Based on regulatory focus theory and the behavioral theory of the firm, we empirically examine the impact of top management teams’ environmental regulatory focus on corporate green innovation preferences and its boundary conditions using data from Chinese A-share listed companies from 2012 to 2022. Results show that environmental promotion focus boosts firms’ preference for substantive green innovation, while environmental prevention focus inhibits it. Additionally, positive environmental performance feedback weakens the effect of promotion focus and mitigates the negative impact of prevention focus. Negative feedback, on the other hand, strengthens the positive influence of promotion focus and exacerbates the negative effect of prevention focus. Further analysis reveals that positive feedback has a stronger moderating role in non-heavy-polluting industries, while negative feedback is more influential in heavy-polluting industries.

Based on upper echelons theory, this study takes A-share high-tech enterprises from 2014 to 2023 as a sample to explore the impact of AI leadership on digital innovation. The results show that AI leadership has a positive impact on corporate digital innovation, with entrepreneurial orientation and organizational routines serving as mediating variables. Both executive political connections and corporate adaptability strengthen the positive impact of AI leadership on digital innovation. Further research reveals that: ①From the perspective of digital innovation types, AI leadership promotes digital product and process innovation but has no significant relationship with digital business model innovation. ②From a dynamic perspective, the positive impact of AI leadership on digital innovation exhibits temporal continuity, yet the impact gradually weakens over time. ③In contexts where industry competitive interaction is more intense, digital infrastructure is more developed, and technological human capital is more abundant, AI leadership has a stronger promoting effect on digital innovation.

This paper proposes the end-to-end paradigm as a new organizational management paradigm driven by artificial intelligence. It aims to address the challenges posed by current AI technologies to the traditional division-of-labor paradigm and promote a deep restructuring of the subjects, units, and operational mechanisms of organizations. Through theoretical construction, this paper introduces the hybrid agent as a new type of actor in the human-machine integrated model, replacing positions with tasks to enable dynamic adjustments of organizational units, and thereby drives the deep integration of management and business activities. Based on this, six core propositions are put forward. Furthermore, by incorporating the practical case of CooCaa Technology Co., Ltd, this paper elaborates on the implementation path and results of this paradigm in real organizational contexts. The findings demonstrate that the end-to-end paradigm is not a marginal improvement of existing organizational theories, but a systematic reconstruction of the fundamental assumptions and core logic of management science, providing a new theoretical perspective for understanding the evolution of organizational forms in the age of AI.

Based on the coupled framework of the Eclectic Paradigm (OLI) and dynamic capability theory, this paper takes the internationalization of BYD New Energy Vehicles as an example to explore the evolutionary mechanism of dynamic capabilities of advanced manufacturing enterprises with full industrial chains and their driving role in competitive advantages. The study finds that: ①Dynamic capabilities and OLI advantages co-evolve: resource-driven reconstruction of ownership advantages, institution-driven acquisition of locational legitimacy, and value-driven upgrading of internalization advantages. ②The full industrial chain structure is the core medium for the coordination between dynamic capabilities and OLI, and its hierarchical evolution of “vertical integration-module adaptation-ecological openness” supports enterprises’ transition from technological control to ecological dominance.③Dynamic capabilities evolve in stages through the path of “resource-driven—institution-driven—value-driven”: focusing on core technology integration and market strategy formulation in the resource-driven stage; strengthening compliance breakthroughs and localization practices in the institution-driven stage; and achieving standard output through ecological empowerment in the value-driven stage.

This paper takes Wafangdian Bearing Group as a case study and adopts a single-case study method to explore how the long-established state-owned enterprises release the potential of digital transformation by digital unlocking. It is found that digital unlocking is the key to the successful digital transformation and “curve overtaking” of the long-established state-owned enterprises lacking resources and capability base. The digital unlocking of long-established state-owned enterprises includes three dimensions, namely, calibrating digital strategy direction, releasing organizational flexibility and activating employees’ motivation. Calibration measures include formulating a digital transformation strategy and aligning with business strategy; release measures include breaking the traditional organizational structure, reconstructing management system and standardizing business processes; activation measures include breaking IT and business barriers, reconstructing employee knowledge system and internalizing employee digital thinking.

