In recent years, a growing number of organizations have rapidly adopted artificial intelligence (AI) technology, aiming to build a sustainable competitive advantage through automation and intelligence. Despite substantial investments in AI, many organizations have yet to realize satisfactory returns. A key reason for this shortfall lies in the disproportionate emphasis on the technical implementation of AI, while neglecting the management of AI use at the employee level. Consequently, AI often fails to be fully integrated into business processes or to realize its full potential. Although AI can effectively reduce costs and improve organizational efficiency, its growing role in tasks previously performed by humans has led to a squeeze on employees' professional value and livelihood. This has given rise to a phenomenon known as “AI disruption awareness”which refers to employees' perception of the threats posed by AI applications. Such awareness may trigger resistance to AI and become a significant barrier to its adoption and effective use. Therefore, as organizations undergo AI-driven transformation, it is essential to understand and address the impact of AI disruption awareness on employees' use of AI.
While academic discussions around AI disruption awareness have grown in recent years, relatively little attention has been paid to its influence on employees' use of AI. Existing research has primarily focused on employees' willingness to use AI, with little attention paid to how AI disruption awareness affects employees' actual AI usage behavior. Moreover, the majority of prior studies have emphasized the negative effects of AI disruption awareness on AI usage, neglecting its potential positive effects. Against this backdrop, this study focuses on employees' AI usage behavior in AI application scenarios, exploring how they adjust their use of AI in response to AI disruption awareness, in order to expand the study of the impact of AI disruption awareness on AI usage. Drawing on the cognitive appraisal theory of stress, the study constructs a model to explore how AI disruption awareness differentially impacts employees' innovative and avoidant use of AI, and the moderating role of strengths-based leadership in this process.
By analyzing two-wave survey data collected from 317 employees, the study yields the following conclusions: AI disruption awareness triggers two distinct strategies of innovative use and avoidant use of AI, and the choice of strategy is influenced by strengths-based leadership. Under the influence of strengths-based leadership, employees tend to make a challenge appraisal of AI disruption awareness, which drives them to adopt innovative usage strategies toward AI. Conversely, in the absence of strengths-based leadership, employees will make a threat appraisal of AI disruption awareness, leading them to adopt avoidant usage strategies toward AI.
The theoretical contributions of this study are as follows: First,it shifts the analytical lens from intention to actual behavior, foregrounding employee agency in AI application. By addressing the key question of “how AI disruption awareness influences employees' AI usage behavior”, this study offers new insights into how employees use AI under the influence of AI disruption awareness. Additionally, by revealing the impact of AI disruption awareness on creative use—a positive AI usage behavior—this study addresses the limitations of previous research, which often adopted a singularly negative perspective. Second, unlike previous studies that mostly explored employees' behavioral performance under AI disruption awareness from a single positive or negative perspective, this study integrates previous research perspectives based on a dialectical perspective, incorporates employees' positive and negative responses into the same framework, and proposes a dual behavioral mechanism of employees' AI disruption awareness, which provides a more comprehensive theoretical explanation for understanding the effects of AI disruption awareness. Third, this study proposes that strengths-based leadership is an important conditioning factor in determining the effect of AI disruption awareness. This not only bridges the gap of past studies' understanding of the boundaries of the differential impact effects of AI impact awareness from a leader's perspective, but also provides effective clues to reconcile the controversy of existing studies on the differential impact effects of AI disruption awareness.

Artificial intelligence (AI) has emerged as a pivotal driving force for scientific and technological breakthroughs. However, its application effects in corporate practices show significant differences:some enterprises have successfully integrated AI deeply into their core business, while others have made huge investments but failed to achieve substantial breakthroughs.
Existing studies mostly regard artificial intelligence as a passive technical resource or tool, ignoring its evolutionary role as a subject that participates in management activities through autonomous decision-making. From the perspective of resource orchestration theory, AI has shown the potential of a resource manager, being able to identify opportunities in real time, allocate elements, and collaborate or conflict with human decisions, which directly affects the pace, direction, and risk tolerance of innovation. Current research has three shortcomings: first, it fails to fully recognize the attribute of AI as a management subject; second, it lacks a systematic analysis of the path through which AI is embedded in the resource management process; third, it ignores the conflict mechanism between humans and intelligent agents in terms of resource dominance.
Drawing on the resource orchestration theory, this paper employs panel data from 3 131 Chinese firms over the period from 2014 to 2023 to investigate the dual roles of AI in shaping radical innovation—both as an innovation resource and as a resource orchestrator. Specifically, it addresses three critical questions: (1) Does AI as an innovation resource have a nonlinear effect on firms′ radical innovation? (2) How does AI, acting as a resource orchestrator, impact radical innovation through the resource management process? (3) How do human researchers moderate these relationships through interaction with AI?
The empirical findings reveal several important conclusions. First, AI as an innovation resource demonstrates an inverted U-shaped relationship with radical innovation. Specifically, the adoption and initial integration of AI resources significantly promote radical innovation by facilitating rapid knowledge recombination, reducing innovation costs, and enhancing the precision of decision-making processes. However, beyond a certain threshold, excessive reliance on AI tends to lock firms into existing technological trajectories, leading to diminishing returns and even inhibiting breakthrough innovation.Second, As a resource orchestrator, AI exerts its influence primarily through resource structuring and capability enhancement. Through automated data integration and analysis, AI strengthens firms′ resource structuring by accelerating and refining the identification of innovation opportunities and facilitating efficient knowledge recombination. However, the impact of AI on resource capability enhancement is nuanced. Initially, the introduction of AI resources may trigger internal resource allocation conflicts, temporarily undermining operational efficiency. Nevertheless, as firms progressively increase AI utilization, operational efficiency improves significantly, enhancing their capability to undertake radical innovation projects. Conversely,the study finds limited evidence of AI′s effectiveness in resource leveraging, suggesting current AI technologies remain inadequate for handling complex managerial tasks requiring sophisticated judgment, political negotiation, or contextual insight.Third, the study explores the interactive dynamics between AI and R&D personnel. The results highlight a clear substitution relationship: AI′s beneficial impact on radical innovation is stronger when the number of human researchers is limited, indicating that AI effectively compensates for insufficient human expertise in generating innovative ideas and strategic decisions. As the number of R&D personnel grows, however, this marginal benefit declines due to increased organizational complexity and potential resistance arising from perceived job threats, limiting AI′s incremental innovation benefits. Additionally, the strength of this substitution effect varies across firm lifecycle stages, being most pronounced during the growth phase and diminishing during maturity and decline phases.
