Entrepreneurial activities are key factors driving regional economic growth, creating job opportunities, and promoting economic transformation. However, with the intensification of global economic pressures and the entry of the Chinese economy into a "new normal", traditional drivers of economic growth are gradually weakening, posing significant challenges to the entrepreneurial environment. Potential entrepreneurs not only need to contend with increasingly fierce market competition but may also face lower success rates, leading to a decline in entrepreneurial activities across various regions.
As the core driving force of the new wave of technological revolution and industrial transformation, artificial intelligence (AI) is rapidly integrating into various fields in China, spawning new industries, new technologies, new business forms, and new business models, thereby demonstrating its tremendous potential to drive a new wave of innovation and entrepreneurship. This rapid integration has transformed traditional industries, leading to breakthroughs in automation, data analysis, and customer engagement, which in turn accelerates economic growth. However, existing research indicates that the impact of AI on regional entrepreneurial activities has dual characteristics, with both positive creation effects, such as the emergence of new markets and job opportunities, and negative substitution effects, including the displacement of certain jobs and sectors. The complex interplay of these positive and negative effects makes the direction and intensity of AI's impact on regional entrepreneurial activities still inconclusive, leaving uncertainty around the overall outcomes for different regions and industries.
Looking back at past technological revolutions, although technological advancements may temporarily replace certain jobs in the short term, they ultimately stabilize total employment by generating emerging industries and creating new job positions. Therefore, with the rapid development of AI technology and its profound impact on the economic landscape of China, accurately assessing the role of AI in regional entrepreneurial activities is of great significance for improving entrepreneurial theory, guiding entrepreneurial practice, and promoting high-quality regional economic development. To this end, this paper takes the construction of national new-generation AI innovation development pilot zones as a typical case, exploring the intrinsic connections and mechanisms between AI development and regional entrepreneurial activities from the perspective of entrepreneurial choices, utilizing county-level panel data from 2012 to 2022 and a double machine learning model.
The research findings indicate that the construction of national new-generation AI innovation development pilot zones has a significant effect on enhancing regional entrepreneurial activities. Mechanism analysis reveals that AI development indirectly promotes entrepreneurial activities by enhancing entrepreneurial capabilities, alleviating financing constraints, and increasing capital returns, with a synergistic effect between entrepreneurial capabilities and capital returns. Further analysis finds that AI can stimulate entrepreneurial activities in technology-intensive industries and productive service industries, effectively driving regional economic structural transformation and high-quality development. Heterogeneity analysis shows that the positive effect of AI on entrepreneurial activities only becomes apparent when the regional population reaches a certain threshold.
This study contributes to the literature in three aspects: Firstly, by revealing the experiments of AI policies and national new-generation AI innovation development pilot zones, it proposes an innovative research perspective to explain the impact of AI on regional entrepreneurial activities. This not only integrates theoretical explanations from the perspective of entrepreneurial choices but also provides empirical support for institutional theories in the AI era. Secondly, the paper introduces a new chain construction path, namely "entrepreneurial capability—financing constraints—capital returns", providing strong support for further clarifying the complex mechanisms between AI and regional entrepreneurial activities. On the basis of the synergistic mechanism between "entrepreneurial capability—capital returns", it proposes enhancing entrepreneurs' AI literacy and resource integration capabilities, forming a positive feedback loop of "capability enhancement-capital appreciation-reinvestment of capabilities", maximizing the synergistic effect of the mechanism, and further promoting the virtuous interaction between technological innovation and capital flow. Thirdly, methodologically, the paper adopts double machine learning methods to solve the problems of model mismatch and curse of dimensionality in complex analyses, thereby effectively improving the accuracy of the conclusions.

In the contemporary scientific and technological context, brain-computer interface (BCI) technology has become a cutting-edge area attracting extensive attention. By enabling real-time sharing and deep integration of neural information among individuals, BCI offers more efficient and precise tools for group decision-making, knowledge innovation, and social practice; however, it also intensifies group differentiation and integration, challenging the conventional operation and power structure of social organizations and presenting new issues in social equity and ethics. Thus, it is crucial to probe the social relationship changes caused by BCI .
This study focuses on exploring the profound influence of BCI technology on social relations, with the aim of comprehensively understanding its implications and providing guidance for the harmonious development of technology and society. The research method mainly involves a comprehensive review of literature and in-depth cross-disciplinary analysis. By collecting and analyzing a large number of research materials from fields such as neuroscience, information engineering, sociology, and ethics, this paper systematically expounds on the relationship between BCI technology and social relations. These materials include academic papers, research reports, and relevant case studies, which form the basis for in-depth exploration.
The research concludes that BCI technology brings about far-reaching changes in social relations. At the individual level, it remolds self-cognition. For example, through BCI-controlled devices like brain-controlled prosthetics, individuals' perception of their body's functions and boundaries is transformed, affecting their self-identity and mental health. Interpersonal interaction patterns also change. BCI-based emotion recognition and subconscious information transmission enable more direct and in-depth communication, but they also raise issues such as privacy infringement. In terms of social behavior norms, the combination of BCI and VR technology creates new virtual social experiences, changing social interaction habits and norms, and blurring the line between virtual and real social interactions.
At the group level, BCI technology innovates collaborative models. In complex projects, it allows for the real-time sharing of members' neural-cognitive patterns, improving collaboration efficiency and knowledge synergy. It also reconstructs social network structures. The connection basis in social networks shifts from traditional relationships to neural-activity-based similarities and complementarities, which has a significant impact on information dissemination and social power structures. Moreover, it reshapes group identity and class relations. The different levels of BCI technology application among groups lead to identity differentiation and class-related changes, exacerbating social inequality.
