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.

Taking the technological catch-up process of Dongfang Turbine in the field of thermal power technology as a case study, this paper adopts the event-path analysis method to analyze the process configuration of Chinese enterprises dynamically adjusting the dominant logic of their ambidextrous learning loops, based on the learning drivers of external response and internal spontaneity. The study finds that domestic enterprises can adjust the dominant logic of their ambidextrous learning loops from the outside in, revolving around the learning axis of “Technology Modification → Imitative Reconstruction”, to achieve technological self-reliance and self-strengthening. First, driven primarily by external responses, the enterprise constructs an exploratory learning-dominated ambidextrous learning loop (technology acquisition—technology modification—imitative reconstruction) to complete the construction of foundational capabilities. With the accumulation of technological capabilities, the enterprise actively breaks the existing path using imitative reconstruction as a key pivot, thereby advancing technological self-reliance. Ultimately, relying on internal spontaneous drivers, the enterprise reconstructs an explorative learning-dominated ambidextrous learning loop (technology modification—imitative reconstruction—independent R&D) to achieve technological self-strengthening.

Drawing on the 2024 National Survey on Returning hometown for Entrepreneurship and employing the signaling theory, this study investigates how the geographic migration patterns of returnee entrepreneurs influence their business performance. We find that entrepreneurs returning from the eastern coastal regions to their inland hometowns exhibit significantly superior performance compared to those who migrate within the same region or return from inland areas to coastal hometowns. The primary mechanism underpinning this difference lies in the fact that coastal-to-inland returnees tend to receive more government subsidies and attention. Further analysis reveals that this performance advantage associated with geographic mobility are concentrated among entrepreneurs who are highly educated, first-time founders, and those operating businesses in the survival stage or emerging industries. However, these advantages are negatively moderated by the intensity of local entrepreneurial competition. These findings suggest that geographic mobility functions as a signaling mechanism. These results indicate that only land-coastal entrepreneurs can transmit signals that align with local government expectations, thereby increasing their likelihood of receiving government support.

Taking Chinese “Lean-and-Healthy” Reform as a quasi-natural experiment and based on the sample of A-share listed firms from 2011 to 2019, this study finds that the reform significantly improves the labor investment efficiency in state-owned enterprises. The effect operates primarily through enhanced managerial governance effectiveness and optimized human capital structure. Heterogeneity analyses show that the effect of the reform is highly dependent on internal and external institutional environments, with more pronounced effects in firms with well-developed legal systems, mature labor markets, clear executive promotion expectations, and strong external supervision. Further research reveals a structural difference in the reform effects: while the reform effectively mitigates overinvestment in labor, its impact on alleviating labor underinvestment is limited and emerges only in firms with strong internal incentives and solid capability foundations, which highlights the asymmetric role of the reform in “reducing redundancy” versus “making up for deficiencies”.

In the era of digital economy, data elements play an increasingly important role in the operation and development of small and medium-sized listed enterprises. This article takes small and medium-sized listed enterprises in the Small and Medium -Sized Comprehensive Index from 2010 to 2023 as the research object, and empirically tests the relationship between data elements and the development resilience of small and medium-sized listed enterprises. The following conclusions are drawn: the application of data elements can exert a positive promoting effect on the development resilience of small and medium-sized listed enterprises through improving financing convenience, enhancing internal control level and net profit level.

Drawing on conservation of resource theory and employing latent profile analysis, this study investigates resilience profiles and their relational patterns within gig work contexts. The results reveal three distinct resilience profiles among platform gig worker: defensive-compensatory (13%), balanced-adaptive (52%), and affectively-enriched (35%). Work meaningfulness and community interaction significantly predicted profile membership. In particular, community interaction most strongly predicted the affectively-enriched profile, whereas work meaningfulness most strongly predicted the balanced-adaptive profile. Both predictors showed the weakest association with the defensive-compensatory profile. Furthermore, the profiles diverged markedly in their implications for sustainable careers, where the balanced-adaptive profile was reported to be the highest levels of well-being, the affectively-enriched profile exhibited the highest service quality, and the defensive-compensatory profile scored lowest on both outcomes.

Based on Role Theory, the research explored the mechanism and boundary conditions of mobile technology usage for work on employees’ work-family conflict through 253 valid employee samples collected in three stages. Research results shed light on the following findings: the use of mobile technology for work could not only directly increase employees’ work-family conflict level, but also indirectly aggravate conflict level through role overload. Organizational support could weaken the positive relationship between the use of mobile technology for work and role overload. At the same time, it weakens the mediating effect of the use of mobile technology for work on work-family conflict through role overload.