This study contributes to the existing literature in several significant ways. Theoretically, it enriches the resource orchestration framework by explicitly considering AI transition from a passive, orchestrated resource to an active resource orchestrator. The study also expands current understandings of human-AI interactions by introducing the concept of "positional competition", suggesting that AI and human researchers may compete rather than collaborate in certain innovation processes. Empirically, this approach is novel in systematically analyzing
the complex nonlinear impacts of AI, considering the dual roles of AI and moderating factors such as human researchers and firm lifecycle stages.

Innovation is the key to sustained organizational growth, and artificial intelligence (AI) is an important innovation enabler. With the release of Big Language Models by DeepSeek, a deep-search company, a new round of discussions in the global AI community has been triggered. More and more companies are privatizing their deployments through AI and restructuring their organizations to create new business models and enhance sustainability. In this context, AI has significant potential for business model innovation due to its deep learning and human-computer collaboration characteristics. However, despite the consensus on the positive impacts of AI technological advances, companies face confusion in practical applications, especially the lack of expertise and capabilities in transforming business models and successfully implement AI, and thus the impact mechanisms of AI-adoption intensity on business model innovation remain unclear.
Thus, the study constructs a theoretical framework of “Resource Acquisition-Capability Enhancement-Value Reconstruction” based on the resource-based view and resource dependence theory. The study empirically examines 337 sets of data from Chinese manufacturing firms using hierarchical regression analysis. It then systematically explores the transmission mechanisms through which AI-adoption intensity affects business model innovation through explorative AI capabilities and exploitative AI capabilities, as well as the moderating roles of environmental hostility and environmental dynamism.
This study mainly draws the following conclusions: (1) AI-adoption intensity has a significant positive impact on business model innovation, consistent with current research on technology-driven business model innovation. It suggests that organizational AI-adoption intensity provides foundational technical resource support for organizations in the context of digital intelligence transformation, and becomes a key path to drive business model innovation. (2) AI-adoption intensity has a positive effect on business model innovation via explorative AI capabilities and exploitative AI capabilities. Specifically, explorative AI capabilities focus on the opportunity creation dimension, while exploitative AI capabilities are dedicated to efficiency enhancement, and the two synergistically promote business model innovation. This finding not only echoes the core viewpoint of organizational duality theory but also reveals the micro-mechanism of the transformation of technological resources to innovation capabilities in the AI context. (3) Environmental hostility and environmental dynamism play a moderating role in the relationship between explorative AI capabilities and exploitative AI capabilities and business model innovation, and at the same time have a significant enhancing effect on the mediating role of dual AI capabilities. This finding suggests that external environmental pressures motivate firms to unleash dual AI capabilities, whereas a stable environment may trigger AI capability rigidity.
The research makes theoretical contributions to advance the intersection of AI and innovation. First, it expands the explanatory boundaries of AI-adoption intensity in the context of intelligence, pointing out that the value realization path of AI technology is different from that of traditional technology due to its cognitive complexity and strong generative characteristics. Therefore, the study explores the impact of organizational AI-adoption intensity on business model innovation based on the resource-based view, which not only echoes the core proposition of the resource-based view that “heterogeneity of technological resources creates competitive advantage”, but is also a useful supplement to the study of technology adoption in the context of intelligent transformation. Second, previous research on AI technology in organizations mainly focuses on the advantages it brings at the technical level, however, the use of technology alone is not enough to bring innovation benefits directly to organizations . The study confirms the importance of explorative AI capabilities and exploitative AI capabilities for business model innovation, emphasizes that technology must be transformed into irreplaceable and hard-to-imitate capabilities to create value, and contributes to the theoretical development of organizational capability research. Finally, by parsing the moderating effects of environmental hostility and environmental dynamism, the study systematically reveals the boundary conditions of explorative AI capabilities and exploitative AI capabilities to drive business model innovation, enriches the discussion of environmental factors in organizational innovation, and enhances the contextualized study of business model innovation.

New quality productive forces are vital for the high-quality development of Chinese society. To strengthen new quality productivity, it's necessary to deepen the innovative development of the digital economy. At present, digital innovation and entrepreneurship are flourishing.As a new digital productivity tool, digital products show broad market prospects.
Some of the large digital innovation platforms offer innovative opportunities for digitally native enterprises to develop their own application products for a large number of platform users. Some native digital enterprises, after experiencing swift expansion, often venture into the platform market with the strategic intent to either fulfill their initial vision or to establish a late-mover advantage, while the other part of the enterprise is struggling at the edge of survival. Therefore, how to improve the vitality of enterprises in the limited market space and profit from digital innovation has become an important practical problem.
To address these research gaps, this paper
takes digital native enterprises of developing mobile application products as the research object. It combines the theory of profiting from innovation, follows the research idea of "knowledge search-iterative innovation-advantage construction", and then explores the internal evolutionary mechanism of digital native enterprises with different lead times and growth stages to realize profiting from innovation in iteration. This paper uses the digital product data and text information of the mobile application industry on the innovative digital platform of the App Store, and adopts the method of literature research, text analysis and case study to conduct an in-depth and comprehensive exploration of the research question.