The innovation of this paper lies in its multi-perspective and in-depth analysis. This paper provides a comprehensive analysis of BCI technology, covering not only the technical aspects but also delving into its social, ethical, and philosophical implications. Such a holistic approach allows for a more thorough understanding of the technology's potential impacts on various aspects of society and human life. In addition to the in-depth analysis, this paper also proposes a series of regulatory and guarantee mechanisms to ensure the responsible development and application of BCI technology. For instance, it suggests the establishment of robust ethical review mechanisms. These mechanisms would play a crucial role in ensuring that BCI research and applications adhere to ethical standards, thereby preventing potential ethical dilemmas and misuse of the technology. Moreover, the paper emphasizes the importance of constructing a comprehensive legal regulatory system. This system would aim to protect personal privacy and rights in the context of BCI technology. Given the intimate connection between BCI and personal neural data, ensuring the security and privacy of this highly sensitive information is of paramount importance. The proposed legal framework would help safeguard individuals from potential privacy violations and other related risks. Furthermore, the paper proposes the formulation of social fairness guarantee systems. The benefits of BCI technology should be distributed in an equitable manner across society. This requires the implementation of policies and measures that can promote equal access to and benefits from BCI technology, particularly for disadvantaged groups.
In summary, through its multi-faceted analysis and the proposal of practical regulatory and guarantee mechanisms, this paper makes a significant contribution to the responsible and sustainable development of BCI technology. It provides valuable insights and suggestions for policymakers, researchers, and other stakeholders in the field, helping to ensure that BCI technology develops in a direction that is beneficial to all of society.

In recent years, the rapid development of artificial intelligence technologies, such as intelligent robots and voice recognition, has become a key force driving the transformation of China′s economy. Artificial intelligence technologies can enhance human intelligence by enabling autonomous learning, communication, interaction, and problem-solving. In order to reduce labor inputs and increase work efficiency, more and more organizations are introducing AI technologies into their work. With the application of AI technology in the workplace, on the one hand, employees recognize that AI usage can help them perform redundant tasks and process complex data, which leads to experience positive emotions . A number of studies have also shown that AI usage can promote employees′ sense of work enthusiasm, job engagement and organizational citizenship behaviors. On the other hand, it can impose new work requirements on employees. The complexity of the technology can induce negative psychological emotions and increase employees′ work stress and job insecurity, which could lead to emotional exhaustion, employees′ burnout, knowledge hiding, and intentions to leave.
Scholars have viewed AI usage as a form of technological stress that leads to anxiety and insecurity, which in turn affects employee performance, proactive behavior, and job crafting. AI usage as a stressor can significantly affect employees′ attitudes and behaviors at work. In addition, organizations that want to stand out in a complex and changing economic environment need to rely on the wisdom of their employees, for example, employee voice. Employee voice in the organization will be affected by work pressure. Therefore, AI usage as a stressor has an impact on employee voice and silence. However, few studies have focused on the double-edged sword effect of its impact on employee voice and silence from the perspective of the cognitive activation theory of stress. This theory posits that employees cognitively appraise the outcomes of stressors as positive or negative, which can spill over into non-work time and trigger adaptive or non-adaptive psychological responses. Regarding AI, such appraisals can lead to problem-solving adaptive responses or emotionally centered non-adaptive ones. In Chinese culture, the concept of "Zi Xing" is reflected in employees′ work as rumination, which is split into problem-solving pondering and affective rumination. AI usage can activate problem-solving pondering and affective rumination among employees, which ultimately influences employees′ voice and silent behaviors.
In Study 1, a scenario experiment was conducted with 240 employees who use AI technology in their daily work, recruited via the Credamo platform in China. A between-subjects experimental design with two factors (AI technology application: high vs. low; job autonomy: high vs. low) was employed. In Study 2 (questionnaire survey) , employees from organizations using AI were recruited via the WJX online data collection platform. A three-stage time-lagged data collection approach was adopted to mitigate the impact of common method bias. Research hypotheses were tested and the empirical results show that through the mechanism of problem-solving pondering, artificial intelligence usage has a positive influence on employee voice and a negative impact on employee silence; via the mechanism of affective rumination, the artificial intelligence negatively affects employee voice and positively influences employee silence; work autonomy strengthens the positive effect of artificial intelligence usage on problem-solving pondering and weakens the positive impact of artificial intelligence usage on affective rumination.
This study makes the following theoretical contributions. First, this study confirms that AI usage can affect employees′ voice and silent behaviors in terms of problem-solving pondering and affective rumination, respectively. This not only broadens the research horizons of the impact of AI usage, but also enriches the antecedent research of employees′ voice and silent behaviors from the perspective of stress cognitive activation theory of stress. Second, this study brings in job rumination in the research framework, which broadened the scope of the impact of AI usage on employees′ attitudes and behaviors, and also provided a novel explanatory framework for the research on the mechanism of the impact of AI usage on employees′ voice and silence. Finally, this study incorporates job autonomy into the impact of AI usage on employees′ voice and silence, further enriching the boundary conditions for the study from the perspective of job resources.

Along with deep implementation of the innovation-driven development strategy, academic entrepreneurship has become an important social phenomenon, attracting the attention of many investment institutions. Academic entrepreneurs and investors achieve win-win outcomes through cooperation, but conflicts often arise due to reasons such as strategic planning, control rights allocation, and profit distribution. How to quickly and reasonably resolve conflicts between academic entrepreneurs and investors has become an urgent topic in practice. Domestic and foreign literature has neglected the interactive relationships between different conflict behaviors of conflict subjects. Current research also lacks a systematic consideration of the entire process of conflicts between academic entrepreneurs and investors, making it difficult to provide effective references for such conflicts.
With a literature review on conflicts between academic entrepreneurs and investors, this study finds that academic entrepreneurship in China is currently in a practice-rich but theory-poor stage, with relatively few studies on the individual level of academic entrepreneurs. Thus, an exploratory study is conducted. First, the literature grounded method is used to code and analyze eight typical cases of conflicts between academic entrepreneurs and investors. Second, to avoid concealment by the parties involved, during the theoretical saturation testing stage, in-depth interviews with three enterprises that have experienced conflicts between academic entrepreneurs and investors are conducted using the grounded theory method , to enhance the effectiveness and reliability of theoretical construction. This results in 20 corresponding categories: operational shortcomings, academic mission, academic thinking, profit goals, decision-making power, trust level, tolerance degree, goal collision, power intersection, incompatibility, technical stance, research confidence, strengthened control, project reevaluation, withdrawal of one party, mutual reconciliation, conflict continuation, macroeconomic environment, industry development, and social attention. By deeply exploring the relationships among these categories, they are integrated into five main categories: adjustment period, collision period, integration period, cooling-off period, and external environment. The core category encompassing these main categories is the "evolution path of conflicts between academic entrepreneurs and investors".
