Strategic entrepreneurship is recognized as a pivotal force for firms to gain a competitive edge in the dynamic and complex business environment. This study delves into the intricate dynamics that propel strategic entrepreneurship by constructing a theoretical model that incorporates network orientation and slack resources as independent variables, while entrepreneurial orientation as a mediating variable and competitive intensity as a moderating variable, offering a comprehensive lens through which to examine the driving mechanism of strategic entrepreneurship. The study adopts a robust methodological approach,employing both hierarchical regression and fuzzy set qualitative comparative analysis (fsQCA) to analyze data collected from 325 manufacturing enterprises in China. These methods allow for a nuanced understanding of the complex causal pathways that lead to strategic entrepreneurship, moving beyond simple correlation by the traditional regression methodology to explore the configuration of conditions that enable it.
The findings contribute to the literature by revealing the nuanced relationship between network orientation, slack resources, and strategic entrepreneurship. Specifically, the study uncovers an inverted U-shaped relationship, suggesting that while moderate levels of network orientation and slack resources are beneficial for strategic entrepreneurship, extreme levels may become detrimental. This underscores the importance of balance and suggests that firms must be judicious in their management of these resources. In other words, network orientation is an important channel for enterprises to access external resources, while slack resources provide a material basis for innovative activities from within the enterprise. As a resource-consuming organizational behavior, strategic entrepreneurship needs the support of network orientation and slack resources. However, excessive network orientation or excess slack resources can lead to management problems such as rising costs and path dependence, which in turn negatively affect entrepreneurial orientation or strategic entrepreneurship. Moreover, the study highlights the mediating role of entrepreneurial orientation, demonstrating how it links network orientation and slack resources to strategic entrepreneurship. This finding emphasizes the centrality of entrepreneurial orientation in the process of strategic entrepreneurship, suggesting that firms must cultivate an entrepreneurial mindset to effectively leverage their resources and seize opportunities. Meanwhile, this study has identified the moderating effect of competitive intensity, showing that competitive intensity enhances the relationship between entrepreneurial orientation and strategic entrepreneurship, as well as between network orientation and strategic entrepreneurship. This suggests that in highly competitive markets, firms may need to intensify their entrepreneurial activities, and properly manage their network engagements to achieve strategic entrepreneurship. However, the study also finds that competitive intensity does not significantly moderate the inverted U-shaped relationship between slack resources and strategic entrepreneurship. This means that, when properly managed, slack resources have a more direct impact on strategic entrepreneurship and may not change significantly depending on the level of competition in the market.
Through fsQCA analysis, the study identifies two distinct paths to high-level strategic entrepreneurship: the resource-driven path and the opportunity-driven path. The resource-driven path suggests that firms can achieve strategic entrepreneurship by integrating slack resources and entrepreneurial orientation in low-competition markets. The opportunity-driven path indicates that strategic entrepreneurship can be achieved through the synergistic effect of opportunities and resources from both internal and external sources. At the same time, the study also identifies two paths leading to non-high-level strategic entrepreneurship, characterized by entrepreneurial motivation deficiency and resource constraints. These paths highlight the challenges that firms may face in their pursuit of strategic entrepreneurship and suggest areas that require attention and improvement. These findings reaffirm that strategic entrepreneurship is a dynamic and complex process shaped by the interaction of multiple factors.
In conclusion, this study provides a comprehensive examination of the driving mechanism of strategic entrepreneurship, contributing to both theory and practice. The findings offer valuable insights for firms seeking to navigate the complex landscape of strategic entrepreneurship and highlight the importance of balancing various factors to achieve sustainable competitive advantage. By understanding the complex interplay among network orientation, slack resources, entrepreneurial orientation, and competitive intensity, firms can more effectively chart their path toward strategic entrepreneurship.

Technology M&A constitute one of the most crucial approaches to enterprise open innovation. It not only exhibits a booming development trend in practice but also receives strong support from the government, thus emerging as an important strategic measure for promoting the innovative development and enhancing the competitiveness of enterprises. According to different motives, technology M&A can be classified into two types: technology-related M&A and technology-diversified M&A. Technology-related M&A enable enterprises to acquire and internalize the knowledge base of target enterprises, effectively enhancing their core competitiveness. However, it also has the drawback of limited exploration space in new research fields. Technology-diversified M&A bring enterprises opportunities to apply new technologies, but they also face challenges in technology integration. In this context, clarifying the complex driving mechanisms behind enterprises' technology M&A decisions has become an important research issue.
Existing research often uses empirical methods, focusing on specific factors without comprehensively exploring multi-dimensional influences or considering internal and external perspectives. Additionally, most studies do not classify M&A samples by motives, leading to inconsistent or contradictory conclusions. This study employs the TOE framework and fsQCA method to analyze the multi-dimensional factors and their interactive mechanisms in technology-related and technology-diversified M&A decisions, aiming to provide a more holistic understanding of the driving forces behind these strategic choices.
The results indicate that first, technology M&A decisions are influenced by three dimensions of conditional variables: technology, organization, and environment. The condition combination of technology-related M&A is not the reverse condition combination of technology-diversified M&A. Second, the study identifies seven distinct pathways for technology-related M&A: (1) technology-driven, (2) dual-wheel driven by patent quantity and institutional factors, influenced by profit-seeking executives, (3) dual-wheel driven by technology and market factors, (4) dual-wheel driven by technology and market factors, influenced by profit-seeking executives, (5) dual-wheel driven by patent quality and environmental factors, influenced by profit-seeking executives, (6) dual-wheel driven by technology and organizational factors, and (7) a "desperate" type driven by urgent needs. Similarly, seven pathways are identified for technology-diversified M&A: (1) driven by internal and external challenges, (2) driven by enterprise scale and profit-seeking executives, (3) precautionary-driven, (4) driven by executive decisions and environmental factors, (5) driven by executive decisions and market factors, (6) imitation-driven, and (7) institutionally driven. These pathways highlight the diverse and complex mechanisms underlying M&A decisions, reflecting the interplay of internal and external factors as well as strategic motivations. Finally, a comparison of the driving paths of technology-related M&A and technology-diversified M&A reveals that enterprises with robust technological foundations are more likely to engage in technology-related M&A, whereas those with weaker technological foundations tend to pursue technology-diversified M&A. State-owned enterprises and large-scale enterprises show a greater inclination towards technology-diversified M&A. Technology-related M&A typically occur when executives are profit-driven and the external environment is favorable, while technology-diversified M&A often occur in situations where executives are cautious and the external environment is favorable.