The findings of this paper are as follows: (1) In the three stages of introduction stage, growth stage, and renewal stage, digital native enterprises need to select and match iterative innovation strategies based on stage context in order to realize advantage construction by utilizing the exclusive mechanism of knowledge search ability. In general, at the introduction stage, enterprises need to carry out responsive iteration through industry cognitive learning and benchmarking observation learning to promote advantage seeking; at the growth stage, enterprises need to carry out forward-looking iteration through technology embedding learning and market-oriented learning to promote advantage construction; and at the renewal stage, enterprises need to carry out leading iteration through cross-border reorganization learning and precision strategy learning to promote advantage continuation. (2) The different lead times of enterprises promote the formation of two different evolutionary paths to realize profiting from innovation in iteration. In the process of advantage construction, the first-mover digital enterprises go through three evolution processes: industry prototype iteration to seize the first mover market, leading design iteration to stimulate the network effect, and integrated iteration to amplify the ecological value. In the process of advantage construction, the late digital enterprises go through three evolution processes: module iteration to locate the niche market, market segment iteration to capture the first network effect, and deep iteration to enhance the differentiation value. Finally, it is found that for the first-mover digital native enterprises, adopting the rapid expansion strategy iteration focusing on the core technology innovation is conducive to maintaining the competitive advantage; for the late-mover digital native enterprises, adopting differentiation strategy iteration focusing on heterogeneous demand pulling is conducive to obtaining competitive advantages.
This paper enhances the theory of profiting from innovation, particularly in digital innovation, by examining the product innovation of digital native firms. It explores the differences in the evolutionary processes of organizations entering the market at various times and how they build advantages through iteration, influenced by the lead time's exclusive effect. The study also investigates how knowledge search impacts evolutionary strategy choices at different growth stages, with a focus on knowledge learning ability as a complementary asset. The findings offer practical insights for digital native enterprises' growth and innovation, guiding both enterprises on how to iterate their products and policymakers on fostering high-quality digital economic development, and stimulating the positive role of digital productivity tools in promoting digital industrialization and industrial digitalization.

In the era of digital economy, digital technologies such as big data and blockchain have shattered the geographical constraints of traditional economies, overturned the inherent development mode of the industry, sparked a new round of entrepreneurial boom, and greatly changed the growth environment faced by entrepreneurial enterprises. Ecological niche enhancement is the essence of the growth and evolution of entrepreneurial enterprises. The niche theory points out that environmental uncertainty will inevitably lead to fierce competition among enterprises, resulting in overlapping and separation of enterprise niches. How to build and maintain advantageous niches for entrepreneurial enterprises is the main challenge they face in their growth and evolution process. The deep development of the digital economy not only brings about a transformation of the growth environment for entrepreneurial enterprises, but may also be a singularity for enterprises to seek independent breakthroughs and occupy a favorable ecological position. Diversified digital technologies and platforms provide new, low-cost, and efficient scenarios for the acquisition, integration, and use of entrepreneurial resources, as well as the construction of core value networks. They also provide new ideas for entrepreneurial enterprises to build and maintain their advantageous ecological niche.
Therefore, this study takes the development of the digital economy as the starting point, measures the level of digital economy development in cities at or above the prefecture level, and combines micro data of listed companies on the China Growth Enterprise Market to empirically test the impact and mechanism of the digital economy on the ecological niche of entrepreneurial enterprises. The results show that (1) the digital economy has a significant effect on enhancing the ecological niche of entrepreneurial enterprises. In addition, the longer a startup is established and the smaller its debt pressure, which is more conducive to improving its ecological niche; the level of regional economic development, infrastructure construction, degree of openness to the outside world, and level of financial development also have a significant positive impact on the ecological niche of entrepreneurial enterprises. (2) In terms of mechanism, on the one hand, the digital economy activates and empowers entrepreneurial enterprises to form differentiated strategies through technological innovation, and constructs core value networks to achieve ecological niche enhancement; on the other hand, the development of the digital economy has reduced the degree of information asymmetry among enterprises, providing support for entrepreneurial enterprises with liquidity, mastering key information on potential resources, reconstructing their core capabilities, and breaking through the original ecological niche level. (3) The heterogeneity test results show that for large entrepreneurial enterprises and non-state-owned entrepreneurial enterprises, the digital economy has a significant impact on enhancing their ecological niche. Meanwhile, the impact of the digital economy on the ecological niche of entrepreneurial enterprises also exhibits heterogeneity in different regions. In the eastern and western regions, the digital economy can significantly promote the improvement of the ecological niche of entrepreneurial enterprises, and the improvement effect in the eastern region is more significant. In the central region, due to the relatively lagging development model of entrepreneurial enterprises, the effect of the digital economy on enhancing the ecological niche of entrepreneurial enterprises is not yet significant.
The main theoretical contributions of this paper are twofold. First, this study incorporates the innovative perspective of "niche" into the growth mechanism of entrepreneurial enterprises, providing an in-depth analysis of the operational mechanisms for enhancing the ecological niche of entrepreneurial enterprises in the digital economy. It offers a new solution approach and unique theoretical perspective on how entrepreneurial enterprises can occupy advantageous ecological niches for rapid growth, making the research both cutting-edge and scientific. Second, by adopting a dual perspective of technological innovation and information asymmetry, this study improves upon existing research that tends to focus solely on either external or internal factors. It broadens the research perspective by simultaneously considering both technological enhancement and information acquisition factors in the process of enterprise development.

Green innovation(GI) has become crucial for the high-quality development of enterprises. With the impact of digital technology on the real economy, digital transformation(DT) has risen to a significant national development strategy. The process of DT implies introducing advanced productivity, which can empower enterprises to transform the development mode to realize GI. However, this process depends to a certain extent on the impact of enterprise agility and ESG information disclosure. Based on the theory of organizational information processing, DT can help enterprises respond to changes in the external environment promptly to promote GI by improving the information processing capability and effectively realizing the agility response of enterprises at the industrial, production, and sales ends. In addition, DT also exists in the interactive communication between enterprises and society. Accroding to the signaling theory, high-quality ESG information disclosure can play a "signaling effect" in conveying a positive enterprise image to society, and it is easy for enterprises to obtain external support and create conditions for GI. Green innovation (GI) is crucial for high-quality enterprise development, while digital transformation (DT) has become a key national strategy, driving advanced productivity. DT enhances enterprise agility and information processing capabilities, facilitating GI through efficient responses across industry, production, and sales. Additionally, DT fosters interactive communication between enterprises and society. High-quality ESG (Environmental, Social, Governance) disclosure acts as a positive signal, attracting external support for GI. Meanwhile, there are multiple interactions between the GI process of enterprises and the government. In recent years, local governments have been paying more and more attention to new quality productive forces. Local governments' focus on new quality productive forces supports industrial upgrading and provides a favorable environment for GI. However, further research is needed to explore the mechanisms of enterprise agility, ESG disclosure, and government attention within the DT-GI framework.