The storyline surrounding the core category of this study is as follows: After venture capital enters an enterprise, conflicts may arise between academic entrepreneurs and investors due to differing views on management and operational goals. These conflicts can manifest as goal collisions, power intersections, and incompatibilities. If the levels of trust and tolerance between the two parties are high, conflicts will not surface; otherwise, a triggering event will lead to the expression of conflict. Different conflict behaviors result in variations during the cooling-off period. The behaviors of academic entrepreneurs and investors are internal driving factors that influence the development of the conflict, while the external environment plays a moderating role throughout the evolution of the conflict.
The results show that the five main categories drive the evolution path of conflicts differently. The adjustment period is the starting point, the collision period is the development stage, the integration period is the climax, the cooling-off period is the endpoint, and the external environment is the external setting. This paper further provides suggestions for conflict prevention: (1) Conduction of due diligence. Before financing, both parties should understand each other's team philosophies and styles and appropriately conduct strategic analysis and evaluation. (2) Reasonable allocation of equity. It is necessary to achieve a balance of control rights between investors and entrepreneurs to motivate entrepreneurs to contribute more to the enterprises' success, helping to establish long-term cooperation between investors and entrepreneurs. (3) Improvement of contractual arrangements. Both parties should formulate suitable systems and actively negotiate at different stages of enterprise development. (4) Identification of and solving personal issues. It is essential to learn to empathize, rationally consider the other party's ideas and behaviors from their perspective, and actively change roles after disagreements occur.
Post-conflict resolution strategies include (1) active communication and addressing the conflict, for both parties should actively seek the causes of the conflict, and present their interests to resolve the dispute points; (2) development of a holistic awareness, which means both parties should rationally weigh the pros and cons of the conflict from the overall interests and long-term development perspective of the enterprise, seeking a unified solution; (3) timely introduction of third-party mediation, which includes government departments, other shareholders, mutual friends, universities, etc.

As a crucial vehicle for "mass entrepreneurship and innovation", the ecosystemization of crowd innovation spaces has become a vital means for implementing the innovation-driven development strategy across regions. However,while much effort has been made to promote transformation and upgrading through ecosystem construction, the sustainability capacities of various ecosystems vary considerably in reality. Existing research has emphasized the macro mechanisms of multi-party interaction in the value co-creation process, but it has overlooked the proactive role of entrepreneurial talents, particularly their psychological cognitive mechanisms. Thus, this study, starting from the perspective of core actors, posits that the key to sustaining value co-creation lies in entrepreneurs' unwillingness to invest time and resources in the ecosystem, i.e., insufficient ecosystem commitment; the exploration of the relationship between entrepreneurs' prior experiences and ecosystem commitment, which holds significant implications for crowd innovation space managers in applicant selection.
Following the cognitive theory of entrepreneurial ecosystems in a social context, this study explores the interaction mechanism between prior experience and ecosystem commitment from the perspective of opportunity. Firstly, the scale of commitment to the crowd innovation space ecosystem is compiled based on organizational commitment. Secondly, 205 entrepreneurs from 58 crowd innovation spaces are selected as research samples for an empirical test. This study is a nested design; therefore, the hypotheses are tested by building a multilevel structural equation model (MSEM) through Mplus 8.0. The results show that (1) entrepreneurs' prior experience has a significant positive impact on commitment to crowd innovation spaces; (2) opportunity belief plays a mediating role between entrepreneurs' prior experience and commitment to ecosystem; (3) the two-stage moderating effect of ecological diversity supports entrepreneurs' identification and development of opportunities within the ecosystem through previous experience, which together stimulate their commitment to the ecosystem.
This study sheds light on the mechanisms of co-action between entrepreneurs' prior experience, a particular human capital, and ecological diversity in relation to their commitment to ecosystem in three aspects. Firstly, it integrates commitment theory into the study of crowd innovation space and proposes the concept of commitment to crowd innovation space ecosystem, offering a micro-level commitment perspective as a foundational tool for crowd innovation space research. Secondly, this study, from an opportunity perspective, opens the "black box" between entrepreneurs' prior experiences and ecosystem commitment in crowd innovation spaces, providing new explanations for the relationship mechanisms between entrepreneurs and such entrepreneurial platforms. Existing research on the relationship between entrepreneurs and entrepreneurial platforms has often been approached from the emotional perspectives of attachment and trust. One overlooked aspect is that entrepreneurial opportunity is crucial for the successful implementation of entrepreneurial projects. Finally, the study validates the two-stage moderating effect of ecological diversity, extending the boundary conditions of opportunity beliefs and ecosystem commitment from an ecosystem characteristic perspective. Specifically, this paper responds to Autio's call to focus on the modifying role of the external environment on opportunity beliefs by identifying the interactive effects of situational and individual factors on opportunity beliefs, further expanding the study of opportunity beliefs.
Further, regarding the practical implications of the interaction mechanism between prior experience and ecosystem commitment , managers of crowd innovation space should consider the alignment between the personal characteristics of entrepreneurs and the characteristics of the crowd innovation space ecosystem when making decisions regarding entrepreneur selection for admission. Compared with "novice entrepreneurs", individuals with entrepreneurial experience have an "entrepreneurial mindset" and specialized knowledge of the industry and function, which avoids the unnecessary cost of immature entrepreneurship to crowd innovation spaces. Secondly, as a key environmental factor in the identification and development of entrepreneurial opportunities, ecological diversity influences the formation of entrepreneurs' ecosystem commitment. Therefore, crowd innovation space managers should enhance ecological diversity and improve the industrial chain to foster an environment conducive to attracting and keeping talented individuals through the strategy of improving ecological diversity and the industrial chain.

