Data elements are strategic and fundamental resources for China's development and serve as a powerful driving force for the digital economy's growth. As a new type of production factor, the data element is unique because it represents an advanced productive force-new productive force. Data elements are of fundamental significance for realizing data value, digital industrialization, and digitalization of governance, and have the characteristics of high transformability, high innovativeness, and high integrability. The exploration of the linkage path to achieve the marketized high-level development of data elements significantly improves new-quality productive forces.
At present, China is in the initial exploration stage in promoting the marketization of data factors. At this stage, research predominantly begins with theoretical analysis, often focusing on a single factor. There is a need for more detailed, stage-by-stage identification of the complex causal relationships and the diverse concurrent paths involved in the marketization of data elements. Regarding research methods, few scholars use fuzzy qualitative comparison to analyze the configuration effect of market-oriented development of data elements, and few works of literature use artificial neural network models to analyze their relative importance. In addition, most existing studies construct an index system from a single stage or link of data element marketization and measure its development level, failing to consider the entire stage of data element marketization development and the identification of related variables. In different stages of data factor marketization allocation, are there core and necessary conditions for the realization of high-level development of data factor marketization? Which paths can be combined to improve the level of data factor marketization? What is the relative importance of each path? These questions still need to be further explored.
Utilizing the theoretical framework of the Technology-Organization-Environment (TOE) strategy typology, this study examines 30 provinces in China as case studies spanning from 2020 to 2022. It applies a fsQCA-NCA-ANN methodology to discover the multiple linkage paths of China's data element marketization and high-level development from the two phases of data element marketization construction and valorization-allocation, as well as the three levels of technological strategy, organizational resources, and external environment based on the grouping perspective.
The conclusions and practical implications are presented. First, more than the technical strategy, organizational resources, and external environment of the two stages must constitute the conditions for the high-level market-oriented development of data elements. Therefore, the high-level development of China's data element marketization results from the synergistic and supporting effects of various antecedents in the two stages. Second, the high-level development of data element marketization is formed by the joint action of multiple factors, and there are two realization paths in the stage of data element marketization construction, i.e., technology-organization-market diversified infrastructure-driven and technology-government-market diversified competition-driven.There are four realization paths in the data element valorization-allocation process, i.e., technology-policy binary endowment-driven, technology-industry binary openness-driven, technology-government-industry multiple openness driven, and technology-organization-environmental balance driven. These paths reflect the various ways in which the high-level development of the marketization of data elements can be achieved across different provinces and under varying development conditions. Configuration analysis reveals a variety of realization paths to achieve high-level development in the two stages of market-oriented construction and value-oriented allocation of data elements. The diversity of these paths reflects the complexity of the two stages. Each province should flexibly choose the appropriate implementation path according to the specific situation to achieve the high-level development of marketization of data elements. Finally, the relative importance of each antecedent condition in the two stages is ranked by ANN sensitivity analysis. In the stage of market-oriented construction, infrastructure maturity is the most influential antecedent condition. In areas with relatively complete information infrastructure construction, paths and combinations such as organizational soundness, government support, and significant data market demand can realize the high-level development of data element marketization. The information commercialization level is the most critical antecedent condition in the value allocation stage. Strengthening the construction of new information facilities and improving the level of information commercialization are still the top priorities at this stage. The balanced development of technology strategy, organizational resources, and external environment can achieve a higher level of marketization of data elements. Therefore, the antecedent conditions of the technological strategy dimension contribute more to the high-level marketization development of data elements.

The innovation ecosystem thrives on collaboration, where dominant firms merge offerings from various partners to create comprehensive customer solutions. This synergy is crucial for value co-creation, yet the dynamics of interdependence among ecosystem actors and the conditions fostering this value are not fully understood. This study, grounded in resource dependence and value co-creation theories, explores the effect of actors' interdependence on value co-creation in innovation ecosystems. Actors' dependence is defined as the extent to which dominant firms and their partners need each other's help to achieve their goals. Actors' dependence is composed of asymmetric dependence and joint dependence. Asymmetric dependence refers to the asymmetrical degree of resource dependence between partner firms and dominant firms, while joint dependence refers to the mutual need for each other's strategic resources. Partner firms' cooperative orientation is defined as the tendency of partner firms to establish mutually beneficial relationships with dominant firms. Dominant firms' governance is characterized by two dimensions: contractual governance and relational governance.Contractual governance emphasizes authority and enforceability, while relational governance emphasizes establishing mutually beneficial and symbiotic cooperative relationships between partner firms and dominant firms.
Drawing on resource dependence theory and value co-creation theory, the study constructs a conceptual framework with actors' dependence as the independent variable, value co-creation in innovation ecosystems as the dependent variable, partner firms' cooperative orientation as the mediator, and dominant firms' governance as the moderator. The scales for the aforementioned variables are mature and widely accepted. Data is collected from a questionnaire survey. The sample companies are chosen from four industries (i.e., electronic information, biopharmaceuticals, new materials, and automobiles) in the Yangtze River Delta region. The screening criteria ensure that the sample companies are suppliers and complementors within dominant firms′ innovation ecosystems. A total of 399 valid questionnaires were emailed to 650 companies across four industries in the Yangtze River Delta region. The sample companies encompass a diverse range of sizes, establishment durations, ownership types, and industry characteristics, demonstrating a high level of representativeness in the study's sample. Multiple stepwise regression analysis was used to verify the hypotheses.
The results show that (1) asymmetric dependence negatively affects value co-creation in the innovation ecosystem, while joint dependence positively affects value co-creation in the innovation ecosystem; (2) partner firms' cooperative orientation mediates the relationship between asymmetric dependence and value co-creation in the innovation ecosystem, as well as the relationship between joint dependence and value co-creation in the innovation ecosystem; (3) the mediating effect of asymmetric dependence on value co-creation in the innovation ecosystem via partner firms' cooperative orientation is negatively moderated by dominant firms' contractual governance, while dominant firms' relational governance does not play a moderating role in this mediating effect; the mediating effect of joint dependence on value co-creation in the innovation ecosystem via partner firms' cooperative orientation is positively moderated by both dominant firms' contractual governance and relational governance.