Based on the application and funding data for the Business Administration discipline from the National Natural Science Foundation of China (NSFC) during 14th Five-Year Plan period for the years 2021~2025, which includes the General Program; the Young Scientists Fund (Categories A, B, and C); the Fund for Less Developed Regions; the Key Program; and the Major Program, this paper uses bibliometrics and text mining methods to examine development trajectories, applicant profiles, institutional and regional distributions, and thematic foci. The results show: The discipline demonstrates a stable growth trend overall, with a notable increase in the application of the Young Scientists Fund (Category C), indicating a continuous improvement in research activity; Major Programs are aligned with national strategic needs and focus on enterprise entities, focusing on research areas such as industrial chain resilience and digital transformation; The Business Administration discipline has actively embraced a problem-oriented approach and methodological standards, leading to significant progress in paradigm transformation and methodological innovation.

This paper uses the difference-in-differences method to analyze the impact of the merger of national and local taxes on the non-local investment of enterprises. The study found that the consolidation of national and local taxes can reduce the number of non-local subsidiaries. The mechanism analysis shows that regional tax administration and space for profit transfer are the related mechanisms. Further analysis shows that the merger of national and local taxes can effectively differentiate different types of enterprises, which increases the actual tax burden of non-local investment enterprises in the tax avoidance category, but has no significant impact on the tax burden of real non-local investment enterprises. The impact of the merger of national and local taxes is obviously heterogeneous, and its governance effect is more significant in the strong government intervention, poor legal environment and private enterprises in the regions where the non-local subsidiaries are located.

This study investigates a supplier’s channel encroachment strategy on a retail platform under asymmetric demand information. Within a two-echelon supply chain consisting of a supplier and a retail platform, we develop a signaling game model and examine three supplier strategies: no encroachment (using the platform only for distribution), committed encroachment (pre-committing to a consignment quantity before the platform places its order), and delayed encroachment (determining the consignment quantity after observing the platform’s order). The results show that when the platform’s commission rate is low, the supplier prefers encroachment. When commission rates are low and market fluctuations are small, delayed encroachment emerges as the optimal strategy. In other cases, committed encroachment is preferred. However, relying on the platform’s order quantity as a demand signal is not always beneficial. When fulfillment costs are high or demand variability is low, disregarding this signal yields greater advantage for the supplier.

This study focuses on the context of AI-generated content (AIGC) advertising, aiming to investigate how two typical disclosure strategies—technical disclosure and relational disclosure—influence user trust through the mediating roles of informational authenticity and expressive authenticity, while further examining the moderating effects of AI appreciation and advertising appeals. Through multiple scenario-based experiments, a moderated dual-mediation model was developed and validated. The results showed that technical disclosure primarily built trust by enhancing informational authenticity, with this effect being more pronounced among users with high AI appreciation and in the context of informational advertising appeals. In contrast, relational disclosure fostered trust mainly by strengthening expressive authenticity, proving more effective for users with low AI appreciation and in the context of emotional advertising appeals.

Based on the “Task-Relationship-Change” three-dimensional leadership theory and the grounded theory, this paper deeply explores the connotation and structure of digital leadership. Through completing exploratory factor analysis and confirmatory factor analysis to test the 6 dimensions of digital leadership, this study develops the digital leadership scale that includes 30 items. The dimensions include digital change thinking, digital vision inspiration, digital tool application, digital strategy promotion, digital communication and collaboration, and digital empowerment support. The results of factor analysis indicate that the reliability and validity of the scale are all at an ideal level. Finally, this study tries to test the relationship among digital leadership, knowledge sharing behavior, and creativity.

