspective of dynamic interaction between internal and external elements, the paper collects 356 sample data from manufacturing enterprises in urgent need for green transformation; then it takes cross-level network embedding and green dynamic capability, etc. as antecedent variables and green performance as an outcome variable, and uses the fsQCA method to analyze the multi-configuration paths by which high-level green transformation of manufacturing enterprises can be achieved. The paper summarizes three types of paths, including “active reform”, “capacity support” and “active imitation”; meanwhile, it summarizes two paths for realizing non-high-level green transformation in which enterprises are “strong in will but weak in capacity” and “powerful but unintentional” . Specifically speaking, the active reform path highlights the heterogeneity of the top management team and the importance of green strategy and innovation behavior. This type of path suits all manufacturing enterprises, especially small and medium-sized manufacturing enterprises with poor transformation conditions, and the key point focuses on enterprises initiative. The capacity support path pays more attention to the application of green dynamic capability and the implementation of transformation behavior, and it is suitable for large manufacturing enterprises integrating transformation resources through dynamic capability advantages. Besides, the active imitation path focuses on imitating the green transformation measures of peer enterprises or parent company, which is more suitable for small and medium-sized manufacturing enterprises and enterprises without rich experience in transformation. On the whole, manufacturing enterprises should design the transformation path following the principle of “seeking common ground while reserving differences” under different situations, which should not only pay attention to some common factors, but also make adjustments and match the path according to their own actual conditions in different stages. Besides, for the two types of paths for sluggish manufacturing enterprises, on the one hand, it is necessary to cultivate, promote and apply green dynamic capability throughout the transformation process; on the other hand, manufacturing enterprises need to get rid of the development inertia, and reform the development model. Even in the case of insufficient transformation capability, they should strive for the transformation path from imitation to independent development.
In summary, this study analyzes the interaction mechanism of the related perspectives of the green transformation of manufacturing enterprises in the complex dynamic network, highlighting the complex characteristics of the transformation process and the initiative nature of paths, which makes remedies for the current research on the “net effect” mechanism of the driving factors from a resource basic view and institutional theory, and broadens the scope of theoretical research on network embedding and dynamic capability. Furthermore, it expands the method of path design under the condition of multi-factor concurrency, and makes up for the disadvantage of singleness in the traditional linear path mining methods to a relatively large extent. Meanwhile, it provides a feasible solution for corporate management's green transformation decision-making, path identification, and matching in different scenarios, and also meets the needs of the organization’s nonlinear management.

The emergence of AI-Generated Contents (AIGC) causes theoretical dilemma of intellectual property law. Existing rules have difficulties in interpretation and application. The definition of intellectual property subject in existing laws is mainly based on established facts,and the emergence of AIGC changes the creation process of intellectual property, shakes the long-standing philosophical foundation of intellectual property system, and also brings difficulties to the judgment in judicial practice.
In the application of AIGC, the devices need to learn, mine, and process a large number of existing works and materials, then automatically calculate and generate contents through algorithmic models according to natural language instructions. In this process, the primary issue is whether AIGC should be classified as intellectual property subject matter. According to the traditional rules and regulations, the subject matter of intellectual property should be human intellectual output. However, human intellectual involvement is really limited in AIGC, while the appearance of AIGC looks like human intellectual output. The opinions on whether the AIGC should be protected under intellectual property law are divided into two categories. Behind this debate are the different choices of process perspective and result perspective.Nowadays, the scope of intellectual property protection shows an obvious trend of expansion, through extensive interpretation of traditional subject matter, or the introduce of new subject matter to the law, to realize inclusive and extended arrangements. As a result, there are also two kinds of legal attitudes towards the development of artificial intelligence, one is to expand the scope of traditional subject matter to cover new things, the other is to design new rules to solve new problems.
In this case, the start point of resolving disputes and disagreements is to accurately and scientifically define the subject matter involving generative AI, and the analysis position should be shifted from intellectual property to a broader perspective of data elements. The current data intellectual property registration’ system in China may be an alternative. From the perspective of data elements, the traditional labor theory of value, individual liberalism and incentive theory should be interpreted to meet the realistic needs of the development of artificial intelligence technology and the balance of interests. Both the technical nature and the technical process show that AIGC is actually simulating human activities of information and data extraction, learning and thinking. The output of AI is essentially the result of information and data processing. Old rules and ideas cannot support new practices, and social costs and historical trends should be taken into account in making new institutions and rules. Combined with the trends of digital economy and industrial development, the social function of intellectual property law and the expansion of intellectual property protection, it is necessary to make a humanistic interpretation, promote interests coordination, facilitate AI knowledge production and rational application, and carry out institutional value judgment and effect evaluation based on the complex relationship between intellectual property and data elements in the digital market.
Considering that the data rules are still in the turnaround zone and the inherent rules of intellectual property need to be adjusted in time, it is essential to comprehensively consider the connection and interaction between the data rules and the intellectual property system to find a solution to the legal issues of AIGC. From the perspective of future data governance, AIGC rules should be constructed according to the separation-of-rights framework rather than limited to the traditional intellectual property system. The definition of rights in AIGC cannot be separated from the characteristics and ownership issues of the data elements.This will help promote the comprehensive governance of artificial intelligence in the future and the long-term development of the digital economy.
