Chinese megacity communities are not only the primary drivers of economic development but also epicenters of systemic contradictions compounded by overlapping risks. In recent years, NIMBY conflicts have arisen with growing frequency within urban communities, posing a severe threat to urban social sustainability and exposing the significant limitations of the traditional state-led governance model. While nonprofit organizations can compensate for governmental governance deficiencies, their mitigating mechanisms, functional boundaries, and contextual differences remain to be systematically examined. To address this gap, the present study conducts an empirical analysis using data from the Chinese Social Survey (CSS). Methodologically, the study applies OLS regression, mediation–moderation analyses, and heterogeneity tests. The findings reveal that: (1) Participation by nonprofit organizations is associated with significantly lower individual NIMBY opposition intent, thereby playing a mitigating role in alleviating NIMBY risks within Chinese megacity communities. (2) Trust in nonprofit organizations serves as a mediating pathway and acts as a social capital vehicle through which nonprofit organizations alleviate NIMBY risks by mitigating individual opposition. (3) Government information disclosure and institutionalized channels for residents’ participation significantly amplify the negative association between nonprofit participation and individual NIMBY opposition intent, thereby strengthening the mitigating efficacy of nonprofit organizations. (4) The mitigating effects exhibit marked community heterogeneity, indicating that the efficacy of nonprofit participation is highly contingent upon the specific governance resources and structural characteristics of the community. This study improves the theoretical framework of NIMBY risk governance and offers empirical evidence as well as practical guidelines for fostering sustainable urban governance in Chinese megacity communities.

Since 2013, the Chinese government has promoted rural revitalization by deploying resident work team members to villages. As policy implementers within the governance framework of China, resident work team members’ levels of public service motivation (PSM) influence the strategic outcomes of rural revitalization. Employing hierarchical regression analyses and moderation tests, this study provides an empirical examination of resident work team members in the Wuling Mountains region of China. The findings indicate that the overall level of PSM among resident work team members is high, yet job burnout is present to a considerable extent. Job burnout is negatively associated with resident work team members’ PSM, and perceived organizational support (POS) moderates this association. At higher levels of POS, the negative relationship between job burnout and PSM is significantly attenuated. Policy implications underscore the need to address resident work team members’ job burnout, strengthen their professional capacity development, standardize the assessment and operational standards for village work, and improve accountability mechanisms, welfare provisions, as well as the alignment of promotion and placement arrangements, thereby fostering an organizational climate that encourages innovation. This study enriches and extends the antecedents and moderating factors of PSM theory, offering theoretical support and policy guidance for realizing China’s rural revitalization strategy and for establishing a comprehensive, multi-level talent-support system for rural development.

As a stabilizer safeguarding China’s food security, the Yangtze River Economic Belt is troubled by farmland abandonment and inefficient utilization of abandoned farmland. Therefore, clarifying the spatiotemporal differentiation and determinants of abandoned farmland utilization is critical to addressing challenges in cultivated land protection. Based on the China Land Cover Dataset (CLCD), this study adopts land-use trajectory analysis, kernel density analysis, and spatial autocorrelation analysis to explore core issues of abandoned farmland utilization from three dimensions: scale, efficiency and stability. The results show that: (1) Since 2022, abandoned farmland utilization policies have raised the annual utilization rate by an average of 2.5 percentage points. Historical abandoned land stocks are absorbed evenly each year, shifting governance from clearing accumulated abandoned land arrears to regularly controlling newly abandoned farmland. (2) Abandoned farmland utilization shows a striking west-high and east-low spatial agglomeration gradient: HH clusters distribute in the upper reaches and LL clusters in the lower reaches, with the upper and middle reaches achieving a 10-percentage-point 4-year growth in utilization rates. Utilization stability follows the middle reaches (91.12%), upper reaches (90.28%), and lower reaches (85.36%). (3) Natural geography, economic levels, labor composition and institutional policies cause these disparities. This research provides theoretical and practical support for differentiated regional governance of abandoned farmland and consolidated national food security.