Abstract: This study aims to develop a scientific and reasonable interprovincial carbon quota allocation mechanism for the construction industry. Methodologically, the k-means algorithm was employed to group China's 30 provinces (autonomous regions and municipalities), the random forest method was used to identify key factors influencing carbon emissions, and the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, Technology, and Environment) model was employed to predict carbon emission trends in the construction industry. A multi-criteria carbon quota allocation system incorporating sustainable development principles was developed, and the Zero-Sum Gains Data Envelopment Analysis (ZSG-DEA) model was adopted to optimize the initial scheme. The environmental Gini coefficient and social network analysis were combined to test the rationality of the scheme. The Slack-Based Measure Data Envelopment Analysis (SBM-DEA) and carbon emission reduction pressure index models were applied to analyze the low-carbon development paths of the construction industry in various regions. The results indicated that the 30 regions were clustered into 3 groups according to construction industry development stages, with technology, affluence, and population serving as the dominant influencing factors for each group, respectively. The total national construction industry carbon quota for 2030 was determined to be 6598.884 million tons, with Guangdong receiving the highest quota of 748.5245 million tons after optimization, while Fujian's quota was reduced by 218.2971 million tons. Through verification using the Gini coefficient and social network analysis, the optimized scheme struck a balance between fairness and efficiency while conforming to the spatial development patterns of the construction industry. The average carbon emission reduction cost was 2.18 unit price/ton, with four differentiated emission reduction pathways identified as low pressure-low cost, low cost-high pressure, high cost-low pressure, and high cost-high pressure, which can achieve emission reduction through strategies such as improving energy efficiency to explore new models, utilizing cost advantages for strict emission reduction, enhancing technological level to reduce costs, and adjusting structure while participating in carbon trading, respectively. Each region should formulate carbon reduction plans according to local conditions to promote high-quality development of the construction industry.