The high-quality development of China's economy necessitates the unlocking of the potential of data elements, the advancement of productivity reforms and innovation, and the creation of new forms of high quality productive forces. However, current research fails to elucidate the mechanisms by which data elements influence the development of new high-quality productive forces within enterprises. It also falls short in addressing how traditional production factors interact with these data elements. As a result, enterprises struggle to understand how to leverage both data elements and traditional production factors to foster the development of their new high-quality productive forces in their day-to-day operations Therefore, this paper comprehensively constructs a theoretical analysis model of the data elements on the development of enterprises' new quality productive forces from three aspects: direct effect, indirect effect and multiplier effect.
Using the panel data of Chinese listed companies from 2011 to 2022, this study examines the impact of the data elements on the development of new quality productive forces from the perspective of effect decomposition. The results show that (1) data elements can effectively empower the development of new quality productive forces of enterprises, and the conclusion is robust;(2) enterprises' new quality innovation and labor skill structure have a mediating effect in the development of enterprises' new quality productive forces empowered by data elements; (3) data elements has a multiplier effect in the process of new quality innovation and labor skill structure promoting the development of enterprise new quality productive forces; (4) the enabling effect of data elements is only obvious in highly competitive, high-tech and non-heavy pollution industries, and is more effective in regions with complete digital infrastructure, high level of data talent agglomeration and open data.
According to the derived conclusions, data elements exert multiple influences on the development of new high-quality productive forces within enterprises. In terms of direct effects, firstly, data elements can improve the decision-making efficiency and quality of enterprises by driving their management decisions. Secondly, through data sharing and integration, on the one hand, enterprises can improve the communication efficiency among various departments;on the other hand, enterprises can improve the collaborative production efficiency within their respective supply chains. Thirdly, the application of enterprise data elements can promote the transparency of enterprise information to alleviate the information asymmetry between enterprises and investors, thus improving the financing efficiency of enterprises. Finally, the intricacy of a company's production processes can be significantly streamlined through the application of data elements. In terms of indirect effects, first of all, on the one hand, enterprises can realize the efficient connection between innovation supply and demand through the application of data elements, reducing the cost and risk of R&D innovation, and thus improving the efficiency of new quality innovation of enterprises. On the other hand, the application of data elements can optimize the technological process and product design of enterprises to ensure the improvement of the quality of new quality innovation. Secondly, through the application of data elements, enterprises will create jobs of high-skilled labor and have a substitution effect on low-skilled labor, which can improve the skill structure of enterprises' labor and thus promote the formation and development of enterprises' new quality productive forces. In terms of the multiplier effect of data factors, the core logic is that it can help enterprises re-understand the traditional factors of production, expand the allocation space of traditional factors, improve the efficiency of traditional resource allocation, and thus magnify the role of other factors in the development of new quality productive forces. This study specifically focuses on the multiplier effects of data elements on two key traditional factors: technology and labor. It finds that the multiplier effect of data elements on technology is reflected in the expansion of innovation boundary and the acceleration of technology iteration, and the multiplier effect on labor is reflected in the further improvement of the comprehensive quality of labor. To summarize, by constructing the analysis model of “direct effect—indirect effect—multiplier effect”, this paper provides empirical evidence and policy implications for clarifying the enabling effect of data elements on enterprises' new quality productive forces and releasing the potential of data elements' new quality productive forces.

The proposal of new quality productive forces has provided a roadmap for building a modern industrial system in line with China's modernization goals. By positioning enterprises as the driving force behind these new productive forces, it is feasible to establish an industrial technological innovation system that is led by businesses and generates strong momentum for the new quality productive forces.Specialized, sophisticated, differential, and innovative (SSDI) enterprises excel at "filling gaps" and "fortifying" industry chains through a relentless approach of incremental technological innovation and strategic focus. This strategy lays the groundwork for the continuous improvement of new quality productive forces. Data elements are essential in the research framework for understanding the rise of new quality productive forces within enterprises because they can effectively integrate technological innovation resources. Therefore, the research on emergence mechanism of new quality productive forces of SSDI enterprises empowered by data element is becoming an urgent topic that warrants immediate exploration.
Firstly, grounded in resource orchestration theory, a conceptual model for new quality productive forces of SSDI enterprises' emergence empowered by data elements is constructed from three stages: the construction of resource combinations, the bundling of these resources to form capabilities, and the utilization of these capabilities to create value. Secondly, the emergence mechanism of new quality productive forces of SSDI enterprises empowered by data element is analyzed from three dimensions: driving innovative allocation of production factors effectively, promoting technological revolutionary breakthroughs synergistically, and achieving deep industrial transformation and upgrading continuously. Subsequently, the study focuses on single champion firms within the manufacturing industry—listed companies that are leaders in SSDI enterprises. It further analyzes the configuration effects of data elements, redundant resources, and dynamic capabilities on the new quality productive forces of these SSDI enterprises. To validate the analysis, the study employs typical cases for confirmatory examination.
Research results indicate that the combination and interaction behavior of data element and traditional production factors can construct resource pool for SSDI enterprises, bundling above elements to form a dynamic capability set in the form of perception capability and integration capability, effectively mobilizing resource endowments to form innovation consortium and creating value by driving quality optimization through technological innovation. From the perspective of resource orchestration, these three stages correspond to the three driving factors of new quality productive forces: innovative allocation of production factors, technological revolutionary breakthroughs, and deep industrial transformation and upgrading. Four types of adaptation configurations that can stimulate new quality productive forces of SSDI enterprises are summarized: "collaborative-breakthrough" refers to new quality productive forces emergence stimulated by cross-border innovation driven by integration capability; "perception-reconstruction" refers to new quality productive forces emergence stimulated by iterative innovation driven by perception capability; "tapping potential-traction" refers to new quality productive forces emergence stimulated by exploratory innovation driven by redundant resources tapping; "internal driving-exploiting" refers to new quality productive forces emergence stimulated by disruptive innovation driven by comprehensive resource bundling.