Based on regulatory focus theory, this study examines how organizational AI readiness, an organization practice during the early stage of AI transformation, shapes employee job crafting. Using three-wave survey data from 398 manufacturing employees, the results reveal that learning motivation partially mediates the relationship between organizational AI readiness and promotion-focused job crafting, while impression management motivation fully mediates the relationship between organizational AI readiness and prevention-focused job crafting. Moreover, protean career orientation positively moderates the effects of organizational AI readiness on both learning motivation and impression management motivation. It also positively moderates the mediating effect of learning motivation in the relationship between organizational AI readiness and promotion-focused job crafting, as well as the mediating effect of impression management motivation in the relationship between organizational AI readiness and prevention-focused job crafting.

Based on the technological-economic paradigm theory framework, this study constructs a relational model between artificial intelligence (AI) and the “lock-in effect”in enterprise suppliers, and explores the mechanisms from the perspective of advantages of the information and competition. On this basis, an empirical test is conducted using samples of non-financial A-share listed companies in China from 2007 to 2023. The results show that AI can effectively mitigate the “lock-in effect”of enterprise supplier. After fully considering the issues of endogeneity and robustness, the results remain valid. AI alleviates the supplier “lock-in effect” by enhancing firms’ information and competitive advantages. Further heterogeneity analysis reveals that the relationship between AI and the supplier “lock-in effect” is influenced by national policies and local tax burdens, and is significant only among manufacturing firms.

Using data from Chinese listed platform enterprises between 2008 and 2023, this study employs a multi-period DID (difference-in-differences) approach to assess the impact of platform enterprise mergers and acquisitions (M&As) on labor income share. The results show that platform enterprise M&As significantly reduce labor income share through three channels: enhancing market power, driving technological progress, and fostering the gig economy. Heterogeneity analysis indicates that the negative impact of platform enterprise M&As on labor income share is more pronounced in firms with high financing constraints, in high-tech industries, and in regions with weaker labor protection. Further analysis reveals that platform enterprise M&As increase the labor income share of high-skilled workers while squeezing the labor income share of low-skilled workers. Additionally, the impact of platform enterprise M&As on labor income share is related to the scale of the merger, with larger merger scales significantly reducing the labor income share of firms.

Using data from A-share listed companies in Shanghai and Shenzhen from 2012 to 2023, this study employs text analysis techniques to identify and define AI-related M&A events, focusing on their impacts on corporate innovation activities. The study finds that conducting artificial intelligence M&As is beneficial to corporate innovation activities, and the mechanism is that artificial intelligence M&As improve innovation efficiency and reduce innovation costs. Heterogeneity tests based on firm characteristics reveal that private enterprises and high-growth firms benefit more from AI M&As in promoting innovation. Industry- and region-level tests further indicate that the positive effect of AI M&As is more pronounced in industries with higher competition, in non-high-tech sectors, and in regions with stronger intellectual property protection and richer data resources. Extended analysis suggests that AI M&As primarily drives non-AI innovation, implying that AI technologies serve as an enabler of firms’ core business innovation. Compared with non-AI M&As, AI M&As also generates greater market value for firms.

Based on the social Information Processing Theory, this study collected three-wave survey data from 278 R&D employees in an electronics technology group in eastern China to explore the interactive effects of creation incentive and creation constraint on employees’ creative deviance. The results indicate that: in organizations with high creation incentive and loose creation constraints (i.e., high sanction flexibility, high avoidance of premature evaluation), employees have a higher degree of psychological safety, making them more likely to engage in creative deviance.

