This study investigates the structure of innovation and entrepreneurship competence among university students in China. Based on an analysis of 33 policy texts on innovation and entrepreneurship education from 2010 to 2022, it constructs a structural model of university students’ innovation and entrepreneurship competence comprising the knowledge layer, ability layer, and literacy layer by employing the Onion Model. From the perspective of policy instruments, a two-dimensional competence–policy instrument analytical framework is established. The analysis reveals that the articulation of university students’ innovation and entrepreneurship competence in policy texts exhibits distinct stage-wise evolutionary characteristics. Furthermore, the current policy support system suffers from three structural imbalances: an over-reliance on supply-side policy instruments, with insufficient synergy from environmental and demand-side instruments; weak support from environmental and demand-side instruments for certain key competencies; and an emphasis on explicit knowledge over implicit literacy in the cultivation logic. Consequently, this study proposes a shift in the policy paradigm from factor input to system generation. Recommendations include optimizing the mix of policy instruments, improving the precision of interventions by environmental and demand-side instruments targeting key competencies, and reconstructing the cultivation system based on the different generative logics of explicit and implicit competence.

In the context of intensifying environmental regulation and sustainability pressures, firms increasingly face the challenge of sustaining green innovation under uncertainty. Green innovation resilience, which is defined as a firm’s capacity to maintain green innovation momentum and adaptively evolve technological capabilities amidst uncertainty, represents a critical organizational competence. Moving beyond static output measures, this resilience captures the intertemporal stability of firms’ green patenting activities during turbulent periods. From a systems perspective, executive compensation arrangements represent an important internal incentive mechanism that interacts with managerial characteristics and external policy environments. This study investigates how executive compensation stickiness—defined as asymmetric pay adjustment in response to firm performance—affects green innovation resilience. Using panel data from Chinese A-share-listed firms, we find that executive compensation stickiness significantly promotes green innovation resilience at the 5% level, suggesting that downward pay rigidity mitigates managerial risk aversion and supports tolerance for short-term setbacks in long-horizon green innovation. Furthermore, this positive relationship is further strengthened when executives possess environmental backgrounds (at the 5% level) and when firms receive government green innovation subsidies (at the 10% level), highlighting the interactive role of individual-level attributes and institutional policy support. Overall, the findings demonstrate how incentive asymmetry functions as a systemic property shaping firms’ adaptive responses and contribute to a broader understanding of green innovation resilience in complex socio-technical systems.

This paper conceptualises burnout in Project-Based Organisations (PBOs) as a systemic emergent property arising from the non-linear interaction between structural demands and human capital. Utilising a System Dynamics (SD) methodology, the study constructs a Causal Loop Diagram (CLD) to visualise the feedback architecture governing the burnout cycle. The analysis identifies the dynamic tension between the Reinforcing Loop of exhaustion (R1) and the Balancing Loop of adaptation (B1). A key theoretical contribution is the positioning of the Project Manager’s Emotional Intelligence (EI) not merely as a soft skill but as a systemic control lever (B2) capable of reducing information delays and shifting the system from reactive to proactive homeostasis. Crucially, the study operationalises these conceptual findings into a Burnout Risk Management Framework (BRMF), accompanied by a practical diagnostic dashboard. This tool offers managers a set of leading and lagging indicators for early detection, bridging the gap between theoretical plausibility and applied risk management in high-entropy project environments.