Research outcomes discuss the theoretical model and mechanism of SSDI enterprises' new quality productive forces emergence empowered by data element and achieve an organic fit between SSDI enterprises' new quality productive forces emergence mechanism and four practical paths revealed by adaptation configuration, so as to offer useful explorations for theoretical system improvement of new quality productive forces. By leveraging the empowerment of data elements, SSDI enterprises can achieve technological revolutionary breakthroughs and promote deep industrial transformation and upgrading. This is accomplished through the accumulation of micro-foundational capabilities and the reconstruction of industrial ecosystems. From a policy design perspective, the study suggests fully activating the "strong chain" and "supplementary chain" functions of SSDI enterprises. This activation is intended to achieve a dynamic optimization of the overall national industrial system, offering practical guidance for stimulating the continuous emergence of new quality productive forces.

Innovation is the first driving force behind high-quality economic development. The key technology bottlenecks and the low-added value of products have been restricting China′s high-quality development. Therefore, it is necessary to adopt appropriate industrial policies to support key technological innovation and the innovation and development of strategic emerging industries. At the same time, the government should improve the competition policy and continuously optimize the environment for industrial development. Industrial policy is an important tool for China′s economic transformation and development, and both the central and local governments have actively implemented different types of industrial policies to support or stimulate the development of specific industries, including financial subsidies, tax incentives, and other policies. Competition policy refers to the various economic policies implemented by the government to protect, promote, and regulate market competition. Existing studies have not fully explained whether the joint implementation of various policies has a synergistic effect on innovation or hinders innovation.
Although some scholars have analyzed the relationship between industrial policy and competition policy, few have demonstrated it from a micro-empirical perspective. To improve policy synergy, optimize policy tools, and ensure the smooth development of innovation, this study explores the impact of industrial policy and competition policy on enterprise technology. It investigates whether the selective industrial policy represented by government subsidies and tax incentives and the functional industrial policy represented by the provision of public services and competition policy can produce policy synergy and achieve the purpose of stimulating enterprise innovation. First, the study finds that, except for functional industrial policies, other policies can effectively improve the level of technological innovation in enterprises. After placing industrial policy and competition policy in a unified analytical framework, it is found that the selective industrial policy represented by the subsidy policy and the competition policy produces significant contradictions and conflicts, which inhibit enterprise innovation, while the conflict between preferential tax policies and functional industrial policies and competition policies is not significant. This suggests that it is necessary to avoid direct subsidy-type industrial policies. From the heterogeneity analysis, we concluded that the level of industry competition can affect the synergistic effect of industrial policy and competition policy. The competition policy and functional industrial policy are more constrained in industries with low competition levels. Further analysis shows that the spatial Durbin model at the city level shows that selective industrial policy and functional industrial policy can have policy spillover effects on neighboring cities and promote innovation in neighboring cities, while competition policy has a policy siphoning effect on neighboring cities and inhibits innovation in neighboring cities.
The possible marginal contributions of this paper are threefold. Firstly, from a micro-empirical perspective, the positive role of industrial policy and competition policy on enterprise innovation is verified, and industrial policy and competition policy are incorporated into the unified analytical framework to study the superimposed innovation effects of different industrial policy tools and competition policy. It is concluded that the policy combination of the two has a conflict inhibition effect on innovation. Secondly, the study uses the spatial Durbin model to verify the spatial spillover effect of industrial policy and competition policy, which has certain policy reference significance for the overall planning of regional innovation and development. Thirdly, by evaluating the innovation effects of industrial policy and competition policy, this study concludes that China′s selective industrial policy still has a strong position, and the competition policy is in a weak position, and there is an obvious conflict and inhibition relationship between industrial policy and competition policy for industries with different levels of competition. Therefore, it is necessary to optimize the combination of policy tools for industries with different levels of competition, steadily promote the transformation of selective industrial policies to functional industrial policies, and establish the fundamental role of competition policies.

The breakthrough innovation in key technologies has significant practical implications for enhancing China's technological competitiveness and ensuring technological security. In order to achieve breakthrough innovation, enterprises need not only to conduct in-depth excavation of their fields, but also to integrate multiple resources across organizational and industrial boundaries. Therefore, enterprises often choose suitable partners to form alliance portfolio based on their development needs. There is value in studying how focal firms can enhance breakthrough innovation performance by managing the knowledge structure and governing the membership of their alliance portfolios.
Firms in an alliance portfolio often require a deep commitment to a particular domain of knowledge or a wide range of novel combinations of cross-domain knowledge in order to realize breakthrough innovations. The result of the knowledge flow can be reflected through the knowledge network divisive faultlines. Specifically, the knowledge elements in the network form high weight edge relationships through repeated connections, while low weight edge relationships are established by a combination relationship between knowledge elements for the first time.
The essence of innovation is the reorganization and creation of existing knowledge. Therefore, it is necessary to start with the knowledge network and dig deeper into the intrinsic connection between the divisive faultlines of the knowledge network and breakthrough innovation. Meanwhile, breakthrough innovation is characterized by complexity and openness. Enterprises need to rely on the resource transfer capability of external cooperative networks to facilitate the transfer of core knowledge within the knowledge network, so as to achieve technological and product innovation breakthroughs. Thus, this paper takes the relationship divisive faultlines and status divisive faultlines of the cooperation network as the moderating variables, and explores how the focal firm governs the relationship of the members within the alliance portfolio to maximize the effectiveness of the knowledge network for breakthrough innovation. In addition, from the proximity perspective, geographic proximity facilitates the formation of cooperative relationships. Focal firms also tend to consider the industry characteristics of their partners when forming alliance portfolios. Therefore, this paper incorporates geographic proximity and industry proximity as the third-order moderating variables into the research framework to explore the role of member proximity attributes within alliance portfolios in influencing the emergence of divisive faultlines.