Based on deterrence theory and supply chain risk contagion, this study empirically examines the impact of customer environmental administrative penalties on corporate ESG performance using a sample of A-share listed companies in Shanghai and Shenzhen from 2009 to 2022. The findings reveal that customer environmental administrative penalties have a supply chain contagion effect and can significantly enhance a company’s ESG performance. Mechanism analysis shows that customer environmental administrative penalties have improved their ESG performance through three aspects: forcing companies to undergo green transformation and upgrading, improving social responsibility and efficiency, and optimizing supervision and governance. Heterogeneity analysis shows that in the context of high public environmental attention, fierce industry competition, and close supply chain relationships, customer environmental administrative penalties have a more significant promoting effect on corporate ESG performance. Further research has found that fulfilling corporate ESG responsibilities under customer environmental administrative penalties is a substantive behavior rather than a strategic tool.

Drawing on the cognitive appraisal theory of stress, through the analysis of three-stage questionnaire data from 350 samples, this study examines the mechanisms and boundary conditions through which knowledge distance influences older employees’ knowledge seeking from younger colleagues. The results show that knowledge distance inhibits older employees’ knowledge seeking from younger colleagues through hindrance appraisal, while it facilitates such knowledge seeking through challenge appraisal. Moreover, age-inclusive human resources practices negatively moderate the relationship between knowledge distance and hindrance appraisal, thereby weakening the negative mediating effect of hindrance appraisal. In addition, age-inclusive human resources practices positively moderate the link between knowledge distance and challenge appraisal, thereby strengthening the positive indirect effect via challenge appraisal.

This study conducts a meta-analysis of 40 independent studies (N=16 143) from 39 articles to examine the relationships between talent management practices and employee work attitudes/performance, as well as the moderating role of industry type. Results indicate that exclusive talent management practices show significant positive correlations with job satisfaction, work engagement, organizational commitment, and extra-role performance, as well as a significant negative correlation with turnover intention, while their correlation with in-role performance is positive but non-significant. Inclusive talent management practices demonstrate significant positive correlations with job satisfaction, work engagement, organizational commitment, in-role performance, and extra-role performance, coupled with a significant negative correlation with turnover intention. Compared with exclusive talent management practices, inclusive practices exhibit stronger correlations with organizational commitment and turnover intention. Furthermore, industry type significantly moderates the relationship between talent management practices and turnover intention, with the correlation being stronger in knowledge-intensive industries than in labor-intensive industries.

Based on the case data of 9 platform-based enterprises, this paper adopts the multi-case study method to discuss the characteristics and antecedents for constructing multiteam systems, and the mechanisms through which they affect the system outputs in these enterprises. Conclusions show that: the multiteam systems established by platform enterprises present characteristics such as dynamics, difference, internal interconnectivity, external connectivity, and inter-boundary synergy, and they exhibit different inter-team coordination patterns depending on the variations in those characteristics; the reasons why platform enterprises establish the multiteam systems not only include the distal factors, such as fragmented teamwork, customer’s needs, and business ecosystem contingencies, but also include the proximal factors, such as digital platform, product/market/customer driven and compensation/assessment driven, and transparent culture; the mechanisms by which these multiteam systems contribute to system involve contain the inter-team coordination, identification, and leadership, as well as different inter-team processes.

Based on the signal theory and using Luckin Coffee and Xiaomi as the focal brands, this research explores the mechanisms and boundary conditions of brand alliance patterns on brand relationship quality through three experiments. The results show that, compared to visual co-branding, consumers have a more innovative perception and stronger brand relationship quality in ingredient co-branding; the mediating role of brand experience varies with alliance patterns and product types. In ingredient co-branding, compared to visual co-branding, the mediating effects of affective experience, behavioral experience, and cognitive experience are significant, while sensory experience and relational experience partially mediate the relationship; For shopping goods versus convenience goods, the mediating effect of relational experience is more pronounced; Perceived innovativeness and brand experience serve as chain mediators in the relationship between brand alliance patterns and brand relationship quality; the level of consumers’ lay rationalism will weaken the positive impact of perceived innovativeness on brand experience.