Climate change and environmental pollution have become increasingly severe. Adherence to sustainable green innovation has become the focus of global attention in the past decade. Due to the "double externalities" of green innovation, China's green innovation is not currently driven sufficiently by innovation concentration. The green innovation value chain and the industrial chain are not flawless. The stakeholders in the value chain lack awareness of self-responsibility, leading to overall inefficiency in China's green innovation. Therefore, it is important to convey the concept of responsible innovation philosophy to the stakeholders in the green value chain and to integrate this philosophy into the green innovation development strategies at the national, industrial, and corporate levels. The development of green innovation in the new energy industry is a crucial step in addressing China's energy shortage and environmental pollution.
As a responsible major nation, China is also a leader in the new energy industry. It is essential for national development and the sustainable ecological environment to study how to implement green innovation with the concept of responsible innovation philosophy in China's local new energy industry.Therefore, considering the actual background of green innovation development in China's new energy industry, this paper explores the impact of responsible innovation on green innovation within the industry. It examines the mediating role of green value co-creation, the influence of multiple stakeholders, and the dual moderating roles of trust relationships and top management team (TMT) heterogeneity among enterprises in the new energy industry cluster. The study constructs a model framework of concept influence, value identity, and innovation output, drawing on resource-based theory and information transmission theory. By collecting questionnaire data from 404 new energy enterprises in 31 provinces in China, empirical research and analysis are conducted to verify the positive promotional effect of each antecedent variable along its corresponding influence path, and it confirms that responsible innovation philosophy can significantly promote green innovation in the new energy industry. The study explores the important role of responsible innovation philosophy with innovation transparency and open participation in the green innovation process of enterprises through deeper conceptual ideas, and finds that green value co-creation plays a partial mediating role between responsible innovation philosophy and green innovation in the new energy industry. The empirical research results indicate that, on the one hand, responsible innovation philosophy has a significant positive promoting effect on green value co-creation, and on the other hand, green value co-creation has a significant promoting effect on green innovation in the new energy industry. The entire process interprets the theoretical model of "concept influence—value identification—innovation output". In detail, TMT heterogeneity positively moderates the mediating role of green value co-creation. Heterogeneous management teams can have more divergent innovative thinking, stronger awareness of innovation and ability to integrate resources, and better grasp the green innovation value of multiple stakeholders to contribute to green innovation in enterprises. The trust relationship between enterprises within an industrial cluster has a positive moderating effect on the relationship between responsible innovation philosophy and green innovation in the new energy industry. The trust relationship of cluster enterprises can reduce the cost of knowledge resource exchange, while sharing labor pools, providing policy subsidies, and fostering healthy competition. New energy enterprises within the industrial cluster will rely on trust to focus on the trust relationship between enterprises, and with its driving force, produce an economic effect of "learning from the good", promoting the impact of responsible innovation philosophy in green innovation.The research conclusion has theoretical and practical significance for green innovation and the efficient development of the new energy industry.
This study also provides some insights for the green innovation development of the new energy industry: firstly, it is important to recognize the importance of the concept of responsible innovation in the efficient development of green innovation in the new energy industry; secondly, the new energy industry should attach importance to the green innovation development of focus enterprises; and finally, within the new energy industry, it is crucial to prioritize the collaborative integration of heterogeneous resources, accept multi-level enterprise management teams, and efficiently access internal and external resources and green ideas.

Digital transformation capability has become a critical factor in assessing the manufacturing sector’s capacity for high-quality development. Research on this capability, in theory, focus on three main areas: the impact of digital transformation capability on manufacturing transformation, the factors influencing digital transformation capability, and the conceptual definition of digital transformation capability. Although studies conducted both domestically and internationally have provided some initial insights and exploratory attempts about this skill, a comprehensive examination of the formation process and internal mechanisms of digital transformation competence in manufacturing is still lacking.
This study adopts a dual case longitudinal research method to explore in depth the digital transformation processes of Haier and Huawei, because they have shown significant performance in the three stages of digital formation, network platformization, and ecological development, and have leading positions and rich experience in digital transformation in their respective fields. Abundant and accessible information on the digital transformation and development of Haier and Huawei provides ample empirical support for this study, with data sourced from a variety of channels including literature, books, official reports, and news, ensuring the reliability of the research data. The study intends to define the idea of digital transformation capabilities within the manufacturing sector by reviewing pertinent local and international literature on the subject.
The research identifies six critical components of digital transformation capability: digital support capability, digital innovation capability, digital application capability, digital operation capability, digital collaboration capability, and sustainable development capability. Technology Diffusion (T), Value Co-Creation (V), Business Model Innovation (B), and Sustainable Development (S) are the four dimensions that comprise the progressive synergy framework that the study employs to reveal the formation process and intrinsic synergistic evolution mechanisms of digital transformation capability in manufacturing enterprises. A comparison study is also carried out to illustrate the parallels and divergences in the processes of digital transformation capacity building between Huawei and Haier, two prominent manufacturers.
The study reveals a coupled synergy between the TVBS framework and the development of digital transformation capabilities, which exerts a critical influence on digital transformation within the manufacturing sector. The four dimensions of TVBS direct the evolution of digital transformation capabilities in a coordinated and progressive manner through three stages: digital formation, network platformization, and ecological development. This progression manifests differently across various manufacturing industries. In the digital formation stage, Haier develops a TV-centric digital transformation capability, focusing on enhancing product and service quality through digital technologies and prioritizing brand value creation. Conversely, Huawei adopts a T-centric approach, emphasizing independent research and development (R&D) to bolster product competitiveness. These divergent strategies influence subsequent decisions regarding business model selection and ecosystem development.
This study introduces an innovative approach by examining the coupling between the process of developing digital transformation capabilities and the TVBS synergy process. It presents a progressive model for digital transformation capabilities in the manufacturing sector, contributing to a deeper understanding of the phased nature of digital transformation. This model addresses the shortcomings of existing research, which often lacks a dynamic and multi-dimensional perspective. As a result, this study provides a novel framework and insights for manufacturing enterprises undergoing digital transformation. It elucidates the regularities and pathways of digital transformation capability development under the TVBS synergy across the stages of digital formation, network platformization, and ecological development. These findings offer theoretical guidance for the management practices of digital transformation in other manufacturing enterprises. Manufacturing firms havce been undergoing changes like digitization, networking, platformization, and ecologicalization in digital transformation. It is essential for them to recognize their transformation stage, emphasize TVBS collaboration, align new tech with business innovation to alter value creation logic, and shape digital capabilities based on their developmental needs. Meanwhile it is noted that not all manufacturing companies may achieve smooth transformations akin to the case studies, and digital transformation may vary across industries, future research would stand to benefit from a multi-dimensional exploration as the integration of digital and real economies continues .

