Numerous researchers have endeavored to amalgamate critical transit-oriented development (TOD) indicators, such as development density, walkability, and diversity, into a single TOD index to assess TOD performance. However, implementing TOD in megacities necessitates a more comprehensive selection of indicators, an objective calculation methodology, and accessible calculation data for the TOD index. This study introduces a method based on multi-indicator TOD performance assessment using multi-source urban big data; it uses Shanghai as a case study to evaluate and analyze the impact of site characteristics on performance. The method constructs the Comprehensive Socio-Economic Development Index (CSEDI) based on four indicators of TOD site operations. It establishes a multivariate regression model utilizing principal component analysis to extract 22 leading component indicators as independent variables from 71 indicators associated with TOD. Within the sample space of 77 rail transit TOD sites in Shanghai, the CSEDI exhibited a robust correlation with the independent variables. The evaluation results of the case study demonstrate consistency with the development characteristics of the city and the sites, indicating that the evaluation method can guide the renovation of existing sites and the development of new sites.
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