Using the data of Chinese listed enterprises from 2015 to 2023, this paper introduces the mediating variables of agility responsiveness and ESG disclosure and the moderating variable of local government's attention to new quality productive forces and empirically explores how
DT empowers GI of enterprises from the perspective of new quality productive forces. The results show that DT has a positive and significant impact on GI; agility responsiveness and ESG disclosure play a mediating role between DT and GI; local government's attention to new qualitative productivity positively moderates the relationship among DT, ESG disclosure and GI, and at the same time strengthens the mediating role of ESG disclosure between DT and GI. Further analysis reveals that the local government's concern on new quality productive forces can positively moderate the relationship between agility responsiveness and GI, and strengthen the mediating role of agility responsiveness in the relationship between DT and GI only when the degree of enterprise capital redundancy is high.
This paper makes several significant contributions to the literature on digital transformation (DT) and green innovation (GI). Firstly, it shifts the focus from the economic impacts of DT to its role in driving green development and green innovation dividends under the framework of new quality productive forces. This approach bridges gaps in current research and offers new empirical evidence on value creation through green-oriented digital transformation. Secondly, the study reveals the dual mediating roles of agility responsiveness and ESG disclosure quality between DT and enterprise GI. Unlike previous research that examined resource input, information sharing, and governance, this paper explores the theoretical mechanisms underlying these relationships, expanding the understanding of how DT empowers GI. Thirdly, it examines the moderating role of local governments' attention to new quality productive forces in influencing the GI process through DT. This research clarifies the contextual boundaries of DT's impact on GI and aligns with China's emphasis on developing new quality productive forces. It provides new empirical insights into how local government focus can shape enterprises' DT and GI, contributing to both theoretical and practical advancements in the field.

Specialized, refined, differentiated and innovative (SRDI) enterprises, as the main carrier of innovation-driven strategy, have become the key stabilizer of the new development paradigm. SRDI enterprises driven by independent innovation have shown a good development trend in their industries. Against the backdrop of building an innovative country, it has become an important issue whether SRDI enterprises can play an exemplary role in innovation and affect the innovation of enterprises in the same industry. Some scholars have paid attention to the peer effect of manufacturing enterprises, general enterprises, leading enterprises and competitors. However, no studies have yet examined the peer effect of innovative leading enterprises such as SRDI enterprises.
In view of this, this study selects listed companies from 2011 to 2021 as research samples,and examines the direct impact of the innovation of SRDI enterprises on the innovation of enterprises in the same industry as well as the moderating roles of industry competition degree and financing constraint;it further investigates the heterogeneity of the above impacts across enterprises with different ownership nature and different scales, and analyzes the threshold effect of the impact of the innovation of SRDI enterprises on the innovation of enterprises in the same industry.
The conclusions include three aspects. Firstly, from the perspective of peer effect, the innovation of SRDI enterprises positively affects the innovation of enterprises in the same industry. Industry competition degree and financing constraint respectively exert positive and negative moderating roles in the impact of the innovation of SRDI enterprises on the innovation of enterprises in the same industry. Secondly, the results of heterogeneity analysis show that in terms of the enterprise ownership nature, the moderating role of financing constraint is not significant in state-owned enterprises in the same industry, but it is significantly negative in non-state-owned enterprises. In terms of the enterprise scale, the innovation of SRDI enterprises has a significant impact on the innovation of enterprises in the same industry of different scales, with large-scale enterprises being more affected; the moderating role of industry competition degree is not significant in large-scale enterprises in the same industry, but it is significant in small-scale enterprises; compared with small-scale enterprises in the same industry, the moderating role of financing constraint is stronger in large-scale enterprises. Thirdly, there is a double threshold effect on the innovation of SRDI enterprises positively affecting the innovation of enterprises in the same industry, and the promotion role weakens as the threshold value increases.
The theoretical contributions include three aspects. Firstly, this study focuses on the peer effect of SRDI enterprises, and expands the research on the relationship between the innovation of SRDI enterprises and the innovation of enterprises in the same industry. Secondly, this study clarifies the moderating roles of industry competition degree and financing constraint, and enriches the situational research on the impact of the innovation of SRDI enterprises on the innovation of enterprises in the same industry. Thirdly, this study reveals the threshold effect of the impact of the innovation of SRDI enterprises on the innovation of enterprises in the same industry, clarifies the differential impact of the innovation of SRDI enterprises on the innovation of enterprises in the same industry at different levels, and deepens the research on the peer effect of SRDI enterprises.
The management implications include four aspects. Firstly, enterprises in the same industry should pay attention to the importance of the peer effect, actively keep pace with SRDI enterprises, adjust imitative behavior according to the innovation level of SRDI enterprise, and stimulate innovation vitality. Secondly, enterprises in the same industry should actively face the industry competition, give full play to the positive role of industry competition degree in the impact of the innovation of SRDI enterprises on the innovation of enterprises in the same industry. Thirdly, enterprises in the same industry should take the initiative to deal with financing constraint, alleviate the negative role of financing constraint in the impact of the innovation of SRDI enterprises on the innovation of enterprises in the same industry. Fourthly, enterprises in the same industry should adjust innovative strategies based on the present situations of ownership nature and scale.

Environmental, social responsibility, and corporate governance(ESG) has emerged as a critical framework for assessing the sustainable development of enterprises. It aligns closely with China’s "dual carbon goals" and "high-quality development" objectives. The government underscores the need to promote green development and accelerate innovation-driven development strategies, thereby providing fundamental guidance for the advancement of ESG. How to balance the resource rigid demand of enterprise green innovation practice and ESG responsibility fulfillment, and take into account the coordination of social contribution and enterprise value maximization, is a major problem to be solved urgently to help high-quality development.
