Through the lens of social identity theory, this work aims to investigate the impact of servant leadership on employee resilience during the COVID-19 pandemic and to explore their underlying mechanisms through two types of social identity: organizational identification and professional identity. To test our hypotheses, an online survey was conducted via a large number of 703 employees working in public organizations in southwest China. Results yielded from the structural equation modeling analysis via AMOS (24.0) indicated that the effect of servant leadership on employee resilience was fully mediated by organizational identification and professional identity, respectively. Besides, the association between servant leadership and employee resilience was sequentially mediated from organizational identification to professional identity, and from professional identity to organizational identification. This study provides the first evidence of the predictive effect of servant leadership on employee resilience through organizational identification and professional identity, highlighting the significance of social identity for building and maintaining employees’ resilience in coping with challenges posed by COVID-19.

Attention on, and interest in, life satisfaction has increased worldwide. However, research on life satisfaction focused toward the urban dwellers’ residential community is mainly from western countries, and the limited research from China is solely focused on the geriatric population via a narrowly constrained research perspective. This study, therefore, aimed to investigate urbanites’ life satisfaction toward their community, combining the psychological (behavioral community engagement, mental state of flow, and cognitive community identity), physical (PREQIs-perceived residential environment quality indicators: e.g., green area), and social perspectives (social capital). The proposed conceptual model was tested on a regionally representative sample of 508 urban community residents in the city of Chengdu, Sichuan province, China. Data were analyzed via a structure equation modelling approach in AMOS software. Findings suggested that all of the psychological, physical and social factors contributed to a prediction of life satisfaction. Specifically, social capital mediated the path from community engagement and flow to life satisfaction, and community identity mediated the path from flow experience and green area to life satisfaction. Additionally, social capital contributed to predict life satisfaction through its influence on community identity. Findings provide suggestions for urban designers and policymakers to focus on creating an urban community equipped with green area, which helps to promote physical activities that are flow-productive, to enhance residents’ identification to their residential community and, therefore, increase life satisfaction.

Sustainable highway maintenance is increasingly important as road agencies face ageing assets, fiscal constraints and growing requirements for service reliability and resilience. Although digital technologies are widely used in inspection, prediction and construction control, less is known about how they support governance across the full maintenance process. This study examines a Chinese scientific highway maintenance pilot through a document-based qualitative case study. Drawing on project documents and public reports, it develops a framework linking three mechanisms: datafied demand assessment, model-based decision-making and adaptive scheduling. The findings show how digital inspection, remote sensing, multi-source data models and smart construction-control platforms turn dispersed deterioration information into traceable condition evidence, translate this evidence into life-cycle maintenance priorities and connect planning with implementation feedback. Project-reported indicators also suggest gains in inspection efficiency and monitoring timeliness, although the evidence does not permit a comprehensive assessment of sustainability outcomes. Together, the mechanisms strengthen the capacity to move from reactive repair towards evidence-based life-cycle maintenance, resource-conscious prioritisation and adaptive service delivery. The study contributes to sustainable transport infrastructure research by explaining the governance processes through which digital technologies can support highway maintenance and the conditions shaping their transferability.