In order to balance the benefits brought about by technological innovation and application effectively, the reasonable choice is to break through the boundaries of traditional information carriers such as works, patents and trademarks, and pay attention to the distribution of benefits involved in various fields such as data collection, protection, processing, transaction, circulation and use. It is necessary to explore the balance between private and public interests and establish a coordination mechanism based on the ‘data property rights’ framework so as to provide a legal basis for the governance of artificial intelligence and the development of the domestic digital economy.

Nowadays, a new wave of intense technological revolution and industrial transformation is reshaping the global innovation landscape and restructuring the global economic framework, with competition between nations no longer confined to geographical boundaries. The game of great powers has been transformed into the competition of science, technology and innovation, and scientific research has become the precondition for the development of technology and innovation. As international scientific and technological competition moves forward to the basic frontier, the major countries in the world are striving to seize the scientific highland through the macro-forces of the government, gain the first-mover advantage in basic research, and hold a lead in future frontier economic development; thus, scientific competitiveness has become a decisive factor in the rise and fall of a country.
The Chinese government has set the tone for basic research policies, from specific policy-making (individual policies) to the overall construction of the policy system (policy mix), and it has been proven that scientific competitiveness through policy tools has become a strategic measure for China's economic and social development in the present and even longer period. At present, accompanied by increasing public attention, the overall level of basic research in China is improving. However, in terms of using policy tools to enhance scientific competitiveness, the government faces obvious shortcomings in China's basic research field, such as low investment intensity and insufficient demand-oriented basic research layout. There are also problems such as diversified policy objectives, dispersed governance structures, multi-level management, and institutional failure in the policy layout. In view of this, the cooperative interaction design of policy systems, the complementary support of policy tools and the cross-use of combinations are the fundamental methods to achieve the efficient development of scientific research and improve the performance of policy practice.
From the perspective of policy science, this study focuses on the basic research field, examines the complex mechanisms and multiple paths of policy instrument combination on scientific competitiveness, and identifies the differences in the province-level division of scientific competitiveness. In this study, the research framework of policy tools is constructed based on the 28 province-level divisions to identify the impact of the use of three broad categories of policy tools—supply, environment and demand—on the enhancement of scientific competitiveness through content analysis and the fsQCA approach and explore their multiple concurrent and complex causal mechanisms. By analyzing the driving mode of scientific competitiveness promotion, this study provides useful policy reference and enlightenment for China's basic research strategic layout.
The results show that (1) a single policy tool does not constitute a necessary condition for high scientific competitiveness, and there are complex and diverse configurations in China's policy empowerment path to enhance scientific competitiveness; (2) supply-based policy tools play a universal role in enhancing scientific competitiveness; and (3) the mechanism for enhancing scientific competitiveness can be divided into four paths: supply-environment synergy, supply-leading path, ternary synergy, and supply demand synergy. In accordance with the four paths, it is essential to optimize the policy system and improve the synergy level of policy tools; for the government, it is imperative to provide continuous and stable support, improve the new system for mobilizing resources nationwide, and leverage the role of the government as the main channel. Given the imbalance between China's current development stage and the growing demand gap for basic research, social funding is also an indispensable and important supplement. Thus, a diversified investment mechanism for basic research is warranted to actively guide and encourage local, corporate, and social forces to increase investment in basic research on the basis of government leadership. Finally, precise implementation of policies in different regions could be achieved by fully considering the heterogeneity in historical background, geographical location, and other factors among different provinces.

Today's international pharmaceutical patent system is centered on Western countries and their industries and does not take into account the knowledge gap between countries in the South and the North. In pursuit of excessive monopoly profits,international pharmaceutical companies representing private interests and their affiliated countries continue to push for enhanced protection of pharmaceutical patents on a global scale,and the ratchet effect comes along with it. At present, academic discussions on the ratchet effect in the field of international pharmaceutical patents are still insufficient, for it is not clarified if the ratchet effect exists in the patent system of pharmaceuticals, and there is a lack of systematic thinking about the ratchet effect on the international protection of intellectual property rights. The development of patent rules in the pharmaceutical industry has a profound impact on the development of society, and therefore the construction of its system needs to take into account the interests of multiple parties. In recent years, China has continued to promote the reform of the regulatory system in the pharmaceutical field. Therefore, it is of theoretical and practical significance in this context to discuss the dilemmas of the ratchet effect and China's response to it.
This paper applies the ratchet effect to the trend analysis of the pharmaceutical patent system, explores its substantive causes with the help of the symbiosis theory of management, and then puts forward feasible countermeasures to the rule of law based on the reality of the Chinese society. Combining the development history of the international pharmaceutical patent system with the basic elements of the ratchet effect, this study explores the internal logical relationship between the two. It firstly explains the specific connotation and operation mode of the ratchet effect and emphasizes the importance of the direction of movement from the perspective of unidirectional movement.The development trend of the international pharmaceutical patent system has been systematically discussed, as well as the dilemmas the developing countries are confronting with due to the ratchet effect, such as limited legislative flexibility, stagnation of industrial competition, and difficulties in accessing medicines.