The alliance portfolio constructed by 175 biopharmaceutical listed enterprises from 2009 to 2022 is selected as the research object. The study empirically analyzes the intrinsic role mechanism of the fault characterizations of the knowledge network and the cooperation network, and the proximity characteristics of the members within the alliance portfolio on the breakthrough innovation. It is concluded that (1) there is an obvious facilitating effect of knowledge network divisive faultlines on breakthrough innovation. The more obvious the faults are in the knowledge network, the better the knowledge base of the focal firms for breakthrough innovation; (2) the relationship divisive faultlines and status divisive faultlines in the cooperation network negatively moderate the effect of knowledge network divisive faultlines on breakthrough innovation; (3) geographic proximity mitigates the negative moderating effect of the relationship divisive faultlines. Industry proximity mitigates the negative moderating effect of status divisive faultlines.
In short, this study expands the divisive faultlines to the knowledge network, and incorporate the knowledge network divisive faultlines, the relationship divisive faultlines and the status divisive faultlines of the cooperation network into the same research framework. Furthermore, it explores the role of the divisive faultlines of the knowledge network on breakthrough innovations, and analyzes the characteristics and influencing factors of breakthrough innovations in-depth. From the viewpoint of proximity, the study provides practical guiding significance for the choice of the partners of the focal enterprises and the governance of the focal enterprises in the alliance portfolio. Focal firms should absorb novel and heterogeneous knowledge while deepening their domain-specific knowledge, balance relationships with each partner, encourage cooperative relationships among partners, and select partners that are geographically and industrially proximate to each other.

The Chinese government has been endeavoring to shore up a new development dynamic dominated by the flows of the domestic economy while ensuring domestic and international flows. But at this stage, there are multiple dilemmas in developing a new development pattern, especially weak product innovation that cannot achieve value-added accumulation has hindered the industrial circular economy. Existing research suggests that supply and demand mismatch is the root cause of product innovation failure, and researchers pay more attention to the supply-side structural reform and demand-side management, while neglecting that these issues involve various institutional mechanism fields, and thus cannot provide specific guidance for practice. It has become an urgent issue for the current research to find a more realistic theoretical analysis framework. Fortunately, the global value chain economy driven by intermediate goods trade has opened a window of opportunity.
As a key medium for connecting domestic and international markets and resources, intermediate goods trade not only drives innovation practices in various countries, but also carries value-added profits from cross-regional circulation. Clarifying the structural characteristics and operational mechanisms of innovation flow and value-added flow carried by intermediate goods trade flow provides both a new perspective for specific dual circulation, and a new target for fostering a new development dynamic. Thus, this study distinguishes and measures the structure of innovation flow and value-added flow by connecting the 2022 ADB-MRIO database with the OECD Business Enterprise R&D Expenditure by Industry thematic data. Using the scenario modified sequential production division model, this paper reveals the impact mechanism of heterogeneous intermediate goods innovation flow driving domestic and international value-added flows, and then it further conducts an empirical test on 14 sub-sectors of the manufacturing industry.
The results show that (1) the embedded intermediate product innovation flow has a significant inverted U-shaped impact on the domestic and international value-added flows of China′s manufacturing industry, while it only shows a short-term promoting effect on major countries dominating the value chain such as the United States, Germany, and Japan. (2) For China′s manufacturing industry, the related intermediate product innovation flow has a significant U-shaped impact on the domestic value-added flow, while it has a sustained negative impact on the international value-added flow. For the manufacturing industry of major countries dominating the value chain, the related intermediate product innovation flow has a significant U-shaped impact on the domestic and international value-added flows. (3) The independent intermediate product innovation flow has a significant U-shaped impact on the domestic and international value-added flows of China's manufacturing industry, while it only shows a long-term promoting effect on the international value-added flow of major countries dominating the value chain. (4) There is an accompanying effect between the development of value-added flow and the improvement of the division of labor position in the industrial chain.
According to the above analysis, the paper present some policy implications. (1) In order to reasonably allocate imported intermediate products and consolidate the domestic circulation, the government should set a red line for external dependence on imported intermediate goods, and dynamically test the quality and effectiveness of innovative resources embedded in intermediate goods. Meanwhile, the functional positioning of various industry research institutions in technological autonomy should be strengthened to guide the transition from embedded intermediate product innovation resources to related and independent intermediate product innovation resources. (2) To improve international circulation, it is necessary to encourage the export of related intermediate goods, and the government should select a group of high-quality related intermediate production enterprises in key domestic industries, and improve the global competitiveness by formulating the “Catalogue of Encouraged Export Related Intermediate Products”. In addition, various industry exhibitions can be utilized to expand the channels for promoting brands and guide more high-quality related intermediate products to participate in the global industrial chain. (3) Phased cultivation of independent intermediate products along with the “Management Measures for Phased Cultivation of Independent Intermediate Products” should be introduced to strengthen the domestic and international dual circulation, and the cultivation should be implemented by the setting of three thresholds: the basic layer, the innovation layer and the selection layer.

Driven by the upgrading of personalized customer demands and the development of market intelligence trends, manufacturing enterprises have undergone an inevitable transition from a product-dominant logic to a service-dominant logic. Servitization transformation has become an important strategic deployment for manufacturing enterprises to obtain a sustainable competitive advantage. As an important external driving force for enterprise transformation and upgrading, digital intelligence technology supports enterprises in establishing digital platforms and analyzing massive customer data, which helps in realizing flexible product and service upgrades to meet customized customer needs. Some scholars have analyzed the impact of digital development and capabilities, among other factors, on servitization, as well as the economic effects generated by the linkage between digitalization and servitization, providing a wealth of theoretical inspiration for understanding the phenomenon of digital intelligence technology driving servitization transformation. However, there are still some gaps. On the one hand, research perspectives are mostly limited to the digital level, with slightly insufficient discussion of digital intelligence in the transformation process of manufacturing enterprises. On the other hand, existing research pays more attention to the synergistic effect of digitization and servitization, lacking discussion on the mechanism of the influence of digital intelligence on the servitization transformation of manufacturing enterprises.