Global competition in science and technology has intensified, and the entity list policy formulated by the US Bureau of Industry and Security based on the Export Control Regulations has emerged as a means of sanctions against China, aiming to curb the rapid advancement of Chinese enterprises in key technology fields. Under the technological blockade, enterprises find it challenging to meet the demand for technological innovation and rely more on external knowledge acquisition. Although some scholars have focused on the impact of the technological blockade on enterprise innovation, there is a scarcity of literature specifically dedicated to the influence of breakthrough innovation on Chinese enterprises. The fields of open innovation and cooperative innovation have gained prominence, but research on the acquisition of external knowledge under the US technological blockade against China and its impact on breakthrough innovation is limited.
Enterprises suffered from the technological blockade are concentrated in high-tech industries. In light of this, this study selects A-share high-tech listed companies in the top five industries with the highest number of export-controlled firms from 2014 to 2023 as research samples. These industries specifically include the manufacturing of computers, communications, and other electronic equipment; technology promotion and application services; wholesale trade; software and information technology services; and research and experimental development. After data screening, a total of 390 samples with 3 900 firm-year observations are obtained. From the perspective of external knowledge acquisition, the study adopts the differential fixed-effect regression model for empirical analysis, with the aim of revealing how the US technological blockade on China impedes the development of Chinese enterprises' breakthrough innovation and exploring the effect of the technological blockade on enterprises' breakthrough innovation and its boundary conditions.
The results indicate that in the short term, the American technological blockade inhibits Chinese enterprises' breakthrough innovation by blocking their access to external knowledge. The inhibitory effect is more pronounced in non-state-owned enterprises, enterprises in industries with a low level of competition, and enterprises with a low level of international experience. However, as time progresses, this inhibitory effect is gradually weakening. Faced with the pressure of the technological blockade, Chinese enterprises accelerate the pace of independent research and development and innovation, adjust or find new models to overcome the challenges brought by the technological blockade, in order to reduce their dependence on external technology and thereby promote breakthrough innovation. The moderating effect test reveals that organizational redundancy has a positive moderating effect on the relationship between the technological blockade and the introduction of foreign technology, and TMT social capital has a positive moderating effect on the relationship between the technological blockade and industry-university-research cooperation and industry-industry cooperation. Thus, the negative impact of the technological blockade could be mitigated by strengthening technological capabilities and expanding research cooperation.
This paper integrates industrial organization theory and resource-based theory, comprehensively considers external environmental factors and internal resource endowments, and deeply analyzes the synergistic effect of the technological blockade (external environment), organizational redundancy (strategic resources), and TMT social capital (strategic capability) on corporate knowledge acquisition (strategic behavior), and subsequently, the impact on corporate breakthrough innovation (strategic performance). It also answers the question of "inhibiting effect or forcing effect". Additionally, from the perspective of external knowledge acquisition and in accordance with the internal recessive characteristics of knowledge, the ways of knowledge acquisition are subdivided into explicit knowledge acquisition (foreign technology introduction and domestic technology purchase) and tacit knowledge acquisition (industry-university-research institute cooperation and industry-industry cooperation) , and reveals the transmission mechanism of two kinds of knowledge acquisition approaches in the relationship between technology blockade and enterprise breakthrough innovation. Furthermore, the paper discusses the moderating effect of organizational redundancy and the social capital of the executive team on the relationship between the technological blockade and knowledge acquisition, offering a solid theoretical and empirical basis for enterprises to develop practical strategies when confronted with the technological blockade.

With the in-depth development of digital economy, digital transformation has become an important force for enterprises to break through the dilemma of value creation. Scholars have analyzed the important impacts of digital transformation on enterprise value creation from multiple angles. In terms of the positive impacts, the existing literature has deeply analyzed how digital transformation promotes enterprise value creation through optimizing resource allocation, enhancing information matching, improving the integration of supply chain, promoting service-oriented transformation, and upgrading business modes. However, due to the long-term inputs and uncertain payoffs of digital transformation, enterprises are also confronted with a series of challenges. For example, the high level of investment and high possession of resources damage the welfare of employees, the resource competition against original businesses increases management costs, and the rent-seeking motivation of enterprises lowers the quality of innovation. The mismatch between digital transformation and business scenarios even leads to a "digital paradox", thus decreasing the value creation of enterprises. In addition, the product-oriented logic with technology innovation and the service-oriented logic led by service innovation are the two main paths of enterprise value creation, but the existing research mainly focuses on the single impact of digital transformation on product innovation or service innovation. Furthermore, whether digital transformation can promote enterprise value creation is influenced by many factors. Whereas, the existing research emphasizes more external factors with less attention on the internal ones of the enterprise. Therefore, it is urgent to explore the relationship between digital transformation and enterprise value creation in depth.
Following the theoretical framework of "behavior-process-performance", this paper takes the A-share listed companies from 2011 to 2022 in China as the sample, and sets enterprise value creation as the dependent variable and digital transformation as the explanatory variable to explore the effect, action path, and moderating conditions of digital transformation enabling enterprise value creation. Market indicators represented by Tobin's Q value reflect both the book value and market value of a company, and are less likely to be manipulated by humans, which can comprehensively reflect the value creation of the company. This article selects Tobin's Q value as the proxy variable for enterprise value creation. Referring to the practices of existing literature, it characterizes the degree of digital transformation in enterprises through text analysis.