Drawing on social information processing theory, this study examines the daily influence of employees’ perceptions of AI creativity on their innovative behavior using the experience sampling method. Data were collected from 103 participants over five consecutive workdays, and a robustness test was conducted using a two-wave, supervisor-subordinate matched survey involving 385 paired responses. The findings reveal that daily perceptions of AI creativity positively predicted employees’ creative self-efficacy, which in turn enhanced their next-day innovative behavior. However, such perceptions also triggered technological anxiety, which in turn attenuated employees’ innovative behavior the next day. Furthermore, AI learning goal orientation moderated these relationships, shaping the effects of daily AI creativity perception on their innovative behavior.

To analyze the optimal decisions of platforms, sellers, and creators under both monetary and traffic incentive modes in content marketing, as well as the mechanisms through which key market factors exert their influence, this study develops profit models for sellers under both incentive strategies. By comparing the decisions and profits, we find that: ① The monetary amount and traffic support provided by sellers are negatively correlated with the creators’ basic traffic, the larger the basic traffic is, the lower the monetary incentive amount and traffic incentive quantity offered by sellers are. ② The creators’ effort is affected by the competition among creators, in specific, the optimal effort level of creators decreases as the number of participating creators increases, suggesting that creators should adjust their efforts based on market competition. ③ Sellers should choose an incentive strategy by considering both the number of creators and their own market scale. When the market scale is large and few creators are recruited, traffic incentives are preferred; As the market scale shrinks or the number of creators grows, monetary incentives become more suitable. This study offers theoretical insights and practical guidance for sellers, creators, and UGC platforms in content marketing.

By constructing a Stackelberg game model in two competing supply chains, this study investigates how the government subsidy policies (no subsidy, unit cost subsidy, and green technology investment subsidy) and consumer preference affect a new energy vehicles (NEVs) manufacturer’s eco-innovation level, profit, and social welfare. The results show that under a given subsidy policy, as the proportion of NEVs-oriented consumers increases or the proportion of oil-fueled vehicles consumers decreases, the NEVs manufacturer’s eco-innovation level increases. Furthermore, compared to the scenario without subsidy, the government subsidies increase the NEVs manufacturer’s eco-innovation level and profit. In the case of subsidies, when the proportion of NEVs consumers is high, the government should provide the unit cost subsidy, otherwise, it should provide the green technology investment subsidy.

Considering that ride-sourcing platforms pay taxi drivers the same rate as private car drivers or charge a commission on taxi orders to open the platform, this study examines the opening strategy selection of ride-sourcing platforms. By analyzing the four cases of non-opening, opening ride-sourcing order, opening taxi order, and mixed opening, the profit models for ride-sourcing platforms are constructed by using operational optimization methods, respectively. The optimal decisions for all scenarios are obtained by maximizing platform profits. The results show that all four strategies may be optimal, and the total number of potential private ride-sourcing drivers in the market and the coverage of taxi market play a key role in the selection of platform opening strategies. Platform opening does not always increase the overall profits of taxis and social welfare. Under the strategy of opening taxi order, there is a specific value of the number of taxis that maximizes the total profits of taxis and social welfare.

Based on institutional theory, this study empirically examines the impact of social trust on corporate ESG rating divergence and its underlying mechanisms using a sample of A-share listed companies in China from 2018 to 2022. The findings reveal that social trust can significantly reduce corporate ESG rating divergence. Mechanism tests indicate that social trust helps improve both the internal and external information environment of enterprises, thereby mitigating ESG rating divergence. Further analysis demonstrates that the inhibitory effect of social trust on ESG rating divergence is more pronounced when companies exhibit stronger internal controls, operate in regions with weaker marketization, have executives with higher environmental awareness, and face greater public environmental concerns. Additionally, social trust shows more significant alleviating effects on rating divergence in the social and governance dimensions of ESG. Economic consequence tests suggest that by mitigating ESG rating divergence, social trust ultimately enhances corporate performance and capital market performance.

ased on the organizational information processing theory, this paper takes 515 valid survey samples from manufacturing enterprises as research samples to study whether and how big data analytics capability affects green innovation. The results show that: big data analysis capability has a significantly positive impact on green innovation; digital supply chain platform plays a partial mediating role in the relationship between big data analytics capability and green innovation; digital supply chain platform and green supply chain integration play a chain mediating role in the positive impact on big data analysis capability and green innovation; control-oriented culture negatively moderates the chain mediating effect.