Then the study makes an operational interpretation and analysis of the causes. It combines the basic elements of the ratchet effect with the international pharmaceutical patent system, thus clarifying the specific operation mechanism of the former in this field. Specifically, the TRIPS "minimum standard" resists regression in the level of protection and constitutes the stopping paw of the ratchet of the pharmaceutical patent system; under the subject-behavior dichotomy, the interaction between multinational pharmaceutical enterprises and their affiliated countries and their respective driving strategies create the driving force of the ratchet and trigger the spread of the TRIPS-Plus rules to the global market. Furthermore, the study draws on the management theory of symbiosis to explore the substantive causes of the ratchet effect, i.e., the result of the creation of a favorable external environment by the affiliated countries in order to enhance the symbiotic power of the pharmaceutical industry's private groups.
Finally, it summarizes and analyzes overseas experience and China's response. After clarifying the operation mechanism and substantive causes of the ratchet effect of the international pharmaceutical patent system, this part zooms in on a concrete response to the ratchet effect. Firstly, two different modes of pharmaceutical patent protection in response to the ratchet effect are examined under the perspective of comparative law: the enhanced protection mode represented by the United States and the European Union, and the lax legislation mode represented by India. In view of the development of China's pharmaceutical industry and the reality of the public healthcare environment, the latter model is more meaningful. Secondly, in terms of specific measures, the paper presents suggestions, including applying the strategy of horizontal institutional transformation, improving the mechanism of information exchange and expression of interests, and making full use of "constructive ambiguity" to prevent the risk of patent expansion. Taking into account the foreign legislative model, China should, based on the realities of the domestic society, build a pharmaceutical patent protection environment suitable for the development of generic enterprises at both the domestic and international levels, so as to improve the accessibility of medicines to the public.

In the complex situation of global economic slowdown, scientific and technological innovation has become a strategic lever for cultivating new driving forces and promoting sustainable economic development. The Yangtze River Economic Belt is a major national development strategy region. By promoting regional coordinated development of scientific and technological innovation and cultivating new driving forces for economic development, it is of strategic significance for supporting national scientific and technological innovation, building a new development pattern of promoting regional coordinated development. In recent years, research on the Yangtze River Economic Belt has become a hot topic in regional economic research. Overall, research related to scientific and technological innovation in the Yangtze River Economic Belt mainly focuses on the evaluation of its technological innovation capabilities, the theory and issues of industry-university research collaborative innovation, as well as the study of the agglomeration characteristics and construction mechanisms of technological innovation belts and corridors. However, there is still relatively little quantitative research on the layout of the Yangtze River Scientific and Technological Innovation Belt at the urban level.
After the analysis of the foundation of scientific and technological innovation development and the progress of scientific and technological innovation cooperation in the Yangtze River Economic Belt, this study comprehensively analyzes the overall development level of scientific and technological innovation in 110 prefecture-level and above cities in 11 provinces and cities in the Yangtze River Economic Belt. Drawing on the methodology employed in the China Regional Science and Technology Innovation Evaluation Report, the study constructs a framework for evaluating scientific and technological innovation in the Yangtze River Economic Belt. The framework comprises three secondary indicators: the allocation of innovation resources, the operational efficiency of these resources, and the output of innovation achievements. It further identifies seven pivotal tertiary indicators. When calculating indicators, it uses the entropy weight method to assign objective weights to the three secondary indicators, which are given equal importance in a ratio of 1:1:1, and further calculates the weights of the seven tertiary indicators. Following the aforementioned criteria and methodologies for city selection, and leveraging the results of indicator calculations and in-depth analysis, the study proceeds to propose the urban layout of the Yangtze River Science and Technology Innovation Belt from different levels of international and national science and technology innovation centers and science and technology innovation pivot cities in the Yangtze River Economic Belt.
According to the comprehensive level and strategic needs of urban scientific and technological innovation development, this paper proposes that the roles of Shanghai, Wuhan, and the Chengdu-Chongqing region as science and technology innovation centers should be reinforced. Additionally, it is necessary to enhance the connectivity and interaction among these three centers to bolster their collective leadership and impetus within the Yangtze River Science and Technology Innovation Belt. Nanjing, Suzhou, Wuxi, Hangzhou, Ningbo, and Hefei in the lower reaches; Changsha and Nanchang in the middle reaches; and Mianyang, Guiyang, and Kunming in the upper reaches—totaling 11 cities—should be designated as the technological innovation pivot cities of the Yangtze River Economic Belt. These cities serve as core nodes facilitating the spillover effects of international and national technological innovation activities, thereby supporting the comprehensive development of innovation throughout the Yangtze River Economic Belt.
The paper proposes the following policy recommendations to enhance regional scientific and technological innovation. First, it is necessary to establish a hierarchical and diversified regional scientific and technological innovation collaboration mechanism to foster more inclusive and effective partnerships among different regions. Second, the government should promote the transfer, transformation, and application demonstration of technology to accelerate the commercialization process and enhance the societal impact of scientific breakthroughs. Third, in order to strengthen regional platform construction, the government should provide shared resources and infrastructure that support innovation activities across the regions. Fourth, institutions need to deepen reforms and mechanisms to create a more conducive environment for innovation, and policymakers should focus on optimizing the allocation of innovation resources.

In recent years, some leading companies in China have been dedicated to building a domestic digital innovation ecosystem, striving to overcome the risks of decoupling and disconnection. Although they have made a series of breakthroughs in key technologies, they still face significant challenges in building an independent and leading digital innovation ecosystem. There are considerable gaps in technology strength, market space, and rules and standards compared with the powerful digital innovation ecosystems represented by international technology giants such as NVIDIA, Google, and Microsoft. These leading companies are at the core of the digital innovation ecosystem, and their growth process is closely related to the development of the digital innovation ecosystem. By focusing on international technology giants, exploring and revealing the formation process and micro-mechanisms of their digital innovation ecosystem leaders, it is of great significance for developing and strengthening domestic digital enterprises and building a domestic digital innovation ecosystem.