This study presents potential contributions as follows. Theoretically, by adopting the fsQCA research method which is adept at handling multiple concurrent causation, this study comprehensively examines the driving factors of technology M&A decisions from three aspects: technology, organization and environment, thereby presenting the multi-dimensional influencing factors and their interaction and matching mechanisms in technology M&A decisions. It deepens the academic community's understanding of the antecedents of technology M&A and helps scholars of consequence research to fundamentally explain the core question of "why enterprises achieve different performance in technology M&A". Practically, the study provides several actionable insights. First, it emphasizes the importance of analyzing M&A outcomes from a multi-dimensional perspective rather than attributing success or failure to a single factor. Second, through a comparative analysis of pathways, the study comprehensively outlines the driving paths for both technology-related and technology-diversified M&A. This enables stakeholders, including governments and shareholders, to better understand the motives behind M&A activities, facilitating targeted management strategies and improving the success rate of technology M&A. Finally, the study suggests that enterprises can use these driving paths to anticipate competitors' M&A decisions, and take preventive and responsive measures in advance. Similarly, governments can leverage these insights to assess the future development of enterprises and provide more effective guidance and support.

In the context of the rapid advancement of new technological revolution and industrial transformation,key core technologies serve as a decisive force in enhancing national competitiveness and ensuring national security, directly influencing a country′s ability to seize the initiative in international strategic competition. Unlike general technologies, key core technologies encompass a series of continuously evolving innovation processes, including knowledge innovation, technology incubation, and the development of key products. The complexity and dynamics of these technologies have led to a lack of consensus in research concerning their definition and identification. This paper thus focuses on the issue of innovation breakthroughs in key core technologies from multidimensional perspectives, including knowledge, technology, and industry. Existing literature primarily emphasizes single-dimensional analyses of knowledge, technology, or industry, without fully developing a comprehensive theoretical framework that encapsulates the intricate dynamics of an integrated innovation system. Moreover, the dynamic and complex coupling interaction mechanisms between system innovation actors during technological breakthroughs, as well as the laws of technological evolution, remain areas in need of further investigation. Therefore, this paper, from the perspective of multi-layer coupled networks, explores the characteristics and evolution of the "knowledge-technology-industry" (KTI) coupled innovation system for key core technologies.
This study first defines the concept of key core technologies. Next, it delves into the analysis of the KTI coupled innovation system through the lens of a multi-layered coupled network approach, which reveals the core logic of innovation. This logic is structured around a sequence of stages: starting with fundamental knowledge innovation, proceeding to breakthroughs in technological principles, and culminating in the development of new technologies. On the basis of the definition of key core technologies and system characteristics, a method for identifying such technologies based on multi-layer coupled innovation network analysis is proposed. This method integrates complex network topology feature measurements, higher-order invariant models, and multiple PageRank centrality algorithms. Finally, the study explores the evolutionary characteristics and critical conditions of the KTI coupled innovation system at different stages of its lifecycle and proposes future research directions to promote breakthroughs in key core technologies.
The results show that the multi-layer coupled innovation network of key core technologies exhibits both multi-layeredness and coupling, with corresponding nodes displaying dynamic core and critical properties. To refine the concept of key core technologies, it is essential to adopt a holistic approach that transcends the examination of individual technologies or isolated layers. The process should initiate with a thorough evaluation of the foundational technological knowledge, the underlying structural framework, and the platforms facilitating transformational applications.A significant focus should be on the (KTI) coupled innovation system, which is central to understanding the complex interactions and couplings between knowledge, technology, and industry subsystems. By analyzing the joint effects within and between layers of knowledge, technology, and collaborative R&D networks in the multi-layer coupled network, key core technologies can be identified. The pursuit of breakthroughs in key core technologies is a dynamic and long-term systemic challenge. By analyzing the stage-specific characteristics and critical conditions of the KTI coupled innovation system′s lifecycle and designing network governance mechanisms, the effectiveness and resilience of system innovation can be enhanced, facilitating breakthroughs in key core technologies.
This paper introduces innovation system theory and complex system theory, providing new research perspectives and directions for the multidimensional exploration of the KTI coupled innovation system. It also offers new methods for exploring the dynamic and complex coupling interaction mechanisms among actors within the innovation system. On the basis of the evolution of the KTI coupled innovation system, the paper investigates the evolution patterns and breakthrough development directions of key core technologies. The paper provides theoretical and methodological support for systematically understanding the essence and evolution of key core technologies, guiding innovation actors in overcoming technological bottlenecks. The findings are crucial for promoting the effective coupling of innovation resources and R&D needs, formulating technological innovation policies and strategic plans by governments and management departments, achieving independent and controllable key core technologies, and ensuring national security and international competitiveness.

In the digital economy era, the traditional boundaries between enterprises and the market are gradually being dismantled. The deep integration of digital technology and production operations has become a crucial driver of innovation and development. By further stimulating group wisdom and deepening open innovation through this integration, manufacturing enterprises can gain a competitive edge. However, Chinese manufacturing enterprises currently face challenges in leveraging digital technology to promote open innovation. There is a lack of scientific and systematic theoretical methods to guide their efforts. Additionally, research on the composition of digital technology affordance and its mechanisms in promoting open innovation is still limited. This gap makes it difficult for enterprises to effectively implement open innovation strategies that are well-adapted to the complex and dynamic environment of the digital economy.
Drawing to technology affordance theory, this study delves into how the accumulative and variable affordances of digital technology drive open innovation in manufacturing enterprises. To ensure sample representativeness, the study selects four types of manufacturing enterprises undergoing digital transformation, namely "digital transport equipment manufacturing", "digital general and special-purpose equipment manufacturing", "digital electrical machinery,apparatus and instrument manufacturing", and "other smart manufacturing", based on the "Classification of Digital Economy and Its Core Industries (2021)" released by the National Bureau of Statistics. It also selects samples from enterprises in regions with different levels of digital development. The study employs a combination of paper-based and e-mail questionnaires to survey middle- and senior-level managers in relevant enterprises, using a multi-time-point data collection method to reduce common method bias and better capture the relationships between variables.
