The emancipation and development of productive forces constitute the fundamental task of socialism and represent the core issue of China's revolution, construction, and reform. New quality productive forces, distinguished from traditional ones, arise as the vanguard in contemporary times, shaped by technological revolutions, innovative production factor allocation, and significant industrial transformation and upgrading. These forces are considered a major component of productive forces. However, an enduring emphasis on an efficiency-centric model of productivity has led to increased spatial disparities within the industrial and economic frameworks. This is evident in the persistent concentration of strategic emerging industries and major infrastructure in the southeastern coastal region, resulting in an escalating issue of differentiation in new quality productivity between and within regions. As the development of new quality productivity emerges as an intrinsic requirement and a pivotal focus for promoting high-quality development, it is imperative to discern the trend of change in its level and disparities within China. What are the underlying sources of these disparities? Moreover, what mechanisms drive the formation of differences between and within regions? Answers to these inquiries will reveal the actual state of China's new productivity development and the dynamics of disparities, providing empirical insights to guide policy-making for the balanced allocation of productive forces and the promotion of integrated regional growth.
However, the lack of consensus on the definition of new quality productivity in academia impedes the development of a theoretical framework for its accurate measurement. Current evaluation systems are static, ignoring the dynamic causality and evolution of these forces. While existing empirical studies have addressed regional differentiation, they tend to focus on spatial differences and sources from a geographical standpoint, neglecting structural differences in economic terms. A significant concern is the insufficient in-depth analysis of the mechanisms that drive the disparities in the levels of new quality productive forces, especially amidst the ongoing inter- and intra-regional differences.
This paper develops an evaluation system for the levels of new-quality productive forces based on the DPSIR model, covering five dimensions: driving force, pressure, state, impact, and response. It assesses the levels of new quality productive forces in 30 provinces and cities in China from 2013 to 2022 using the entropy method. The analysis identifies the sources of differences in these levels from both the spatial and structural perspectives, utilizing Dagum's Gini coefficient and variance decomposition methods. Furthermore, the study uncovers the mechanisms behind these differences through the quadratic assignment procedure. The results indicate that China's new quality productive forces have consistently increased, showing a spatial gradient distribution of 'high in the east, low in the west, high in the south, and low in the north'. Regional differentiation and disparities among provinces and municipalities have emerged as key features of China's uneven development in new quality productive forces. Although spatial disparities have declined, they remain at elevated levels over time. Inter-regional and intra-regional differences drive east-west and north-south disparities, respectively, and the overall spatial pattern remains predominantly characterized by east-west differences. Structurally, disparities in the driving force, impact, and response systems account for over 75% of the total variance in productivity levels. Among the subsystems—response, impact, driving force, pressure, and state—their influence on overall disparities decreases in that order. Additionally, any increase in subsystem disparities contributes to the widening of productivity gaps.
Compared to the existing literature, this paper makes several key contributions. First, it develops an evaluation system for the levels of new quality productive forces based on the DPSIR model from the five dimensions of driving force, pressure, state, impact, and response. Second, the study takes a dual spatial perspective—'East-Middle-West' and 'North-South'—and employs both spatial and structural analyses using Dagum's Gini coefficient and variance decomposition to uncover the sources and evolutionary characteristics of differences in new quality productive forces. This approach advances the methodology for decomposing disparities in the levels of productive forces. Third, utilizing a relational data analysis paradigm, the study applies the quadratic assignment procedure to empirically investigate the mechanisms driving differences in the levels of new quality productive forces, offering insights to support coordinated improvements in productivity across regions.

Amidst the convergence of a new wave of technological revolution and industrial transformation with China's shift towards a new economic development model, the current level of productive forces has reached a critical juncture where it can no longer sustain the demands of high-quality growth. In this context, there is an imperative to expedite the transformation and application of digital innovation outcomes to catalyze the emergence and growth of new quality productive forces. This is not only an intrinsic requirement but also a pivotal strategy for fostering high-quality development within the framework of the new development stage and the new development philosophy.
Drawing on the theories of new quality productive forces and virtual agglomeration, this study utilizes data from 30 Chinese provinces spanning from 2015 to 2022. It employs fixed effect models, two-stage least squares (2SLS) models, and spatial spillover effect models to comprehensively analyze the impact, underlying mechanisms, and spatial spillover effects of industrial digitalization on the development of new quality productive forces.
This study confirms that (1) industrial digitalization can significantly drive the development of local new quality productive forces,and the conclusion is robust through the test of confounding factors, extreme value test, measurement error test, and bidirectional causality of endogeneity; (2) diversified virtual agglomeration and specialized virtual agglomeration are important mechanisms by which industrial digitalization drives the development of local new quality productive forces; (3) industrial digitalization has a spatial spillover effect in driving the development of new quality productive forces, and diversified virtual agglomeration is an important spatial mechanism; (4) and industrial digitalization has no impact on the specialized virtual agglomeration of other regions.
This paper contributes to the study of new quality productive forces by examining the impact factors of industrial digitalization. It integrates six levels of digitalization—smart agriculture, manufacturing, and services—to explore mechanisms, pathways, and spatial effects of industrial digitalization driving new quality productive forces. Furthermore, it constructs a theoretical model of "industrial digitalization —diversified virtual agglomeration/specialized virtual agglomeration—new quality productive forces" to deeply explore the virtual agglomeration mechanism of driving new quality productive forces, which enriches the study of the mechanisms driving new quality productive forces through industrial digitalization. Additionally, it employs the spatial DuPont model to analyze the spatial spillover effects, enhancing the understanding of virtual agglomeration's spatial mechanisms.