The existing literature has systematically analyzed various roles in the ecosystem, including those of leaders (or coordinators) and complementors. Despite significant progress in related research, most of these studies assume that the role of ecosystem leaders remains unchanged. In reality, most digital innovation ecosystem leaders undergo complex growth processes before becoming core leaders. However, there is still a lack of theoretical elucidation on the formation process and micro-mechanisms of ecosystem leaders.
Given the above theoretical background and practical context, this paper explores the role formation process and micro-mechanisms of digital innovation ecosystem leaders from a co-evolution perspective. The aim of this paper is to address three key questions: How can digital enterprises become digital innovation ecosystem leaders? How do collaborative mechanisms for architecture design and context-driven innovation drive organizational role transitions? What are the insights for building a domestically led digital innovation ecosystem for Chinese digital enterprises facing ecological construction challenges? Specifically, using NVIDIA as a case study, this paper summarizes and refines general rules for the formation of the digital innovation ecosystem leader role according to its 1993-2023 development history in the digital innovation ecosystem, and further analyzes the collaborative mechanisms for architecture design and scenario-driven innovation.
Firstly, the paper conducts theoretical analysis based on longitudinal case studies. Secondly, it integrates patent technology network analysis into the case study, using quantitative analysis to support the findings of the case study to ensure the rigor and scientificity of the research. Thirdly, the paper incorporates event analysis into the case study approach by conducting a detailed analysis of the development process of the case object to identify 125 key events. It is found that (1) in the following and catching-up stage, through organizational focus strategy and the introduction of self-developed chip architecture designs, NVIDIA deepened external cooperation and linked with industry giants to support the enterprise to become an industry explorer; (2) in the catching-up and surpassing stage, it focused on the forward-looking layout of the industry and tested the potential market to realize the role transition towards the leader of the industry chain through organizational expansion strategy and the open architecture design of the general industry structure; (3) in the leading stage, it has been striving to meet the demands of ecosystem partners and autonomously defines markets through the organizational ecological strategy and ecological architecture design for AI so as to support the enterprise to become leader in the digital innovation ecosystem.
The digital innovation ecosystem centered around ecosystem leaders is accelerating its formation and forming competitive barriers, but existing research has not thoroughly explored the process and mechanism of how leaders emerge in the digital innovation ecosystem. This paper proposes a co-evolution model of "environmental perception-system transformation-role transition" to explore how NVIDIA, from 1993 to 2023, progressed from an explorer in the chip market, surpassed competitors to become an industry leader, and ultimately transformed into a leader in the digital innovation ecosystem, guiding both technological advancements and market trends. This study deepens the theoretical research on the role formation of the digital innovation ecosystem, and provides implications for promoting the construction of a domestic-led digital innovation ecosystem.

An innovation ecosystem (IE) is the evolving set of actors, activities, and artifacts, along with the institutions as well as complementary and dependency relations. Artificial intelligence (AI) is increasingly adopted by organizations for innovation,giving rise to platform-based innovation ecosystems for collaborative innovation and value co-creation. However, most research has focused on the co-evolution of platform architecture and platform governance and the role of boundary resources provided by the platform owner, while heterogeneous artifacts provided by complementors are rarely explored. Specifically, the industrial and managerial literature still lacks information about how heterogeneous artifacts can foster collaborative innovation in the AI innovation ecosystem.
Thus, this paper presents a framework for the collaborative innovation process of technological complementarity by using a comprehensive research model to examine the impact of collaboration in the AI innovation ecosystem. The conceptual framework termed “elements-process-performance” from the perspective of complex system, captures the intrinsic mechanisms of collaborative innovation between platform owners and complementors. The elements of innovation refer to the technological components within the ecosystem, comprising both core components and complementary technologies. The process of innovation encompasses the way complementors integrate these technologies to foster innovation. The innovation performance assesses how the empowerment of core technical components affects collaborative innovation performance.
After reviewing the relevance of studying the innovation system, the study proposes a bipartite network (BN) model to describe the relationships between complementors and technology components based on real-world data from “Baidu Brain” which is an AI open platform in China; then through analyzing the properties of the projected network of the bipartite network, it quantifies the structural features of component interdependency at the node-level, group-level, and whole network-level; the process of innovation is modeled as a bounded, iterative, trial-and-error search over a complex landscape using an NK model, and several simulation experiments are conducted to observe the complex relationship patterns between innovation performance and components' interdependency; finally the study manages to predict the ecosystem innovation performance based on empirically observed patterns from the Baidu Brain ecosystem.
The analysis reveals that complementary component strategies can affect collaborative innovation in ecosystems in four ways: (1) the level of technological interdependence formed by embedding complementary components into the ecosystem through component strategies has a negative impact on the potential for collaborative innovation; (2) the higher the proportion of core components in the system (C-Ratio), the lower the performance of collaborative innovation; (3) it hampers collaborative performance by raising the ratio of core components above a threshold, indicating over-reliance on the platform's core elements without enough complementary components impedes synergy;(4) an inverted U-shaped relationship exists between component interdependency E-I index and innovation performance. These important findings further emphasize that collaboration among different actors in the ecosystem plays a critical role in achieving higher innovation outcomes.