By empirically examining data from a sample of 312 manufacturing firms, the study finds that (1) both accumulation affordance and variation affordance have a significant positive impact on open innovation in manufacturing firms; (2) resource reorganization and resource relocation are key links connecting the affordance of digital technologies and open innovation in manufacturing firms, playing a partly mediating role; (3) managerial digital cognition is an important internal contextual factor in the process of enterprise digital transformation, which can enhance the effect of cumulative affordance on resource relocation, and at the same time improve the effect of variable affordance on resource reorganization; while it does not play a significant moderating role in the relationship between cumulative affordance and resource reorganization, and variable affordance and resource relocation.
This study makes both theoretical and methodological contributions as follows. First, it develops a novel theoretical analytical framework of 'digital technology affordance-resource reconfiguration-open innovation', which remedies the insufficient explanatory power of existing theories regarding the impact mechanism of digital transformation on open innovation in manufacturing enterprises. Second, it empirically verifies the role of managerial digital cognition in the transmission pathway through which digital technology affordance affects open innovation, thus further clarifying the key boundary conditions for effective open innovation in the context of manufacturing digital transformation.
From a practical perspective, the findings imply that manufacturing firms should take business needs as the guide and advance open innovation by integrating accumulative and variable affordances in a coordinated manner. Meanwhile, enterprises need to leverage the "multiplier effect" of digital resources and expand the scope of open innovation by utilizing market data to accurately capture customer demands and potential business opportunities, dynamically reshaping resource systems to enhance organizational agility, and adopting data analytics to explore new approaches to resource utilization and optimize targeted resource reallocation. In addition, organizations should actively upgrade managerial digital cognition to provide core strategic support for the formulation and implementation of innovation-driven development strategies in the digital era. This can be achieved by regularly conducting training programs on digital technology applications and data element utilization, as well as by strengthening managers' understanding and mastery of the underlying logical framework and architecture of digital operation systems.

The transformation to intelligent manufacturing is a crucial pathway for Chinese enterprises to achieve high-quality development and serves as a key strategy for advancing new industrialization and enhancing new productive forces. However, existing literature predominantly focuses on the benefits of smart manufacturing transformation for individual enterprises, including aspects such as total factor productivity, energy efficiency, and cost management, with limited attention to the disparities in transformation progress across enterprises or the spillover effects on upstream and downstream segments of the supply chain.
To address these gaps in the literature,this study empirically examines the supply-chainspillover effects of smart manufacturing transformation using supply-chain relationship data from Chinese A-share listed manufacturing companies between 2009 and 2022, and analyzes the underlying mechanisms driving these effects. First, it develops a theoretical framework centered on "vertical leadership" and "peer group effects". It posits that the transformation to intelligent manufacturing is not only characterized by technological innovation and network externalities, but also generates a closed-loop, synergistic diffusion effect throughout the supply chain via demonstration effects, knowledge sharing, and technology transfer. Empirical results indicate that the intelligent manufacturing capability of focal firms has a significant positive impact on their supply-chain partners; specifically, an increase of one standard deviation in the focal firm′s intelligent manufacturing level is associated with a 7-percentage-point increase in the intelligent manufacturing level of linked firms. Further robustness checks—using first-difference model, controls for industry and regional trends, instrumental variable methods, and difference-in-differences approaches—consistently confirm the robustness and significance of this positive spillover effect.
Then, the mechanism test reveals that key leading firms, particularly those in core supply-chain positions and state-owned enterprises, are more likely to exercise vertical leadership, thereby significantly enhancing the spillover effects of intelligent manufacturing transformation. Moreover, when supply-chain firms share common shareholders, the resultant peer group effect effectively facilitates the transmission of intelligent manufacturing expertise and technological information from focal firms, accelerating the coordinated transformation process among upstream and downstream enterprises.
Moreover, by analyzing the heterogeneity in the propagation direction of supply-chain spillover effects, this study finds that the intelligent manufacturing transformation of focal firms predominantly spills over to upstream suppliers, creating a "reverse pressure mechanism" that compels suppliers to proactively enhance their intelligent manufacturing capabilities to meet the transformation demands of the focal firms. In contrast, the effect on downstream customer firms is not significant, indicating that upstream supply-chain partners face greater pressure and driving forces during the transformation process. Regarding the learning behaviors of supply-chain firms, further empirical tests reveal that when firms are at a disadvantage in intelligent manufacturing within their industry or region, their transformation largely relies on conservative learning strategies—characterized by passive imitation and following—in order to mitigate market risks and swiftly narrow the gaps with more advanced peers; conversely, when conditions for proactive learning exist, this positive effect is not significant.
In summary, this paper provides an in-depth investigation of intelligent manufacturing transformation from the perspective of supply-chain spillovers, thereby supplementing and extending the existing literature on collaborative effects in firm transformation. The study not only reveals the significant positive spillover effect of focal firms′ intelligent manufacturing transformation on their supply-chain partners, but also elucidates the crucial role of core enterprises—particularly those exercising vertical leadership through their dominant positions and state ownership—in promoting overall supply-chain digitalization. Furthermore, the paper highlights that supply-chain firms generally adopt conservative and passive imitation strategies, which offers new insights for small and medium-sized enterprises confronting high-risk transformations. Drawing on these insights, the paper recommends strengthening systematic policy support for intelligent manufacturing transformation, fully leveraging the leading role of flagship and state-owned enterprises, and promoting deep inter-connectivity and information sharing among all supply-chain participants through demonstration projects and cross-sector collaborations, thereby achieving coordinated enhancement and high-quality transformation across the entire industrial chain.

In the context of global digital transformation, innovation has become a key driver of economic and social development.This is particularly evident in the manufacturing sector, where the rise of industrial Internet platforms is advancing the platform economy, providing strong support for the digital transformation of enterprises and the enhancement of their innovation capabilities.To better understand how industrial Internet platforms drive enterprise innovation, this paper delves into the mechanisms at play.