The results show that digital transformation has significantly improved enterprise value creation, and it is more significant among small-scale enterprises, state-owned enterprises, mature enterprises, and enterprises in eastern China, but shows no significant impact on the value creation of large-scale enterprises, enterprises in the recession period, and enterprises in the central and western regions. The mechanism tests indicate that digital transformation promotes enterprise value creation through product innovation and service innovation, and product innovation is the main path of digital transformation to promote enterprise value creation. Moreover, the investment efficiency and absorption ability of enterprises provide a solid foundation for digital transformation to promote enterprise value creation.
The contributions can be concluded in three aspects. First, wider samples are selected to investigate the impact of digital transformation on enterprise value creation, which helps to more comprehensively reflect the general impact of digital transformation. Second, it is proposed to follow the product-oriented logic and service-oriented logic of value creation to build the bridge of product innovation and service innovation between digital transformation and enterprise value creation, which breaks through the limitations of previous research that discussed the value creation effect of digital transformation from the single perspective of technology innovation, and extends the application depth of innovation theory in the digital scenario. Third, from the integrated perspective of resource and capability, the moderating effects of investment efficiency and absorption ability between digital transformation and enterprise value creation are investigated, which enriches the scenario mechanism research of the economic consequences of digital transformation. The conclusions provide empirical evidence and theoretical support for enterprises to improve the positive impacts of digital transformation through the dual paths of product and service innovation, as well as from the integrated perspective of resource allocation and absorption ability.

In the digital era, digital transformation has become an important driving force to promote technological innovation in manufacturing enterprises. It can affect the innovation performance of manufacturing enterprises from the following aspects: first, digital transformation facilitates real-time sharing of information and knowledge, enabling enterprises to identify new development opportunities, which promotes the formulation of novel value propositions and the realization of value creation; second, manufacturing enterprises with advanced digital transformation are more likely to harness digital technology as a robust technological underpinning for their innovation efforts, thereby transforming their innovation development models; third, digital technology can bolster the innovation development model of enterprises, making it more agile and responsive to market demands;fourth, digital transformation can reduce the innovation cost of enterprises: it significantly inhibits cost stickiness by lowering adjustment costs and management expectations, with this inhibitory effect being long-lasting; moreover, digital transformation enables full-process monitoring of the innovation process; finally, digital transformation can improve the quality and quantity of innovation knowledge that manufacturing enterprises can obtain. Therefore, digital transformation exerts a profound influence on the manufacturing industry, and its significance demands the attention of industry stakeholders.
In addition to the close relationship between enterprise digital transformation and its technological innovation, the dynamic capabilities are also crucial in the specific process of building a comprehensive digital and intelligent environment for manufacturing enterprises. According to the study of dynamic capabilities, the implementation of digital transformation can help enterprises respond to changes in the external environment, and acquire and reshape resources to accelerate the adaptation to the external environment, which in turn enhances the dynamic capabilities of the enterprise; at the same time, in the context of digital transformation, the demand for research and development personnel in the manufacturing enterprises has increased dramatically. However, the relationship between the proportion of R&D personnel in these enterprises and their innovation performance remains a subject of debate among scholars. Some researchers posit that the presence of R&D personnel positively influences a company's innovation performance, while others argue that the correlation is not as straightforward and may involve more complex dynamics. Despite this, the literature seldom delves into the role of the proportion of technical R&D personnel in the nexus between a company's digital transformation and its innovation performance. Against this backdrop, in order to explore how digital transformation improves firms' innovation performance and its specific mechanisms, the study selects the Chinese manufacturing companies listed on the A-share market from 2009 to 2022. Following winsorization and other data cleaning procedures, the final sample comprises 1 207 companies, yielding a total of 15 338 observations for analysis. The study applies the Bootstrap method to test the hypotheses, and applies the stepwise method as well as the sequential method to further test the robustness of the results.
The final results show that the digital transformation of manufacturing enterprises positively affects their innovation performance; the absorptive capacity of manufacturing enterprises plays a partial mediating role between their digital transformation and innovation performance; the proportion of R&D personnel in manufacturing enterprises has a moderating effect on the mediating role played by absorptive capacity, i.e., when the proportion of R&D personnel in manufacturing enterprises to the total number of employees is higher, it can effectively enhance the role of absorptive capacity in the digital transformation of enterprises, which will be more effective in enhancing the mediating effect of absorptive capacity between enterprise digital transformation and innovation performance.
In practice,enterprises should tailor their digital transformation strategies to their resources, setting clear 3-5 year digital goals and establishing support systems for talent, standards, and culture. They should leverage professional digital teams for integration and cooperation, creating efficient digital workshops. Since it is crucial to design future digital team structures and platforms, enterprises should focus on absorptive capacity, build open innovation networks, and foster a knowledge-sharing culture to enhance innovation. In addition,in order to strengthen talent development, it is essential to establish performance evaluation systems, increase R&D personnel number to drive innovation and prevent talent loss.

The energy crisis and environmental issues are two major challenges facing contemporary society, and existing studies have shown that new energy vehicles play an important role in sustainable development, for they are conducive to conserving energy, reducing carbon emissions, enhancing air quality, and improving climate conditions. With the support and guidance of China's industrial policy, China's new energy vehicle industry as an emerging industry has been developing rapidly. Although China has enacted many policies for the development of the new energy automobile industry to facilitate the rapid growth of production and sales, there are still controversies about the relationship between industrial policy and the technological innovation of enterprises. Some scholars have pointed out that the financial subsidy policy has a promotional effect on the level of technological innovation of new energy automobile enterprises, and some scholars believe that the government's subsidy policy has a crowding-out effect on enterprise R&D investment, which is not conducive to the technological innovation of enterprises. Whether China's current new energy vehicle industrial policy can really help new energy vehicle enterprises improve their technological innovation capability needs to be discussed. In addition, existing research on the relationship between industrial policy and technological innovation of enterprises mostly focuses on a single policy dimension, ignoring the totality of the policy and the mutual influence of the policies. What is the current trend of China's new energy vehicle industrial policy? Which type of policy has the most effective impact on the technological innovation capability of enterprises? Such questions need further research and discussion.