In fact, digital intelligence technology itself does not confer a competitive advantage, and it needs the collaborative absorption and integration of innovation resources and innovation capabilities to provide the foundation and driving mechanism for servitization transformation. From the perspective of the relationship between resources and capabilities, existing researches believe that innovation resources are the basis for improving innovation capabilities, and resources and capabilities complement each other and enable collaborative innovation. The application of digital intelligence technology emphasizes the complementarity between technology and resources and capabilities. Therefore, it is an important issue worth exploring how innovation resource allocation and dual innovation capabilities play a chain role in the application of digital intelligence technology and the servitization transformation of manufacturing enterprises. In view of this, this study combines the dynamic resource-based view and the dual innovation theory, and on the basis of the logic of "resource-capability-behavior", builds a chain mediating model of "digital intelligence technology application - innovation resources allocation - dual innovation capabilities - servitization transformation of manufacturing enterprises".Taking A-share listed manufacturing enterprises from 2013 to 2022 as research samples, this paper discusses the effect and complex mechanism of digital intelligence technology application on the servitization transformation of manufacturing enterprises.
It is concluded that, firstly, digital intelligence technology application can promote the servitization transformation of manufacturing enterprises. The widespread application of digital intelligence technology such as artificial intelligence, big data, and blockchain can help manufacturing enterprises expand their service business, deepen service value, and realize the transformation from a product-dominant logic to a service-dominant logic. This effect is more significant in state-owned enterprises, high-tech enterprises, and heavily polluting enterprises. Secondly, digital intelligence technology application promotes the servitization transformation by optimizing innovation resource allocation and improving dual innovation capabilities. Both of them play independent mediating roles and have a chain mediating effect between digital intelligence technology application and servitization transformation. Further analysis of the relationship between innovation resource allocation and dual innovation capabilities shows that innovation human resource allocation has a more significant effect on improving exploratory innovative capability, while innovative capital resource allocation has a more significant effect on improving exploitative innovation capability.
In terms of the theoretical significance, from the technical perspective, this paper analyzes the effect and mechanism of digital intelligence technology and its different dimensions on servitization transformation, deepens the theoretical connotation of technology availability, expands the application scope of dynamic resource-based view and dual innovation theory, and enriches the research scope of digital intelligence technology application and the research on the pre-influencing factors of servitization transformation. For the managerial implication, this paper provides a possible path for manufacturing enterprises to use digital intelligence technology to promote servitization transformation, and provides inspiration for manufacturing enterprises to combine digitalization with servitization.

In order to maintain the dominant position occupied by the United States in the global science and technology industry chain, the U.S. Department of Commerce has included Chinese firms in the Entity List, which has intensified the uncertainty of market competition and challenged the innovation capacity of Chinese firms. The Entity List is a coercive economic measure by which the United States attempts to decouple China's science and technology, aiming to curb China's ability to sustain innovation in the high-tech field through trade sanctions, export and investment controls, and a ban on cooperation between Chinese and American enterprises and universities, such as high-level talent training exchanges.
The great power game affects the global development pattern, and the capability of scientific and technological innovation has a direct impact on the competitiveness of both sides of the game, and enterprises are the main body of innovation. Therefore, an in-depth study of the impact of the U.S. Entity List on enterprise innovation can help reveal the opportunities and challenges embedded in the event, help enterprises identify bottlenecks in their own innovation and development, adjust their innovation strategies, and seek to develop key technological directions and entry points. At the same time, government departments can more accurately assess and predict the economic and technological risks that may arise from the incident, formulate response programs and countermeasures, and provide support and guidance for the innovative development of enterprises. However, there is inadequate literature that analyzes the impact on firms' innovation capabilities from the perspective of the great power game. Regarding the impact of the Entity List, the existing literature mainly studies the motivation of sanctions, the risk of decoupling and cutting off the industrial and supply chain, the legal logic, and the impact of enterprises' entry into the Entity List on their innovation capability is rarely discussed, and there is no consensus on the impact of the Entity List.
Taking 1216 Chinese A-share listed companies from 2017 to 2022 as samples, this paper adopts a staggered difference-in-difference model to test the impacts on the innovation capability of Chinese enterprises and the possible development paths against the backdrop of the Sino-US game. It uses the number of patent applications to characterize the innovation output, and examine the overall innovation capability and substantive innovation capability of enterprises through the "total number of patent applications" and "number of invention patent applications", respectively. The study then conducts the PSM equilibrium test to prevent the sample self-selection bias in the control group from affecting the robustness of the results.
It is found that (1) under the impact of entering the entity list, the innovation capability of Chinese listed companies appears to be enhanced with a lag and short-term; (2) the channel analysis reveals that firms included in the entity list enhance their innovation capability through the intangible asset reserve, growth capacity improvement, and value discovery channels; (3) the heterogeneity analysis shows that private firms, as well as access to government subsidies, low agency costs, moderate and less social responsibility, and control of management's base compensation, innovation capability is more significantly positively affected by the entity list. Further analysis reveals that access to the entity list enhances innovation efficiency but does not significantly affect innovation persistence, which may explain the short-term nature of the effect, and that organizational resilience is a potential motivator of firms' enhanced innovation capability.
Therefore, enterprises in the Entity List of should enhance continuous R&D investment, optimize the innovation output process with a focus on substantive innovation; optimize the management of intangible assets, and shape a good corporate image; it is also critical to enhance the efficiency and sustainability of innovation, and establish an emergency response mechanism to enhance organizational resilience under crisis events. While the government should promote cooperation among industries, universities and research institutes to accelerate the application and commercialization of innovation outputs, improve the regulation of corporate information disclosure, strengthen the construction of scientific research infrastructures, promote the efficiency and sustainability of innovation, and shorten the R&D cycle of enterprises.