Thus, dominant firms within innovation ecosystems should bolster their incentives for partner firms that face resource disadvantages. They should also work to strengthen the cooperative orientation of their partners. Tailored governance mechanisms should be applied to different partners, i.e., they should employ contracts to clearly define in cases of significant power imbalance between themselves and their partner firms, or leverage relational governance to foster cooperation for partners with high levels of interdependence.
Through the lens of resource dependency theory,this study contributes to the understanding of environmental adaptation dynamics and boundaries. It examines the innovation ecosystem, focusing on how partner firms' cooperative orientation acts as a mediator in value co-creation, negatively affecting asymmetric dependence and positively affecting joint dependence. Furthermore, the study regards the dominant firms' contractual governance and relational governance as moderating variables and their distinct moderating effects on how the cooperative orientation of partner firms influences value co-creation within the innovation ecosystem, mediated through the interdependencies among the various actors involved. By doing so, it explains how interdependence influences value co-creation and the conditions under which this occurs. The research further enriches the literature on value co-creation antecedents, emphasizing partner firms' roles and offering a fresh perspective on how interdependence with dominant firms affects value co-creation, thus providing direction for enhancing value co-creation in innovative ecosystems.

In order to promote economic development and achieve the goals of carbon peak and carbon neutrality, it is urgent to develop a low-carbon economy. The diffusion of low-carbon technology innovation (LCTI) in the whole society, especially in enterprise organizations, is an important way to promote the development of low-carbon economy. While the rapid development of digital technologies has prompted innovation systems to evolve into platform ecosystems for innovation and technology diffusion,the emergence of a new organizational pattern has changed the context of LCTI diffusion. Platform ecosystem is an organizational form in which platform enterprises use digital technologies and standards to design platform architecture and interface rules to attract complementors and users to jointly provide products and services for users. On the one hand, it connects multiple subjects, aggregates extensive and scattered resources, and interacts with users to accurately match their needs, thus reducing the search and transaction costs of enterprises and users. On the other hand, the layered modular technology architecture of the platform ecosystem allows enterprises to refine, reorganize and integrate the LCTI modules of the platform into their own products, enabling them to innovate low-carbon products independently, flexibly and at low cost. In practice, platform ecosystems change the diffusion process of traditional LCTI by reshaping the ways of information interaction, knowledge learning, technological innovation and value co-creation among enterprises. Platform technology architecture makes LCTI diffusion show new characteristics, such as networking and collaboration. Although platform ecosystems have a significant impact on the diffusion process of LCTI, the underlying mechanism is still unknown. Therefore, it is urgent to explore how platform enterprises design and optimize technology architecture to give full play to the advantages of platform ecosystems to promote LCTI diffusion.
Existing literature mainly analyzes the influence mechanism of environmental regulations, such as government subsidies, carbon tax, and carbon trading, and consumers′ characteristics, such as low-carbon preferences, environmental awareness, and perception disparity, on LCTI diffusion based on traditional organizational networks. Few studies have considered the changing organizational form, especially the emergence of platform ecosystems. It is insufficient to guide LCTI diffusion activities in the platform ecosystem. Therefore, following innovation diffusion theory, this paper explores the influence mechanism and action path of platform technology architecture on LCTI diffusion with the lens of the AMC model, and it clarifies the action mechanism of policy and institutional and social and cultural environment. Using data from a sample of 280 manufacturing enterprises in China, this study uses regression analysis to examine these hypotheses.
The results suggest that the relationships between LCTI diffusion and platform technology architecture (i.e., the modules′ synergistic specificity, the conformability of the platform interface, and platform openness) are inverted U-shaped. Information awareness, adoption motivation and application capability play partial mediating roles in the relationships between LCTI diffusion and platform technology architecture. The policy and institutional environment positively moderate the relationship between adoption motivation, application capacity and the diffusion of low-carbon technology innovation, respectively. The social and cultural environment positively moderate the relationship between information awareness, application ability and low-carbon technology innovation diffusion, separately. The moderating effect of social and cultural environment on the relationship between adoption motivation and low-carbon technology innovation diffusion is not significant.
This paper extends the applicability of innovation diffusion theory in the context of platform ecosystem and provides new insights for theoretical research on LCTI diffusion. First, it unravels the influence mechanism of platform technology architecture on LCTI diffusion, which expands the relevant research on platform ecosystem and provides an important theoretical basis for a better understanding of innovation diffusion in platform ecosystem. Second, it reveals the mediating role of the behavioral attributes of complementary enterprises from a microscopic perspective, which enriches the theoretical results of LCTI diffusion. It is very important to further study the macrodiffusion law of LCTI. Third, it clarifies the mechanism of policy and institutional environment,as well as social and cultural environment,as boundary conditions, which emphasizes the importance of social and cultural environment in the diffusion process of LCTI.

In the face of the pressing need for high-quality growth domestically and the increasingly unstable and complex global environment, China must take the lead in innovation and accelerate the creation of new high-quality productive forces. As an effective model for fostering innovation and development, industry-university-research (IUR) cooperation has gained widespread recognition and prominence in driving innovation-driven development. However, in practice, IUR cooperation still confronts numerous challenges. Among these, uncertainty and opportunistic behaviors generate significant risks, while inequitable benefit distribution, ambiguous intellectual property rights, and poor coordination remain the core obstacles to the effectiveness of cooperation. Clearly, there are risks and opportunities in IUR cooperation, and the openness paradox causes a significant divide in the docking process between Chinese firms and academic institutions. As a result, figuring out how to encourage the deep integration of IUR and investigate the novel avenue of collaborative innovation development has become essential.