The findings provide insights for management innovation in platform enterprises. Platform enterprises as ecosystem builders and leaders, should effectively manage complementary innovation. As a coordinator, it is necessary to pay attention to the network pattern among collaborative innovation entities and effectively manage and coordinate the actions of internal complementarity through institutional design. In addition, platform enterprises also need to pay attention to the management and coordination of modular components. When the E-I Index of a partition of the complementary dependency network deviates from the optimal level, adjustments can be made by enhancing the standardization and flexibility of core components, encouraging participation from complementary enterprises, increasing the diversity of complementary components, reducing the proportion of core components, and modifying the complementarity of technical components.
This study focuses on how platform enterprises manage and coordinate with complementor enterprises. Given the complexity of technology dependence, integrated application of innovation ecosystems and collaboration innovative theory, it utilizes data-driven and simulation modeling methods to explore the complex relationship logic between technological dependence and collaborative innovation. This paper advances the understanding of the intersection of innovation and AI and provides suggestions for complementary innovation and the ecosystem development.

Big data-driven firm-user interactive innovation has become an essential model for firms. The open innovation community (hereinafter referred to as OIC), as the carrier of firm-user interaction, is favored by firms. Compared with other online communities that focus on knowledge sharing, user innovation behavior is substantial in the OIC that emphasizes the mission of innovation. In OIC, users′ innovation behavior with various knowledge can help firms gain access to a plethora of external knowledge and innovative capabilities. Fostering user innovation behavior remains at the nexus of both societal and scholarly attention.
Most of the present studies have focused solely on users′ individual needs and desires for the community, disregarding the unique nature of the non-employment relationship between users and communities. Besides, current factors are insufficient in explaining users′ voluntary innovation behavior driven by passion and idealism. The ideology-infused psychological contract offers a suitable research perspective. As a type of psychological contract, it demonstrates a reciprocal relationship between the user and the community based on a shared philosophy, and ideology. Further, ideology-infused psychological contracts are considered a prominent aspect of the volunteer literature, so it is plausible to posit that ideology-infused psychological contracts could serve as a potential framework for understanding user voluntary innovation behavior. Therefore, this paper intends to discuss the influence of ideology-infused psychological contract on user innovation behavior in the context of OIC. In addition, community incentives are an important situational factor to explore user innovative behavior, but their impact on specific types of users still needs to be delved. This study further explores the moderating impact of community material incentives, social incentives and activity incentives on the relationship between ideological psychological contract and user innovation behavior.
By drawing on the self-determination theory, the theoretical framework of this paper is constructed. According to this theory, users who have their psychological needs for competence, autonomy, and relatedness satisfied are more likely to have stronger autonomous motivation, leading to more innovation behavior. Additionally, this theory also suggests that extrinsic incentives can impact innovative behavior driven by autonomous motivation, which explains the moderating effects of community incentives. An empirical analysis of 385 questionnaires from the Haier community, MIUI, Huawei consume and Dajiang community by SPSS 23.0 and AMOS 24.0 statistical analysis software is conducted in the study. The research results show that the ideology-infused psychological contract has a significant positive impact on user innovation behavior; the negative moderating effect of material incentives is not significant; and social incentives and activity incentives play a significant positive moderating role in the relationship between ideology-infused psychological contract and user innovation behavior.
This study has three theoretical contributions. First, it enriches the research on the psychological contract and extends the application background of psychological contract from organizations to OIC. Second, by exploring the impact of ideology-infused psychological contract on user innovation behavior, the study reveals the ideological factors affecting user innovation behavior, that is, the belief of striving for the lofty mission of the community. The findings complement the lack of existing research on the role of reciprocal relationships between communities and users in user innovation behavior and provides new theoretical perspectives and directions for exploring the drivers of user innovation behavior. Third, the study tests the moderating effect of different incentive factors on the relationship between ideology-infused psychological contract and user innovative behavior, which helps to fully understand the role of community incentives.
In practice, this paper provides three management recommendations. First of all, the community should prioritize user relationship management and foster the development and nurturing of ideology-infused psychological contracts. Second, the community needs to formulate appropriate material incentive measures to realize the promotion effect of material incentive on the innovation behavior of users who hold ideology-infused psychological contracts. Finally, setting more social rewards and activity rewards is crucial for the community. These incentives will bolster users trust in the community and cultivate a greater sense of competence, thereby fostering increased user innovation behavior. In summary, this paper provides reference for enterprises to stimulate users' innovative behavior and formulate effective incentive measures.

In the context of digital China, how to build a strong industrial internet platform to promote the development of new quality productive forces is particularly important. As the product of the deep integration of digitalization and industrialization under the new industrial revolution, the industrial internet platform can realize the ubiquitous connection, flexible supply, and intelligent decision-making of manufacturing resources and is a strategic infrastructure to accelerate the formation of new quality productive forces. At present, how to build an effective industrial internet platform architecture to bridge the gap in the use of data elements and promote the development of new quality productive forces is a key problem to be solved.