This paper supplements the research literature on the overall perspective of China's new energy vehicle industrial policy through a big data approach to provide suggestions and references for in-depth analysis of new energy vehicle industrial policy. The study utilizes the LDA model to calculate the theme intensity of new energy vehicle industrial policies, and combines the data of 165 new energy vehicle enterprises during the period of 2012-2020 with the double fixed effect model to examine the impact of industrial policies on the technological innovation of enterprises. The results show that China's new energy vehicle industrial policies mainly focus on green environmental protection, infrastructure construction and financial subsidy policies, and the three themes can enhance the quantities of invention, application and appearance patents, and promote technological innovation of enterprises; however, there are differences in the impact of different types of industrial policies on technological innovation of enterprises, among which the infrastructure type of industrial policy has the best effect on the promotion of technological innovation of enterprises. The best effect of infrastructure industrial policy on enterprise technological innovation is found in the infrastructure type of industrial policy. Further analysis of the mechanism reveals that there is a positive moderating effect of enterprise human resource integration capacity between the three themes and enterprise technological innovation, and that the improvement of enterprise human resource integration capacity can further promote enterprise technological innovation.
The conclusions help to improve the understanding and assessment of China's new energy automobile industry policies and provide effective suggestions for the future development of China's new energy automobile industry. The contributions of this study are mainly as follows: first, broadening the perspective of industrial policy research. It uses big data analysis methods and text analysis tools to conduct a scientific and holistic assessment of industrial policy, and it studies and discusses the relationship between industrial policy and corporate technological innovation from a holistic perspective. Second, new methods are introduced to assess industrial policy. The article leverages the Latent Dirichlet Allocation (LDA) model to conduct a thorough assessment of industrial policy, drawing insights from its textual framework. This approach introduces an innovative method for evaluating industrial policies. Furthermore, it contributes to the existing research on human resources by examining the role of human resources through the lens of core competencies, specifically focusing on the integration capabilities of human resources.

As a new economic form, the digital economy brings strong momentum to promote green technology innovation and support innovation-driven development. Meanwhile, the high-quality development of China's digital economy relies on the mutual promotion of efficient markets and capable governments. At present, the effect of the digital economy on green technology innovation has been widely recognized, but due to differences in research perspectives and insufficient consideration of market or government threshold factors, the relevant conclusions are highly controversial. Thus, this paper systematically studies the threshold effect of digital economy on green technology innovation under the synergistic support of market and government. This is of great significance for accelerating the emergence of green technology innovation and achieving the "dual carbon" goal.
In order to deeply analyze the complex relationship between digital economy and green technology innovation, this paper uses the panel data from 30 regions in China during 2011-2022, and then applies threshold panel regression techniques, taking the market support, government support, and their synergy as threshold variables, and empirically analyzes the threshold effect of digital economy on green technology innovation under the synergistic support of market and government. The results are as follows. The impact of digital economy on green technology innovation has a significant positive nonlinear effect based on the synergistic support of market and government. Under the conditions of marketization and opening-up level, the promotion effect of digital economy gradually increases, and the promotion effect is the largest under the high threshold of marketization. Under the conditions of government technology support and government governance intensity threshold, the positive effects of digital economy show the differential effects of first rising and then falling and declining, respectively. When market and government synergy surpasses a critical threshold, the digital economy’s growth momentum continues to accelerate. The positive nonlinear effects of digital infrastructure, digital industrialization and industrial digitalization on green technology innovation all show a significant upward trend, and the positive effects of digital infrastructure are stronger as a whole.
In light of the conclusions reached in this study, the following practical implications are proposed. Firstly, local governments should comprehensively deepen market-oriented reforms, promote the high-speed flow and effective allocation of green innovation resources, and reduce the cost of green innovation. Meanwhile, it is essential to further explore and deepen an open innovation environment, build a regional platform for green innovation exchange and cooperation, and accelerate the promotion of green technology innovation. Secondly, when utilizing government technology support, each region should identify the focus and foothold for enhancing green technology innovation, and enhance the efficiency of digital economy in empowering green technology innovation. At the same time, when using government governance measures, each region should pay attention to the scientific combination of green technology innovation in different cycles. Thirdly, each region should steadily improve the level of synergy between the market and the government, give full play to the leading role of the market in empowering green technology innovation in the digital economy, and supplement it with the guidance and supervision role of the government, thereby achieving an organic combination of effective market and proactive government. Fourthly, all regions should accelerate the development of the digital economy and do a good job of top-level design, including the vigorous development of digital infrastructure construction, the active expansion of the development of digital industries, and the strengthening of the strategic leadership of information and communications technology.
Compared with existing research, the theoretical contributions of this paper are as follows. First, this paper expands the threshold effect theory and further enriches the nonlinear research on the impact of the digital economy on green technology innovation. Second, it reveals the mechanisms by which different types of markets and governments affect green technology innovation in the digital economy, further improving the theoretical scope of empowering green technology innovation with the digital economy. Third, this paper promotes the research on the synergistic mechanism between the market and the government, further deepening the understanding of the relationship between digital economy and green technology innovation.

Innovation is key for sci-tech innovation companies to achieve breakthroughs in new technologies and products, thereby gaining a competitive advantage. However, employees in such enterprises face the paradox of innovation motivation source: when they firmly believe in the value of their innovative ideas to the company, they may choose to avoid or disregard superiors' rejections, leading to creative deviance. Given the high complexity and high value characteristics of creative deviance, many scholars have begun to explore the driving mechanisms behind such behaviors. However, existing research on the mechanisms influencing creative deviance has been conducted based on traditional linear perspectives while not paying enough attention to the particularities of creative deviance behavior. This results in a lack of systematic and holistic understanding of the mechanisms behind the emergence of creative deviance. Creative deviance possesses both the illegality of the act and the legitimacy of its intended purpose, embodying a paradoxical nature due to the persistent yet opposing elements of righteous goals and deviant actions. This characteristic determines that creative deviance is a complex behavior, not driven by a single factor but resulting from the synergistic interplay of multiple factors. Therefore, the driving mechanism of creative deviance should be explored from a complexity perspective.
