Assessment of carbon emission efficiency in China’s construction industry based on an innovative “efficiency-space-time” integrated model

Purpose This study aims to assess the carbon emission efficiency (CEE) of China’s construction industry through an integrated “efficiency-space-time” model. It addresses regional imbalances and spatiotemporal characteristics to support regionally coordinated and differentiated emission reduction policies. Design/methodology/approach Utilizing an innovative multidimensional model that combines the super-efficiency SBM model, exploratory spatial data analysis, kernel density estimation and Dagum Gini coefficient decomposition, this research evaluates CEE across 30 Chinese provinces from 2006 to 2021. The framework integrates efficiency measurement, spatial dependence, temporal evolution analysis and regional disparity decomposition. Findings National CEE trended up with fluctuations, with pronounced east-west and south-north disparities. Spatial autocorrelation strengthened, high-high CEE clusters dominated Eastern coastal regions, while low-low clusters migrated west. Dagum Gini decomposition identified inter-regional gaps (contributing 47.63%–67.48% of total inequality) as dominant, with the largest disparities between the Eastern Coast and the Middle Yellow River. Kernel density curves highlighted central/western polarization, transitioning to unimodal distributions in the east post-2018, signaling reduced intra-regional disparities. Originality/value This study constructs an integrated “efficiency-space-time” framework, overcoming limitations of static analyses and oversimplified regional divisions. By introducing eight comprehensive economic zones, it refines spatial heterogeneity analysis and offers actionable insights for region-specific low-carbon transitions. The methodology bridges efficiency measurement, spatial interaction and temporal evolution, providing a replicable model for global multiregional low-carbon transitions.