IUR cooperation is introducing previously unexplored development potential, driven by the digital era. Blockchain is widely acknowledged as a significant disruptive force in contemporary industry, with its characteristics of decentralization, security, and transparency continually expanding its application areas. With the help of data trust (digital signatures, timestamps), result trust (smart contracts, formula algorithms), and historical trust (chain structure, timestamps), blockchain can quickly and cheaply establish trust while giving multiple subjects a strong foundation for collaborative innovation. Then, can enterprise blockchain applications enhance their IUR cooperation from the standpoint of the open paradox? If it can, what mechanisms does it specifically affect? The majority of existing literature remains at the theoretical level of analysis, lacking empirical validation.Against this backdrop, the study selects the Shanghai and Shenzhen A-share listed companies from the manufacturing sector in China as a research sample for 2016 to 2022, and examines the effect of enterprise blockchain applications on their IUR cooperation and its mechanism from the open paradox standpoint.
The findings suggest that enterprise blockchain applications can promote their IUR cooperation, which still holds after various robustness treatments, and the promotion effect is particularly substantial in large, state-owned enterprises and declining enterprises. According to the mechanism test, enterprise blockchain applications mainly promote their IUR cooperation through the trust enhancement effect. Further analysis reveals that enterprise blockchain applications can not only build the trust mechanism in the stranger relationship network, but also realize the "double reinforcement" of emotional trust and digital trust in the acquaintance relationship network, thus strongly promoting IUR cooperation. In addition, absorptive capacity enhances the relationship between enterprise blockchain applications and their IUR cooperation, and this moderating effect is partially realized through the trust enhancement effect. Specifically, absorptive capacity not only directly moderates the relationship between enterprise blockchain applications and their IUR cooperation, but also indirectly moderates the total effect by moderating the pre- and post-radius of the mediating effect.
This paper presents several innovations. First, it empirically investigates how enterprise blockchain applications affect their IUR cooperation from an open paradox perspective. This not only expands the scope of research on open paradox, but also provides new insights into the deep integration of technology and economy in the context of the digital era. Second, it examines the mediating function of trust between enterprise blockchain applications and their IUR cooperation from the perspective of informal institutions, carefully differentiating between the various forms of acquaintance trust and stranger trust. This not only supports the claim in the literature that blockchain can create trust mechanisms, but also further reveals the "trust-constructing" and "trust-reinforcing" effects of blockchain in the relationship networks of strangers and acquaintances, respectively. Third, drawing on the dynamic capacities theory, it further investigates the mediated moderating effect of absorptive ability between enterprise blockchain applications and their IUR cooperation. The significance of trust mechanisms is further reinforced by this investigation, which also emphasizes the critical role that absorptive capacity plays in promoting IUR cooperation.

Two-way direct investment of "bringing in"(inward investment) and "going global" (outward investment) is the carrier of the dual circulation of domestic and international markets, and the technology spillover effect of inward investment and the reverse technology spillover effect of outward investment have synergistically improved the internal structure and the traditional layout of China's industrial chain. Therefore, it helps to break through the technological bottlenecks of the key links of the industrial chain,further enhance the degree of independence and controllability of key links in the industrial chain. The Fourteenth Five-Year Plan and the 2035 Vision explicitly states the specific requirements of "guiding the key links of the industrial chain to remain in China,adhering to the equal importance of " bringing in " and "going global ",improving the industrial chain protection mechanism,and further upgrading the level of modernization of the industrial chain". Thus, the question arises of how to utilize two-way foreign direct investment (FDI) to increase the independence and controllability over key links that are bottlenecks in the industry chain becomes a core issue to promote the safety and stability of key links in the industrial chain.
From the perspective of two-way technology spillover,this paper focuses on the issue of two-way FDI to increase the independence and controllability over key links in the industrial chain bottlenecks. It uses the statistical database from 2000 to 2023 on China Economic Network, and combines input-output table and input-output extension table data for theoretical deduction and empirical testing. This study constructs the "bottleneck" industrial chain centrality (KICce) and industrial chain intermediary degree (KICme) index as the dependent variables to measure the degree of independence and controllability over key links in the industrial chain.
The study comes up with five conclusions. Firstly,two-way FDI effectively increases the independence and controllability over the key links that are bottlenecks in industrial chain,and its enhancement effect on the centrality of the industrial chain is stronger than that of the intermediary degree of the industrial chain. Secondly,two-way FDI to increase the independence and controllability of the key links in industry chain as a percentile incremental function,the intensity of the two-way technology spillovers,OFDI reverse technology spillovers and FDI technology spillover effects,decrease in descending order. Thirdly,technological innovation, as a mediating variable,assumes the role of a single mediator of multiple explanatory variables between two-way FDI and the degree of independence and controllability of the key links that are bottlenecks in the industrial chain. Fourthly, two-way FDI enhances the degree of independence and controllability of key links that are bottlenecks in the industrial chain, resulting in internal "double threshold" and external "single threshold" effects. Fifthly,there is regional,industrial and time heterogeneity of two-way FDI to increase the independence and controllability over the key links that are bottlenecks in the industrial chain.
On the basis of the empirical findings,some policy implications are obtained. Firstly,the government should make targeted measures based on specific conditions to bolster the support for two-way direct investment. Secondly,the values of high-tech talents should be stressed to enhance the national capability of original innovation and basic research. Thirdly,it is essential to give full play to the advantages of the new system of pooling national resources and strengths to achieve the organic unity of the roles of the market and the government to break through the technological bottlenecks in the key links. Fourthly,more efforts will be made to foster new quality productive forces to achieve industrial innovation and industrial chain upgradation. Therefore, China should leverage its latecomer advantage in two-way FDI, as well as the benefits of technological spillover to further increase the independence and controllability over the key links that are bottlenecks in the industrial chain.