As a new type of digital infrastructure, the industrial Internet platform connects the platform itself, the various entities within its ecosystem, and external resources. It not only fosters synergies between production and innovation processes but also offers new momentum and opportunities for enterprise innovation. Based on the theories of resource orchestration and open innovation, this paper focuses on Chinese manufacturing enterprises. It adopts a hierarchical framework of "platform—platform ecosystem—participating enterprises" to explore the relationship between the key capabilities of industrial Internet platforms, platform ecological embedding, and enterprise innovation performance, while also analyzing the role of platform network relationships (including strong ties and bridging ties) within this framework.
The key capabilities of the industrial Internet platform, such as industry foundational capabilities, technical capabilities, policy grasp capabilities, and social resource integration capabilities, form the essential foundation for promoting platform ecological embedding and significantly improving the innovation performance of participating enterprises. Platform ecological embedding, which refers to the interaction and resource flow between the platform and its participating enterprises, enhances the technological progress and innovation outcomes of participating enterprises through mechanisms like knowledge transfer, technology spillovers, and innovation collaboration. Building on the concept of platform ecological embedding, platform network relationships (strong ties and bridging ties) play distinct roles in the relationship between platform ecological embedding and enterprise innovation performance. Therefore, platform network relationships not only directly contribute to the improvement of innovation performance but also moderate the relationship between platform ecological embedding and innovation performance.
Manufacturing enterprises constitute the core user base of industrial Internet platforms, possessing complex and diverse demands for such platforms. The industry characteristics of these enterprises align closely with the capabilities offered by the platforms. Investigating the application scenarios of manufacturing enterprises can provide valuable insights into the pivotal role that industrial Internet platforms play in fostering enterprise innovation. Thus, this study targets manufacturing enterprises located in the Yangtze River Delta and the Pearl River Delta regions. Initially, the research team conducted in-depth interviews with 23 enterprise representatives, and formed the initial questionnaire based on the feedback obtained from these interviews. The questionnaire survey was carried out from October 2023 to August 2024, and was designed in two stages to mitigate common method bias while maintaining the feasibility of the research. Additionally, the paper verified the moderating role of platform network relationships in the relationship between platform ecological embedding and enterprise innovation performance. The research findings indicate that the key capabilities of industrial Internet platforms significantly enhance the innovation performance of participating enterprises, with platform ecological embedding acting as a mediator. Furthermore, platform network relationships (strong ties and bridging ties) not only directly improve innovation performance but also positively moderate the relationship between platform ecological embedding and enterprise innovation performance.
This study integrates research in the fields of resource orchestration theory, open innovation theory, and enterprise performance, focusing on the relationship between industrial Internet platforms and enterprise innovation performance in specific contexts. In contrast to previous literature, this paper provides an innovative contribution by simplifying the complex concept of the industrial Internet platform by relating it to the traditional understanding of a digital platform. It delves into the unique key capabilities of industrial Internet platforms, the internal mechanisms linking platform ecological embedding to enterprise innovation performance, and expands the application of resource orchestration and open innovation theories. The empirical analysis supports the conclusions, offering a new perspective for evaluating the value of industrial Internet platforms and providing theoretical insights for Chinese manufacturing enterprises on how to effectively allocate resources and foster innovation within the platform ecosystem.

Small and medium-sized enterprises (SMEs), as a vital engine for driving high-tech industries, play an essential role in bolstering China's economic resilience and promoting high-quality economic development. “Specialized, refined, unique, and innovative” (SRUI) SMEs exhibit strong innovation capabilities and distinctive competitive advantages. Understanding the mechanisms that underpin the high-quality development of SRUI SMEs is crucial for devising scientifically grounded policy measures, optimizing resource allocation, and enhancing firms' competitiveness. However, theoretical research on SRUI SME development remains underdeveloped compared to practical advancements, with limited quantitative studies and a predominance of qualitative analyses. Notably, the existing literature has primarily concentrated on external environmental factors that facilitate the high-quality development of SRUI SMEs, while relatively little attention has been paid to the role of firms' internal technological capabilities. Technological capability, defined as the accumulation of internal knowledge and innovation practices within a firm, serves as a repository of technological expertise that is fundamental to the development and enhancement of products and processes. It constitutes a critical driver for sustaining competitive advantages, improving performance, and advancing high-quality development. Technological complexity and technological knowledge integration capability represent two core dimensions of firms' technological capabilities.
Drawing on endogenous growth theory, economic complexity theory, path dependency theory, and innovation diffusion theory, this paper proposes an inverted U-shaped relationship between technological complexity and the quality of SRUI SME development. Furthermore, grounded in knowledge-based theory, this study incorporates firms' knowledge integration capabilities into the analytical framework to examine how organizational capabilities influence and reshape the relationship between technological complexity and SRUI development quality. The sample selection encompasses those featured in the five consecutive annual lists from 2019 to 2023, resulting in a robust sample of 1 738 nationally acclaimed SRUI-listed companies for the analysis. The quality of enterprise development is assessed across four key dimensions: specialization, refinement, differentiation, and innovation. Relevant data and control variables are drawn from the CSMAR and CNRDS databases. Technological complexity and knowledge integration capability are quantified using firms' IPC classification codes, with data sourced from the National Intellectual Property Administration (NIPA) and the PatSnap database.
The results indicate the following: (1) There is an inverted U-shaped relationship between technological complexity and the high-quality development of SRUI SMEs. When a firm's technological complexity remains below the threshold of 218.766, its increase significantly enhances development quality. However, surpassing this threshold may lead to capability traps, path dependence, and barriers to technology diffusion, which inhibit development quality. (2) Both the depth and breadth of firms' knowledge integration positively moderate the relationship between technological complexity and high-quality development, facilitating the achievement and amplification of the peak benefits of technological complexity. Compared to knowledge integration depth, integration breadth enables the peak positive effect of technological complexity on development quality to be achieved more quickly while significantly enhancing the maximum level of development quality. (3) The impact of technological complexity on development quality is multidimensional, exhibiting significant heterogeneity depending on firm-specific characteristics, industry attributes, and regional factors.
Building on the above findings, this study advocates for firms to optimize the allocation of technological resources, strategically enhance technological complexity, and mitigate the risks of capability traps and resource misallocation stemming from excessive complexity. Firms should systematically advance their knowledge integration capabilities. By efficiently utilizing their technological resources and established organizational practices, they can maximize the untapped value of their current technological assets. Additionally, firms are encouraged to expedite the development of digital infrastructure to strengthen their capacity for managing, organizing, and reutilizing intricate technological combinations. Moreover, governments should formulate nuanced and targeted support policies that align with firms' industry-specific attributes and regional contexts, fostering balanced and sustainable high-quality development on a national scale. This study offers critical theoretical insights into the boundary conditions for innovation and economic growth within economic systems, while also providing actionable guidance for firms in the formulation of innovation management strategies and technological policy frameworks.

