Evaluation of total-factor electricity energy efficiency and analysis of influencing factors in Shanghai

The escalating energy consumption and inefficient development models pose significant challenges to China’s sustainable growth and dual-carbon goals. As a critical energy input, electricity plays a central role in decarbonization, with Shanghai serving as a key case for analysis. This study presents a comprehensive evaluation of Shanghai’s total-factor electricity energy efficiency (TFEEE) using an integrated analytical framework. Data preprocessing was conducted via logarithmic normalization and artificial neural networks (ANN), followed by a super-efficiency slack-based measure (SBM) model incorporating undesirable outputs (e.g., carbon emissions). Key drivers were identified using random forest and quantile regression, while a novel composite spatial weight matrix was developed to examine spatial agglomeration effects. Results reveal: (1) a generally upward trend in TFEEE from 2015 to 2022; (2) significant spatial clustering and scale-driven development; (3) a negative impact of the secondary industry on efficiency; and (4) technological innovation as the primary contributor. Policy recommendations include smart grid development, industrial restructuring, and regional coordination mechanisms, offering strategic insights for Shanghai’s 15th Five-Year Plan. This work advances the measurement and interpretation of urban electricity efficiency through methodological innovation and spatial analysis, providing a replicable reference for other megacities pursuing carbon neutrality and high-quality socio-economic development.