Since the implementation of the "Made in China 2025" strategy in 2015, the size of China's manufacturing industry has grown substantially, and its overall capacities have greatly improved. China has held the title of the world's largest manufacturing nation for 13 straight years. Meanwhile, the world is undergoing the most significant changes, characterized by a cooling global economy, the emergence of new trade protectionism and deglobalization trends, increasing geopolitical conflicts, and other global economic uncertainties. China's manufacturing industry is facing a progressively complex external environment. Enhancing its manufacturing resilience is an inevitable requirement for China's manufacturing industry to resist external uncertainties, promote high-quality development of the manufacturing industry, and smoothly realize the transition from a "big manufacturing country" to a "powerful manufacturing country". Digital transformation is the process by which enterprises utilize digital technologies to enhance efficiency, improve business processes, and innovate value creation methods. It can enhance manufacturing resilience through various means, such as promoting production process reengineering, enhancing collaborative innovation capabilities, and improving resource allocation efficiency and total factor productivity. Therefore, there are significant theoretical and practical implications for exploring how digital transformation can boost the resilience of manufacturing.
There is limited research on manufacturing resilience through the lens of digital transformation.Using panel data samples from 30 provinces from 2010 to 2022, this study adopts the dynamic threshold effect model, the moderated mediation effect model and the differential GMM model to analyze the impact of digital transformation on the development resilience of the manufacturing industry. It is found that (1) from a perspective of evolution, the resilience of China's manufacturing industry has slightly declined. Although the difference in manufacturing resilience varies among provinces, it shows an overall shrinking trend. (2) The regression results of the benchmark model demonstrate that digital transformation has a significant enhancing effect on manufacturing resilience. Furthermore, this effect is not linear. There exists a dynamic threshold effect, and when the level of digital transformation meets or exceeds the threshold, its impact on manufacturing resilience will exhibit a marginal decline. (3) The results of heterogeneity test indicate that the impact of digital transformation on manufacturing resilience varies among enterprises, industries, and regions. Compared to private enterprises and small and medium-sized enterprises, digital transformation has a more significant impact on enhancing the manufacturing resilience of state-owned or large enterprises; in low threshold areas, except for textiles, there is a significant enhancing effect on the manufacturing resilience of various subsectors of the manufacturing industry, while there are differences in effects within high value areas; compared to eastern and central China and low human capital areas, digital transformation has a more significant impact on enhancing manufacturing resilience in the western region and high human capital areas in China. (4) During the process of enhancing manufacturing resilience, digital transformation has a moderated mediating effect.Technological innovation is the mediating variable, and financing constraints and external financing are the moderating variables. Simultaneously, this digital transformation has significant industry and regional homogeneity effects. Hence, China should pay more attention to enhancing manufacturing resilience, and continuously strengthening the foundation of digital transformation by vigorously promoting a "new infrastructure". To enhance targeted digital transformation and manufacturing resilience from a heterogeneous perspective and consider technological innovation and financing convenience, it is necessary to fully leverage the peer effects of digital transformation and accelerate the process of digital transformation in the manufacturing industry through a digital transformation resource sharing platform.
The marginal contribution of this article lies in three aspects. The study first adopts a single indicator method to measure manufacturing resilience, which avoids the causal inversion problem that may occur when using a multi-factor indicator system to measure manufacturing resilience. Then it analyzes the nonlinear relationship between digital transformation and manufacturing resilience based on a dynamic threshold effect model, which enriches the theoretical connotation of the relationship between digital transformation and manufacturing resilience. Lastly, it advances the understanding of the relationship between digital transformation and manufacturing resilience by clarifying the internal mechanism of the relationship between digital transformation and manufacturing resilience, and the peer effects of digital transformation on manufacturing in different industries and regions.

The accelerating growth of users′ demand for innovation challenges traditional internal R&D; thus, collaboration between firms and users becomes a prevalent form of open innovation. With the rapid development of Internet technology, it is easier for users to participate in firms′ innovation processes. In such circumstances, users are not only passive product consumers but also active value co-creators. As the Internet has emerged as a pervasive platform for users to interact with each other, online communities are becoming distinct and increasingly important user groups for many firms, and a growing number of firms have tapped into online communities to search for complementary innovation from users.
As a new type of innovative organization formed spontaneously by a large number of users who join and leave freely, the relationship between community size and new product development performance has been controversial. Scholars who hold the resource availability view believe that the time and effort of community members are the most critical resources in a community, and the larger the community, the more resources it has, which makes it more attractive to current and potential community members, increases the likelihood of promoting community members′ contribution behaviors, and then improves the new product development performance at the community level. While some other scholars believe that a large community will meat potential problems such as information overload, free riding, opportunism, loss of knowledge assets, etc., and increase the cost of communication and coordination within the community, which will reduce the motivation of community members to contribute and ultimately improve the innovation performance of the community. However, online communities are highly dependent on the continuous participation of members to create value. The success of a community depends on its ability to maintain a large enough membership pool. Therefore, understanding the relationship between online community size and new product development performance is a key challenge for firms using online communities to improve innovation performance. Moreover, the mobile and temporal nature of online communities leads to a weak relationship involving dynamic sharing members or self-organized cooperation among community participants, the whole community is thus characterized by boundary ambiguity, accompanied by problems such as serious user loss, low frequency of interaction, low degree of user participation, and high overlap of members in community operation. These issues severely limit the role of online communities in driving new product development. Hence, how to effectively manage online communities against the weak relationship and boundary ambiguity is also a realistic problem for firms looking to improve the performance of new product development by using online communities.
This study focuses on the relationship between community size and new product development performance. According to the external bridging view and internal bonding view of online communities, this paper leverages secondary data collected from the product creative workshop community on the Steam gaming platform to empirically test the impact of online community size on the new product development performance, both from the collective community and individual member perspectives. Furthermore, this paper explores the joint moderating effect of internal bonding capital and external bridging capital on the relationship between community size and new product development performance in online communities. The results suggest that online community size positively affects the collective new product development performance of community members, but negatively affects individual new product development performance. In addition, when the degree of external bridging and internal bonding of online communities is high, the positive relationship between online community size and collective new product development performance of community members is stronger, while the negative relationship between online community size and individual new product development performance of community members is weaker.