Organizational strategy and dynamic capability are crucial factors in the process of enterprise digital transformation, as they greatly impact the achievement of enterprise technological innovation goals. Existing theoretical studies have primarily focused on the relationship between path-dependent strategy and technological innovation from the perspectives of knowledge dependence, technology locking, and technology path dependence. These studies are relatively independent, and scholars have not yet realized the complementary and restrictive effects of these factors. Moreover, although few studies examined the potential synergistic effects of organizational strategies and dynamic capabilities, there is a clear need for further research to explore the matching difference perspective. It is evident that the realization of technological innovation performance by an enterprise should not be limited to consideration of the top-level design at the strategic level. Rather, it should also be matched with the dynamic capability of concrete implementation in the process of practice. The path-dependent strategy of an enterprise affects its ability to allocate resources to enhance dynamic capabilities. Organizational resilience reflects the enterprise's capacity to guarantee the implementation of its strategy based on its unique resources and capabilities. These two factors play a role in the enterprise's technological innovation performance. However, the existing research has not yet addressed this question.
Therefore, following strategic configuration theory and dynamic capability theory, this study discusses how the combination of path-dependent strategy and organizational resilience at different levels affects the performance of technological innovation in terms of growth effect, assimilation effect, and utilization effect. It examines the digital transformation of over 430 high-tech enterprises by sending questionnaires to 362 middle- and senior-level managers engaged in the digital transformation business. The hypothesis is verified using polynomial regression and the response surface technique.
It is found that in the scenario of consistency matching, the growth effect and assimilation effect of enterprises technological innovation are higher when there is a higher consistency of high path-dependent strategy and high organizational resilience, compared to low path-dependent strategy and low organizational resilience. Conversely, when there is a low path-dependent strategy and low organizational resilience matching, enterprises have a higher level of utilization effect (compared to highly path-dependent strategy and high organizational resilience). Additionally, a higher level of policy support moderates the relationship between the growth effect, assimilation effect, and utilization effect of technological innovation in enterprises with a low path-dependent strategy and low organizational resilience consistency level. With high-level policy support, the relationship between path-dependent strategy, organizational resilience consistency matching and enterprise technological innovation performance is not a simple linear one. Instead, it follows a 'U' shape (growth effect), an inverted 'U' shape (assimilation effect), and another inverted 'U' shape (utilization effect). Optimal technological innovation performance is achieved when an enterprise implements a low level of path-dependent strategy and has low organizational resilience, as opposed to highly path-dependent strategy and high organizational resilience. In the scenario of inconsistent matching, enterprises' technological innovation growth, assimilation, and utilization effects are becoming higher when the low path-dependence strategy-high organizational resilience matching has higher variability compared to highly path-dependence strategy-low organizational resilience. High-level policy support plays a moderating role in the low path-dependence strategy-high organizational resilience capability inconsistency match with enterprises' growth effect, assimilation effect, and utilization effect relationships. The relationship between path-dependent strategy and organization resilience incongruity match and the assimilation effect and utilization effect of technological innovation of enterprises show an inverted 'U' shape, and thus optimal performance is achieved when the enterprise implements a lower level of path-dependent strategy and possesses a high level of organization resilience, as opposed to high path-dependent strategy and low organization resilience.
Different from previous literature, this paper pioneers the exploration of the influence of consistency matching and difference matching of different levels of path-dependent strategy and organizational resilience on enterprise technological innovation performance, and extends the connotation of it. The empirical analysis supports the conclusions of this paper and strengthens the empirical research basis of technological innovation theory. The research results also have guiding significance for enterprises with different strategic activities and different levels of dynamic capabilities to improve technological innovation performance.

As a strategic and fundamental industry supporting economic development, the digital industry has increasingly highlighted its supporting role in economic and social development and has become an important support for the development of the digital economy. At present, a new round of scientific and technological revolution and industrial transformation has reshaped the global competition landscape, and competition around the Internet, cloud computing, big data, artificial intelligence, quantum computing and other digital industries has become increasingly intense. In this context, the Chinese government has been endeavoring to "accelerate the implementation of innovation-driven development strategy" and "build an internationally competitive digital industrial cluster". As the source of industrial innovation-driven development, intellectual property rights are the exclusive rights of intellectual labor created in social practice. Strengthening the protection of intellectual property rights can provide a solid legal shield for Chinese innovation subjects and the innovation and development of digital industry. The comprehensive implementation of intellectual property protection can effectively increase the severity of the punishment of intellectual property infringement and illegal acts, improve the comprehensive intellectual property management system, open up the whole chain of intellectual property creation, application, protection, management and service, and create a good legal environment for the innovation and development of the digital industry. Then, how can intellectual property protection promote the development of digital industry innovation？Is there a spatial spillover effect between them? The answers to the above questions are of great significance for China to seize the opportunities for the innovation and development of the digital industry, promote the construction of a modern industrial system and effectively implement the innovation-driven development strategy.
On the basis of the panel data of 277 prefecture-level cities in China from 2009 to 2022, a bi-directional fixed-effect model is employed to investigate the empowering effect of intellectual property protection on digital industry innovation. Then, the mediating effect model is used to examine the mechanism between intellectual property protection and digital industry innovation. Finally, the spatial effect between intellectual property protection and digital industry innovation is analyzed by the spatial Durbin model. The research results show that, first, intellectual property protection can directly promote digital industry innovation, and this conclusion remains unchanged after a series of robustness tests, including an exogenous impact test, a placebo test, an instrumental variable test and alternative explanatory variables. At the same time, the enabling effect of intellectual property protection on digital industry innovation also has a heterogeneous impact due to different urban population sizes. Second, the results of the mediating effect show that the allocation of innovation capital, the cost of information disclosure and the independent research and development environment are the action paths of intellectual property protection to empower digital industry innovation. Third, by using two formal matrices of inverse distance weight and economic weight, it is verified that IP protection and digital industry innovation have significant spatial agglomeration characteristics. The LM, Hausman, and LR tests show that the SDM model can be used to examine the relationship between IP protection and digital industry innovation. In addition, SDM model test results show that IP protection has a significant positive spatial spillover effect on digital industry innovation.