This study selects 278 cities in China as research samples, and employs a mixed-methods approach, integrating qualitative comparative analysis with regression analysis, to develop a sophisticated mediation model. This methodology is designed to provide a comprehensive view of the intricate interactions among variables. The study combines the relationship between configuration perspective and complexity, and uses mixed QCA and spatial regression analysis methods to analyze how the industrial internet platform drives the development of new quality productive forces from the perspective of data elements in a more granular manner. The results show that (1) the configuration analysis shows that all industrial internet platforms fully release the value of data elements in the way of "different paths lead to the same goal". Specifically, there are six paths for data element application, which can be classified into three modes: cloud service-core platform-driven, edge computing-driven, and edge-cloud service-core platform-driven. There is only one path for data element maintenance, which is platform driven. While there are four paths for the aggregation of digital talents, which can be classified into three modes: edge-big data platform-driven, distributed platform-driven under non-high cloud services, and distributed platform-driven under non-high data. (2) The complex intermediary mechanism shows that the four configurations of cloud service-core platform-driven, full platform-driven, and edge-big data platform-driven fully unleash the value of data elements, thereby driving the development of new quality productive forces. However, due to some incomplete architectures, while improving data elements, there are still difficulties in enterprise cloud migration, inflexible platform architecture, and low data utilization efficiency, which is insufficient to achieve a qualitative enhancement in productivity.
The article's marginal contributions are threefold. First, it pioneers a shift in focus from viewing industrial internet platforms as monolithic entities to recognizing them as collaborative ecosystems of sub-platforms, driving the evolution of new quality productive forces. This approach significantly diverges from traditional research, thereby broadening the scope and application range of digital platform studies. Second, it innovatively introduces the perspective of data elements, combines the relationship between configuration ideas and complexity, and reveals the complex relationship between the configuration of industrial internet platform and the development of new quality productive forces in a more granular way, which has important practical significance for the development of new quality productive forces in China under the complex system view. Third, this study develops a hybrid method of QCA and spatial regression analysis, providing new ideas and methods for analyzing complex mediation problems and expanding the statistical applications of complex mediation models in digital contexts.
The management implications are as follows:First, from the perspective of complex systems, it is necessary to grasp the "diversity of platforms" and "concentration of combinations" to avoid the development dilemma of constructing a single platform. Second, it is imperative to expedite the ongoing cycle of data element accumulation, application, maintenance, and development. This proactive management of data elements will empower industrial internet platforms and their applications to extend their reach into a broader range of industries and domains. Third, it is essential to adhere to the concept of the system, focus on the grand strategy of "digital China" ,and advance the convergence and integration of policies related to industrial Internet, digital transformation and the development of new quality productive forces.

In the era of "New Normal" with VUCA characteristics,how to enhance resilience has become the key for enterprises to avoid dangers and shift into safety and achieve sustainable development. As a strategic choice for knowledge expansion, technological diversification is beneficial for enterprises to diversify external risks, improve their perception and adaptability to the environment and then achieve resilient growth. Although existing research pays attention to the effect of technological diversification on enterprise resilience, the "bridge" between the two needs to be further explored. Continuous innovation related to operational efficiency and strategic flexibility is an important ability to achieve continuous development. According to the theoretical logic of "resource-capability-result", continuous innovation drives enterprises to change their mindset, continuously breaking through development bottlenecks and exploring new growth paths through the integration of diversified technologies. Therefore, continuous innovation may play a mediating role between technological diversification and enterprise resilience. In addition, the results of technological diversification depend on the combination of internal technological exploration and external technological relationships, making enterprises embedded in dual network relationships. In particular, the density of internal collaboration network characterizes the close relationship between internal inventors, which directly affects the effective transfer of diversified technological knowledge and information sharing; the heterogeneous resource advantages brought by the high degree of external collaboration network centrality can effectively alleviate the dilemma of knowledge homogenization in high-density internal cooperative networks, and then accelerate the process of diversified technological development and integration. However, existing research has not focused on the boundary effects of dual networks on the relationship between technological diversification and continuous innovation. Hence, this study aims to explore the internal mechanism between technological diversification and enterprise resilience, and investigate the boundary effect of internal collaboration network density and the three-way moderating effect of external collaboration network centrality from the perspective of dual network.
Following the resource-based theory and the theoretical logic of "resource-capability-result", this study conducts the empirical analysis using a sample of Shanghai and Shenzhen A-share listed enterprises in the new energy automobile industry. The resilience and control variables information of these enterprises is collected from CSMAR and patent data is collected from Incopat. Finally, an unbalanced panel dataset of 285 enterprises from 2010 to 2021 is constructed. The hypotheses are tested by the individual and time-fixed effect models using Stata 15.0.
The results show that (1) there is an inverted U-shaped relationship between technological diversification and enterprise resilience; (2) continuous innovation plays the mediating role in the inverted U-shaped relationship between technological diversity and enterprise resilience; (3) internal collaboration network density negatively moderates the relationship between technological diversification and continuous innovation; (4) external collaboration network centrality further mitigates the negative impact of internal collaboration network density on the relationship between overall technological diversification, unrelated technological diversification, and continuous innovation.
