Digital technology drives global industrial transformation. The synchronized development of organizational digital transformation and innovation systems is pivotal in corporate strategy and governmental governance. The dynamic interaction mechanisms among digital economy, government innovation policy, and regional innovation capacity remain insufficiently explored. This study employs panel data from 15 prefecture-level cities within the Yangtze River Delta urban agglomeration, spanning the years 2012 to 2020, and uses the panel vector autoregression (PVAR) model to investigate the interrelationships among the digital economy, government innovation preferences (the government’s supportive attitude and policy inclination towards innovative activities in the fields of science and technology as well as economic development), and regional innovation capacity. This research emphasizes the impact of the digital economy on regional innovation capacity and the influence of government innovation preferences on regional innovation capacity. The findings indicate that both the digital economy and government innovation preferences significantly enhance technological and product innovation, with this effect being particularly pronounced in the initial stages but diminishing over time. The three dimensions of the digital economy exert varying effects on technological and product innovation. Specifically, digital application has the most substantial impact on technological innovation, whereas infrastructure has a more pronounced effect on product innovation. Overall, the influence of government innovation preferences on technological and product innovation is less significant than that of the digital economy. The intensity of government innovation preferences has a greater impact than does the structure of government innovation preferences; however, in the long term, the structure of government innovation preferences can exert a more stable and sustainable influence. This study offers policy implications for constructing an innovation ecosystem driven by the synergy between government and market forces, particularly in optimizing data governance systems and planning sustainable transformation pathways, which hold practical value.

The fragmentation of resources, ecological imbalance, and the disintegration of essential factors in modern urban–rural development have become core bottlenecks constraining the achievement of global sustainable development goals. Existing research often focuses on static analysis or single-dimensional exploration, making it difficult to fully reveal the evolutionary patterns of urban–rural sustainable development systems and the core mechanisms of digital empowerment. This study adopts ecological wisdom as a theoretical perspective, introduces system dynamics methods, and constructs a three-dimensional linkage system simulation model of digital technology, factor circulation, and ecological wisdom capital. Based on model simulation data, a 70-year long-cycle simulation is conducted to explore the leverage effect of digital technology and the self-organizing evolutionary mechanisms of the system. The findings are as follows: First, the transformation of urban–rural sustainable development from fragmentation to synergy is essentially a self-organizing phase transition process. Within the system, digital technology, factor circulation, and ecological wisdom capital form a mutually beneficial symbiotic relationship through positive feedback mechanisms, driving the system toward higher-order evolution. Second, key variables such as community participation, urban–rural ecological resilience, and development pressure exhibit significant threshold effects. Only when the investment scale and institutional guarantees for these variables reach critical values can the system’s path dependence be broken, significantly driving synergistic transformation. Third, as an exogenous lever, digital technology can break down barriers to factor segmentation, reduce energy loss during system transformation, and achieve systematic integration of urban–rural resources, public services, and ecological capital with lightweight investment, serving as the core breakthrough for promoting synergistic transformation. This study integrates ecological wisdom and digital technology into the system dynamics analysis framework of urban–rural synergistic transformation, clarifies the dynamic transmission pathways of digital technology empowering urban–rural synergy, overcomes the limitations of traditional static research, enriches the cross-disciplinary application of ecological wisdom and system dynamics in the field of urban–rural development, and provides a scientific policy basis for the mutual construction of the digital economy, ecological protection, and urban–rural integration.

School-enterprise cooperation is a crucial strategy in China's vocational education and a vital aspect of vocational education reform. Conducting a comprehensive empirical study and evaluation of the effectiveness of school-enterprise cooperation in China's vocational education can enhance the quality and efficiency of such cooperation. Nevertheless, current evaluations of school-enterprise cooperation are predominantly theoretical, and there is a scarcity of systematic indicators and empirical research methods. To address this gap, the author adopts scientific, systematic, goal-oriented, and operational principles and utilizes stakeholder theory and system contract theory as the theoretical basis and framework. The author constructs three primary indicators, namely,participation, return, and potential, and several secondary indicators from the viewpoints of cooperation objectives, process, and results of vocational education school-enterprise cooperation for both schools and enterprises using factor analysis and the fuzzy comprehensive evaluation method. This evaluation offers precise empirical verification and a theoretical and practical reference for the high-quality practice of school-enterprise cooperation in China's vocational education.

Agricultural production waste (APW) is characterized by pollution, increasing volume, spatial dispersion, and temporal and spatial variability in its generation. The improper handling of APW poses a growing risk to the environment and public health. This paper focuses on the planning of APW recycling networks, primarily analyzing the selection of temporary storage sites and treatment facilities, as well as vehicle scheduling and route optimization. First, to minimize the required number of temporary storage sites, a set coverage model was established, and an immune algorithm was used to derive preliminary site selection results. Subsequently, the analytic hierarchy process and fuzzy comprehensive evaluation method were employed to refine and determine the optimal site selection results for recycling treatment facilities. Second, based on the characteristics of APW, with the minimization of recycling transportation costs as the optimization objective, an ant colony algorithm was used to establish a corresponding vehicle scheduling route optimization model, yielding the optimal solution for recycling vehicle scheduling and transportation route optimization. This study not only improved the recycling efficiency of APW but also effectively reduced the recycling costs of APW.

Employees’ helping behavior is critical for team efficiency and innovation. However, the literature highlights competing perspectives on whether receiving help elicits a pattern consistent with reciprocity or defensive ingratitude. Grounded in the help-as-status model and self-regulation theory, we developed a dual-pathway model to examine how received task-related help may influence recipients’ subsequent differentiated helping behaviors through the lens of status threats. We further investigate the moderating role of a competitive climate in this process. On the basis of a two-wave survey of 252 full-time employees, our findings reveal that receiving task-related help is positively associated with perceived status threat. This threat, in turn, serves as a plausible mediator of the link between receiving help and subsequent dependency-oriented help while exerting a suppressive effect on autonomy-oriented help. Furthermore, a competitive climate appeared to intensify the indirect pathway to dependency-oriented help, though the evidence for moderation of the autonomy-oriented help pathway was mixed. By exploring these defensive psychological mechanisms within a single national organizational context, this study offers a cautious, status-based explanation for managing the complexities of prosocial interactions. While the findings provide nuanced insights into post-help dynamics, we acknowledge the inherent boundaries of our two-wave, self-reported survey design. However, the positive direct association with autonomy-oriented help may be consistent with multiple processes beyond status threat, including unmeasured gratitude, reciprocity norms, learning orientation, or enhanced relational quality.