This paper suggests that fully leveraging the supporting and leading role of digital innovation achievements in industrial digitalization development, cultivating local specialized virtual clusters and guiding the diversified development of cross-regional virtual clusters, is an important strategic measure to drive the development of new quality productive forces and solidly promote high-quality development. Therefore, government departments should accelerate the formation of the important driving role of digital innovation achievements in the transformation and application of new quality productive forces. This can be achieved by accelerating the development of local industrial digitalization through financial policies and tax policies. In addition, by publicizing quality cases, establishing mutual assistance platforms and conducting digitalization training, government departments can provide guidance, consulting and platform services for industrial digitalization transformation to help traditional industries better understand the value of digital transformation and enhance their digital technology application capabilities to accelerate industrial digitalization. Meanwhile, it is necessary to cultivate cross-regional coordinated development models to achieve the spatial spillover effects of driving new quality productive forces. Government departments can encourage enterprises within and outside the region to build digital service platforms through promoting enterprise cooperation and industry association coordination, jointly conducting technological research and actively sharing transformation experience, and cooperating on digital projects to form cross-regional coordinated development models for industrial digitalization. Lastly, the government should tailor virtual clustering strategies to suit local specificities. By offering essential foundational resources, maintaining market order, establishing safety benchmarks, and furnishing technical support, the government can facilitate virtual economic engagement for local businesses. This is achieved through the provision of digital infrastructure, ensuring digital security, and enacting relevant digital policies and regulations.

In recent years, digital economy is an important driving force for Chinese modernization, and the policy deployment of digital economy is significant for China's modern industry, market, and governance system. Technological innovation drives the high-quality development of the digital economy and provides a new engine for the digital economy to promote Chinese modernization. At present, China has entered a critical period of comprehensively promoting Chinese modernization. Theoretically clarifying the mechanism of promoting Chinese modernization through the digital economy based on technological innovation and measuring its impact in practice are theoretical and practical issues that need to be solved urgently. However, scholars are limited to the study of the pairwise relationship among the digital economy, technological innovation, and Chinese modernization and rarely incorporate the three into a unified framework for analysis; the five measurement dimensions of Chinese modernization have yet to be measured separately; moreover, there is a lack of quantitative analysis and nonlinear analysis of the mutual relationship.
Therefore, in accordance with the " Five-Sphere Integrated Plan" made in the 20th National Congress, this study analyzes Chinese modernization from the five dimensions of "economy, politics, culture, society, and ecological civilization modernization", and integrates digital economy, technological innovation, and Chinese modernization into the unified analysis framework to deeply analyze the impact mechanism of technological innovation-driven digital economy on Chinese modernization.Relevant data from 2015 to 2022 for the digital economy, technological innovation, and Chinese modernization in 30 provinces have been collected. Data sources include the Statistical Yearbook of China Culture and Related Industries (2016-2022) for cultural modernization, Baidu Index for democracy and rule of law construction, and the government information openness index and government online service index from the Guomai e-government network. Remaining data were obtained from the China Statistical Yearbook and provincial Statistical Yearbooks (2016-2023), with missing values supplemented by the interpolation method. The dynamic panel models and threshold models are constructed to measure the impact of the digital economy driven by technological innovation on Chinese modernization and its five dimensions (economic, political, cultural, social, and ecological modernization). The entropy method is employed to build the comprehensive evaluation index system of the Chinese modernization level, and Chinese modernization is further divided into "economic, political, cultural, social and ecological civilization modernization", while the comprehensive evaluation index system of the digital economy level (2 first-level indexes, 4 second-level indexes and 9 third-level indexes) is divided into industrial digitalization and digital industrialization to accurately measure the level of technological innovation, the level of digital economy and the level of Chinese modernization.
It is concluded that, first, the digital economy is significantly promoting Chinese modernization. Then, on the whole, the digital economy has a positive impact on Chinese modernization, initially growing and then subsequently diminishing in its impact. From the perspective of five dimensions of Chinese modernization, the impact of digital economy on economic, political, cultural, social and ecological civilization modernization is different in different stages: the effect of economic, political and cultural modernization increases first and then decreases positively, and the effect on social and ecological civilization modernization follows a U-shaped pattern. Third, technological innovation increases first and then decreases in the active adjustment of the digital economy, in the positive adjustment of the digital economy to promote Chinese modernization. After crossing a certain threshold, technological innovation positively moderates the impact of digital economy on economic, political, cultural, social and ecological modernization.
This paper presents some novelties in three aspects. Firstly, the analysis is carried out within the unified framework of digital economy, technological innovation, and Chinese modernization to study the mechanism of the digital economy driven by technological innovation on Chinese modernization (overall and five dimensions). Secondly, Chinese modernization is measured as a whole with the five dimensions investigated, respectively, and the influence effect among digital economy, technological innovation and Chinese modernization (the whole and the five dimensions) is explored. Thirdly, the threshold model is constructed to explore the nonlinear changes of Chinese modernization (overall and in five dimensions) when the digital economy and technological innovation are taken as threshold variables, respectively.

Sustainable entrepreneurship is highly regarded by scholars as the key solution to achieving the goal of sustainable socio-economic development. However, in pursuing costly sustainable entrepreneurial activities, entrepreneurs often find themselves trapped in a “green prison” due to the contradiction between the pursuit of individual interests and collective sustainable development goals. The acquisition of legitimacy is valued as the password to unlocking the "green prison" of sustainable entrepreneurial enterprises, meanwhile, there is a continuous and dynamic evolutionary process in the acquisition of legitimacy, and the dynamic evolution law in the process of obtaining legitimacy has not been explored.
Therefore, this paper introduces the niche theory into the legitimacy study, interprets the growth of sustainable entrepreneurial enterprises as a process of improving their individual niche within the larger population niche from the meso-perspective between individuals and populations, and constructs a set of legitimacy scale and niche measurement index system for sustainable entrepreneurial enterprises to identify the dynamic change path of legitimacy along the three dimensions and three levels of the sustainable entrepreneurial niche.
Questionnaires were distributed to enterprises or non-profit organizations in Shaanxi Province, the Yangtze River Delta and the Pearl River Delta, and the subjects have been established for no more than eight years and are engaged in the industries of renewable energy, energy conservation, water resource management, pollutant prevention and waste management, new environmentally friendly materials and processes, and their related service industries. A sample of 363 sustainable entrepreneurial enterprises is selected for the empirical analysis. The results show that (1) cognitive legitimacy, normative legitimacy and regulatory legitimacy are the most important for low, middle and high niche sustainable entrepreneurial enterprises; (2) cognitive legitimacy has a positive impact on the improvement of sustainable entrepreneurial enterprises in the three dimensions of low niche; (3) normative legitimacy has a positive impact on the improvement of sustainable entrepreneurial enterprises in the three dimensions of the middle niche; (4) regulatory legitimacy has a positive impact on the improvement of sustainable entrepreneurial enterprise in both economic and social dimensions, and there is an inverted U-shaped relationship with the improvement of sustainable entrepreneurial enterprise in high ecological niche in environmental dimension.