Using data from 2369 A-share listed manufacturing firms from 2007 to 2022, this study empirically examines the impact and mechanism of the opening of high-speed rail (HSR) on the high-quality development (HQD) of firms. The study finds that the opening of HSR significantly contributed to the HQD of firms. The mechanism test found that the opening of HSR can promote the HQD of firms by reducing supply chain dependence, and mainly by reducing downstream customer dependence. Meanwhile, the behavioral tendency of firms to reduce supply chain dependence is more obvious in the scenario of higher environmental uncertainty. Heterogeneity studies show that for non-state-owned firms, high-tech industries, and firms in regions with poor supply chain policy environments and digital policy environments, the opening of the HSR has a more significant effect on the promotion of HQD of firms. Further research finds that firms’ reduction in supply chain dependence is beneficial in promoting firm performance stability and accelerating the efficiency of financial flows along the supply chain, but it is also accompanied by a loss of product flow efficiency.

Based on the proactive motivation model, this study incorporates four moderating variables: leader-member exchange, team member exchange, citizenship pressure, and career agility. An integrated framework is developed to explain the transformation from voice intention to voice behavior, drawing on three types of motivational forces: “reason to” “can do” and “energized to”. Using a two-wave survey design, a total of 366 valid responses were collected and analyzed. The results reveal a moderate positive correlation between voice intention and voice behavior. Leader-member exchange and team member exchange, as sources of “can do” motivation, enhance the positive influence of voice intention on voice behavior. Meanwhile, citizenship pressure and career agility, serving as sources of “energized to” motivation, exhibit distinct moderating effects. Specifically, citizenship pressure demonstrates an inverted U-shaped effect on the relationship between voice intention and voice behavior, whereas career agility shows a positive moderating effect on this relationship.

Based on system justification theory, this study explored the mechanism through which bystanders’ observed of coworkers’ deviant helping behavior influences moral voice, utilizing data gathered from multi-wave questionnaire surveys (Study 1, 325 participants) and a situational experiment (Study 2, 218 participants), and the empirical results indicated that moral outrage and moral justification play a dual-mediating role between observing coworker deviant helping behavior and moral voice, i.e., observing coworker deviant helping behavior suppress moral outrage and reduces moral voice. Observing coworker deviant helping behavior increase moral justification and decreases moral voice. In addition, the renqing-oriented organizational climate perceptions plays a positive moderating role in the above relationships.

Classifying anthropomorphized brand roles into servant brands and partner brands, this study examines the mechanism and boundary conditions of awe towards nature on consumers’ preferences for anthropomorphized brand roles based on the cognitive load theory. Experimental results reveal that awe towards nature enhances consumers’ preference for servant brands (compared to partner brands). The need for accommodation mediates the above effect. Self-affirmation moderates the effect of awe towards nature on increasing the preference for servant brands: for consumers who have not undergone self-affirmation, awe towards nature enhances their preference for servant brands (compared to partner brands), while for consumers who have experienced self-affirmation, awe towards nature reduces their preference for servant brands (compared to partner brands) instead.