Innovation has become the first engine of China′s economic development,and as the mainstay of the private economy continues to gain prominence, the family firms have become the key to promoting the development of innovation in China. However, China′s family firms are not innovative enough, which is not only detrimental to the development of the firm itself, but also negatively affects the transformation and upgrading of the social economy.Introducing non-family shareholders and achieving equity diversification are important ways for family firms to improve competitiveness and achieve sustainable development. Currently, in China′s listed family firms, the non-family shareholders, both in terms of shareholding proportion and appointed director proportion, have reached a certain scale and have become important participators. In this context, whether the involvement of non-family shareholders can promote innovation in family firms, and how to better achieve this promotion, have become common concerns for both academics and practitioners.
On the basis of resource base theory, principal agent theory, and socio emotional wealth theory, this paper analyzes the impact and mechanism of non-family shareholders′ involvement on family firms′ innovation. To achieve this analysis, data on non-family shareholders' shareholdings and appointed directors is manually collected and organized from the annual reports of listed family firms in China from 2006 to 2023. The data is then matched with the firms' patent information. By setting variables and constructing a panel fixed-effects model, the impact and mechanism of non-family shareholder involvement on family firms' innovation are empirically examined. Additionally, heterogeneity analysis is conducted in the context of rich family firm characteristics. Furthermore, from a practical perspective, the optimal shareholding interval for non-family shareholders is quantitatively measured to better promote the innovation of family firms, and the impact of non-family shareholders′ over-appointment of directors on family firms′ innovation is tested based on the logic of non-reciprocal allocation of equity and control.
The study finds that both ownership involvement and control involvement of non-family shareholders significantly promote the innovation of family firms, and the conclusions still hold after a series of robustness tests. Mechanism analysis suggests that non-family shareholders involvement promotes innovation of family firms by advancing the process of professionalization of firm management and improving the efficiency of firm resource integration. Heterogeneity tests indicates that when clan culture is strong, the actual controllers of family firms tend to exhibit stronger corporate control preferences, which weakens the positive impact of non-family shareholders' involvement on family firms' innovation. However, a stringent external regulatory environment can constrain the profit distribution and decision-making preferences of family firms that are oriented by kinship ties. Under such circumstances, in order to meet regulatory requirements, family firms may further clarify property rights and improve corporate governance mechanisms. Clarifying property rights can mitigate the adverse effects of market failures on corporate innovation. Therefore, the more robust the external regulatory environment, the more pronounced the positive impact of non-family shareholders' involvement on the innovation of family firms is likely to be. It is further found that when non-family shareholders′ shareholding is between 20% and 40%, the promotion of family firms′ innovation is the greatest; and the over-appointment of directors by non-family shareholders significantly promotes family firms′ innovation.
This paper contributes to the literature on family firms and innovation in several ways. First, it extends existing research by identifying new mechanisms through which non-family shareholders promote innovation: improving resource integration efficiency and enhancing firm management professionalization. These findings complement prior studies focused on risk-bearing capacity and resource redundancy. Second, the paper quantifies the optimal non-family shareholding range for maximizing innovation, offering a basis for optimizing equity structure. Third, it examines the impact of non-family shareholders' over-appointment on boards using the logic of non-reciprocal allocation of equity and control. Finally, the paper adopts a cautious approach to shareholder relationships, enhancing the rigor and reliability of empirical results. Overall, it expands research on firm innovation and governance and provides practical insights for family firms to embrace non-family shareholders and improve board governance.

Effective investment promotion can facilitate the formation of urban agglomeration economies, driving innovation development among enterprises and cities and exerting a long-term impact on urban economic growth. Under the acceleration of the innovation-driven development strategy, China has set higher standards for innovation quality. However, higher quality implies higher barriers to innovation, leading enterprises to seek more resources and reduced risks alongside increased efficiency and quality through collaborative innovation. Investment opportunely provides a foundation of trust and resource conditions for such innovative collaboration. Due to spatial differences in the allocation of factor resources, these factors often need to flow across regions. Therefore, transportation infrastructure, exemplified by high-speed rail, can effectively lower the cost of capital and innovative factor flows, playing a pivotal role in promoting the linkage between investment-driven innovation factors among enterprises and cities. This study defines factor linkage as the flow of one factor leading to the connection of other factors and explores the impact of high-speed rail on the relationship between corporate urban investment and innovation from the perspective of factor linkage, providing significant insights for optimizing factor resource allocation and achieving regional integration in China.
In terms of research methodology, this paper primarily employs a continuous difference-in-differences (DID) model and incorporates multidimensional fixed effects to control for the influence of other confounding factors. It focuses on analyzing the channels through which high-speed rail affects the linkage between investment and innovation, specifically: the innovation quality channel, the investment sustainability channel, and the investment spillover channel. The study manually collects and compiles a panel dataset covering domestic investments and cross-regional collaborative innovations by A-share listed companies from 2005 to 2022, and constructs an indicator to measure the integration between investment and innovation. To capture intercity high-speed rail connectivity, the analysis uses continuous variables such as service frequency instead of binary indicators of mere connectivity, thereby more accurately reflecting the intensity of intercity linkages.
The study finds that high-speed rail connectivity can promote the increase in the number of cooperative patents in recipient cities driven by enterprises' off-site investments, triggering the linkage effect between investment and innovative factors. Moreover, after a series of robustness checks including endogeneity tests, parallel trend tests, and placebo tests, the conclusions remain robust. Mechanism tests demonstrate that high-speed rail connectivity can strengthen the driving effect of investment on innovation through the innovation quality pathway, the investment sustainability pathway, and the investment spillover pathway. High-speed rail can enhance the driving effect of investment on high-quality innovation; the higher the investment sustainability, the more high-speed rail can promote the driving effect of investment on innovative factors; and investment can also drive the linkage of urban innovative factors through inter-industry spillover and inter-firm spillover, among other avenues. Heterogeneity analysis proves that when capital factors flow to central cities, larger cities, or transport hubs, or when they move within urban agglomerations, the driving effect of high-speed rail connectivity on the investment-innovation factor linkage is greater. Thus, the study proposes to enhance the high-speed rail network, maximize spillover effects of transportation hubs, support long-term investment in innovation, and encourage enterprises to pursue technological breakthroughs through diversified pathways.