The main theoretical contributions of this paper are threefold. First, the introduction of the "niche" theory of organizational ecology into the study of organizational legitimacy provides a new solution to the problem of obtaining the legitimacy of sustainable entrepreneurial enterprises, helps to improve the study of the interactive relationship between organizational niche and organizational legitimacy, and enriches and expands the application scope of the niche theory. Second, most existing studies focus on macroscopic population niche or microscopic individual niche, while this paper focuses on the improvement process of individual niche within a population niche from the meso perspective between individuals and populations, which advances the understanding of the connotation and extension of niche theory. Third, it constructs a set of legitimacy scale and niche measurement index system for sustainable entrepreneurial enterprises, which provides a reliable measurement tool for the follow-up research on sustainable entrepreneurial enterprises.
The research results have important practical implications for the development of sustainable entrepreneurial enterprises in China. First, in the low ecological niche of sustainable entrepreneurial enterprises, cognitive legitimacy is the most important, and enterprises should take the acquisition of cognitive legitimacy as the key task of development. Second, in the middle niche of sustainable entrepreneurial enterprises, normative legitimacy is the most important, and enterprises should take normative legitimacy acquisition as the key task of development. Thirdly, in the high ecological niche of sustainable entrepreneurial enterprises, regulatory legitimacy is the most important, and enterprises should take the acquisition of regulatory legitimacy as the key task of development.The findings of the study not only broaden the scope of niche theory research, but also provide new guidance on how to obtain legitimacy for sustainable entrepreneurial enterprises to achieve growth.

In recent years, the industrial robot industry in China has experienced rapid growth and significant development. Industrial robots are widely recognized for their crucial role in facilitating the transformation and upgrading of the manufacturing industry. As a result, the need for high-quality technological innovation within the industry has become more pressing than ever before. However, some scholars have pointed out that a structural imbalance within the industrial innovation chain underlies the industry's development dilemma. By focusing on the cross-layer embedding of innovative agents within innovation networks, this research highlights the importance of collaboration across different stages of the innovation process.
Cross-layer embeddedness underscores the interconnectedness of different stages throughout the innovation process. By analyzing the interactions between science, technology, and product networks, researchers can gain a clearer understanding of how innovations are developed, refined, and ultimately brought to market. By examining how innovation agents are simultaneously embedded within multiple networks, researchers can gain insights into their contributions to the overall quality of innovation outcomes. This study pays special attention to the interaction between different innovation stages. During the innovation process, new discoveries in scientific research can stimulate technological innovation, and the practical application of technology can reveal unknown problems in the field of science. Technological achievements can be transformed into products, and the market application of products can reveal technological shortcomings. Innovation agents within the scientific, technological, and product development networks interact with each other at each stage, creating a cyclical process where each stage influences and propels the progress of subsequent stages. To explore the impact of cross-layer embeddedness of innovative agents within innovative networks on quality outcomes, the study uses interactions of centrality measures in the science and technological network embeddedness, the interactions of centrality measures in the technological and product network embeddedness, the interactions of structural holes in the science and technological network embeddedness, and the interactions of structural holes in the technological and product network embeddedness. These interactions serve as analytical indicators that reflect the characteristics of cross-layer embeddedness of innovation agents.
Using the multi-source heterogeneous data from China′s industrial robot industry collected from 2008 to 2022, the study constructs collaboration innovation networks for science, technology and product, respectively. By calculating network indicators with Ucinet, it then empirically explores the mechanism and scenario conditions of how technological innovation agents′ cross-layer embeddedness contributes to the enhancement of innovation quality. It is found that there is a significant positive impact of the cross-layer embeddedness of innovation agents on innovation quality. Specifically, the more positions the innovator occupies in the structural hole bridge, that is, the higher the degree of control that the innovator has over other innovators in the network, the stronger the connection function in the two-layer network, and thus the higher the innovation quality. However, the extent of cross-layer partner overlap in innovation agents does not appear to moderate the role of cross-layer embeddedness on innovation quality in a significant manner.
In summary, this study introduces an improved measurement method for partner overlap, clarifies the role of situational factors in influencing innovation quality through cross-layer embeddedness, and enriches and deepens existing research dimensions by examining the cross-layer embeddedness of innovative agents within multi-layer networks, approached from an innovation chain perspective.The findings of this study have important implications for policymakers, industry practitioners, and researchers in the field of industrial robotics. By advancing stakeholders′ understanding of the impact of cross-layer embeddedness on innovation quality, they can better strategize and allocate resources to enhance the overall innovation ecosystem. Additionally, the study underscores the necessity for ongoing collaboration and knowledge sharing among various actors in the innovation chain to drive sustainable growth and development within the industrial robot industry. The study provides valuable insights into the dynamics of innovation within the industrial robot industry and offers a framework for understanding the role of cross-layer embeddedness in enhancing innovation quality. By bridging scientific research, technological innovation, and product development, this study lays the groundwork for future advancements in industrial robotics.

Intellectual property is a strategic resource that is crucial to enhancing the overall national interest and fostering comprehensive competitiveness. The Outline for Building a Strong Country With Intellectual Property Rights calls for strengthening the protection of intellectual property rights in the whole-chain, including the creation, application, protection, service and management of intellectual property rights. This new connotation is intended to emphasize the value of a composite system of intellectual property and highlight the importance of a single component of intellectual property. However, the existing research has relatively neglected the research on the intellectual property service subsystem. At the same time, the previous research focused on intellectual property as a single system, in fact, intellectual property management is a complex system, including multiple subsystems, affected by both internal and inter-subsystem. Therefore, this paper establishes a four-in-one management system of intellectual property creation, application, protection and service, adopts a composite system measurement model, builds a composite system of intellectual property whole-chain management and measures the degree of collaboration.
