Judicial big data reveals systemic risks in China’s transfer of development rights

Transfer of development rights (TDR) has been widely adopted as a prospective planning instrument to address land use externalities, yet substantial uncertainties arising from diverse stakeholders across the project lifecycle undermine project success. This study introduces judicial big data and proposes an Event-Factor-Process-Stakeholder (EFPS) analytical framework to identify and quantify these uncertainties as explicit risks, and systematically reveal the multidimensional characteristics and underlying transmission pathways of TDR risks in China. Our findings demonstrate that TDR risk events exhibit a persistent nationwide upward trend, with 94.23% driven by multiple concurrent factors among the 24 identified risk factors. Risks permeate all project phases, following a pattern of multi-phase accumulation, concentrated outbreak and subsequent mitigation, with local governments (49.02%) and farmers (41.05%) as primary risk-generating stakeholders. Through probabilistic dependency inference and hierarchical structuring, our study identifies rights holder identification, spatial positioning, zoning regulation and supervision deficiency as four root-cause risk factors that propagate through dual pathways of social imbalance and engineering failure to higher-level factors. Targeted policy recommendations addressing root-cause factors responsible for 74.76% of observed risk events are proposed, centered on refined rights registration, enhanced planning coherence, and a full-cycle multi-stakeholder supervision system. This study advances a structured analytical paradigm for risk research and provides actionable decision support for prioritizing and managing TDR risks.