This study makes marginal contributions from two aspects. First, regarding the research perspective, by focusing on the linkage between investment and innovative elements as the primary research angle, this paper expands the research boundaries concerning the flow of factors and the causal impact among them. Furthermore, it investigates the role of high-speed rail in driving the effect of capital elements on innovative elements, as well as the pathways through which high-speed rail influences this process. Second, concerning the construction of indicator models, this study constructs a scientifically measured indicator that gauges the driving effect of enterprises' cross-regional investments on urban cooperative innovation. The indicator takes into account the lagging relationship between the two, which breaks away from the conventional measurement approaches used in existing research for constructing multi-factor indices.

In the context of China's transformation toward an innovation-driven economy, collaborative innovation has become a key strategy to enhance national competitiveness. Innovation consortia—collaborative alliances among enterprises, universities, research institutes, and governments—are emerging as vital platforms to aggregate innovation resources, facilitate knowledge flows, and drive breakthroughs in key technologies. However, the construction levels of such innovation consortia vary significantly across regions and industries in China, and the mechanisms for achieving high-level development remain insufficiently explored. This study aims to identify and analyze the configuration paths that lead to high-level construction of innovation consortia in China, providing theoretical insight and practical guidance for future policy-making and institutional design.
This study builds upon the "strategy tripod perspective" to conceptualize the key factors influencing innovation consortium development. Methodologically, the study adopts dynamic qualitative comparative analysis (QCA), which is well-suited for exploring causal complexity in social phenomena. By leveraging dynamic QCA, the study examines how different combinations (configurations) of internal and external conditions lead to high or non-high levels of innovation consortium construction.The empirical analysis is based on data collected from 370 innovation consortia in China. These consortia span a diverse range of industries and regions and have been evaluated based on a multidimensional assessment framework encompassing innovation input, resource agglomeration, collaborative output, governance mechanisms, and institutional support. Variables selected for the configurational analysis include innovation resource integration capability, talent gathering capability, technological achievement transformation capacity, institutional guarantee capability, and industrial development level.
The results of the dynamic QCA reveal four distinct configuration paths leading to high construction levels of innovation consortia.(1)Institutional coordination and resource integration-driven type: This configuration is characterized by the absence of mature industrial bases and large-scale participants but relies heavily on strong institutional support and effective innovation resource integration. It is typically seen in emerging sectors requiring strategic coordination and initial resource mobilization.(2)Industry-oriented transformation type: This path features the presence of leading enterprises and a pressing need for industrial upgrading. It emphasizes the role of industrial drivers and organizational leadership in guiding collaborative innovation and transforming traditional sectors.(3)Technology talent-led type: In regions or industries with limited resource endowment and industrial maturity, this configuration leverages high-end scientific and technological talents to compensate for systemic shortcomings. The participation of top researchers and flexible talent mechanisms plays a crucial role in enhancing innovation capacity.(4)Multi-dimensional advantage resource empowerment type: This type thrives in areas with established industrial systems, abundant innovation resources, and comprehensive institutional support.
These findings suggest that there is no single optimal path for innovation consortium development. Rather, multiple equifinal paths exist that depend on the interplay of resource availability, industrial context, and institutional arrangements. The study offers several theoretical contributions. First, it extends the application of the strategy tripod perspective to the domain of innovation governance, demonstrating its suitability for explaining the multi-faceted nature of collaborative innovation. Second, it enriches the empirical literature on innovation consortia by identifying configuration types that reflect China's diverse innovation landscape.
Moreover, the study has important practical implications. Policymakers should tailor their support strategies based on the specific configuration types of innovation consortia. For instance, resource integration and institutional innovation are crucial in nascent sectors; industry-led consortia require regulatory incentives and supply chain alignment; talent-driven models benefit from flexible talent policies and achievement transformation mechanisms; and mature regional systems should focus on deepening cross-domain collaboration and market-based innovation resource allocation. In terms of methodological contribution, the adoption of dynamic QCA allows for a nuanced understanding of how multiple conditions interact to produce outcomes. This approach moves beyond linear causality and embraces configurational thinking, which is especially relevant for complex policy systems such as innovation governance.
In conclusion, this study provides a novel analytical perspective and robust empirical evidence on the paths to high-level innovation consortium construction in China. It highlights the importance of context-specific strategies, coordinated governance, and multi-actor collaboration in building a more effective and inclusive national innovation system.

Amid the intensifying global geopolitical risks and the in-depth evolution of the technological revolution, China encounters formidable challenges, including the containment of its scientific and technological innovation resources by Western nations and the heavy dependence on crucial technologies and resources. Consequently, accelerating the breakthroughs of core technologies in key fields has become an imperative for China to secure a competitive advantage in the global technological landscape. The "Jie Bang Gua Shuai" mechanism, which refers to an open competition mechanism for selecting the best candidates to lead key research projects,with chief technology officers assuming responsibilities. It has emerged as a novel paradigm in scientific research organization, bearing substantial significance in optimizing the allocation of scientific and technological resources and expediting the conquest of key core technologies.
The principal aim of this study is to investigate the manner in which the "Jie Bang Gua Shuai" mechanism propels the resolution of core technical conundrums. In conjunction with the resource allocation theory, this study undertakes a meticulous dissection of the operational mechanism of the "Jie Bang Gua Shuai" mechanism within the context of facilitating the research and development of core technologies in key fields. Special emphasis is placed on the functions of core innovation elements, resource allocation entities, and the central mechanism of resource allocation therein. This study uses the coal industry in Guizhou Province as a case study. The industry fully cooperates with universities and integrates resources in line with national strategic needs, adopting the "Jie Bang Gua Shuai" mechanism to address the core technological challenges of intelligent mining in coal mines. The study examines how to effectively optimize resource allocation from three perspectives: the "information-talent-funding" innovation element joint mechanism, the "government-industry-university" innovation subject collaborative mechanism, and the "active government effective market" resource allocation coordination mechanism. Furthermore, this study explores how to effectively optimize resource allocation in the process of analyzing cooperation with universities and deeply analyzes the process of Guizhou Province's "Jie Bang Gua Shuai" mechanism to promote core technology research and development.