This study focuses on selecting 31 provinces and cities in China (excluding the Hong Kong Special Administrative Region, Macao Special Administrative Region, and Taiwan region of China) as the research subjects. Data pertaining to China's intellectual property whole-chain management from 2001 to 2022 is collected for analysis. According to the whole-chain intellectual property right management composite system model, the study calculates the synergy degree of the intellectual property whole-chain complex system and the synergy degree of the creation, application, protection and service subsystems in 31 provinces and cities, and analyzes the synergy degree of the intellectual property whole-chain in different regions of China from six regions. Finally, it empirically tests the contribution degree of the whole-chain of intellectual property synergy to the economic level.
The results show that, first of all, the degree of synergy of China's regional intellectual property whole-chain composite system is characterized as "being unstable in the middle and superior in the east to the west". With the exception of Tibet, Gansu, Qinghai and Ningxia, China's provinces and cities have reached a moderate level of synergy in intellectual property whole-chain management. Secondly, the intellectual property application system is the weakness of China's intellectual property whole-chain composite system, and its degree of synergy is lower than other subsystems, and its development is relatively slow. The degree of synergy in the subsystem of intellectual property creation continues to rise, but the regional differentiation is obvious. The degree of synergy of the subsystem system of intellectual property protection showed a rising trend after 2010. Before 2014, the synergy degree of intellectual property service system was in a slow development stage, and then showed a rapid rise. Finally, the synergy degree of the intellectual property whole-chain composite system has a certain contribution to economic development, and has a greater role in promoting the economic level of Qinghai, Ningxia and Tibet.
The theoretical contributions of this paper are threefold. First, from the perspective of the whole-chain, the intellectual property service system is included, and an intellectual property compound system of "creation - application - protection - service" is constructed, which is closer to the development status of regional intellectual property in China, and also enriches the existing research on the synergy degree measurement of intellectual property compound system. Second, from the middle perspective, this study focuses on the differences and similarities in the performance of intellectual property synergy among provinces, and puts forward more targeted policy suggestions for the promotion path of the whole-chain of intellectual property synergy among provinces, which is conducive to comprehensively enhancing the effectiveness of the implementation of China's intellectual property strategy. Third, this study confirms the relationship between the degree of synergy of intellectual property complex system and the level of economic development, which not only expands the study of the degree of synergy of intellectual property complex system, but also helps to understand the impact of synergy on regional development. The conclusions have important policy implications to further play the leading role of the government in the collaborative management process of the whole-chain of intellectual property rights in the new situation.

Regional innovation forms the foundation of national innovation, and the improvement of the levels of regional innovation is conducive to improving the levels of national innovation, thereby enhancing the comprehensive strength of the country.In reality, the enhancement of regional innovation performance is the result of the synergistic effects of various complex factors, and it warrants an exploration of the intrinsic connections between influencing factors and regional innovation performance from a holistic perspective.Therefore, the comprehensive study of the necessity and sufficiency of various factors affecting regional innovation, as well as their configuration, is increasingly becoming a hot issue in management research.However, the existing research often focuses on the influence mechanism of a single factor on regional innovation performance, and ignores the impact of the common effect of multiple factors on regional innovation performance.
Informed by the existing literature and TOE theoretical framework, this study adopts the NCA and fsQCA methods and collects the data of 31 provincial-level administrative divisions to study the combined effects and configuration paths of multiple factors such as technology input, technology capability, organization structure, organization linkage, policy environment, facility environment on regional innovation performance.For the TOE research model of regional innovation performance, from the perspective of discrete mathematics and combinatorics, the configuration path is generated by the permutation and combination of six antecedent conditions, and the possibility of predicting the configuration is analyzed by assuming that the higher regional innovation performance can not be achieved only by a single factor combined within the TOE theoretical framework.
The analysis results show that there are three conditional configuration paths.(1) Configuration S1 is based on technical capability, organization linkage and facility environment, and the edge conditions include technology input and organization structure.This indicates that regions exhibiting stronger technological capabilities, denser organizational linkages, and superior facility environments tend to achieve higher levels of regional innovation performance, especially when these regions are characterized by substantial technology input and intricate organizational structures.(2) Configuration S2 is based on technology capability, organization linkage and facility environment and the edge conditions are technology input and policy environment.This shows that on the basis of strong technology capability, dense organization linkages and higher facility environment levels, regions are likely to achieve higher regional innovation performance, especially when they also have access to greater technological input and a more favorable policy environment.(3) Configuration S3 is based on technology capability, organization linkage and facility environment, and the edge conditions refer to organization structure and policy environment.This shows that on the basis of strong technology capability, enhanced organization linkages and higher facility environment levels, regions with more complex organization structures and higher policy environment levels have higher regional innovation performance.
The innovative nature of this study is underscored by its novel double triangle effect of regional innovation performance, which is the core triangle composed of technical capability, organization linkage and facility environment, and the edge triangle composed of technology input, organization structure, and policy environment.The other two edge conditions can be enhanced to equivalently replace a weaker edge condition that cannot be effectively enhanced, so as to supplement the three core conditions, and then promote the improvement of innovation performance in the region.
The NCA method and the traditional fsQCA analysis method adopted in this study has not incorporated the impact of temporal changes.In the future, other models and research paradigms could be adopted to include the effects of time series in the research domain.Besides, Subsequent research can further explore the spatial characteristics of key economic belts from the perspective of geographical economics.