This study selects A-share listed companies in China from 2009 to 2022 as research samples and employs a system GMM model to empirically examine the dynamic interaction between green innovation behavior and ESG responsibility fulfillment. It also investigates the contingent effect of social supervision on this relationship. Additionally, the study explores how regional differences, property rights nature, and pollution intensity affect this interaction, thereby enriching the understanding of the scope and effectiveness of the relationship between green innovation and ESG responsibility fulfillment.
The study finds that there is a dynamic interaction between green innovation behavior and ESG responsibility fulfillment, that is, the improvement of green innovation behavior in the current period significantly improves the level of ESG responsibility fulfillment in the same period, and the ESG responsibility fulfillment in the current and lagging periods promotes the improvement of green innovation behavior.ESG responsibility fulfillment has a lag effect on green innovation behavior; media supervision plays a moderating role in the interactive intertemporal relationship between green innovation behavior and ESG responsibility performance. The current and lagging two-period social audit can significantly promote the impact of current and lagging two-period ESG responsibility performance on green innovation behavior. Further analysis shows regional and ownership differences: the interaction between ESG responsibility fulfillment and green innovation behavior is more pronounced in the eastern region compared to the central and western regions. State-owned enterprises exhibit a stronger interaction than non-state-owned enterprises, particularly those in heavily polluting industries. By integrating temporal and spatial dimensions, this study examines the long-term dynamic interaction mechanism between green innovation behavior and ESG responsibility fulfillment. It cross-validates the relationship between the two and enriches the understanding of the interplay between green innovation and ESG practices.
This paper proposes that green innovation and ESG responsibility should be regarded as value investments. By optimizing the allocation of resources and improving resource utilization efficiency, enterprises can promote sustainable development. Additionally, it is essential to build a robust supervision ecosystem that leverages the synergistic effects of social and media supervision to encourage enterprises to transform external pressures into momentum for green innovation. The paper also calls for the development of differentiated strategies that provide targeted policy support based on regional and ownership differences. This includes encouraging green innovation in the western regions and enterprises with weaker R&D capabilities, while leveraging the leading role of state-owned enterprises in green innovation and ESG compliance. Ultimately, these measures aim to achieve full coverage of green innovation and ESG practices, thereby driving efficient and sustainable development across the board.
This paper makes three key contributions to the existing literature. Firstly, it explores the two-way interaction between green innovation behavior and ESG responsibility fulfillment, analyzing their dynamic inter-temporal relationship beyond the static short-term impact. This provides new insights into balancing the resource demands of green innovation and ESG responsibility. Secondly, it focuses on the moderating role of informal institutions, particularly social supervision and media auditing, in the relationship between green innovation and ESG responsibility. This highlights the importance of social embeddedness and provides a new reference for self-discipline and supervision. Thirdly, the paper examines the inter-temporal impact of green innovation and ESG responsibility from various perspectives, including regional differences, property rights, and pollution levels, enriching the understanding of their interaction and offering a more nuanced approach to future research.

The focus of government policy mirrors the strategic direction and key priorities in establishing a talent framework for scientific and technological innovation. Policy integration is a potent strategy for tackling the fragmentation that often plagues innovation talent policies. As China stands at a critical juncture for high-quality development propelled by scientific and technological innovation, where new quality productive forces,which are highly reliant on technological advancements, necessitate a commensurate human resource reserve and sustained talent supply. Consequently, the emergence of new quality productive forces imposes even higher demands on talent's innovative capacity. Given the national strategic orientation towards fostering new quality productive forces, policies related to these talents have garnered significant attention. Current research predominantly focuses on qualitative descriptions, characteristic profiles, and content evaluations of such policies. Against the backdrop of China's complex and profound social transformation and arduous reform and development tasks, fragmented governance and one-dimensional policy tools have proven inadequate in addressing increasingly sophisticated policy challenges.Policy integration, a systematic concept advocating collaboration among government departments, originates from Western theories but resonates with China's advocacy of 'overall planning and consideration.' Tracing the evolution of China's policies for scientific and technological innovation talents and clarifying the focus of policy attention at different stages can provide valuable feedback for subsequent policy formulation and implementation by government departments. Invoking government attention theory and policy integration theory can facilitate the overall planning of policies for scientific and technological innovation talents, enhance governance effectiveness, and provide the core impetus for the development of new quality productive forces.
By employing Python-based LDA topic modeling and social network analysis, this study explores the attention allocation patterns and integration transformation logic of 645 central policies on scientific and technological innovation talent from 1985 to 2023. From the perspective of the evolution of attention stages, policies for scientific and technological innovation talents have undergone a reform exploration period, a strategic deployment period, a comprehensive development period, and an innovation-driven period, with distinct emphases in attention allocation that overall tend towards three-dimensional development. From the perspective of the characteristics of attention allocation focus, the national strategic positioning of science and technology permeates throughout the entire process, and the deep integration of science and technology with the economy serves as the fundamental driving force for the transformation and development of policies for scientific and technological innovation talents. From the perspective of integration and transformation logic, policies for scientific and technological innovation talents constitute a top-down systematic project, evolving around both departmental integration and entity integration.
The research implications are as follows: Firstly, introduce a policy iteration mechanism to construct a dynamically adjusted ecosystem for the development of scientific and technological innovation talents. Secondly, strengthen national strategic guidance to facilitate the effective integration of the scientific and technological innovation chain with the talent cultivation chain. Thirdly, adopt policy integration as the governance approach to improve the overall framework of policies for scientific and technological innovation talents. In the future, efforts should be made to integrate policies targeting scientific and technological innovation talent with diverse innovation policies, thereby constructing a systematic, open, and collaborative framework for talent development aimed at nurturing new drivers of new quality productive forces. This study integrates the theories of policy attention and policy integration, with a focus on the cutting-edge issue of scientific and technological talent development amidst the emergence of new quality productive forces. It analyzes the evolution and transformation logic of central government policies on scientific and technological talent development using an integrated analytical framework, echoing the governance reforms oriented by the 'panoramic comprehensive rationality' in recent years. The theoretical significance of this research lies in enriching the single perspective of the theory of policy attention and expanding its application scenarios within the Chinese institutional context. The research findings contribute to a comprehensive understanding of China's experiences and lessons learned in building the scientific and technological talent system, thereby providing insights for accelerating the construction of a talent system suitable for the development of new quality productive forces.