Based on grounded theory, a digital resilience scale was developed and a digital resilience model for manufacturing workers was constructed, centered on the core categories of “tough resilience” “determined transformation” and “flexible growth”. This model comprises three dimensions and 16 items. To further examine the scale’s external validity, a theoretical model linking “manufacturing workers’ digital resilience-promotive moderation focus-innovative proactive behavior” was constructed based on the proactive motivation model, incorporating visionary leadership as a moderating variable. Findings revealed: manufacturing workers’ digital resilience positively influenced promotive focus and innovative anticipatory behavior; promoting focus partially mediated the relationship between manufacturing workers’ digital resilience and innovative anticipatory behavior; visionary leadership positively moderated not only the relationship between digital resilience and promoting-focused mediation, but also the indirect effect of digital resilience on innovative anticipatory behavior through promoting-focused mediation.

Based on the conservation of resource theory, using data from 391 dyads of three-stage questionnaires of employees and their immediate supervisors, this study explored the inhibiting mechanism of perceived dirty work on employee’ taking charge behavior, and examined the mediating effect of psychological availability, as well as the moderating effect of perceived investment in employee development. The results showed that: perceived dirty work had a significantly negative effect on employee’ taking charge behavior; psychological availability had a partial mediating effect in the relationship between perceived dirty work and employee’ taking charge behavior; perceived investment in employee development not only positively moderated the relationship between psychological availability and employee’ taking charge behavior, but also positively moderated the mediating effect of perceived dirty work on employee’ taking charge behavior through psychological availability.

This paper combines knowledge from industrial clusters and enterprise growth theories to analyze the mechanism through which industrial cluster support affects the development of specialization, refinement, differentiation, and innovation (SRDI) among manufacturing SMEs and employs a sample of manufacturing SMEs in Zhejiang Province for empirical analysis. The findings indicate that industrial cluster support can effectively enhance the SRDI development level of manufacturing SMEs; however, the strength of industrial cluster support is moderated by both internal and external factors of the enterprises. Specifically, when manufacturing SMEs face severe “bottleneck” challenges, the supportive effect of industrial cluster support is more pronounced, whereas this supportive effect diminishes when manufacturing SMEs have higher levels of digital construction or cater to higher-level clients.

From the debtor’s perspective, this study uses a multi-period difference-in-difference model to examine the relationship between the establishment of bankruptcy courts and corporate innovations by taking A-share listed companies in Shanghai and Shenzhen from 2015 to 2023 as the research sample. The study finds that the establishment of bankruptcy courts can significantly promote corporate innovation. Increased risk resistance capacity and an optimized business environment are the mechanisms. Further research finds that bankruptcy courts have a biased effect: they only promote incremental innovation, but have a negative impact on breakthrough innovation. For non-state-owned firms and those with lower litigation risk, the role of bankruptcy courts in promoting corporate innovation is more significant. Bankruptcy courts can promote continuous innovation and continuous incremental innovation, but have a limited impact on continuous breakthrough innovation.

Based on the data of China’s A-share listed companies from 1999 to 2022, we discuss the impact of CE entrepreneurs on corporate green innovation. The results of the mechanism analysis show that the CE entrepreneurs reduce entrepreneurs’ investment in corporate green innovation through the two aspects of the proliferation of negative corporate reports and the exacerbation of financing constraints. To explore the distinction between the characteristics of the CE entrepreneurs and their corporations, we find that when the CE entrepreneurs only control one firm, the inhibiting effect on green innovation is more obvious after obtaining the CE identity. The economic consequence test finds that the CE enterprises reduce their investment in green innovation, which is “long and slow”. At the same time, they shift to charitable donations and advertising campaigns, which can quickly improve their reputation.

Based on the Emotion-As-Social-Information theory, this study explores the effects of service AI’s explicit and implicit emotional cues on customer satisfaction through four online scenario-based experiments. The findings reveal that explicit emotional cues from service AI positively influence customer satisfaction. Implicit emotional cues of service AI moderate the relationship between explicit emotional cues and customer satisfaction. Specifically, when service AI presents positive (vs. neutral) implicit emotional cues, the positive (vs. neutral) explicit emotional cues more effectively enhance customer satisfaction. The above effects are achieved through customers’ different emotional expectancy violation and perceived pleasure towards service AI Customers’ goal orientation moderates the impact of implicit and explicit emotional cues on perceived pleasure.

Focusing on atypical green products, and based on construal level theory and dual-process theory, this study conducted four experiments to explore the matching effect of green attributes and mental simulation on green purchase intention, and explored its mechanisms and boundary conditions. The results show that: for atypical green products, consumers’ green purchasing intention is stronger when green core attributes match process simulation, and when green peripheral attributes match outcome simulation. Processing fluency plays a mediating role in this process. As the boundary condition, cognitive load moderates the impact: when consumers are at a high level of cognitive load, whether it is green peripheral attribute or green core attribute, guiding consumers to conduct outcome simulation can have a more positive impact on green purchase intention.