Since the outbreak of the China-American trade friction in 2018, China has faced increasingly severe challenges in key core technology fields. Despite a surge in the number of international patent applications, China's dependence on foreign intellectual property has not diminished, indicating an underlying weakness in innovation quality. Against this backdrop, the “Specialization, Sophistication, Differentiation, and Innovation” (SSDI) policy for small and medium-sized enterprises (SMEs), initiated by China's Ministry of Industry and Information Technology in 2011 and formally implemented in 2018, aims to cultivate “Little Giant” companies that excel in innovation and dominate niche markets. These firms are vital for driving technological innovation, enhancing industrial chain levels, and strengthening international competitiveness. However, while existing research suggests that the SSDI policy has encouraged increased R&D investment and innovation output, there is a paucity of in-depth analysis on whether it effectively improves the quality of corporate innovation. This research aims to contribute to a more comprehensive understanding of the factors that influence innovation policy outcomes. This is crucial for policymakers seeking to refine the SSDI policy and for firms looking to optimize their innovation strategies in the face of evolving market conditions and policy environments.〖HJ*2/5〗
This paper first proposes hypotheses on the impact and mechanisms of the SSDI policy on the technological innovation of “Little giant” enterprises, as well as the differential effects of the policy under varying levels of market transparency through a theoretical model. Further, this paper utilizes data from listed companies on the Shanghai and Shenzhen A-shares market from 2018 to 2023 which is sourced from the CSMAR and CNRDS databases, and employs a multi-period difference-in-differences (DID) method to test the above hypotheses. The research findings reveal that the SSDI policy significantly enhances both the innovation quality and quantity of “Little Giant” enterprises. Moreover, the policy has a gradient promotion effect, meaning that “Little Giant” enterprises outperform provincial and municipal SSDI enterprises in terms of technological innovation levels, and the latter, in turn, outperform other enterprises. By alleviating financing constraints, providing risk compensation, and promoting the accumulation of human capital, the SSDI policy substantially improves the innovation performance of “Little Giant” enterprises. In terms of human capital, it is the high level of human capital that is the key factor in improving the innovation quality of “Little giant” enterprises. Further research finds that the enterprises adopt different innovation strategies under varying levels of corporate information transparency. Specifically, when corporate information transparency is low, “Little Giant” enterprises receiving SSDI policy support tend to opt for strategies that increase the quantity of innovation rather than its quality, thereby engaging in “innovation pandering” behavior. In contrast, when corporate information transparency is high, the SSDI policy effectively promotes the innovation quality of “Little Giant” enterprises. These findings are pivotal as they not only substantiate the SSDI policy efficacy but also highlight the conditional nature of this effectiveness, contingent upon the level of corporate information transparency. By revealing the differential impact of the policy in various market conditions, this study offers valuable insights for policymakers aiming to refine the SSDI policy and for “Little giant” enterprises seeking to optimize their innovation strategies.
The possible marginal contributions of this paper are threefold. Firstly, current research on the effect of the SSDI policy mostly focuses on the quantity of innovation, this paper examines the impact of the policy on both the quantity and quality of enterprise innovation at the same time, which helps to comprehensively assess the effect of the policy. Secondly, most of the existing innovation policies only support technological innovation of enterprises from the aspect of financial support, and lack the design of human capital incentives. This paper not only analyzes the role of financial support of the policy, but also pays special attention to the role of different human capitals in the process of innovation, which provides an important idea for the incentive design of the innovation policy. Thirdly, the impact of innovation policy on the quality of enterprise innovation is controversial, and why the effect of the SSDI policy remains to be further analyzed. Following the information asymmetry theory, this paper analyzes the differentiated innovation strategies that enterprises may adopt under different market transparency conditions, and emphasizes the importance of constructing a transparent and efficient market information mechanism to stimulate the innovation vitality of enterprises.

As an important part of the global economy, family businesses exert significant economic and social influence in many countries, but very few of them are passed on to the third, fourth and subsequent generations. Strategic entrepreneurial behavior is an effective tool for family businesses to break the pattern of short life spans. Enterprises that implement strategic entrepreneurship often show stronger vitality and development potential, and can quickly adjust their strategies, seize opportunities, and create unique competitive advantages in the face of market changes and competitive pressure. Intergenerational involvement is a dynamic process of changing the ownership and management rights from the first generation of founders to the second generation of successors in a family business, which involves the investigation, selection and training of successors, and requires a scientific intergenerational involvement system. Previous studies have focused on the influence of institutional factors such as family governance, professional managers, and familial culture on the strategic entrepreneurial behavior of family firms in the process of intergenerational involvement of family firms. However, since the strategic goal of the family business is not only to obtain economic gains, it must take into account the non-financially oriented family logic, emphasizing collectivity, loyalty and continuity. Additionally, the phenomena of "cronyism" and "circle culture" in Chinese society add complexity to the intergenerational involvement and strategic entrepreneurial behavior of family firms. Merely applying causal symmetry to understand this relationship between intergenerational involvement and strategic entrepreneurial behavior of family enterprises may result in a one-sided view.Therefore, it is necessary to further explore the influence of multiple intergenerational involvement systems on the strategic entrepreneurial behavior of family firms.
From the perspectives of the interaction and symbiotic evolution of the formal system, informal system and strategic entrepreneurship involved in the intergenerational involvement of family firms, this study takes 34 family firms as case samples to analyze the conditional and obstructive factors affecting the strategic entrepreneurial behavior of family firms from a configuration perspective. This study attempts to answer two questions: Can a single element of the intergenerational involvement system drive the strategic entrepreneurial behavior of family firms? What are the intergenerational institutional entities that drive strategic entrepreneurship? The conclusions are as follows: (1) A single condition of the intergenerational involvement system is not a necessary factor to drive the strategic entrepreneurship of family businesses, and the single elements of second-generation multiculturalism, family entrepreneurship,family governance system, leadership identity, and family institution setting are not the necessary conditions for improving strategic entrepreneurial behavior, and the complex combination of multiple conditions in the intergenerational involvement system is the effective path to improve strategic entrepreneurial behavior. (2) There are three configurations that lead to high-strategic entrepreneurial behaviors, which can be summarized as the triple helix driven by "regulation-cognition-norm", the four-dimensional drive of "regulation-norm-cognition-identity", and the coupling type of formal system and informal system substitution.
