Spatiotemporal Dynamics and Influencing Mechanisms of Carbon Emission Efficiency in China’s Construction Industry

Abstract

The construction industry stands at the forefront of China’s endeavors in carbon reduction, making it imperative to examine the spatiotemporal variations in carbon emission efficiency (CEE) to drive the industry’s low-carbon transition. This research leverages statistical data from 2007 to 2022 and applies the super-efficiency SBM model to assess CEE across 30 Chinese provinces, shedding light on its spatial distribution patterns. Moran’s I index is employed to scrutinize spatial clustering of CEE, revealing clustering tendencies. Furthermore, the geographic detector method identifies the factors that account for these spatial variations. The research reveals notable spatial diversity in CEE among provinces, with the eastern coastal areas demonstrating higher efficiency and the western interior areas demonstrating lower efficiency. Spatial autocorrelation analysis further confirms the presence of spatial dependence, characterized by pronounced “High–High” or “Low–Low” agglomeration trends. Enterprise scale and energy structure emerge as primary explanatory factors of spatial differences, and interaction effects are more influential than any single factor. These findings provide empirical evidence that can inform a more balanced low-carbon transition of China’s construction industry across regions. Tailored policy suggestions are proposed to address the distinct characteristics of each region, aiming to support steady progress toward China’s dual carbon goals.