The theoretical contributions of the study are as follows: firstly,it clarifies the relationship between technological diversification and enterprise resilience in the context of a long-term and turbulent environment, and expands the theoretical space of technological diversification and enterprise resilience; secondly,the paper provides empirical evidence for the effect of continuous innovation on enterprise resilience and bridges the gap in the discussion of mechanisms underlying technological diversification and enterprise resilience; finally, from the perspective of dual network,it reveals the boundary effects of dual networks in the relationship between technological diversification and continuous innovation, and deepens the contextual mechanism for the transformation of technological diversification into continuous innovation. The practical contributions are proposed. Enterprises should first cultivate internal skills and moderately expand diversified technology fields based on risk assessment. Then it is necessary to seek change proactively. Enterprises should cultivate continuous innovation ability to leverage the positive effects of technological diversification on enterprise resilience. Finally, enterprise should pay attention to collaboration,encourage inventors to "go out", maintain loose partnerships internally and build a wide collaborative R&D network externally.

In the present fast-paced business world with high uncertainties, open innovation has become an indispensable strategy for firms seeking more heterogeneous information and staying competitive and thriving. However, there is still a critical need for a robust theoretical framework that can accurately predict and explain the realization of open innovation performance, and enlighten firms on how to cooperate and deal with internal and external knowledge partnerships in an open situation. The theory of HeXie (harmonious) management emerges as a promising avenue to address this need, especially the He principle and the two fields offer a conceptual lens that aligns with the complex demands of open innovation systems and provides insights into how firms can unlock their intrinsic value through open innovation initiatives. The purpose of this study is to delve into the mechanisms that underlie the realization of open innovation performance in high-tech manufacturing firms, utilizing the He principle as a guiding framework.
According to the He principle, the research constructs a comprehensive framework to explore the multifaceted pathways to open innovation performance in firms, and figure out how innovation openness exerts a positive influence on open innovation performance under the dual moderation of inclusive organizational culture and intellectual property protection. Empirical tests are made with the panel data from 662 high-tech manufacturing A-share listed firms spanning the period from 2012 to 2021 in China to validate the theoretical framework. Then, the model of fixed panel effects is built for data analysis: the study first examines the direct effect of innovation openness on financial and market performance, and then respectively analyzes the moderating effects of inclusive organizational culture and intellectual property protection policies; finally, it makes robustness analysis and heterogeneity analysis.
　The findings support the fact that the depth and breadth of innovation openness have a significant positive impact on firms' financial performance. However, it's noteworthy that the breadth of innovation openness does not exert a significant influence on firms' market performance, while the depth of innovation openness has a significant negative effect on market performance. This distinction between financial and market performance underscores the nuanced nature of open innovation outcomes. The study also reveals that the presence of an inclusive organizational culture strengthens the positive relationship between the depth of innovation openness and firms' financial performance. This finding underscores the importance of nurturing a work environment where diverse perspectives are valued and integrated into the innovation process. Lastly, it uncovers that the impact of the breadth of innovation openness on firms' financial performance is significantly enhanced in regions with well-developed intellectual property protection policies. This suggests that the interplay between openness and intellectual property protection can be leveraged to optimize financial performance outcomes. What's more, compared with the breadth of innovation openness, inclusive culture has a more significant moderating effect on the depth of innovation openness on financial performance; compared with the depth of innovation openness, the moderating effect of intellectual property policy on the breadth of innovation openness is more significant on financial performance. Intriguingly, the study further explores heterogeneity in the relationship between innovation openness and firms performance and finds that non-state-owned firms and those led by managers with overseas backgrounds experience a more pronounced impact of innovation openness on their performance. This nuanced insight emphasizes the importance of considering organizational characteristics and leadership profiles in the context of open innovation.
In conclusion, the study significantly contributes to the understanding of the pathways through which high-tech manufacturing firms realize open innovation performance. The theoretical framework of this paper is helpful to guide firms to achieve the dual pursuit of short-term and long-term goals and the balance of uniqueness and legitimacy in the context of open innovation. The conclusions provide valuable guidance for firms aiming to maximize the benefits of open innovation and adapt to the challenges in the dynamic business environment. Furthermore, it informs policymakers and practitioners about the significance of fostering inclusive organizational cultures and tailoring intellectual property protection policies to amplify the positive impacts of innovation openness.

The surge in digital technologies like big data, AI, and cloud computing has made the digital economy a key driver for China's high-quality economic growth. As the micro subject of the market economy, enterprises carry the important function of promoting the high-quality development of the economy as well as transformation, and digital transformation has become an inevitable trend for enterprises to move into the future. As enterprises' digital transformation involves a full range of changes in the business model, process management and operation mode, digital transformation is never easy. Therefore, enterprises only rely on their own resources and capabilities are not enough to successfully complete the digital transformation, how to use external forces to break the dilemma of digital transformation and obstacles to become an important reality of common concern in the academic and practical circles. Institutional investors, due to their unique resources, information and professional advantages, are participating in corporate governance in a diversified way and influencing the strategic decisions of companies.
With the rise of social network analysis techniques, firms are interconnected rather than isolated in capital markets, and it is more common for multiple institutional investors to hold shares in the same firm. This network of interconnectedness through common shareholdings constitutes an institutional investor network. Within this network, institutional investors can form synergies and play a role at the group level. In the context of accelerated digital transformation, one question worth exploring is the role of institutional investors' network clusters in the digital transformation of enterprises. Therefore, it is worth exploring the relationship between institutional investors' network clusters and digital transformation.