This study explores the linkage effect of different subdivisions of the intergenerational involvement system of family firms on the strategic entrepreneurial behavior of family firms,offering three key contributions: First, it addresses gaps in existing research by analyzing strategic entrepreneurial behavior through the lens of intergenerational involvement, moving beyond prior focus on individual traits (e.g., gender or cultural background of successors), and thus it enriches the research on the influencing factors of strategic entrepreneurial behavior of family firms. Second, from the configuration perspective, this study empirically explores the synergistic driving effect of five key factors at the two levels of formal system and informal system of intergenerational involvement of family firms on strategic entrepreneurial behavior, which is a useful supplement to the existing literature. By revealing three driving paths of strategic entrepreneurial behavior of family firms, this paper opens the "black box" of the research on the driving mechanism of strategic entrepreneurial behavior, and further reveals the differences between the driving mechanisms of strategic entrepreneurial behavior among different family firms. Third, the findings suggest actionable strategies for family firms, including adopting best practices, innovating formal systems (e.g., succession planning), and leveraging informal systems (e.g., trust-building) to enhance entrepreneurial outcomes.

With the advancement of the global digital wave, digital technologies such as big data, the Internet of Things, and artificial intelligence are rapidly developing and penetrating into economic, social, and cultural fields. This has given rise to some enterprises that rely on digital technology for rapid development and those that have successfully caught up through digital transformation. Digital transformation has become an important opportunity and challenge for most enterprises, facing a situation of 'either transformation or elimination'. However, in the digital transformation practice of traditional enterprises, some companies are still in a wait-and-see state, lacking the motivation for transformation. Others rely on third parties for local digital transformation or purchase industrial software from large IT companies. This results in transformation being limited to certain local links of the value chain, with digital resources operated separately from traditional resources, making it difficult to achieve maximum efficiency. As an important component of new quality productivity, advanced manufacturing has leading advantages in technology, management, and concepts. Its digital transformation performance is better than that of traditional manufacturing enterprises, and digital resources are more easily integrated with traditional resources. Its transformation practice has a demonstrative effect. Therefore, this study aims to explore the internal and external driving factors of digital transformation in advanced manufacturing industries and discuss different driving modes to leverage the leading-the-way effect and stimulate the industrial vitality. This has important practical significance for enhancing the international competitiveness of the manufacturing industry and promoting overall transformation and upgrading.
This study explores the driving pathways of advanced manufacturing enterprises in the process of digital transformation by constructing a theoretical framework based on resource orchestration theory. This framework is referred to as the "external environmental pressure-internal resource orchestration" model. By using extended necessary condition analysis (E-NCA) and fuzzy set qualitative comparative analysis (fsQCA), an empirical analysis was conducted on 43 listed advanced manufacturing companies. The objective is to identify the key factors influencing corporate digital transformation and to examine their interactions.
The study finds that there is no single condition variable alone constitutes a necessary condition for digital transformation, with the bundling of process resource playing a central role in all configurations. Four patterns are identified that promote digital transformation in enterprises: (1) digital technology integration driven by business environment incentives, (2) digital scenario transition driven by business environment incentives, (3) organizational reshaping influenced by dynamic competition, and (4) organizational reshaping supported by government digital attention. These patterns not only deepen the understanding of antecedent variables in digital transformation but also provide specific guidance for managers on how to effectively allocate and combine resources in the digital age.
The theoretical contributions of the study are threefold. First, on the basis of the "external environmental pressure-internal resource orchestration" framework, it identifies configurations that promote the digital transformation of advanced manufacturing enterprises, and reveals the joint mechanism between environment and organization in the digital transformation process. Second, it highlights that the transformation driving pathways of advanced manufacturing enterprises at the current stage significantly differ from traditional manufacturing companies. Advanced manufacturing enterprises stronger focus on "continuous digitalization". Finally,by integrating the resource orchestration process with specific corporate resource practice, the study defines and measures data resource structuring, process resource bundling, and ecosystem resource leveraging, thereby extending the resource orchestration theory.
In terms of managerial implications, the study suggests that corporate managers should shift from linear thinking to system thinking, pay close attention to the external environment, and formulate digital transformation plans aligned with corporate development. Concurrently, it is essential for advanced manufacturing enterprises to accurately identify and leverage data resources, process resources, and ecosystem resources. Additionally, advanced manufacturing enterprises should establish an interconnected industrial ecosystem and foster ecosystem value through open innovation and platform-based strategies. Furthermore, governments should strengthen digital capability, optimize the development environment of industrial clusters, and activate the synergistic effects of industrial clusters through supportive policies and innovation platforms, which ultimately promoting the effective allocation and sharing of resources. Overall, this study provides theoretical guidance and practical recommendations for advanced manufacturing enterprises undergoing digital transformation and makes a significant contribution to promoting corporate transformation and enhancing international competitiveness.

With the trend of multi-technology products and multi-application technologies, technology diversification has become the basis for scientific and technological innovation teams (S&T innovation teams) to conduct research. S&T innovation teams are the main inventors of patents. Although some S&T innovation teams have mastered diversified technical knowledge, they cannot fully utilize the varied knowledge of their team members because they fail to understand how technology diversification affects the disruption of patents, leading them to fall into the 'technology diversification trap'. Therefore, it is of practical significance to study the impact mechanism of technology diversification within S&T innovation teams on the disruption of team patents.
Building on existing research into technology diversification and patent disruption, this paper makes two novel contributions. First, from the perspective of the scientific research subject of enterprises and other organizations—S&T innovation teams, this study focuses on the impact of the degree of technology diversification of S&T innovation teams on the disruption of their patents. Second, by drawing on the concepts of 'pre-event learning', 'during-event learning', and 'post-event learning' from knowledge management, the indicators of patent disruption are innovatively reorganized by logically structuring the events before the patent is generated, during the invention process, and after its publication. This leads to the development of corresponding multi-factor indicators of 'pre-event', 'during-event', and 'post-event', thereby proposing a three-stage factor indicator system of patent disruption from the perspective of S&T innovation teams. The aim is to explore the impact of the degree of technology diversification on the disruptive factors of the three stages of invented patents.
First, this study identifies and calculates the technological diversification levels of these innovation teams. Second, it proposes a three-stage factor indicator system for patent disruption from the perspective of innovation teams (pre-event, during event, post-event). Finally, statistical analysis methods are utilized to measure the effects of technological diversification on the three-stage factors of patent disruption and to conduct robustness tests. The phenomenon of technological diversification in the field of artificial intelligence, along with the evident data characteristics of relevant indicators across the three stages, is examined in this study.