The findings provide new insights into understanding the relationship between online community size and innovation performance by discussing the effect of online community size on the relationship between members' collective and individual new product development performance separately. Moreover, the study further highlights the importance of external community ties by examining the joint moderating effect of external bridging capital and internal aggregation capital in online communities.

Digital government, as a fundamental and pioneering project in the construction of Digital China, can lead and drive the coordinated development of the digital economy, digital society, digital ecology, and digital culture, and has become an essential choice for enhancing government governance effectiveness and promoting innovation in governance models. Breakthrough innovation, as an innovative activity that can create new market value or reshape existing market patterns, often comes with a significant demand for resource investment, and its outcome conversion has a high level of uncertainty. Enhancing the performance of breakthrough innovation is crucial for fostering high-quality economic growth. Research indicates that the development of digital governance not only spurs innovation in digital governance models but also enhances the quality and efficiency of public services. It accelerates the adoption and experimentation of new technologies across various sectors of society and creates a conducive business environment for enterprises. In addition, the construction of digital government can stimulate the development of the digital economy and scientific and technological innovation, constituting the "external environment" for the development of new productive forces. As a product of the close integration of government construction and modern technology, digital government makes scientific decisions through the analysis and interpretation of data information, reduces the R&D uncertainty faced by enterprises during the breakthrough innovation process, and points out the direction for enhancing the performance of enterprises' breakthrough innovations.
This paper draws on transaction cost theory, digital governance theory, and other relevant conceptual frameworks to investigate the impact of digital government construction on the breakthrough innovation performance of enterprises. Employing a fixed effects model and the two-stage least squares method, the study analyzes a comprehensive sample of all A-share listed companies from 2015 to 2022. The research delves into the effects of digital government initiatives on corporate innovation and further examines the underlying mechanisms and moderating effects. The findings show that digital government construction has a positive impact on breakthrough innovation performance of enterprises. New quality productive forces play a mediating role between digital government construction and breakthrough innovation performance of enterprises; financing constraints and media attention positively moderate the relationship between digital government and breakthrough innovation performance of enterprises, while industry competition degree negatively moderates the relationship between digital government and breakthrough innovation performance of enterprises.
The marginal contributions of this paper mainly include the following three aspects: First, it analyzes the impact of digital government construction on the breakthrough innovation performance of enterprises in the era of the digital economy, thereby enriching the study of the economic consequences of digital government construction. Second, it explores the external driving forces of breakthrough innovation performance of enterprises from the perspective of digital government construction, providing new ideas for the research on the influencing factors of breakthrough innovation performance in enterprises. Third, it clarifies the pathways through which digital government construction enhances the breakthrough innovation performance of enterprises, and investigates whether digital government construction can improve the breakthrough innovation performance of enterprises by enhancing new quality productive forces.
The research conclusions of this paper focus on the following three aspects: First, to promote the construction of a high-quality digital government and create a digital ecological environment, relevant government departments should continuously advance the work of building a digital government, and grounded on the construction of digital infrastructure, they should harness digital reforms to promote changes in governance concepts and the reshaping of government functions. Second, to vigorously cultivate and develop new quality regional productive forces, and continuously empower enterprises to achieve breakthrough innovation performance improvement, all regions should implement policies and guidelines to promote the rapid development of new quality productive forces and encourage enterprises to increase innovation investment through policy guidance and incentive mechanisms.Third, to optimize the impact of digital government initiatives and augment the policy-targeting precision, a differentiated strategy is essential.With the consideration of the diverse external circumstances of enterprises, the digital government development strategy must be fine-tuned to heighten its relevance to various enterprise types.

Patents are the most effective carriers of technical information and have become key assets in the innovation competition between enterprises and countries. Universities are a major focus area for the National Intellectual Property Administration's crackdown on "abnormal" patents. While most university patents in China tend to be shelved after the grant of patent rights, and the investment in university scientific research resources has not produced practical application value, resulting in serious waste. Both the crackdown on abnormal patents and the transformation and utilization of patents are directly related to patent quality. Thus, it is urgent to evaluate the quality of university patents. However, it is difficult to assess the quality of patents manually through human means amidst millions of patent applications. Patent quality changes with market changes and technological development, so the dynamic nature of patent quality assessment can reflect the latest changes in the market and technology in a timely manner, which can improve the accuracy of patent assessment. Therefore, it is particularly important to seek a dynamic assessment method that is both accurate and generalizable to judge the quality of patents.
In order to achieve accurate assessment of the quality of announced patents, this study constructs a dynamic patent quality assessment model based on deep learning. The model takes into account both the static and dynamic characteristics of patents, including multiple indicators in legal, market, and technological aspects, making the assessment results more comprehensive and objective. In terms of static assessment, indicators include the remaining validity period of the patent right, the number of claims, and the number of examples, which reflect the basic attributes and legal value of the patent. By constructing a static assessment quality interval, the quality status of the patent is clarified at the static level. In terms of dynamic assessment, the market transaction situation and technological development trends of similar patents are considered, including indicators such as average monthly transaction price, average monthly transfer price, transaction volume, and technical feature indicators. These indicators help capture the performance and technological influence of patents in the market, thereby better reflecting the dynamic quality of patents. By integrating static and dynamic assessments, an open deep learning assessment model is constructed to provide the corresponding quality assessment interval according to the classification numbers. This not only improves assessment efficiency but also provides strong data support for the transformation and application of patents.