Amid the increasingly fierce market competition environment, leaders are under increasing pressure in terms of organizational performance. They are more likely to develop a one-dimensional frame of thinking oriented towards economic profit, that is, the bottom-line mentality (BLM). Previous studies have shown that leader BLM is an important incentive to trigger employees′ deviant behavior. However, most scholars mainly focus on the destructive aspect and rarely consider the influence of leader BLM on employees′ constructive deviant behavior. Bootleg innovation, as a special form of constructive deviant behavior, has attracted much attention in recent years.
It describes employees pursuing unauthorized innovation activities aimed at benefiting the organization.As the leader BLM is characterized by both "profit-seeking" and "exclusivity", its influence on employee behavior may be more complicated. Subordinates may engage in private risk-taking behavior because they feel less constrained by rules, or reduce the active innovation behavior because their personal needs cannot be met. Therefore, drawing on the cognitive-affective personality system theory, this paper intends to construct a dual-pathway model to deeply analyze the relationship between leader BLM and employees′ bootleg innovation, make up for existing research limitations, and provide more complete, universal, and guiding theoretical support for enterprise management practice.
This empirical study employs an online+offline questionnaire survey method for data collection. Respondents primarily consist of employees from the technology research and development departments and manufacturing departments within the Internet, manufacturing, cultural, and creative industries. After exclusion of incomplete questionnaires and those completed in a very short time, the study yields a total of 404 valid responses, indicating an effective response rate of 80.8%. During the data-processing phase, confirmatory factor analysis, common method bias tests, descriptive statistical analysis, and hypothesis testing are performed using AMOS 24.0 and SPSS 26.0 software.
The results show that (1) leader BLM has a positive direct effect on employees′ bootleg innovation. The main reason is that the expected results of employees′ bootleg innovation meet the requirements of leaders′ bottom line, and leaders′ expectations for the completion of bottom-line tasks also provide more inclusiveness for employees′ diversified innovation methods. (2) Through the mediation of the perceived acceptability of norm violation and psychological contract violation, leader BLM has a double-edged sword effect on employees′ bootleg innovation. On the one hand, leader BLM enables employees to get the signal that "violation of norms is acceptable", stimulates risk-taking spirit, and promotes bootleg innovation; on the other hand, the leader′s neglect of employee needs will cause psychological damage to subordinates and lead to psychological contract violation, weaken the willingness to return to the organization, and is not conducive to bootleg innovation. (3) Employee perspective taking positively moderates the relationship between leader BLM and perceived acceptability of norm violation, negatively moderates the relationship between leader BLM and psychological contract violation, and moderates the indirect effect of leader BLM on dual paths of employees′ bootleg innovation. When employees have a high level of perspective taking, leader BLM has a positive significance on employees′ bootleg innovation through the cognitive and emotional dual path mechanism. These findings not only extend the research on the influence of the leader BLM on employees′ bootleg innovation but also reveal the influence mechanisms and boundary conditions of the leader BLM on employees′ bootleg innovation.
This paper makes contributions to the research on the leader BLM and employees′ bootleg innovation from the following three aspects. Firstly, it enriches the theoretical research of leader BLM on employees′ constructive deviant behavior and expands the depth of the research. Secondly, drawing on CAPS theory, it discusses the double-edged effect of leader BLM on employees′ bootleg innovation, making up for the deficiencies of integrated studies on leader BLM and enriching the research on leader BLM mechanism. Thirdly, it examines the moderating effect of perspective taking from the perspective of empathy and expands the boundary conditions for the role of leader BLM.

Amid the ongoing global technological revolution and industrial transformation,enhancing independent innovation capabilities and achieving breakthroughs in core technologies have become crucial directions for China to accelerate the implementation of its innovation-driven development strategy. Innovation,in essence,is a process of recombining existing knowledge elements. Because of the high complexity of knowledge and the scarcity of innovative resources,knowledge best retains its informational value when disseminated in relatively concentrated settings. Breakthrough inventions and innovations particularly require novel combinations of knowledge and the full mobilization of innovative resources. In recent years,innovation activities have demonstrated distinct industrial and regional agglomeration characteristics,which have become an important micro-foundation for localized innovation capability and created conditions for breakthroughs in core technologies. Further accelerating the localized agglomeration of innovation activities and enhancing localized innovation capability are key to achieving China's transition from a “major innovation nation” to an “innovation powerhouse”.
A unified and orderly market system can ensure the free entry and exit of enterprises and optimize the allocation of innovative resources. This requires leveraging market mechanisms and enhancing localized innovation capability by strengthening the role of enterprises as the main actors in technological innovation. However,the legacy of centralized resource allocation under the planned economy and the persistence of GDP-centric growth models since the reform and opening-up have given rise to local protectionism and regional market segmentation,severely constraining China's high-quality economic development. In response,China has undertaken innovative theoretical explorations and institutional reforms regarding how to build a high-level socialist market economy system. Among these,the Negative List system for market access represents a major nationwide market-oriented reform initiative. It aims to eliminate regional entry barriers through a unified national approach,promoting the formation of a unified national market. The “non-prohibited=permitted” market rule helps foster a more transparent and open market environment,ensuring the autonomy of market entities and stimulating market vitality. Against this backdrop,examining the impact of the Negative List system on localized innovation capability is a crucial step in verifying whether it achieves its intended policy objectives.
This paper uses the Negative List system for market access as its starting point to explore the impact and mechanisms of relaxed market access regulations on localized innovation capability. The research demonstrates that easing market access restrictions enhances the innovation capability of localized industries,with significant heterogeneity across sectors and regions—particularly evident in service industries and areas outside the five major urban agglomerations. In terms of mechanisms,deregulation affects localized industry innovation capability at the industry level by “facilitating enterprise entry and intensifying market competition”,and by “accelerating the flow of innovation factors and promoting knowledge spillovers” at the regional level. Extended analysis confirms that the relaxation of market access controls under the Negative List model primarily leads to “quality-driven expansion” rather than “inefficient involution” in regional innovation agglomeration. Specifically,deregulation improves the innovation performance of high- and medium-high-tech firms,thereby encouraging their regional clustering.