Empirical results show that the technological diversity of S&T innovation teams in the field of artificial intelligence has different impacts on factors at various stages of team patent disruption. (1) Among pre-event factors, technological diversification shows a significant negative effect on the novelty of team patents. (2) In terms of during-event factors, the higher the team′s level of technological diversification, the lower its R&D coefficient; that is, the number of patents per inventor and applicant is low. (3) In terms of post-event factors, the higher the technological diversity of the S&T innovation teams, the greater the number of patent citations and market potential. (4) In addition, differing from existing literature, this study proves that the degree of team technological diversification has no significant correlation with the growth and scale of the team's patent disruptive pre-event factors. This demonstrates that the technological diversification of the S&T innovation teams does not increase the disruptive level of the patents invented by the team through selecting high-growth or large-scale subdivisions prior to invention.
This research enriches the existing logic for constructing indicator systems related to patent disruption by introducing the pre-event, during-event, and post-event concepts, and for the first time, analyzes the impact of technological diversification on patent disruption from the perspective of S&T innovation teams. This provides insights for assembling high-level S&T innovation teams and enhancing patent disruption levels: team members with different knowledge backgrounds are often better positioned to understand market demand and integrate multiple technologies, which can enhance the market potential and citation volume of patents, crucial for teams to distinguish themselves in competition. However, the negative impact of technological diversification on the novelty and R&D coefficients is also worthy of attention, indicating that in the process of pursuing technological diversification, S&T innovation teams should balance the pursuit of technological diversification with the maintenance of innovation uniqueness and the enhancement of R&D efficiency.

Amid the drive for high-quality innovative development, Chinese local governments are prioritizing talent attraction as a means to boost regional innovation. However, attracting talent does not equate to fostering innovation. Whether talent subsidies can truly motivate employees to innovate remains underexplored, leading to gaps in understanding the theoretical and empirical links between the two. Existing research has primarily examined the impact of talent subsidies on innovation at the enterprise or regional level, yielding mixed results. Delving into the micro-mechanisms of how talent subsidies drive employee innovation can not only enrich macro-level research but also offer practical insights for governments and enterprises in leveraging talent subsidy policies effectively. Meanwhile, the literature on social identity in organizational contexts highlights the need to investigate how social policies and socialized identities influence employees' social identity and motivation. Talent subsidies typically involve monetary subsidies, yet its role in motivating innovation is debated. Beyond financial benefits, receiving a subsidy confers a "talent" status, creating a sense of in-group identity that can enhance employees' self-esteem and learning motivation, ultimately stimulating innovative behavior. Thus, this paper employs social identity theory to analyze how talent subsidies trigger social identity and incentivize innovation, addressing the deficiencies in prior studies.
The measurement data for model variables was collected through a structured questionnaire survey, and full-time employees who received government talent subsidies were recruited via the academic research platform "Credamo" in November 2023. The participants were from 30 provinces, cities, and autonomous regions across China, including major economic hubs such as Beijing, Shanghai, and Shandong. The respondents represent diverse industries, including manufacturing, electronic information, renewable energy, finance, and others. To mitigate common method bias, the questionnaire was administered in three distinct phases. A total of 468 valid responses were collected, yielding an overall response rate of 89.5%. Following the completion of variable measurements, a series of analyses were conducted, including tests for common method bias, confirmatory factor analysis, and assessments of main effects and mediating effects. The findings indicate that employees' receipt of government talent subsidies does not directly increase their innovative behavior. Instead, the subsidies enhance innovative behavior indirectly by significantly boosting employees' self-efficacy. External motivation plays a significant moderating role in this relationship. When employees' external motivation is high, the positive effects of talent subsidies on self-efficacy and innovative behavior diminish, and the capacity to motivate innovation is lost. Additionally, compared to the perceived value of talent subsidies, the implementation of human resource management (HRM) practices—such as the amount of talent subsidies provided—has a weaker incentive effect on employees' self-efficacy and innovative behavior.
In terms of theoretical contributions, firstly, this paper provides a micro-mechanical explanation of the impact of government talent subsidy policies on employees' innovative behavior; secondly, this paper uses talent subsidies as a social policy as a social identity antecedent, responding to the academic community's call to strengthen research on the social identity of groups outside the organization and its impact; thirdly, this paper verifies the negative moderating effect of external motivation, expanding the boundaries of social identity in motivating employee behavior; finally, it verifies the difference in the motivational effect and boundary between the amount of talent subsidies and employees' perception of them, contributing to the implementation of human resource management practices and the perception literature.
In practice, companies can help employees achieve "social recognition" and boost innovation by publicly recognizing their achievements, offering additional rewards, and providing knowledge and skills training. To mitigate the negative impact of external motivation, companies could tie subsidies to skill development tasks in performance evaluations. Employees not receiving subsidies may experience psychological disadvantages or feelings of unfairness due to social comparisons, and thus companies should address this by increasing salary, showing more care, and organizing team-building activities to motivate all employees to participate in innovation. Governments should optimize talent subsidy policies by expanding their scope, increasing intensity, and directing them strategically. This includes extending subsidies to more employees, providing group subsidies for research teams and enhancing overall innovation efficiency.

To efficiently execute various innovative tasks within teams, members strive to transform teamwork characteristics from bottom to top, autonomously determining which aspects of the work should be retained or discarded. That is, member job crafting runs through the entire innovation process of teams, thus having a profound impact on team creativity. It is worth noting that variations in KSAOs (knowledge, skills, abilities and others) among team members will naturally result in differences in the extent to which they customize their work methods or processes, leading to the inevitable and significant phenomenon of job crafting differentiation within teams.
Thus, using the categorization-elaboration model (CEM), this study explores when and how team member job crafting differentiation affects team creativity by building up a mediated moderation model. It analyzes the data by SPSS from 64 teams, including 343 members with a multiple-source and time-lagged research design and examines the moderating role of team peer monitoring and the mediating role of team knowledge integration. It is found that, first, team member job crafting differentiation has a double-edged sword effect on team knowledge integration, and team peer monitoring significantly moderates the relationship between team member job crafting differentiation and team knowledge integration. Specifically, under high-level team peer monitoring, team member job crafting differentiation can promote team knowledge integration. However, under low-level team peer monitoring, team member job crafting differentiation can hinder team knowledge integration. Second, team knowledge integration affects team creativity positively. Third, team knowledge integration mediates the influence of the interaction of team member job crafting differentiation and team peer monitoring on team creativity. To be more specific, under high-level team peer monitoring, team member job crafting differentiation can promote team creativity via team knowledge integration. However, under low-level team peer monitoring, team member job crafting differentiation can hinder team creativity through team knowledge integration.