Through empirical analysis, this study uses the announcement patent data from the National Intellectual Property Administration to select 1 000 samples for the extraction of static assessment quality intervals and dynamic assessment quality intervals. By establishing distribution interval charts for static and dynamic assessments and using specific screening methods, high and low screening intervals are determined, and corresponding assessment quality intervals are calculated. On this basis, the results of static and dynamic assessments are integrated to construct a deep learning assessment model for accurately assessing the quality of announced patents. The model considers multi-dimensional factors such as the technical level of patents, degree of innovation, and market demand, and can output three levels of assessment grade signals: normal, low, and high. It also uses a redirection mechanism for further analysis of abnormal or borderline assessment results. In addition, the model's training used a BP neural network, including an input layer, a hidden layer, and an output layer, where the hidden layer was designed with two intermediate layers and three neuron units to enhance the model's processing capability and precision. With continuously updated patent data, the model can learn and adjust itself to improve the accuracy and reliability of the assessment.
The dynamic patent quality assessment model based on deep learning proposed in this study is not only innovative in theory but also has high practical application value. It provides a new perspective and method for patent assessment, and helps to promote the effective transformation and rational use of patents. Future research can further optimize the model structure and explore more valuable assessment indicators to improve the model's assessment precision and practicality.

Entrepreneurial defection refers to the unauthorized disclosure of the technology, market, and other resources of the parent company by employees of a startup enterprise to competitors, or the same work or entrepreneurial behavior carried out by employees based on the same resource endowment as the parent enterprise after quitting the job.This behavior will take away the relevant knowledge, skills, networks and other resources of the parent company, and consequent market competition will grow more fierce for the parent company.According to the resource-based theory, the quantity and scarcity of a company's resources are directly related to its core competitiveness.For the parent company, this passive loss of resources can lead to a decline in competitiveness and damage to organizational interests.From the perspective of emotional event theory, such defection events belong to negative events within the enterprise and are a sign of entrepreneurial failure.These negative events can cause personal and emotional fluctuations for entrepreneurs.According to the high-order echelon theory, the behavior or emotional changes of entrepreneurs affected by their interests will be transmitted to the organizational level, bringing changes in organizational emotions, human resources, innovation, competitive strategy, and performance.It can be seen that entrepreneurial defection is a concept different from resignation entrepreneurship and derivative entrepreneurship, and it is also a common phenomenon that widely exists in the real economy, but is often overlooked by scholars and business professionals.The damage degree of entrepreneurial defection is a multidimensional and comprehensive indicator used to measure the damage that defection events may cause to the parent company and its entrepreneurs.The dimensions and measurement of the damage degree of entrepreneurial defection are closely related to the impact of subsequent entrepreneurial defection events, and it is an urgent issue to be addressed in subsequent empirical research on entrepreneurial defection.
Therefore, from a literature review and theoretical derivation, the study defines the concept and dimensions of the damage degree of entrepreneurial defection; it then uses a grounded research method to analyze the data from three in-depth interviews with entrepreneurial enterprises that have experienced defection events.The interview data is subjected to open coding, axial coding, and selective coding, and a theoretical saturation test is conducted.The structural dimensions and measurement items of the damage degree of entrepreneurial defection are summarized.Finally, the exploratory factor analysis and confirmatory factor analysis on the dimensions and items are made on the basis of 275 and 553 questionnaires, and ultimately a complete measurement table for entrepreneurial defection damage is obtained.
The scale for measuring the entrepreneurial defection damage degree includes two dimensions: emotional damage and interest damage.The former includes three items: "I feel depressed and unhappy due to employee defection incidents," "I don't feel sorry for my employee, but he left me," and "I am worried about how to deal with the possibility of employee defection incidents happening again in the future." The latter includes "employee defection has intensified industry competition,employee defection has a short-term impact on the company's performance," and "employee defection has to some extent weakened the company's competitive advantage in the market."Through case analysis, it can be observed that defection incidents occurring within entrepreneurial enterprises can have an impact on the normal operation of the enterprise and the personal emotions of entrepreneurs.Moreover, through two rounds of market research, it has been confirmed that entrepreneurs who have experienced defections account for about 10% of all entrepreneurs, indicating the prevalence of entrepreneurial defections.
The entrepreneurial defection damage measurement table developed in this study is proven to be of good reliability and content validity,and it can meet the requirements of psychological measurement, and thus the study promotes the understanding of the phenomenon of entrepreneurial defection in scientific research, especially from the perspective of entrepreneurs, and provides a measurement tool for further research on entrepreneurial defection.

With the rise of the intelligent revolution, artificial intelligence (AI) came into being. AI refers to the process of simulating and extending human intelligence, enabling computer systems to possess cognitive abilities similar to those of humans. Achieving this goal typically relies on core technologies such as machine learning, deep learning, natural language processing, and pattern recognition. Human-computer interaction (HCI) is a technology that involves the mutual influence and interaction between humans and AI, focusing on the design and implementation of user-friendly interfaces to facilitate interaction between users and computer intelligent systems. HCI encompasses important aspects such as user experience, human-computer interface, and interaction design. The human-computer interaction between leaders and AI refers to the communication process where leaders interact with AI based on common goals.
In the traditional context, leaders play a key role in decision-making and commanding in organizations, and their behavioral characteristics usually reflect subjectivity and personal experience. However, on the basis of data analysis and model training, AI can quickly extract and analyze valuable information, reflecting the objectivity of technology. In contrast, leaders' behavior is limited by personal resources and cognitive bias, while AI's data-driven decision-making provides objective and unbiased analysis results, forming a sharp contrast. Yet, there is a lack of research on the interaction between leaders and AI, so it is necessary to explore it in depth.