The research findings unequivocally demonstrate that the "Jie Bang Gua Shuai" mechanism augments the efficiency of resource allocation and fosters the research and development of core technologies through pivotal innovation elements such as open and equitable bilateral information, open and collaborative scientific and technological talents, and diverse and flexible scientific research funds. Guizhou Province's practice serves as a paradigmatic example of the efficacy of this mechanism, with its process mechanism encompassing the joint mechanism of innovation elements like information, talent, and funds; the collaborative mechanism of innovation entities such as the government, industry, and universities, and the coordination mechanism of resource allocation between the "active government" and the "efficient market". In accordance with these insights, three pathways for promoting R&D of core technologies are proposed: first, by clarifying project requirements and target frameworks, establishing an effective talent team selection mechanism, and building a sustained and stable funding support system, breakthroughs in core technologies can be effectively promoted, driving technological innovation and industrial upgrading; second, it is crucial to strengthen cross-departmental and cross-regional cooperation among various innovation entities; thirdly, it is essential to coordinate the allocation of resources between the government and the market. This coordination should not only leverage the government's strategic, service, and reform guidance mechanisms to provide policy support and directional guidance for innovation entities but also fully utilize the market's decisive role in the allocation of scientific and technological resources.
This study plugs the research void in the process of "Jie Bang Gua Shuai" and stimulates theoretical dialogue, thereby making substantial and valuable contributions to the academic domain. It also proffers invaluable theoretical and practical implications for optimizing the allocation of scientific and technological resources and promoting the research and development of core technologies. Future research endeavors could expand the ambit of case studies and adopt quantitative analytical methodologies to provide more robust data support and a scientific foundation for policy formulation and refinement.

With the highly frequent iteration of science and technology and the rapid development of the economy, market competition is becoming increasingly fierce. It is no longer sustainable to rely on factors and investment to drive the development of enterprises, and innovation has become the requirement of the times. However, every benefit will beget a disadvantage. While innovation brings social progress, its potential negative impact may harm the public and society at some point. By integrating ethics and social expectations into the innovation process, responsible innovation provides a good paradigm for solving the negative externalities of innovation. However, it is inevitable for employees to make mistakes in the innovation process due to the long cycle of responsible innovation, multiple constraints and complex uncontrollable factors. So, how can employees maintain the willingness and vitality of responsible innovation with high trial and error costs? An organizational fault-tolerant atmosphere may provide a solution. But does organizational fault-tolerant atmosphere only promote responsible innovation in a positive way? Is there a possible inhibitory effect?
Through the review of existing literature, this study finds that most of the current studies on organizational fault-tolerant perception start from the positive side, while few studies focus on its negative side. The most common view is that the fault-tolerant atmosphere of the organization provides employees with error flexibility and trial and error space to enhance their sense of psychological security and sense of innovation self-efficacy, so as to stimulate more responsible innovation behaviors. However, as the old saying goes, one cannot lead an army with a merciful hear, this study questions whether organizational fault-tolerant perceptions serve as a "sword of honor" or a "charter of pardon". Specifically, it examines if the moral excuse that "mistakes are permissible" fosters a sense of immunity to failure among employees. Such indulgence might lead to repetitive errors, thereby significantly reducing the likelihood of responsible innovation.
However, this study examines whether organizational fault-tolerant perception consistently impacts employees' responsible innovation through two opposite paths: innovation self-efficacy and moral disengagement. Is it different in different situations In order to answer the above questions, this thesis introduces socially responsible human resource management and discusses these two paths in this context. Integrating the discussion above, this thesis builds a double-edged sword model and systematically discusses the mechanism of organizational fault-tolerant climate on responsible innovation. On the basis of the empirical study of 317 self-filled questionnaires from employees in China, a moderated mediation analysis is conducted using SPSS and Mplus software to verify the hypothesis in this thesis.
The conclusions are drawn in four aspects. (1) Organizational fault-tolerant perception has a double-edged sword effect on employees' responsibility innovation. (2) Innovation self-efficacy plays a mediating role between organizational fault-tolerant perception and employees' responsible innovation. Moral disengagement plays a mediating role between organizational fault-tolerant atmosphere and employees' responsibility innovation. (3) Socially responsible human resource management perception (SRHRMP) can strengthen the relationship between organizational fault-tolerant perception and innovation self-efficacy, and weaken the relationship between organizational fault-tolerant perception and moral disengagement. The higher the level of SRHRMP, the stronger the positive influence of organizational fault-tolerant perception on employees' sense of innovation self-efficacy. SRHRMP plays a moderating role in the positive relationship between organizational fault-tolerant perception and employee moral disengagement. The higher the level of socially responsible human resource management, the weaker the positive influence of organizational fault-tolerant perception on employee moral disengagement. (4) SRHRMP can strengthen the sense of organizational fault tolerance and influence the intermediary path of employee's responsible innovation through the sense of innovation self-efficacy, weaken the sense of organizational tolerance and affect the intermediary path of employee's responsible innovation through moral disengagement. The higher the level of SRHRMP, the stronger the indirect effect of innovation self-efficacy. SRHRMP moderates the indirect effect of employee moral disengagement between organizational fault-tolerant perception and employees' responsible innovation. The higher the level of SRHRMP, the weaker the indirect effect of moral disengagement.

The Chinese government has set ambitious goals of peaking carbon emissions by 2030 and achieving carbon neutrality by 2060. In the context of the dual carbon goals, enterprises, as the core subjects of economic activities, are not only key contributors to economic growth but also the primary drivers of carbon reduction. Their green transformation is crucial for survival and development. Green technology innovation is essential for enterprises to achieve this transformation, offering a pathway to balance economic benefits with environmental protection. However, green technology innovation is characterized by dual externalities and faces significant challenges, including long development cycles, substantial investments, and high risks. Moreover, the current institutional and market environments require further improvement. The implementation of corporate green development strategies largely depends on the cognition and capabilities of the executive team. Therefore, exploring how technology-expert executives can empower green technology innovation and achieve carbon reduction with synergistic efficiency is of great significance.