Drawing on grounded theory and the health belief model, this study investigates the factors influencing surrogate health information seeking intention among older adults in the context of generative artificial intelligence (GAI). Grounded theory was employed to identify core elements and construct a theoretical model, which was subsequently validated through a survey-based empirical study. A total of 55 valid interview records transcripts and 291 questionnaire responses were collected. The findings indicate that perceived susceptibility, GAI trust, GAI literacy, and health information literacy significantly and positively influence surrogate health information seeking intention; perceived privacy risk significantly and negatively influences GAI trust; and information quality and perceived service experience indirectly and positively influence surrogate health information seeking intention by enhancing GAI trust. Health information literacy negatively moderates the effect of perceived susceptibility on surrogate health information seeking intention, while other interaction effects did not reach statistical significance.

Using 2012 to 2022 panel data of Chinese A-share listed firms, this study examines how the level of artificial intelligence (AI) affects firms’ internationalization performance, measured in terms of intensity, depth, and breadth. Grounded in dynamic capabilities and integrating Schumpeterian and Ricardian rents, we develop a three-stage sensing—seizing—reconfiguring framework. The results show that the level of AI technology significantly improves firms ‘internationalization performance, with effects robust to endogeneity and alternative specifications. Mechanism analyses indicate AI promotes internationalization by improving knowledge recombination, enhancing innovation quality, and easing financing constraints. Heterogeneity tests reveal stronger effects for firms with higher export technological complexity, non-state-owned firms, or in regions with lower digital financial development.

This study uses venture-capital-backed enterprises listed on the National Equities Exchange and Quotations from 2013 to 2021 as a sample to investigate how signing valuation adjustment mechanism agreements influences startup innovation. The result show that entering into these agreements leads to a significant reduction in firms’ innovation output. Mechanism analysis reveals that after signing the agreements, firms prioritize value realization over value creation in their decision making, as evidenced by a decrease in the R&D investment and the proportion of R&D personnel, accompanied by an increase in the proportion of selling expenses and sales staff. Heterogeneity tests show the innovation decline is more pronounced for firms with weak corporate governance and high operating environmental uncertainty after signing the agreements. Extended analysis further finds that venture capitalists exert an “information effect” by appointing directors to the board, which raises their tolerance for failure, generating a positive impact on corporate innovation.

Based on corporate investment theory, using a sample of manufacturing firms listed on the Shanghai and Shenzhen A-share markets in China from 2010 to 2022, this study explores the impact of over-indebtedness on the financial asset investments of these firms. The findings reveal that over-indebtedness drives financial asset investments in manufacturing firms by increasing financing constraints and intensifying principal-agent conflicts. From the perspective of investment motivation, profit-seeking is identified as the primary motive behind over-indebtedness-driven financial asset investments. In terms of investment efficiency, such investments are found to be inefficient and exhibit a trend of over-investment, which to some extent indicates a tendency for manufacturing firms to “shift from the real economy to the virtual economy”. Heterogeneity analysis shows that the promoting effect of over-indebtedness on financial asset investments in manufacturing firms is more pronounced under conditions of weak external audit supervision, greater distortion in factor markets, lower cost pass-through capabilities, and smaller macroeconomic fluctuations.

This study utilizes the government debt clearance as a quasi-natural experiment and selects data from A-share private listed companies from 2009 to 2023 to examine the impact on private enterprises’ commercial credit financing using the Difference-in-Differences model. The results show that clearing government debts can significantly reduce the commercial credit financing of private enterprises, thereby repaying the funds previously withheld from suppliers. The underlying mechanism lies in the fact that government debt clearance reduces the demand for commercial credit financing from private enterprises by increasing cash flow levels, enhancing inventory liquidity, and alleviating financing constraints. In contexts characterized by greater development capability of enterprises, higher supplier concentration, and a lower level of regional legalization, the effect of government debt clearance on reducing commercial credit financing for private enterprises is more pronounced.

First, based on fundamental theories of leadership, this study constructs a comprehensive analytical framework and clarifies the nature of related concepts, especially the unique meaning of time leadership relative to other leadership behaviors. Second, the study systematically reviews the influence of leadership time traits, as well as the influence and theoretical mechanism of time leadership behavior in detail. Finally, the study outlines future research directions to address existing limitations regarding conceptual ambiguity, the novelty of research perspectives, the hierarchy of action mechanisms, the variability of research contexts, and the diversity of research methods.