Measurement and spatiotemporal evolution of the green resilience index of the construction industry in Chinese provinces

Purpose This study aims to develop and quantify a green resilience index for China’s provincial construction industry. By revealing the ability of various regions to achieve green transformation and recovery in the face of environmental disturbances, market fluctuations and unforeseen events, the study explores the inherent patterns of spatiotemporal evolution and regional differentiation in green resilience. The findings provide systematic empirical support for a deeper understanding of the construction industry’s green transformation. Design/methodology/approach Based on the DPSIR (drivers–pressures–state–impact–responses) framework, a multi-dimensional evaluation system for green resilience in the construction industry is established. First, the entropy-weighted TOPSIS method is applied to assess the green resilience levels across provinces quantitatively. Next, the Dagum Gini coefficient decomposition is employed to thoroughly examine differences between and within regions. Subsequently, kernel density estimation is used to visually capture the dynamic changes in index distribution. Finally, traditional and spatially lagged Markov chain models are utilized to investigate the dynamic transitions and path dependency of green resilience states. Findings From 2013 to 2022, the overall green resilience of China’s provincial construction industry exhibited an upward trend, despite pronounced regional disparities. The kernel density curves shifted rightward and displayed multimodal distributions, suggesting that some provinces achieved leapfrog improvements in resilience. The Dagum Gini decomposition indicates that variations in economic foundations, industrial structures and resource endowments are key factors driving the uneven distribution of green resilience. Furthermore, the Markov chain analysis reveals that regions with lower resilience tend to persist in their state, whereas high-resilience regions demonstrate a “Matthew effect,” leading to development lock-in and significant spatial spillover effects. These findings underscore the path-dependent nature of the green transformation process. Originality/value This study is the first to introduce the concept of green resilience to the construction industry. It establishes a multidimensional evaluation framework based on the DPSIR model and employs advanced methods – including entropy-weighted TOPSIS, kernel density estimation, Dagum Gini coefficient decomposition and spatial Markov chain analysis – to elucidate the spatiotemporal evolution of green resilience. The results offer novel theoretical insights and empirical evidence that can inform strategies for green transformation and regional collaborative governance in the construction sector.