Research on spatiotemporal evolution and trend prediction of marine economic efficiency in China’s coastal regions – a dynamic analysis using super-SBM and grey forecasting model

Purpose Under the national strategy of “Building a Strong Maritime Country,” this study aims to scientifically evaluate the high-quality development level of China’s coastal marine economy through quantitative analysis. This study aims to reveal the spatiotemporal evolution law of marine economic efficiency in China’s coastal regions and establish a dynamic assessment system to forecast future development trends. Design/methodology/approach This research develops a marine economic efficiency evaluation system based on the undesirable-output super-SBM model to measure and analyze the efficiency of 11 coastal provinces (excluding Hong Kong, Macao and Taiwan) from 2011 to 2022. Combined with grey prediction models, it forecasts marine economic efficiency trends for 2023–2030. Findings (1) China's marine economic efficiency showed significant regional disparities during 2011–2022, with developed eastern coastal provinces like Shanghai reaching the frontier while others like Liaoning lagged behind. (2) Projections for 2023–2030 indicate an overall 1.58% annual efficiency growth, but innovation-driven regions will outperform traditional resource-dependent areas, highlighting the need for technological transformation. (3) Despite national efficiency improvements, widening regional gaps emphasize the urgency to transition from factor-driven to innovation-driven marine development, particularly for struggling central-western regions. Originality/value As the first study to integrate the super-SBM model with grey prediction techniques, it overcomes the limitations of traditional efficiency research that relies solely on cross-sectional data, offering a novel methodological framework for dynamic time-series analysis. The conclusions provide a basis for coastal provinces to formulate differentiated policies.