Drawing on the AMO framework, this study explores the different configurations that stimulate employee creative deviance by incorporating ability, motivation and opportunity multi-level factors from an integrative perspective.Specifically, it incorporates creativity, innovation self-efficacy, constructive responsibility perception, performance pressure,leader's idea rejection, and the dynamics of playfulness into the integrated research model. The analysis is carried out using the method of fuzzy-set qualitative comparative analysis (fsQCA) to integrate factors at the ability, motivation and opportunity levels to find the configurations that stimulate employee creative deviance.
The samples derived from tech-oriented small and medium-sized enterprises in regions such as Henan, Beijing, and Guangzhou involve employees who are frequently involved in innovation activities within their companies. The survey was conducted through a combination of online and offline methods, ultimately collecting a total of 368 valid responses. Then the fsQCA method is used to carry out configuration analysis and explore the collective effect of different influence factors on employee creative deviance. The research identifies four equivalent configurations that drive employee creative deviance behavior, which can be categorized into three types: motivation inspiration driven by creativity, efficacy-led opportunity empowerment and motivation-driven efficacy enhancement. The combination of innovation self-efficacy and leaders' idea rejection emerges as a significant factor in fostering creative deviance. Furthermore, constructive responsibility perception and performance pressure are found to have a substitutive effect in the configurational paths driving creative deviance. Employee creative deviance displays distinct traits, aligning with either pro-organizational or personal self-interests, based on the distinction between intrinsic and extrinsic motivations. This finding contradicts the conventional wisdom in prior research, which posits that 'creative deviance is inherently spontaneous'. It suggests that deviant innovation could either be a spontaneous expression of loyalty, reflecting pro-organizational sentiments, or a rebellious response to institutional norms driven by work pressures.
This study contributes both theoretically and practically. Theoretically, it explores the driving paths of creative deviance from a configurational perspective, enriching the factors that influence creative deviance and broadening the research viewpoints on this behavior. By emphasizing the need for a holistic and systematic investigation into this complex behavior, the study deepens the understanding of the nature and influencing factors of creative deviance. Furthermore, this study uncovers various pathways that lead to the emergence of creative deviance, enhancing the comprehension of its formation mechanisms. Practically, the findings of this study assist organizations and managers in gaining a deeper understanding of the nature and formation mechanisms of creative deviance, enabling a correct recognition of its positive utility and patterns. It encourages the creation of an organizational climate that can stimulate innovative actions among potential innovators, guides and manages employee creative deviance to maximize positive outcomes, and empowers the organization for future growth and high-quality development.

With the flattening of organizations and the rise of team collaboration, employees' role boundaries are gradually blurring. To enhance the innovation capability and market competitiveness of enterprises, it is necessary for employees to go beyond fixed job responsibilities and develop a broad awareness of "work roles," undertaking a variety of tasks within the organization. In rapidly changing internal and external environments, illegitimate tasks have become prevalent in the workplace. However, current discussions on the impact of illegitimate tasks remain insufficient, particularly regarding their influence on employees′ innovative behavior. As an emerging work characteristic, illegitimate tasks affect employees′ job demands and resources, ultimately influencing the generation and implementation of innovative ideas. Existing research is mainly limited to empirical verification or single-perspective analysis, making it difficult to deeply reveal the intrinsic mechanisms of illegitimate tasks. Consequently, there is also a lack of discussion on the comprehensive moderating effects between job characteristic variables and organizational environment variables.
To expand the understanding of the relationship between illegitimate tasks and innovative behavior, this study is based on the Job Demands-Resources (JD-R) model and further analyzes the roles of work engagement and job burnout in the relationship between illegitimate tasks and employees′ innovative behavior, while introducing work relevance and moral leadership as moderating variables. The research targets medium-sized enterprises in the Yangtze River Delta region, including Shanghai, Jiangsu, and Anhui, with a focus on high-tech industrial parks. The industries are concentrated in the information technology service industry, biopharmaceutical industry, new energy industry, high-end equipment manufacturing industry, and other fields. In the rapidly developing economic environment, these enterprises face complex competition and innovation pressures, making their employees′ innovative behavior and mechanisms for handling illegitimate tasks more typical and valuable for research.
This study uses a sample of 585 employees from medium-sized enterprises in the Yangtze River Delta region and constructs a multi-stage moderated dual mediation model. It is concluded that, first, illegitimate tasks positively influence innovative behavior by enhancing employees′ work engagement. Second, illegitimate tasks negatively impact innovative behavior through job burnout. Third, work relevance moderates the effect of illegitimate tasks on employees′ innovative behavior; specifically, the higher the work relevance, the stronger the positive impact of illegitimate tasks on innovative behavior through work engagement, and the weaker the negative impact of illegitimate tasks on innovative behavior through job burnout. Finally, during the moderation process of work relevance, a higher level of moral leadership strengthens the positive moderating effect of work relevance on the relationship between illegitimate tasks and innovative behavior via work engagement and also strengthens the negative moderating effect of work relevance on the relationship between illegitimate tasks and innovative behavior via job burnout.
The theoretical contributions of this study lie in three aspects. First, this research enhances the understanding of the positive aspects of illegitimate tasks by exploring the “double-edged sword” effect of illegitimate tasks on employees′ innovative behavior. It addresses the gap in previous studies that predominantly examined the negative impacts of illegitimate tasks from a single perspective, offering a new interpretive angle for comprehending illegitimate tasks from multiple perspectives, especially the positive pathways. Second, the introduction of work relevance as a job characteristic enriches the boundary conditions in the research on illegitimate tasks and employees′ innovative behavior. This study moves beyond the limitations of examining boundary influences solely from the levels of individual traits and cognition, clarifying under what circumstances the relationship between illegitimate tasks and existing work is more likely to stimulate their positive aspects. Third, this study elucidates the interaction mechanisms among job characteristics, employee behavior, and leadership behavior by constructing an integrated model moderated by both moral leadership and work relevance. The research not only investigates the boundary influences of a single job resource but also analyzes the combined effects of work relevance and moral leadership. This demonstrates how leadership styles and job design can be integrated to optimize work outcomes and provides a theoretical foundation for subsequent research to consider the comprehensive effects of various job resources.