Digital Technologies for Sustainable Highway Maintenance Governance: Evidence from a Scientific Maintenance Pilot in China

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.