Compared with the existing literature, the marginal contribution of this paper lies in three aspects. First, from the theoretical level, the influence mechanism of intellectual property protection enabling digital industry innovation is expounded, which provides a new perspective for the academic circle to carry out cross-research on intellectual property protection and digital industry innovation. Second, from the perspective of innovation capital allocation optimization, reduction of information disclosure costs, and creation of a good independent research and development environment, the mediating effect model is used to analyze the transmission path of intellectual property protection enabling digital industry innovation, in an attempt to provide empirical evidence for the implementation of innovation-driven development strategies and the construction of digital industry clusters. Thirdly, the use of spatial Durbin model to reveal the spatial spillover effect of intellectual property protection enabling digital industry innovation can provide useful reference for bridging the "digital divide" and radiating digital industry innovation in the later-developing regions.

The patent pledge financing pilot program is warranted to mitigate financial issues faced by enterprises, particularly within the scientific and technological sectors, by exploring novel approaches to patent pledge business management. The implementation of the patent pledge financing pilot program represents an innovative step towards reform and evolution. After 15 years of implementation and testing, it is necessary to evaluate and reflect upon the policy impact derived from the patent pledge financing pilot program.
Accordingly, this study adopts the quintet developmental perspectives of “innovation, coordination, greenness, openness, and sharing” to offer direction and constructs an index system for the evaluation of elevated quality economic development. Through the utilization of the entropy weighted TOPSIS model,it quantitatively evaluates the degree of high-quality economic development at a city level across China from 2005 through to 2022. Treating the patent pledge financing pilot program as a quasi-natural experiment, this study employs a double-difference approach to scrutinize the program′s impact on China′s high-quality economic development.The following hypotheses based on the correlation analysis are proposed: (1) patent pledge financing pilots can promote the high-quality development of China's economy; (2) patent pledge financing pilots may promote the high-quality development of China's economy by enhancing innovation capacity, promoting industrial structure upgrading, and optimizing the allocation of financial resources; (3) there is heterogeneity among cities in the impact of pilot patent pledge policies on high-quality economic development.
The research results obtained from the empirical study are consistent with the research hypotheses constructed in this paper and lead to the following main conclusions: First, whether or not control variables are added, there is an obvious positive correlation between the pilot policy of patent pledge financing and the high-quality development of the pilot cities, indicating that the pilot policy of patent pledge financing can significantly promote the high-quality development of the pilot cities' economy. The results of the parallel trend test and a series of robustness tests indicate that the benchmark regression results are robust. Second, the results of the role mechanism test show that there is a partial mediating role in the influence mechanism of the pilot patent pledge financing policy on the high-quality development of the pilot cities' economy by enhancing regional innovation capacity, promoting industrial level upgrading and optimizing the allocation of financial resources. Finally, there is obvious heterogeneity in the promotion effect of the patent pledge financing pilot policy on the high-quality economic development of the pilot cities. Specifically, the impact of the pilot policy is more significant for cities located in the eastern region than for cities located in the central and western regions; while the effect of the pilot policy is more significant for cities with stronger intellectual property protection, higher government efficiency, a higher level of marketization, financial development and human capital.
In summary, this paper constructs an evaluation index system for the level of high-quality economic development, and investigates the impact of patent pledging on the high-quality economic development using the double-difference method in a natural experiment based on the pilot of patent pledging. The pilot program of patent pledge financing is used as a quasi-natural experiment, and the double-difference method is used to explore the impact of patent pledge on the high-quality development of the economy in depth. The study finds that the patent pledge financing pilot has a significant positive impact on the high-quality development of the economy, and its internal mechanism is as follows: the patent pledge financing pilot promotes the high-quality development of the city's economy by enhancing innovation ability, optimizing the industrial structure and financial asset allocation. Further research finds that the impact of the patent pledge financing pilot on the high-quality development of the economy is heterogeneous for cities with different levels of intellectual property protection, government efficiency, marketization, human capital and financial development. The findings help to gain a better understanding of the theoretical framework for analyzing the impact of patent pledges on the high-quality development of China′s economy and offer empirical evidence for related research.

Innovation network communities are organizational models that emerge due to cooperative innovation in the process of industrial technology development. The improved performance of innovation network communities not only facilitates the formation of a stable R&D community to promote the transformation of scientific and technological achievements, but also enhances the attractiveness of the community to bring more heterogeneous knowledge to the community. However, at present, the scale of China's innovation groups is unevenly developed, poorly stable, and has poor innovation performance. Therefore, it is necessary to clarify the improvement path of the performance of innovation network communities, to provide directions for the formation and cultivation of innovation groups within the industry, and to provide references for the development of industrial innovation.
At present, research on innovation network communities and innovation performance has become the focus of academic attention, but there are still the following problems: on the measurement of innovation performance, the existing studies are generally conducted from the macro-network and micro-network perspectives of innovation networks, and there are fewer studies on the innovation performance of innovation network communities under the meso-network perspective; In the analysis of factors affecting innovation performance, most of them focus on the impact of network characteristics of innovation network communities on the innovation performance of organizations within the community, and few studies focus on the impact of the own attributes of innovation network communities on their own innovation performance. In the selection of models, most of them use regression to explore the impact of single or several key variables on innovation performance. In terms of model selection, most research has used regression to explore the impact of a single or a few key variables on innovation performance, without portraying the interaction between variables.
To address these gaps, this paper constructs an analysis framework of innovation performance of innovation network communities from two dimensions of organizational embeddedness and network embeddedness by embedding theory, identifies and tracks innovative network communities with the Louvain algorithm, calculates the innovation performance of communities by using the entropy power method, selects the antecedent variables affecting the innovation performance of communities by using the random forest algorithm, and explores the innovation performance improvement path of innovation network communities by using the NCA and fsQCA methods.
Taking China's IC industry's 2012-2020 joint patent application data as a data source to conduct empirical analysis, the study concludes that first, knowledge width, knowledge depth, social value, cohesiveness, and cooperation intensity are the main factors that influence the innovation performance of innovation network communities, where knowledge width has a mid-level effect on innovation performance of innovation network communities, and none of the individual conditions is necessary to produce high innovation performance of innovation network communities. Second, there are two types of paths to enhance the innovation performance of communities: knowledge resource-driven and social dependency-driven. The knowledge resource-driven type includes: "Deep-R&D" type (technological knowledge-driven stabilizing innovation enhancement path), "Cross Border-Exploration" type (co-innovation pathways driven by technological knowledge). The social resource-driven type refers to the "cooperative-exploration" type (diversified innovation paths under conditions of strong social relationship dependence) and "gathering-excavation" type (specificized innovation paths under conditions of strong social relationship dependence). Third, in the knowledge resource-driven path, the effects of cooperation intensity and social value are interchangeable for innovation performance improvement. In the social resource-driven path, the width of knowledge is a substitute for the combination of depth and cohesion.