This study examines the non-linear relationship between European Structural and Investment (ESI) Funds and socio-economic development across EU member states from 2007 to 2020. To accomplish this, the study utilises a novel methodological approach, employing panel threshold regression to analyse the complex interactions between these variables. Using the Human Development Index (HDI) as a comprehensive measure of socio-economic progress, this research goes beyond traditional metrics, such as GDP, to capture a multidimensional view of development. The threshold variable, represented by the ratio of ESI Funds paid to GDP, highlights critical inflexion points where the impact of funding shifts, revealing both positive and negative effects. The study finds that ESI Funds positively impact socio-economic development up to a threshold of 0.7% of GDP, beyond which their effectiveness diminishes, emphasising the need for strategic allocation and management. Additionally, the analysis of control variables identifies a critical threshold range between 2% and 2.3% of GDP, indicating the growing importance of ESI Funds in fostering development within complex socio-economic contexts. This paper contributes to the foundational model of socio-economic development informed by ESI Funds, offering valuable insights for policymakers by emphasising the importance of balancing funding levels with strategic allocation to avoid diminishing returns.

Background: Ports play a strategic role in the efficiency and sustainability of European transport corridors; however, empirical evidence on their performance remains limited, particularly for Eastern European countries. This study aims to assess the technical efficiency and productivity dynamics of Romanian ports along the Danube corridor in a context of structural change and evolving cargo flows. Methods: Technical efficiency is estimated using an output-oriented Data Envelopment Analysis (DEA) model under variable returns to scale, followed by bias correction and determinant analysis employing the Simar–Wilson bootstrap procedure. Productivity change is examined separately using the Malmquist Productivity Index based on original DEA distance functions. Results: The analysis reveals substantial heterogeneity in efficiency levels across ports, with bias-corrected estimates indicating that efficiency differentials are structural rather than statistical. Cargo specialization emerges as the main determinant of efficiency, while location effects are found to be asymmetric. Efficiency levels are largely stable over time, and productivity change is modest, being driven exclusively by efficiency change, with no evidence of technological progress. Conclusions: These findings suggest that the performance of ports along the Romanian Danube corridor is shaped primarily by structural and organizational factors rather than temporal dynamics, underlining the importance of targeted policy interventions focusing on traffic consolidation, port specialization, and coordinated spatial and hinterland planning to enhance inland port performance within European transport corridors.

Rising geopolitical risks have become a defining feature of the global business environment, yet how firms—particularly those from latecomer economies—adjust their innovation strategies under such conditions remains insufficiently understood. Integrating resource dependence theory with the innovation ecosystem perspective, we propose that geopolitical risk induce firms to engage in cross-industry innovation as a strategic response to mitigate their reliance on international technological ecosystems, which traditionally provide cross-industry complementarities but are increasingly subject to disruption. Analyzing a panel of 12,354 Chinese listed manufacturing firms from 2012 to 2022, and employing fixed-effects negative binomial regression models implemented in Stata 18, we find that firms exposed to higher levels of perceived geopolitical risk are more likely to pursue innovations beyond their industry’s technological boundaries in subsequent years. This effect is weakened by industry technological complexity but strengthened by the firm’s nationalism, reflecting both reactive responses to external uncertainty and proactive efforts toward technological self-reliance. Our study contributes to innovation research by revealing how geopolitical forces reshape firms’ innovation trajectories and by extending resource dependence theory to the context of ecosystem-based interdependence. From a policy perspective, governments can promote rational and constructive nationalist narratives that encourage firms to commit to innovation in strategically vulnerable technologies.

Although innovation is widely recognized as an important driving force for enterprise development, there may not be a simple linear relationship between innovation and enterprise value. An in-depth investigation of the relationship between enterprise innovation and enterprise value is of great significance for the development of new energy vehicle (NEV) enterprises and the industry. Utilizing the sample of Chinese NEV listed companies from 2012 to 2022, this study empirically examines the effects of enterprise innovation on enterprise value from two perspectives: innovation input and innovation output. The results indicate that enterprise innovation does not necessarily promote the growth of enterprise value in all cases. Innovation input exhibits a U-shaped effect on enterprise value, while innovation output has a linear positive impact. And the operational efficiency of enterprises plays a partial mediating role. Furthermore, we explore the effects of internal and external environments on the relationship. High internal control costs weaken the U-shaped relationship of innovation input and reduce the positive impact of innovation output on value. In contrast, greater market competition attenuates the U-shaped effect of innovation input but strengthens the positive effect of innovation output on enterprise value. These findings highlight the contingent nature of innovation value creation in complex industrial systems and provide insights for strategy and policy in the NEV industry.

