Land

Addressing the challenge of misalignment between high capital input and operational efficacy in Corporate Social Responsibility (CSR) led rural revitalization often highlighted in relevant studies, this study establishes a dual perspective Post-Occupancy Evaluation (POE) framework that integrates objective efficiency measurement with subjective mechanism diagnosis. Leveraging multi-source official data from 11 China Resources Hope Towns, we apply an entropy-weighted super-efficiency DEA model for holistic assessment, complemented by an in-depth diagnostic of the Jinzhai project. The results indicate that operational performance is not a linear function of investment scale but exhibits significant heterogeneity. The analysis delineates distinct inefficiency typologies: the “Scale Restricted” type, characterized by effective management constrained by insufficient functional agglomeration, and the “Management-Constrained” type, marked by challenges in converting physical assets into economic vitality. Notably, the Jinzhai case exposes a critical “Delivery Utility Divergence,” where high technical efficiency coexists with moderate resident satisfaction revealed by survey data, highlighting structural gaps in service accessibility. Consequently, this research proposes a “Diagnose-Feedback-Optimization” closed-loop governance framework. It advocates a paradigm shift from uniform construction delivery to differentiated operational strategies, specifically structured expansion, asset activation, and service patching, to effectively align facility supply with resident needs throughout the full lifecycle.

To address the persistent challenges of the “disconnect between macro-level spatial zoning and micro-level land allocation” and the paradox of “localized intensification accompanied by overall inefficiency” in territorial spatial governance, this study adopts a multi-scale coupling perspective to explore an optimized spatial pattern that promotes the coordinated development of production, living, and ecological functions (PLEFs), thereby enhancing the systematic and scientific basis of spatial governance. Taking the Central Yunnan Urban Agglomeration (CYUA) as a case study, a coupled optimization framework integrating macro-scale spatial zoning and micro-scale land allocation was established. First, using multi-period land use data (2000–2020) in conjunction with multi-source geographic and socio-economic datasets, the correspondence between land use types and PLEFs was constructed, and the spatiotemporal evolution characteristics of these functions were systematically analyzed. Second, the GMOP-PLUS model was employed to simulate and optimize land use patterns for 2035 under multiple development scenarios, and dominant spatial types were further refined based on grid-scale spatial suitability evaluation results. Third, the NRCA model was applied to identify comparative functional advantages at the county level. These advantages were comprehensively integrated with the revised dominant spatial types following the principle of “seeking common ground while preserving differences,” ultimately enabling the delineation of optimized territorial spatial development zones. The results indicate the following: (1) Throughout the study period, ecological space remained the dominant land use type (exceeding 75%), although its proportion gradually declined. Living space expanded markedly, while the internal structure of production space shifted toward industrial and mining land uses. (2) The planning control scenario was identified as the most suitable development pathway, exhibiting a spatial configuration characterized by a “central core with stronger development in the southeast than in the northwest.” Under this scenario, production and living spaces continued to expand, whereas ecological space maintained its dominant status. (3) Spatial suitability evaluation revealed a high degree of functional compatibility across the study area (79.01%), with ecological suitability prevailing. The revised dominant spatial types were predominantly ecological (78.94%), forming a hierarchical structure described as a “living core–production composite ring–ecological periphery.” (4) By integrating dominant spatial types with comparative functional advantages, the study area was classified into five major categories of territorial spatial development zones, for which differentiated governance strategies were proposed. This study provides methodological insights and practical guidance for improving refined territorial spatial management and advancing regional sustainable development.

Agriculture is particularly vulnerable to climate change, as shifting seasonal patterns disrupt farming cycles and changing rainfall patterns, along with extreme weather events, present significant challenges. From the perspectives of risk perception and risk attitudes, this study elucidates the decision-making mechanisms underlying climate adaptation behaviors among maize growers in China, providing insights to inform climate adaptation policies, land management strategies, and food security protection. This study surveyed 752 maize growers in Jilin province, China, and employed factor analysis to quantify climate risk perception and risk attitudes. Using the Probit model and moderation analysis, this study examines the impact of climate risk perception on adaptive behavior and investigates the moderating effect of risk attitude on the relationship between risk perception and climate adaptation behavior. It then explores heterogeneity across production scales and generations. (1) We categorize adaptation behaviors into three types—capital-based, labor-based, and technology-based—according to the input factors involved. Climate risk perception promotes all three types of adaptation behaviors, whereas risk aversion primarily exerts a significant inhibitory effect on technology-based adaptations. (2) Risk attitudes exert a negative moderating effect on the relationship between climate risk perception and the adaptation behaviors of maize growers. Specifically, a higher propensity for risk aversion attenuates the positive influence of risk perception on labor-based and technology-based adaptation behaviors. (3) Heterogeneity analysis reveals that the moderating effect of risk attitude is more pronounced among small-scale farmers and younger generations. In contrast, it remains statistically insignificant for large-scale operators and older-generation cohorts. Therefore, it is important to enhance farmers’ awareness of climate risks by strengthening the dissemination of meteorological information and early warnings. Technical guidance should be intensified to improve maize growers’ understanding and mastery of relevant technologies. Develop targeted land-use strategies for climate change adaptation based on maize growers’ age, farm size, and geographic location.