Full title: The performance evaluation of marine ecological civilization construction (MECC): A case study of coastal cities in Jiangsu Province, China

Conducting Marine Ecological Civilization Construction (MECC) will help to form the coordination of socio-economic, marine ecosystem, and stable marine society. How to evaluate the performance of MECC precisely is an urgent problem in the development of coastal areas. In this study, a comprehensive evaluation indices system consisting of 41 indicators and five dimensions was constructed to reflect the performance of MECC in three coastal cities of Jiangsu Province. Entropy and AHP methods were integrally used to determine the weight of each index, and then, Technique for Order of Preference by Similarity to ideal Solution (TOPSIS) method was applied to depict the relative performance level of marine ecological civilization. The results showed that: (1) From 2011 to 2021, the MECC of Jiangsu coastal regions has gradually increased from 0.3649 to 0.5933, indicating that the development of Jiangsu is undergoing a transformation from resource intensive to environmentally friendly. (2) Different cities had different strengths in marine subsystem layer, with Lianyungang dominated by resource endowment, Yancheng capitalizing on its environmental strengths, and Nantong being significant in marine economic. (3) A decade long dynamic showed that Yancheng achieved the largest improvement by 84.82% from 2011 to 2021, followed by Nantong (69.48%) and Lianyungang (38.15%). (4) For further promoting MECC process, Jiangsu should strategically prioritize land-sea coordination, undertake comprehensive governance and waging a resolute battle for comprehensive marine governance in critical areas. The comprehensive performance evaluation indices system of MECC proposed in this study would be robust and reliable for application in other areas. Meanwhile, the results and recommendations of Jiangsu Province could be valuable for further enhancing MECC development and providing scientific bases for local decision-makers.