Following the social network theory and attention-based view, this study adopts 2010-2022 A-share listed companies in Shanghai and Shenzhen as the research samples, and examines the direct effect and potential mechanism of network clusters on enterprises' digital transformation from the perspective of institutional investors by using the panel double fixed effect model, mediating model, and moderating model. The study finds that institutional investors' network clusters have a non-linear effect on corporate digital transformation, showing a U-shaped trend of change. The moderating effect analysis shows that the centrality of institutional investor network strengthens this U-shaped relationship. Mechanism analysis shows that when the shareholding ratio is less than 8.5%, institutional investors' network clusters inhibit digital transformation through the "strategic collusion" effect; when the shareholding ratio is greater than 8.5%, institutional investors' network clusters promote digital transformation through the "supervisory governance" effect and "resource synergy" effect. Heterogeneity analyses show that institutional investors' network clusters exhibit different governance behaviours towards corporate digital transformation depending on the type of institutional investor group, the type of enterprise, and the information environment.
The contributions of this paper include four aspects.The study explores institutional investors' network impacts on corporate digital transformation. It first highlights the social networks of investors, enriching research on their economic outcomes and digital transformation factors. It then reveals the non-linear effects of these networks on digital governance and the dynamic scale of investors' shareholding in transformation. The paper also uncovers the "U" relationship mechanism and its dynamic patterns, providing insights into the mechanism of institutional investors' network clusters on digital transformation, and the dynamic behavioural pattern of institutional investors' network clusters on digital transformation. It further examines the boundary conditions under which institutional investors' network clusters affect digital transformation, deepen the understanding of institutional investors' network clusters as a mode of equity governance, and expand the breadth and depth of academic research.
This study offers tailored recommendations that, at the listed company level, companies should acknowledge institutional investors' network power; at the institutional investor level, it is necessary to make full use of the resources in the investment network, focus on the close relationship with other institutional investors in the network, and choose structural holes with location advantages to embed in the network and improve the influence; at the government level, it is important to encourage more institutional investors to participate in the market by means of preferential policies and simplified procedures to increase their number and scale of investment, so as to enhance market vitality and efficiency.

With the rapid advancement of science and technology, the world has entered the era of big science, where the scale, complexity, and influence of research activities have expanded, making research integrity a key issue. Ensuring research integrity is not only about regulating researchers' behavior but also about balancing scientific freedom with public interest. The effectiveness of the external governance system for research integrity plays a crucial role in maintaining the health of the research ecosystem and the sustainable development of science. However, the current governance system shows a clear fragmentation in practice, posing significant challenges to improving research integrity.
Drawing on holistic governance theory, the study conducts the systems analysis and employs interdisciplinary methods, to deeply analyze the shortcomings of the current governance system. First, in terms of concept, the definition and scope of research integrity lack clarity and consistency, leading to differing interpretations among governance bodies. Issues like illegal gene editing and helicopter science are not fully covered, resulting in incomplete governance of research misconduct. Second, the liability system is unclear, with an over-reliance on civil and administrative remedies. Civil penalties lack deterrence, while administrative measures, though central, often fall short in addressing serious misconduct. Lastly, governance tools are fragmented and homogenized, leading to repetitive sanctions, increasing costs, and reducing flexibility. Furthermore, current governance focuses too much on post-incident punishment, lacking preventive measures and innovation.
This study argues for the need and feasibility of reconstructing the external governance system. First, the research community's self-regulation is weak, requiring a governance system that combines external oversight with internal self-regulation. Second, given the significant public interest in research outcomes, research integrity should be viewed not just as an internal issue but as one that affects broader public interest. Finally, the challenges in policy implementation necessitate applying holistic governance theory to research integrity. Traditional administrative control models struggle to address the complexities of modern research, and holistic governance offers new solutions.
Consequently, three key shifts for reforming the governance system are proposed. First, governance objects should be redefined using a unified approach that integrates horizontal two-dimensionality and vertical four-dimensionality. Horizontal identification should be based on the criteria of "deviation from norms as the core connotation" and "adverse outcomes as the essential extension",while vertical identification should focus on "integrity of research, reliability of results, respect for ethics, and primacy of responsibility". Integrity in research underscores that adherence to scientific norms should be the cornerstone of scholarly endeavors, transcending the mere focus on individual integrity. Reliability of results highlights the importance of ensuring the safety and validity of research outcomes. This principle rejects the 'results-at-all-costs' mentality and acknowledges the inherent uncertainty and unpredictability of scientific research within the modern risk landscape. Respect for ethics places the ethical considerations of science and technology at the forefront, aiming to minimize the risk of dehumanization in research. While the primacy of responsibility emphasizes the convergence of external accountability with an internal sense of duty, for scientists are both answerable to the public and committed to their professional responsibilities, thereby jointly mitigating the risks associated with scientific research conduct. Second, a triple responsibility system is proposed, layering the framework for research misconduct based on “scientific norms, civil contracts, and significant legal interests”, thereby integrating governance with the rule of law. Lastly, governance mechanisms should shift from punishment to a balance between prevention and discipline, using education and preventive measures as core objectives. Leveraging big data, AI, and blockchain can modernize governance and improve efficiency.
This study promotes the transformation of the external governance system of research integrity from a traditional administrative control model to a more synergistic and diversified governance model by introducing holistic governance theory. Through these transformations, the governance capacity of the research integrity system will be significantly enhanced, providing strong support for the healthy development of the research ecosystem and the sustainable advancement of scientific research.