Drawing on the characteristics of localized agglomeration and network spillovers in innovation activities,and incorporating both comparative technological advantages and network positions across industries,this study measures localized innovation capability at the industry level using patent data,thereby contributing to the literature on innovation. Since the Negative List is generally formulated and adjusted on an industry-specific basis,and the extent of government regulation varies significantly across sectors,this study provides a more comprehensive assessment of the system effects on enhancing innovation capability in different industries by measuring the relaxation degree of market access in each industry. As China transitions to a stage of high-quality development driven by high-tech innovation,this study investigates whether market entry relaxation fosters “quality-driven expansion” via high-tech firm entry or triggers “inefficient involution” through low-tech firm entry. The findings provide theoretical and empirical insights into how high-standard socialist market economy reforms can support high-quality innovation development.

As a core channel for university–industry technology transfer, patent licensing plays a vital role in driving the industrial application of innovative achievements through market-oriented allocation of technology use rights, thereby supporting the development of new productive forces and the construction of a modern industrial system. The design of exclusivity in licensing agreements is a critical factor determining the success of university-enterprise collaboration, as it relies on the strategic trade-off between costs and benefits made by both parties. However, existing studies on the exclusivity of university-enterprise technology licensing primarily focus on the unilateral interests of either universities (supply side) or enterprises (demand side), ignoring the interactive decision-making process of both parties. Moreover, most research only explores the marginal net effects of single-level factors, failing to reveal how the interaction of multiple characteristics influences the choice of patent licensing forms
To address these gaps, this study adopts a configurational perspective and integrates the Technology-Organization-Environment (TOE) framework to investigate the multi-condition interactive mechanisms underlying exclusive licensing agreements. Six conditional variables are selected across three dimensions: patent quality and technology maturity (technology dimension), university Technology Transfer Offices (TTOs) and the number of historical university-enterprise transfer cases (organization dimension), and technology market activity and similarity of competing products (environment dimension). These conditions interact as individual factors and, more importantly, combine configurationally to determine licensing exclusivity. Therefore, this paper employs fuzzy-set qualitative comparative analysis (fsQCA),which is a method specifically designed to investigate the combined influence of multiple antecedent conditions on a given outcome,to explore how the technological, organizational, and environmental conditions and their interplay collectively shape exclusivity in technology licensing. Using the fsQCA approach, the study analyzes a large sample of invention patent licensing data between 211 universities and enterprises in China from 2000 to 2024, with 8 254 valid patents involving 99 universities and 5 092 enterprises
The results identify seven conditional configurations that facilitate the formation of exclusive licensing. These configurations are further classified into five typical driving modes: the university high transaction cost-driven mode, the university high transaction cost-enterprise low competition-driven mode, the university high transaction cost-high competition-enterprise low benefit-driven mode, the enterprise high benefit-low competition-driven mode, and the enterprise high competition-high benefit-driven mode. Building on these modes, this study develops a Condition-Driver-Effect-Function (CDEF) mechanism model, encapsulating four operational mechanisms underlying exclusive licensing: cost-driven, supply redundancy-driven, revenue-pulled, and competitive revenue-driven. Notably, no sufficient configurational conditions for non-exclusive licensing were identified. This outcome may stem from the complexity of non-exclusive licensing mechanisms—such as reliance on implicit factors like inter-organizational network relationships—and the disruptive impact of national open licensing policies on the traditional logic of non-exclusive licensing
This study makes three key contributions. First, it breaks through the limitations of traditional statistical methods by using the TOE framework and fsQCA to reveal the complex interactive effects of multi-level factors (technology, organization, environment) on exclusive licensing, providing a multi-path solution for the choice of university-enterprise licensing forms. Second, it expands the application of fsQCA in large-sample research, addressing the lack of generalizability in small-sample configurational studies and enhancing the reliability of empirical results. Third, it identifies that the absence of TTOs or limited historical cooperation—both leading to high transaction costs due to information asymmetry—are core conditions in most exclusive licensing configurations, highlighting the critical role of organizational factors in university-enterprise technology transfer
The findings also yield actionable implications for universities, Enterprises and policy makers. Universities should use professional TTOs to classify patents: high-quality, mature patents are suitable for exclusive licensing with high-potential enterprises, while low-value, immature patents can adopt non-exclusive licensing to stimulate market participation. Enterprises should select licensing forms based on market competition: exclusive licensing for high-demand, competitive markets to gain monopoly advantages, and non-exclusive licensing for less competitive environments to reduce costs. Governments should provide policy support (e.g., tax incentives, subsidies) to promote high-value patent licensing, strengthen intellectual property protection, and build technology trading platforms to optimize university-enterprise matching.

Knowledge is a critical strategic asset for organizations striving to establish competitive advantages and achieve sustainable growth. Employees serving as knowledge owners and knowledge disseminators are not always inclined to share their knowledge within the organizational framework. Instead,they may withhold or conceal knowledge due to personal interests and competitive pressures in the workplace. Knowledge hiding is a common phenomenon in organizations. Existing literature regards knowledge hiding as the opposite of knowledge sharing and argues for a negative relationship between knowledge hiding and performance. However,knowledge hiding also has potential positive effect on organizations. Therefore,more empirical evidence is warranted to resolve the ongoing debate over the impact of knowledge hiding on individual performance and team performance.
The existing literature primarily focuses on employees' personal factors and divides knowledge hiding into evasive hiding,rationalized hiding,and feigned ignorance,overlooking the role of leaders and the influence of organizational contexts. There is a growing emphasis on conceptual distinctions among different types of knowledge hiding,but research on the consequences of knowledge hiding tends to treat them collectively,lacking a thorough examination and discussion of the distinct impacts of various types of knowledge hiding on individual performance and team performance.