This study unveils the double-edged sword effect of team member job crafting differentiation on team creativity, highlighting a significant theoretical breakthrough in elucidating the influence mechanism of such differentiation on team creativity. It establishes a crucial theoretical foundation for proactively mitigating the adverse effects of team member job crafting differentiation while harnessing its positive outcomes. Furthermore, the research indicates that team peer monitoring acts as a moderating factor in the relationship between team member job crafting differentiation and team knowledge integration, broadening the application scope of team peer monitoring. Additionally, the study delves into the mediating role of team knowledge integration in the interplay between team member job crafting differentiation and team peer monitoring, specifically on team creativity. The conclusion underscores the necessity for scholars to delve deeper into the intricate dynamics between team member job crafting differentiation and team creativity, thereby enriching their understanding of the process mechanism governing team member job crafting differentiation and its impact on team outcomes, particularly team creativity.
There are some practical implications. First, for team leaders, it is essential to recognize the inevitability of team member job crafting differentiation and its dual impact. Leaders can optimize task allocation by leveraging the strengths of individual team members, enabling them to maximize their potential while minimizing time and energy wasted on constant work process adjustments, ultimately fostering team creativity. Additionally, enhancing communication between leaders and team members is crucial to preempt potential conflicts arising from job crafting differentiation and cultivate a better climate for generating novel and valuable ideas. Second, a heightened focus on team peer monitoring is warranted. Elevated levels of team peer monitoring foster a shared sense of purpose among members, so that they will perceive job crafting differentiation as a natural occurrence, thereby facilitating knowledge integration and bolstering team creativity. Besides, team members can provide each other with clear clues about tasks through team peer monitoring, and members are closely connected with each other, which is conducive to improving team enthusiasm,and further enhances contact among members. Last, team leaders should prioritize the positive influence of team knowledge integration on team creativity. Encouraging active knowledge integration among team members is pivotal for efficiently tackling innovative tasks,for it will ultimately amplify team creativity.

In the digital era, the development of virtual agglomeration has enabled enterprises to become organizations that are not constrained by geographic boundaries, characterized by integration and synergy. While as data becomes a new production factor, organizations need to develop digitalization capabilities to harness the value of data elements, improve the level of synergy and operational efficiency, and adapt to the development trend of virtual agglomeration.This adaptation is essential for securing new spaces for growth and gaining competitive advantages. Against this backdrop, this study analyzes digitalization capabilities from the perspective of virtual agglomeration, including the formation, structure, and influence of digitalization capabilities in order to provide a systematic research model.
Firstly, this study defines the concept of organizational digitalization capability from the perspective of virtual agglomeration. Most of the research on digitalization capability in the literature focus on individual organizations at the micro level, and it is less likely to put digitalization capability into the organization's virtual agglomeration to study, and it has not formed a systematic system. This research defines digitalization capability as an organizational capability system that emerges from the application of digital technology to integrate the internal and external capabilities of an organization and create value. The aim is to optimize business synergy and resource sharing of interenterprise and obtain the scale effects of resources that virtual agglomeration can provide.
Secondly, this study discusses how organizations within virtual agglomerations form digitalization capabilities and what conditions and mechanisms are involved in their development. Considering the characteristics of virtualization and agglomeration, the analysis of digitalization capability formation is categorized based on virtual and agglomeration orientations. On the virtual orientation side, effectively linking organizations across different geographic spaces to achieve agglomeration requires the use of digital technology; the abundance of resources can exponentially enhance organizational capabilities in the virtual space; virtualization has led to a fragmented marketplace, necessitating that organizations strengthen their ability to adapt to market changes. Thus, the conditions for the formation of digitalization capabilities are driven by technology, resource, and market.On the agglomeration orientation side, inter-organizational links are needed to form agglomerations, and an efficient link is a fundamental requirement for the formation of digitalization capabilities; advantaged organizations can assist disadvantaged organizations by coordinating agglomeration activities to promote this capability; inter-organizational cultural distance makes cooperation unstable, and there is a need to build a culture of agglomeration and enhance trust. Therefore, the conditions for the formation of digitalization capabilities includes linkage, empowerment, and cultural factors.
Next, it explores and analyzes the structure of organizational digitalization capability in virtual agglomeration, and reviews the development of measurement methods. Because of the different research contexts and target objects, the structure of digitalization capabilities is divided into different levels. Virtual agglomeration emphasizes the interconnection between organizations, and these organizations formed can be conceptualized as a network organization composed of nodes and links, and the measurement of digitalization capabilities should focus on these two aspects. Additionally, considering integration, platform, and smart attributes is crucial. This study outlines key digitalization capability measurement approaches: using established scales for preliminary assessment, identifying substitute objective indicators, and employing grounded theory methods. However, these measurement methods are not accurate,highlighting a need for innovative measurement techniques tailored to virtual agglomeration contexts.
Finally, the influence of digitalization capabilities on organizations and the mechanisms of action are summarized. This study concludes that the direct influence of digitalization capability on agglomeration is manifested in agglomeration upgrading. Specifically, the influence of digitalization capability on agglomeration upgrading is reflected in the products, processes, and models. In addition, the analysis of the influence mechanism process shows that the agglomeration environment plays a moderating mechanism in the aftereffect of digitalization capability on agglomeration; while the dynamic capability plays a mediating mechanism in the after-effect of digitalization capability on agglomeration. This study broadens the theoretical framework for understanding organizational digitalization capabilities. It offers a more nuanced comprehension of the development, composition, and post-implementation dynamics of digitalization capabilities. Furthermore, it furnishes novel research insights and directions, enhancing the execution of digitalization capability initiatives within virtual agglomeration.