First of all, this paper focuses on the evolution of the relationship between leaders and AI under human-computer interaction, including the stages of "command execution", "mirror symmetry", "intelligent leadership" and "interactive symbiosis", as well as the new requirements faced by leaders, including re-examining the leadership role, reshaping leadership skills, adhering to the unique characteristics of human beings, and demonstrating leadership empathy. Secondly, taking decision-making, empathy and innovation as dimensions, this study discusses the role and function of leaders and AI in various dimensions and the interaction between them. In the aspect of decision-making, the differences between leadership decision-making and AI decision-making, the advantages and limitations of AI decision-making, and how to enhance the effect of decision-making between man and machine are discussed. In the aspect of empathy, it discusses whether artificial intelligence is emotional, related theories, and how to establish an emotional connection between man and machine. In terms of innovation, this paper discusses the innovation interaction between man and machine from the generation stage, elaboration stage, defense stage and implementation stage. Finally, this paper proposes corresponding practices, including shaping AI ethics to ensure that algorithms are good, leaders play the role of responsible subjects, and data governance to promote the development of organizational intelligence.
In summary, this study offers theoretical significance in three aspects. Firstly, previous studies have mainly focused on how a particular leadership behavior can use AI to enhance effectiveness or improve the relationship between superiors and subordinates. There is a lack of research on the human-machine interaction between leaders and AI. This study enriches the literature on human-machine interaction and expands the development of leadership research in the context of organizational intelligence, while also providing a new research perspective for the field of human-machine interaction. Secondly, this study utilizes the “leader-follower” research framework to deeply explore the evolution of the relationship between leaders and AI. It applies traditional interpersonal interaction patterns to the field of human-machine interaction, revealing the dynamics of the interaction between leaders and AI, and further promoting the development of human-machine interaction theory. Finally, by analyzing the interactive processes between leaders and AI in decision-making, empathy, and innovation, this study reveals the leadership transformation in the context of organizational intelligence. It analyzes the impact of AI on the roles and functions of leaders, helping the theoretical community to re-examine the new changes in leadership and grasp the leadership needs and development direction in the era of intelligence. This provides a foundation for constructing leadership theories for the intelligent era.

The digital economy has become a new engine for promoting high-quality economic development, and it plays an indispensable role in revitalizing the real economy, fostering new driving forces for economic development, and promoting the transformation and upgrading of traditional industries. In the era of the digital economy, Chinese enterprises are still faced with the challenge of low digital penetration rates. Digital transformation is at the core of an enterprise's strategy to improve quality and efficiency, and how enterprises can effectively promote digital transformation and achieve practical results has become an important issue to be resolved. While digital transformation is a kind of strategic change, which needs to be driven by top management to make top-level thinking, design, and resource allocation. Therefore, the CEO, as the maker and executor of the strategic decision, the personal characteristics of the CEO will have an impact on the level of enterprise's implementation of digital transformation.Specifically, the CEO's intellectual traits have a directional impact on whether and how an enterprise adopts digital transformation through three mechanisms: cognition, confidence and choice, which in turn affect the level of digitization and the effectiveness of transformation.
This study integrates upper echelons theory and intellectual management theory, and makes an empirical analysis with data from 2015 to 2021 of 1031 A-share enterprises listed in Shanghai and Shenzhen markets; finally it proposes a theoretical framework for the relationship between CEO's intellectual traits and corporate digital transformation. It is found that CEO intellectual traits have significant effects on enterprise digital transformation, in which their education level and emotional stability, agreeableness and extroversion have significant positive effects on digital transformation, but conscientiousness significantly inhibits digital transformation, and their experience and openness have the inverse U-shaped and U-shaped nonlinear influences on digital transformation, respectively. The results of the study are robust as a whole, but the impact of CEO intellectual traits on firms' digital transformation shows heterogeneity when the level of regional digital finance development, industry competitiveness, nature of property rights, and industry attributes are different.
This study highlights the importance of the CEO in a firm's digital transformation strategy, enriches the evidence of upper echelons theory, and expands the application areas of intellectual management theory. The personal characteristics of top executives have an important impact on corporate strategic decisions and the effectiveness of digital transformation, and corporations should take their cognitive structure and personality traits into account when selecting, nurturing, and employing people.Therefore, the study also provides guidance for enterprises' selection and replacement of CEO in response to their needs of digital transformation. First, in order to adapt to the needs of digital transformation, enterprises should give priority to highly educated talents under equal conditions when selecting and hiring CEOs. Second, CEOs need to emphasize the importance of cultivating their character, especially to play to their strengths of agreeableness, extroversion and emotional stability. However, CEOs also need to recognize some potential flaws in their personality traits. Third, non-state-owned enterprises should prioritize CEOs who are moderately open to balancing the opportunities and risks associated with digital transformation. Manufacturing firms should place more emphasis on the role of CEO knowledge traits for digital transformation, while non-manufacturing firms are appropriate to focus on CEO personality traits. Finally, recognizing, adapting to, and utilizing the heterogeneity mechanism can help to better select and cultivate CEOs to promote digital transformation, so that enterprises can gain more advantages for survival and development in the digital era.
Overall, this paper integrates the theory of intellectual management and the theory of upper echelons, discusses the complex influence mechanism of CEO's intellectual traits on the digital transformation of enterprises, and clarifies the CEO's intellectual traits required for the digital transformation of enterprises, so that enterprises can obtain advantages for survival and development in the digital era. Then the introduction of non-linear mechanisms based on the literature enhances our understanding of the complexity of the relationship between CEO intellectual traits and corporate digital transformation. Furthermore,it introduces the Big Five personality theory to examine CEO personality traits and explores the effects of CEO personality traits more systematically.

In the context of China's industrial transformation under the "Quality-driven Manufacturing" initiative, leader perfectionism-manifested through high-performance goals and a zero-tolerance attitude toward errors-has demonstrated significant potential in driving creative outcomes and facilitating organizational development, warranting in-depth investigation. However, current research on leader perfectionism remains predominantly rooted in Western contexts, lacking substantive expansion and contextualized exploration within indigenous settings. This limitation results in insufficient understanding of the projection domains inherent in leaders' pursuit of perfection, as existing theoretical frameworks fail to fully account for culturally-specific manifestations of perfection-oriented leadership behaviors.On the one hand, regarding leaders' pursuit of perfection in "content", Western studies focus on leaders' high demands for task performance, while paying insufficient attention to relationship building. On the other hand, leadership traits are contextually embedded, where cultural influences cannot be neglected, as the connotations of perfectionism vary across cultural contexts. In traditional Chinese culture, Confucian philosophy emphasizes "reverence for tasks" and "benevolence" , while Taoist thought advocates "natural order" and "harmony". These philosophies collectively reflect values that impose high standards and strict requirements for both "task execution" and "interpersonal conduct". When projected into management practices, this cultural heritage highlights the dual emphasis on the objective "substance" of task implementation and "harmonious" development of interpersonal relationships.Consequently, clarifying the conceptualization of leader perfectionism within indigenous contexts becomes imperative, warranting scholarly exploration.
