Full Title: Spatiotemporal Characteristics and Multiple Driving Paths of the Low-Carbon Transition in Household Consumption: A Configurational Analysis Using Dynamic QCA
Author(s): Shunyi Li and Langchao Zhang
Publisher(s): Nature
Publication Date: December 4, 2025
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Description (excerpt):
This study investigates the spatiotemporal characteristics of household consumption carbon emissions and explores the complex causal mechanisms underlying the low-carbon transition of household consumption at the provincial level in China. Utilizing household consumption data from 29 provinces between 2005 and 2020, we apply the Consumer Lifestyle Approach (CLA), Theil Index, and Moran’s I to examine temporal trends and spatial patterns. A theoretical framework based on the Technology-Organization-Environment (TOE) perspective is developed to identify key drivers of low-carbon transitions, and a dynamic Qualitative Comparative Analysis (QCA) is conducted to uncover configuration-based pathways. The results indicate that: (1) the carbon intensity of household consumption initially increased with fluctuations and subsequently declined over time. Spatially, emissions exhibit a “high in the north, low in the south” pattern, with persistent inter- and intra-regional disparities and significant positive spatial autocorrelation. (2) No single factor is found to be a necessary condition for the transition, but the influence of several variables increases over time. Notably, economic development and environmental awareness gradually emerge as dominant contributors to low-carbon transition. (3) Two high-level configurational models of household consumption low-carbon transition are identified: the government support-driven model and the “government support-economic development level-residents’ environmental awareness” driven model. The consistency adjustment distance within each configuration is notably large, with significant regional differences, revealing the marked heterogeneity of the low-carbon transition of household consumption across different regions in China during the process of economic development.