In view of this,this study investigates the impacts of various types of knowledge hiding on performance from both individual and team perspectives,grounded in leader-member exchange theory. Firstly,from two dimensions—the extent of leader's support and the leader's comprehension of employee knowledge—knowledge hiding is divided into four types: complicit hiding,collusive hiding,hiding in plain sight,and evasive hiding. Secondly,the study collected 373 valid responses through a questionnaire survey conducted among leaders and employees of multiple teams in different organizations. The hypotheses are verified by constructing a multiple linear regression model. The empirical results indicate that complicit knowledge hiding promotes both individual performance and team performance. Collusive knowledge hiding has an inverted U-shaped effect on individual performance and team performance. Knowledge hiding in plain sight has an inverted U-shaped relationship with individual performance but is positively related to team performance. Evasive knowledge hiding is negatively related to individual performance but has no significant effect on team performance. Different from previous literature,this research innovatively introduces the dimensions of knowledge hiding classification,and reveals the complex impact of different types of knowledge hiding on performance from both individual and team perspectives,providing a new exploration perspective to solve the problem of inconsistent effects of knowledge hiding in existing researches,and enriching literature on the relationship between knowledge hiding and performance.
Considering the substantial disparities in the impact of various types of knowledge hiding on individual and team performance,it is imperative for enterprises to enhance the comprehension of knowledge hiding among both leaders and employees. A thorough understanding of the distinct types of knowledge hiding and their varying effects on performance is crucial. Knowledge hiding,often seen as a natural and rational behavior adopted by individuals and organizations to protect their own interests under the assumption of rationality,should be acknowledged by leaders and employees. Through training and other initiatives,their mindset should be shifted to confront the reality of knowledge hiding behavior,accurately identify its different forms,and respond appropriately to improve performance. Moreover,enterprises should fully appreciate the pivotal role of leaders in addressing knowledge hiding behavior. Leaders should be encouraged to employ a diverse range of strategies to tackle different types of knowledge hiding,transform the nature of such behavior,and thereby enhance performance. Close attention should be paid to the interactions between leaders and employees. By integrating institutional management with humanistic care,establishing a rational team culture and a trusting work environment,and fostering positive interactions and interpersonal trust,the detrimental effects of knowledge hiding on team performance can be mitigated. For instance,companies can dismantle hierarchical barriers,boost employees' sense of belonging,and strengthen the trust between leaders and employees through regular team-building activities and open communication channels. This approach can help transform evasive hiding into collusion hiding,ultimately leading to improved individual and team performance.

In the face of technological transformations and market turbulence in the digital era, technology-based small and medium-sized enterprises (SMEs), as vital agents in the implementation of innovation-driven development strategies, are often constrained by their digital capabilities. This constraint may lead to the formation of rigid knowledge structures and patterns of thinking during their long-term development. Existing studies have yet to thoroughly explore digital capability constraints as a significant barrier for technology-driven SMEs in real-world scenarios, nor have they adequately addressed how to resolve these limitations to foster innovation. Conversely, the activity of knowledge fields can effectively promote innovation and the dissemination of knowledge. Moreover, for technology-based SMEs, the skillful integration and strategic orchestration of existing resources are key to gaining an innovative edge, facilitating the expansion of current products and technologies into broader application domains. Therefore, exaptation, which involves the serendipitous discovery of new market opportunities through the utilization of existing resources, serves as an alternative source of innovation, offering a unique approach for the leapfrog development of technology-based SMEs in the digital age.
In order to address the question of "how technology-based SMEs can achieve exaptation by overcoming digital capability constraints",this study selects technology-based small and medium-sized enterprises as research samples. These SMEs are characterized by a total number of employees less than 500, a proportion of technology personnel greater than 10%, and a revenue of less than 200 million yuan. The data was collected by questionnaire, and a total of 450 questionnaires was distributed, with 332 valid questionnaires and a valid questionnaire response rate of 73.8%. The primary variables under investigation encompass digital resource collaboration capability constraints, digital operation capability constraints, knowledge inertia, knowledge field activity, and exaptation. The measurement of these variables is grounded in well-established scales from both domestic and international sources. Specifically, all variables were assessed utilizing a
5-point
Likert scale. The Cronbach's alpha values of each variable scale were all above 0.8, indicating that the scales have high reliability and can effectively measure the corresponding variables.
Leveraging the collected data, this study undertakes an empirical analysis into the relationship among digital capability constraints, knowledge inertia, and exaptation. The analysis employs a comprehensive methodological framework, including reliability and validity testing to ensure the robustness of the measurement instruments, descriptive statistical analysis to elucidate the mean, standard deviation, and correlation coefficient of each variable in the model, and hypothesis testing to validate the proposed theoretical relationships.
The results show that (1) both digital resource collaboration capability constraints and digital operational capability constraints exert a significantly negative impact on exaptation, with the former having a more pronounced effect; (2) both constraints significantly positively affect knowledge inertia, with digital resource collaboration capability constraints being more likely to lead to an increase in knowledge inertia; (3) knowledge inertia negatively affects exaptation and plays a significant mediating role between the two types of digital capability constraints and exaptation; (4) knowledge field activity negatively moderates the relationship between knowledge inertia and exaptation, and it also moderates the mediating effect of knowledge inertia between the two types of digital capability constraints and exaptation.
In summary, this paper integrates dynamic capabilities theory and knowledge base theory to further refine the types of digital capability constraints faced by technology-based SMEs, while also analyzing the mediating role of knowledge inertia and the moderating effect of knowledge field activity. The study clarifies the mechanisms by which digital capability constraints impact exaptation in technology-based SMEs, providing valuable theoretical support and practical insights. These SMEs should prioritize digital capability building as a strategic intiative, addressing constraints through self-assessment, collaborative innovation, and investment in key technologies. Additionally, these enterprises need to adapt to evolving market and technological trends by establishing efficient knowledge management systems and fostering a culture of innovation to prevent knowledge inertia from hindering progress. Furthermore, enhancing knowledge field activity is critical. By creating platform-based organizational structures and leveraging policy support, SMEs can facilitate knowledge flow and resource sharing, driving innovation and growth.