The theoretical significance of this research is that it expands the innovation network research from the macro-network and micro-network to the meso-network level, analyzes the innovation performance enhancement paths of the innovation network communities, quantitatively understands the development of the industrial communities, and enriches the theoretical system and application scope of the innovation network research. In practical terms, the results of this research can help guide the existing innovation groups in the industry to adopt effective cooperative behavior and form a reasonable and efficient association structure with targeted purposes. At the same time, it provides guidance for the formation and cultivation of innovation groups in China, the realization of industrial technological research and the cracking of technological dilemmas.

In the digital era, digitalization enhances enterprise efficiency, fosters social collaboration, and optimizes resource allocation. However, it also complicates systems, increasing their complexity and vulnerability. Consequently, it's crucial for businesses to develop employee resilience and cultivate 'anti-fragile' capabilities to address emerging challenges. Therefore, it is urgent for enterprises to cultivate employee resilience and build employees' 'anti-fragile' capabilities to cope with potential difficulties. However, most of the existing studies focus on the impact of the support of internal resources obtained by employees in the process of work on the employee resilience. Due to the non-linear characteristics of the digital age, it is difficult to rely only on internal resources to meet new challenges, and it is more important to pay attention to the acquisition and utilization of external resources with novelty and heterogeneity. Leader boundary-spanning behavior can not only obtain external resources, but also help employees filter out valuable and meaningful resources for work in the digital era of resource explosion, and deliver them in time after integration, which has been widely regarded as an effective way to manage resources obtained across organizational boundaries.
Drawing on the theory of resource conservation, this study constructs a double-mediation model of the influence of leader boundary-spanning behavior on employee resilience from the perspectives of "cognitive" and "capability", and discusses the moderating effect of digital level.
It validates a moderated dual-mediation model with 226 leader-employee dyadic data across three stages. The results show that leader boundary-spanning behavior can promote employee introspection and capability evolution, and thus enhance employees' resilience. Digital level promotes the positive effect of leader boundary-spanning behavior on employee introspection and capability evolution, and promotes the positive effect of leader boundary-spanning behavior on employee resilience through employee introspection and capability evolution.
The theoretical significance of this paper is as follows: First, following the theory of resource conservation, it tests the mechanism of the influence of leader boundary-spanning behavior on employee resilience, thus enriching the research results in the field of leader boundary-spanning behavior. Secondly, this paper delves into the process mechanism through which leaders' boundary - spanning behavior impacts employees' resilience, as examined from the perspective of resource utilization. Third, from the perspective of the enterprise environment, the understanding of the boundary conditions of leader boundary-spanning behavior is expanded. By unveiling the disparity in the effect of leader boundary-spanning behavior at different levels of digitization, it not only offers a novel perspective for relevant research but also broadens the theoretical research scope by taking the digitization level as a moderating variable.
This practical implications are three-fold. First of all, in the process of improving the employee resilience, leaders should not only focus on internal work, but also increase the interaction with external members, obtain and screen necessary resources, and pass them on to employees. At the same time, enterprises also need to pay attention to training and promoting boundary-spanning behaviors of leaders. Secondly, attention should be paid to the utilization of resources and giving full play to the role of external resources. Enterprises should establish and improve the resource sharing mechanism between leaders and employees, as well as among employees, and encourage employees to engage in self-learning and ability improvement based on available resources, so as to achieve a win-win situation of employees' personal growth and the organization's sustainable development. Finally, enterprises should adapt to the digital trend, make full use of the characteristics of rich resources and openness in the digital era, and help the sustainable development of enterprises; while it is necessary to deepen the integration of digital technology with enterprise production and operation activities during enterprise management and enhance the level of digital technology application and digital management.

Promoting sustainable entrepreneurial activities in line with carbon neutrality objectives is critically important. However, this entrepreneurial model is deeply rooted in social logic and green concepts and is often significantly influenced by the mentoring styles of entrepreneurship mentors. Grounded in social learning theory and the concept of triadic reciprocal determinism, this study develops a moderated mediation theoretical model. Using data from self-employed individuals with higher education backgrounds, the study examines the impact of entrepreneurship mentors′ mentoring styles on the sustainable entrepreneurial behavior of startup entrepreneurs. Additionally, it analyzes the mediating role of entrepreneurial involvement and the moderating effect of the entrepreneurial ecosystem. Between March and May 2024, researchers conducted surveys in university incubators across Jiangsu, Zhejiang, and other regions. Electronic questionnaires were distributed through social network connections, resulting in 410 valid responses after thorough screening and verification.
The measurement of variables includes five items for the capability-enhancing mentoring style, focusing on skill development and intellectual stimulation; five items for the opportunity-enhancing mentoring style, emphasizing resource sharing and platform building; and five items for the motivation-enhancing mentoring style, addressing vision inspiration and personalized care. Entrepreneurial involvement is measured across three dimensions: familiarity, importance, and commitment to the entrepreneurial industry and context. Sustainable entrepreneurial behavior is assessed using four items related to human health, employment opportunities, ethical norms, and the natural environment. Drawing on the Global Entrepreneurship Monitor(GEM)and research in the Chinese context, the study examines the entrepreneurial ecosystem is examined through the lenses of government policies, market environment, and sociocultural factors.