There is no consensus on whether leader perfectionism facilitates or impedes innovation. These divergent perspectives on the perfectionism-innovation relationship may stem from insufficient analysis of the informational attributes conveyed by leaders' perfectionistic traits. Grounded in social information processing theory, this study investigates the underlying mechanisms by which leader perfectionism affects creative problem-solving through its effect on employees' self-regulation processes.Simultaneously, organizational climate reflects shared normative expectations promoted by the organization. A performance climate advocates competition-oriented values aligned with "exacting standards" for task perfection, while a mastery climate emphasizes "symbiotic cooperation" consistent with "stringent relational expectations" for interpersonal perfection, thereby intensifying information interpretation. Furthermore, from the perspective of individual trait congruence, star employees exhibit dual needs for high social status and superior performance, which may foster mutual reinforcement or complementary alignment with leaders demonstrating dual perfection expectations. Therefore, this study incorporates motivational climates and star employee status to investigate their boundary conditions.
This study conceptualizes leader perfectionism through dual-dimensional framework: task-oriented leader perfectionism comprising "perfectionistic concerns for tasks" and "perfectionistic strivings toward tasks",alongside relationship-oriented leader perfectionism encompassing "perfectionistic concerns for relationships" and "perfectionistic strivings toward relationships." This study, based on the data coding results from grounded theory analysis and the review of some academicians, constructs a questionnaire comprising 28 items. The questionnaire was disseminated via the Credamo platform, targeting employed workers as participants, and a total of 285 valid questionnaires were collected.Empirical findings demonstrate task-oriented and relationship-oriented leader perfectionism facilitate employee creative problem-solving through the mediation of performance and role-seeking feedback, respectively. The performance and mastery climate positively moderate these indirect relationships, while star employee status exerts partial moderating effects-specifically, its moderating role is exclusively observed in the relationship between relationship-oriented leader perfectionism and role-seeking feedback.

Along with the strategy of innovation-driven development, public procurement has become an effective tool for supporting cutting-edge technological innovation and achieving sustainable development. However, existing studies lack a consensus on the connotation of innovation-oriented public procurement, resulting in inconsistent conclusions in terms of concept definition and measurement dimensions, and systematic research gaps on its influencing factors, mechanisms and policy effects. To further clarify the content, research scope, and boundaries of innovation-oriented public procurement, this study makes a comprehensive review of relevant domestic and international literature, and employs bibliometrics and content analysis to systematically summarize the research frontiers, development trends, and hot topics of this theme, aiming to construct an integrated research framework. Simultaneously, in accordance with the typical contextual characteristics of China and representative literature, the paper prospects the future research trends of innovation-oriented government procurement in the hope of providing effective references for both the academic and practical communities.
Firstly, this paper conducts a quantitative analysis of foreign research achievements on innovation-oriented government procurement based on the WOS database. Overall, there is a continuous increase in the volume of publications on innovation-oriented public procurement, with developed countries being the main research subjects, exhibiting a significant characteristic of interdisciplinary fusion. Then it elaborates on the relevant concepts, types, and evolutionary processes of the functions of innovation-oriented public procurement. This paper holds that innovation-oriented public procurement is a practical activity to meet public demand, stimulate innovation and create social value through public procurement in order to achieve specific policy goals in technology, industry or society. It is found that the end user of the product, the degree and form of innovation and the strategic orientation are the basis for the classification of innovation-oriented public procurement. In terms of functional positioning, the evolutionary process of government procurement supporting innovation can be roughly divided into four stages: commercialization, standardization, policy orientation, and strategic orientation. Thirdly, the implementation of innovation-oriented public procurement is influenced by individual, organizational and environmental factors. In order to effectively exert the innovation incentive function of public procurement, it is necessary for the transaction subjects to have a sense of change and a certain professional ability, put forward high requirements on factors such as organizational resource and innovation willingness, innovation-supporting policies, markets and cultural environments. In addition, innovation-oriented public procurement releases spillover effects on corporate performance, industrial upgrading and social development, but it is also accompanied by risks such as crowding out private R&D investment and exacerbating technology lock-in. The aforementioned process mechanisms are also influenced by contextual factors such as organizational and market levels. Given the above analysis, this study further constructs the integrated research framework of innovation-oriented public procurement.
Finally, in order to provide theoretical and practical guidance for future research, this study makes a comprehensive integration of the current situation of domestic research in this field and the unique situational characteristics of China, and proposes future development directions for innovation-oriented public procurement research in the Chinese context. Researchers should (1) conduct localized research on innovation-oriented public procurement in China , which involves typical Chinese contextual factors such as transition development stages, fiscal decentralization institutional background, and "guanxi culture"; (2) explore innovation-oriented public procurement from a multi-factor, multi-level interactive perspective,such as the studies on compound influencing factors and the synergistic effects of policies; (3) optimize the research methods and technical means of innovation-oriented public procurement from the aspects of qualitative research, large sample data and meta-analysis; (4) enrich the research objects and contents from the perspectives of procurement subjects, forms and effects; (5) carry out research on the mode reconstruction of innovation-oriented public procurement against the backdrop of digital economy, and how to utilize digital technology to restructure the standardized procurement processes, while leveraging public procurement to drive iterative innovation in the digital industry, will be the key issue in this field.