The existing literature has extensively explored the driving factors of green technology innovation, particularly focusing on the role of technology expert executives in enhancing various aspects of enterprise performance. These studies highlight how such executives contribute to improving technological efficiency, promoting technological capital accumulation, elevating innovation levels, increasing option value, and ultimately boosting overall enterprise performance. However, there is little literature regarding the role of technology expert executives in promoting enterprise carbon reduction and achieving synergistic effects. Against the strategic backdrop of green and high-quality development, how to realize the win-win situation of economic performance and environmental performance of enterprises has become an important research issue. Using the data of China's A-share industrial listed enterprises from 2012 to 2023, this paper constructs a theoretical framework of technical expert executives, green technology innovation and the synergy of carbon emission reduction and corporate performance improvement, and discusses the impact of technical expert executives on corporate carbon reduction synergies and its mechanism.
On the basis of theoretical analysis and empirical tests, it is concluded that technical expert executives have a significant positive impact on the synergy of carbon emission reduction and corporate performance improvement. Technical expert executives can effectively reduce the carbon emission intensity of enterprises, improve the financial performance of enterprises, and enhance the coupling and coordination degree of carbon reduction and performance improvement of enterprises;while green technology innovation plays an intermediary role between technical expert executives and the synergy of carbon emission reduction and corporate performance improvement. Technical expert executives have preference for green technology innovation and unique technical expertise, which helps to enhance the willingness and ability of enterprises to innovate green technology and improve the level of enterprises' green technology innovation. Green technology innovation can not only improve the efficiency of energy use, reduce resource consumption, strengthen the end pollution control and reduce the carbon emission intensity of enterprises; it can also help enterprises reduce costs and increase performance, enhance the green core competitiveness of enterprises and improve the financial performance of enterprises, so as to achieve the coordinated promotion of carbon reduction and performance improvement of enterprises.
Further research finds that the stability of the senior management team and good internal governance can provide a strong organizational guarantee for technical expert executives, while the short-sighted management will weaken the positive impact of technical expert executives on enterprises. The positive effect of technical expert executives in promoting the synergy of carbon emission reduction and corporate performance improvement is more significant in enterprises with high internal governance level, strong stability of senior management team and low short-sightedness of management. From the heterogeneity of external environment, the positive effect of technical expert executives in promoting the synergy of carbon emission reduction and corporate performance improvement is more significant in enterprises subject to strong environmental regulations, fierce market competition, and more government subsidies and tax incentives.

The digital innovation ecosystem (DIE) serves as an effective structural framework for driving industrial and organizational development. It integrates multiple stakeholders from industry-university-research, spans horizontal and vertical relationships across chains, and harnesses interdisciplinary resources to continuously deliver innovative solutions. However, existing studies inadequately explain the criteria for defining DIE boundaries, the phenomenon of boundary ambiguity, the interactive relationships between DIE and its environment, which severely hinders the foundational construction and analytical interpretation of DIE. The autopoietic system is the third generation of system theory, which emphasizes the structure and boundary of the system in the output elements of maintaining the system movement. To understand the autopoietic movement of DIE, the autopoietic system theory that can reflect the origin characteristics of output movement is used to construct and explain the digital innovation ecosystem, and further explore the formation and evolution process of digital innovation ecosystem
As a third-generation system theory, the autopoietic system has gained broad application and exhibited unique advantages over first and second generation theories (e.g., dynamic equilibrium, self-organization). However, domestic scholars have remained relatively underexplored in this field compared to their international counterparts. Current research on autopoietic system primarily focuses on sociology, management, psychology, computer science, environmental science, and the history and philosophy of science. This study adopts an integrated connotation-structure-characteristics-evolution framework to investigate the endogenous motion mechanisms of DIE through the lens of autopoietic system theory. From this perspective, DIE is conceptualized as a composite unitary entity formed by the coupling of innovation actors such as industry, academia, research, and application sectors. Fusion interfaces constitute its elemental components, spontaneously generating phase-space boundaries during system output-driven motion. DIE has typical characteristics of self-discipline, self-individuality, self-differentiation and mutual penetration. The generation of digital innovation ecosystem involves the agglomeration of factor-complex relationship and the integration between element unit and compound unit. Specifically, elements required for digital innovation ecosystems aggregate through self-organization by innovation agents (e.g., enterprises) or hetero-organization by institutions (e.g., governments); and in the integration phase, digital innovation ecosystems begin self-demarcation through productive movements of constituent elements, evolving into composite unit entities. Innovative entities such as industry, academia, research, and application also detach from the elemental parts of dynamic equilibrium systems or self-organizing system complexes in the form of autopoietic system units. Meanwhile, macroenvironments such as the economy and politics also emerge in the form of unit entities. This study constructs a galaxy model to depict the productive movements and inter-penetrative interactions of self-generating systems. It posits that the self-generative dynamics of digital innovation ecosystems correlate with positive factors (e.g., shared coding, mutual trust, common values) and negative factors (e.g., cognitive biases, information asymmetry) at fusion interfaces, while also being influenced by permeation resources provided by environmental unit entities like innovation agents
From the perspective of autopoietic system, this paper provides theoretical support for the construction of digital innovation ecosystem and the continuous development. Firstly, it is essential to establish a sense of autopoiesis among innovation entities, including production, learning, research, and application, as well as third-party platforms such as online industrial Internet platforms and offline industrial innovation alliances. These entities should develop autopoietic consciousness by clarifying their vision and mission from an autopoietic perspective, aligning with the goals of the autopoietic system, encouraging autonomy, and promoting internal self-organization. Secondly, an equal interaction mechanism should be designed to fully reflect the mutual penetration between innovation entities and third-party platforms. This mechanism should consider the self-development of innovation entities and ensure mutual respect among all parties. All innovation entities, regardless of size, should be treated as equal units, and smaller nodes in the innovation network should not be overlooked. Finally, the efficiency of interface integration should be enhanced. This includes reducing information asymmetry among innovation entities, improving knowledge search efficiency at the fusion interface, and strengthening trust between innovation entities and the fusion interface organization. Additionally, establishing common values for an independent and integration-oriented digital innovation ecosystem and improving the common coding efficiency of the interface are crucial steps.