Drawing upon institutional theory and resource dependence theory, this study selects data from A-share listed manufacturing firms in Shanghai and Shenzhen spanning 2011 to 2022. Utilizing a difference-in-differences methodology, it investigates the impact and underlying mechanisms through which the National Big Data Comprehensive Pilot Zone (NBDCPZ)—a policy not explicitly targeted at carbon reduction or emission abatement—affects corporate carbon performance. The findings reveal that the NBDCPZ significantly enhances enterprises’ carbon performance, a conclusion that remains robust after a series of sensitivity analyses. Mechanism analysis indicates that the NBDCPZ improves corporate carbon performance through digital driving, green innovation, and the strengthening of human and financial capital security. Additionally, heterogeneity analysis demonstrates that the facilitating effects of the NBDCPZ on carbon performance are more pronounced in industries with higher pollution levels, regions with stricter environmental regulations, firms led by executives with elevated green awareness, areas characterized by stronger governmental governance, higher media attention, and heightened public environmental concern.

This study constructs a quasi-natural experiment of policy synergy with the help of the “Broadband China” strategy and the smart city pilots. It also explores the incentive effect of policy synergy on digital intelligence development based on the data of 281 prefectural cities from 2010 to 2021 by using double machine learning algorithms. The results show that: ①policy synergy significantly contributes to urban digital intelligence development, and shows a better enabling effect than a single policy. ②Policy synergy can also “double wheel” the development of urban digital intelligence through market incubation mechanisms of promoting non-agricultural entrepreneurship and increasing entrepreneurial vitality, and government support mechanisms of inducing government subsidies and intensifying government attention to innovation. ③The digital intelligence driving effect of policy synergy has a “first-mover advantage” in cities with an excellent business environment and a perfect legal system guarantee, and the positive effects of policy synergy are more prominent in central cities and economic zones east of HU Huanyong.

Based on the resource dependence theory and dynamic capability theory, this study collects data samples of ChiNext companies from 2012 to 2022 to reveal the impact mechanism of digital technology applications on the growth of ChiNext companies. Research has found that the application of digital technology by ChiNext companies has a significant positive impact on their growth, and this impact is more pronounced in private enterprises, large enterprises, enterprises in the eastern region, and enterprises in provinces with higher levels of digital economy development. Further research has found that the positive impact of the application of digital technology on the growth of ChiNext companies is moderated by the threshold of dynamic capabilities, and the impact becomes significantly positive after crossing this threshold.

Based on the resource-based view and social network theory, this paper constructs an analytical framework that integrates “resource support-resource allocation” and “innovation peer effect-competitive collusion effect” to investigate the impact of cross-owners on corporate R&D investment. Using a sample of A-share listed companies from 2007 to 2022, the findings reveal that the relationship between cross-owners and corporate R&D investment is inverted U-shaped. The moderation analysis indicates that redundant resources and market power weaken the inverted U-shaped relationship between cross-owners and corporate R&D investment, whereas digital transformation and operational efficiency strengthen this relationship. The heterogeneity analysis reveals that the inverted U-shaped relationship between cross-owners and corporate R&D investment is more pronounced in private enterprises and firms located in regions with higher levels of marketization, compared to state-owned enterprises and firms in regions with lower marketization levels.

Based on the sample of Chinese A-share listed firms from 2011 to 2021, this study treats the intelligent manufacturing pilot policy as a quasi-natural experiment to empirically examine the impact of intelligent manufacturing on firms’ data technology innovation and its underlying mechanisms. The findings show that the intelligent manufacturing policy has a significantly positive effect on firms’ data technology innovation. Mechanism analysis reveals that this effect operates primarily through enhancing firms’ informatization capabilities, increasing data factor investment, and facilitating knowledge spillovers. Heterogeneity analysis reveals that intelligent manufacturing has a more significant promoting effect on data technology innovation in firms in highly marketized regions, firms in industries with rapid technological iteration, manufacturing firms, and large-scale firms. Furthermore, the economic consequences analysis suggests that the intelligent manufacturing policy not only increases the quantity of firms’ innovation output but also significantly improves its quality.