The study′s key findings are as follows:(1)The mentoring style of entrepreneurship mentors and its three dimensions of capability-enhancing, opportunity-enhancing, and motivation-enhancing mentoring styles all significantly influence the sustainable entrepreneurial behavior of startup entrepreneurs, with the opportunity-enhancing mentoring style having the greatest impact and the motivation-enhancing mentoring style having the smallest impact.(2)The mentoring style of entrepreneurship mentors and its three dimensions have a significant positive impact on entrepreneurial involvement, with the opportunity-enhancing mentoring style having a particularly significant impact. Opportunity-enhancing mentoring style play a pivotal role in providing entrepreneurial resources and platforms for startup entrepreneurs, significantly boosting their industry involvement. In contrast, motivational mentors′ verbal encouragement and experience sharing have a comparatively smaller influence on entrepreneurs′ involvement.(3)Entrepreneurial involvement and its two dimensions both play a mediating role in the influence of the mentoring style of entrepreneurship mentors and its three dimensions on the sustainable entrepreneurial behavior of startup entrepreneurs. The mentoring styles of entrepreneurial mentors significantly influence the effectiveness of entrepreneurial involvement, helping entrepreneurs establish themselves more successfully in the industry and access greater business opportunities and resources.(4)The entrepreneurial ecosystem moderates the relationship between the mentoring style of entrepreneurship mentors and entrepreneurial involvement, with the moderating effect of the opportunity-enhancement mentoring style being more significant. Entrepreneurial mentors play a crucial role in helping startups overcome challenges such as resource scarcity and limited market opportunities by enabling access to high-quality resources.〖HJ*2/7〗
The study validates a three-dimensional model of entrepreneurship mentor mentoring styles using AMO theory and Chinese data. It introduces a mechanism where mentorship styles influence sustainable entrepreneurial behavior through entrepreneurial involvement, offering a fresh perspective on sustainable entrepreneurship research. Furthermore, it expands the application of triadic reciprocal determinism in the cognitive domain of entrepreneurs, and forms a more complete system for environment-behavior research, providing empirical evidence for investigating the antecedents of sustainable entrepreneurial behavior. In practice, the sustainable entrepreneurial behavior of startup entrepreneurs is closely related to the mentoring style of entrepreneurship mentors. To foster this relationship, startup entrepreneurs must establish a precise and empowering connection with their mentors, leveraging the mentors′ resources to identify market opportunities and enhance their entrepreneurial engagement and commitment. Meanwhile, governments and universities should shape a high-quality entrepreneurial ecosystem and connect social resources for entrepreneurs to promote the innovative growth and sustainable development of start-ups.

Digitalization is continuously transforming the participants, processes, outcomes, and environment of innovation activities, creating a digital innovation environment that presents new challenges to the analysis of participants' innovative behaviors. Currently, the antecedent variables, basic effects, and mechanisms of individual behaviors in digital innovation have been extensively discussed by scholars. They have focused on the uncertainties in team behaviors emerging from individual behaviors in digital innovation contexts, as well as the contradictory psychological motivations for individual innovation behaviors from diverse perspectives. This has laid the preliminary basis for team behaviors research by examining team cooperation foundations, content, processes, environments, and more. However, contradictory views persist regarding the psychological motivations behind individual innovation behaviors among existing research, and the outcomes of team behaviors research are also scattered due to the complexity of the research. There is an urgent need to systematically review the influencing characteristics of team behaviors in digital innovation and study the underlying mechanisms.
To fully understand the influencing characteristics and logical effects of team behaviors in digital innovation, this study reviews 263 literatures from the Web of Science database spanning from 2010 to 2023, focusing on digital innovation, innovation teams, team behaviors, and the digital transformation of the three. It evaluates the research orientation of team behaviors in digital innovation and conducts an analysis of the main influencing factors and potential mechanisms of digital innovation team behaviors. The analysis of research orientation indicates that while the research fields and contexts of digital innovation team behaviors are diverse, they generally shift from focusing on "individual psychological traits in digital scenarios" to addressing "complex and innovative collaborative patterns and decision-making." Despite the lack of integrated results in exploring the characteristics and influence trends of team behaviors, centering around management context changes, micro-management issues, and cross-level studies, the study concludes the main influencing factors and potential mechanisms of digital innovation team behaviors with a focus on emerging themes including "functionality/purpose" and "cognitive evaluation", effectively aggregating existing scattered research results. As a result, the study primarily consists of two aspects of literature review and commentary. On the one hand, it reviews the factors influencing team behaviors in digital innovation from the perspectives of participant emotions, cognition, and decision logics. On the other hand, it proposes potential research directions for the mechanisms of digital innovation team behaviors characteristics from the perspectives of open perception mechanisms, interactive adaptation mechanisms, and creative decision-making mechanisms.
The potential mechanisms and research trends are proposed accordingly. As for the open perception mechanisms, they are of great research significance for understanding the generation of team conflicts, the formation of innovation opportunities for teams at different levels, and the development of collaborative relationships in digital innovation. As regards the interactive adaptation mechanisms for digital innovation team behaviors, the interactive adaptation process of digital innovation team behaviors is viewed as a collection of "bearing capacities and constraints" of innovation teams. Cross-level studies from holistic perspectives such as resource integration, dynamic capabilities, and strategic entrepreneurship can be more effective in understanding the important question of how "individuals and organizations with specific goals can adopt new technologies better than others" in digital innovation. Concerning the research on creative decision-making, it will help to systematically understand the mechanism's action path and evaluation dilemma by further integrating with the relevant achievements of innovation and entrepreneurship process analysis, digital situational response, and organizational digital preparation.
In short, the findings indicate the dynamic attributes and cross-level impacts of digital innovation processes extension, boundary integration, and value creation, and they also help further clarify the antecedents/outcome variables, intermediary mechanisms, and moderating effects influencing the formation and development, transition of activity boundary of digital innovation team behaviors. Specifically, this study makes theoretical contributions in two aspects. On the one hand, it supplements the basic theories of digital innovation team behaviors characteristics and provides references for contradictory views on reconciling the psychological motivations of individual digital innovation behaviors. On the other hand, it enhances the basic theoretical analysis of the mechanisms of digital innovation team behaviors and proposes research focal points with potential theoretical value for cross-level studies.