Consumer attitude uncertainty can hinder disruptive innovation (DI) diffusion in the new energy vehicle (NEV) market and weaken enterprises’ incentives to adopt new technologies. This study develops a dual-layer coupled network model linking consumer attitude dissemination and enterprise R&D strategy evolution under bounded observability. Our simulations show three main findings. First, stronger discouragement of counter-attitudinal dissemination markedly suppresses diffusion and lowers steady-state adoption. Second, diffusion strengthens when consumers weight public information more and firm messaging less, particularly under stronger policy support. Third, network structure shapes diffusion: stronger inter-enterprise connectivity increases adoption, and consumer topology and interaction breadth exert different effects under different network types. These results clarify how information environments, policy support, and cross-layer behavioral modulation jointly shape diffusion regimes.

The safe and efficient integration of small unmanned aircraft systems (sUAS) into the National Airspace System (NAS) requires a systems-based understanding of the interrelations among human, technological, and regulatory components. Existing Federal Aviation Administration (FAA) guidelines restrict most operations to visual line of sight (VLOS), which constrains operational scalability and underscores the need for system-level innovations supporting beyond-visual-line-of-sight (BVLOS) operations. This study adopted a socio-technical systems approach to evaluate how first-person view (FPV) technologies influence operator workload and situational awareness (SA), key human performance elements within the broader sUAS safety system. Participants meeting FAA Part 107 eligibility criteria were assigned to one of three visual configurations: (a) traditional VLOS, (b) FPV using a 21-inch monitor, or (c) FPV with immersive goggles. Workload was measured with the NASA Task Load Index (NASA-TLX), and Level 1 SA was assessed via post-task recall. ANOVA results revealed no statistically significant differences across visual conditions, indicating no evidence that FPV integration either increased cognitive load or impaired perceptual awareness compared to traditional methods. Complementary analysis of NASA’s Aviation Safety Reporting System (ASRS) identified SA as the most recurrent human-factor issue, suggesting system-level implications for human–machine interaction and training design. These findings contribute to the systemic understanding of human factors in UAS operations, supporting FPV’s potential as a viable subsystem for achieving safe and effective BVLOS integration within complex socio-technical aviation systems.

Against the backdrop of China’s commitment to achieving carbon peaking by 2030 and carbon neutrality by 2060, inter-provincial carbon emissions form a complex interconnected spatial network—clarifying its operational mechanisms is crucial for optimizing regional carbon reduction strategies. Based on 2006–2021 data from 30 Chinese provinces, this study constructs the China Provincial Carbon Emission Spatial Correlation Network (CPCESCN) using a modified gravity model. Social Network Analysis (SNA) explores its structural characteristics, while motif and QAP correlation analyses identify endogenous structural and attribute variables. Innovatively integrating Exponential Random Graph Models (ERGM) and Stochastic Actor-Oriented Models (SAOM), it investigates the network’s static formation mechanisms and dynamic evolution drivers. Results show CPCESCN has a stable multi-threaded structure without isolated nodes, with Jiangsu, Guangdong, Shandong, Zhejiang, Henan, and Sichuan as high-centrality core nodes with high centrality. GDP, green technology innovation, urbanization rate, industrialization rate, energy consumption intensity, and environmental regulations significantly influence network dynamics, with reciprocal relationships as key endogenous drivers. While geographic proximity still facilitates network formation, its impact has weakened notably, and functional complementarity has become the dominant evolutionary driver—based on the findings, policy suggestions are proposed, including deepening inter-provincial functional cooperation, implementing differentiated carbon reduction policies, and optimizing multi-dimensional low-carbon transformation systems.