Based on a comparative case study of the Shuangtong Platform and HCH, this paper explores the construction paths of corporate incubator-led entrepreneurial ecosystems from the perspective of resource orchestration theory. The research findings show that under the impetus of different parent incubation contexts, corporate incubators complete the construction of an entrepreneurial ecosystem through three key processes: structuring platform resources, enabling service capabilities and leveraging multi-party collaboration. Due to the differences in the parent incubation contexts, Shuangtong Platform and HCH show significant distinctions in each link of resource orchestration, evolving into two unique construction paths: “dependent” and “leapfrog”. In the context of the parent company’s development bottleneck, the former follows a passive adaptation and efficiency-first construction logic. It tends to maximize the utilization of the parent company’s existing resources and control risks, ultimately forming a complementary and focused entrepreneurial ecosystem. Under the guidance of the parent company’s innovative trends, the latter adheres to the construction logic of proactive layout and innovative breakthroughs, focusing on the expansion of outward-oriented resources and the capture of cutting-edge opportunities, ultimately forming a diversified and complementary entrepreneurial ecosystem.

By systematically reviewing studies related to service robot service failures, this study clarifies the concept of service robot service failures, summarizes the research progress of service robot service failures, and proposes a research framework for service robot service failures research, which includes three research themes: the consequences of service failures of service robots and their underlying mechanisms; service recovery strategies and the application of relevant theories of such failures; and the contextual conditions for service recovery. Finally, in view of the existing research gaps, this study outlines directions for future research.

This study takes A-share private enterprises in Shanghai and Shenzhen from 2013 to 2022 as the sample to empirically examine the impact of state-owned equity on the ambidextrous innovation performance of private enterprises and its mechanism from the perspective of innovation factors. The results show that state-owned equity significantly promotes the improvement of the ambidextrous innovation performance of private enterprises, and has a greater role in promoting the breakthrough innovation performance. The mechanism analysis shows that state-owned equity can enhance the ambidextrous innovation performance of private enterprises by alleviating financing constraints, optimizing talent structure, and promoting technical cooperation. Further analysis shows that managerial myopia weakens the promotional effect of state-owned equity on the ambidextrous innovation performance of private enterprises. Heterogeneity analysis further finds that the promotional effect of state-owned equity is more significant in private enterprises in competitive industries, with high growth potential, and with a high level of digitalization.

Taking the establishment of the Big Data Comprehensive Pilot Zone as an exogenous shock event for data factor agglomeration, this study employs panel data from 283 cities between 2011 and 2021 to construct a multi-period difference-in-differences model to investigate the impact of data factor agglomeration on urban entrepreneurial vitality. The study finds that data factor agglomeration significantly enhances the urban entrepreneurial vitality. Furthermore, this enhancement is more pronounced in eastern cities with better infrastructure and richer talent pools, as well as in municipalities and provincial capitals with higher administrative levels, more resources, and greater policy support. These advantages may help to give full play to the clustering effect of data factors, thus accelerating the innovation and entrepreneurship process. The results of the mechanism test show that data factor agglomeration enhances the urban entrepreneurial vitality in two ways: by promoting the release of the effectiveness of traditional factors and by promoting data factors to work together with traditional factors.

From a governance perspective, the K-means clustering method is used to identify three user groups. The NCA and fsQCA methods are combined to explore how the virtual brand community governance mechanisms affect the innovative behavior of different user groups. The findings are as follows: First, there are similarities in the impact of virtual brand community governance mechanisms on the innovation behavior of different user groups. Network convention is the common necessary condition, and users’ innovation behavior is jointly driven by multiple governance mechanisms. Second, there are differences in the impacts. Member embeddedness is the unique necessary condition for core users, and community incentive is the unique necessary condition for long-tail users. Knowledge protection is more crucial for leading users to engage in innovation behavior, while network conventions and member embeddedness are more important for core users to carry out innovation behavior. In addition, for some core users and long-tail users, the relationship governance mechanism plays a more important role in their innovative behavior.