数字经济与新质生产力赋能渔业生态资源效率优化

——基于机器学习及可视化分析的经验证据

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中图分类号： TP181;F124;F326.4 文献标志码：A

Digital Economy and New Quality Productive Forces Empowering Fishery Ecological Resource Efficiency Optimization： Empirical Evidence from Machine Learning and Visualization Analysis

LI Zongheng WEI Youzhou （College of Economics and Management，Shanghai Ocean University， Shanghai 2Ol3O6， China）

Abstract： The improvement of resource ecological eficiency contributes to achieving sustainable development. The rapid development of the digital economy and new quality productive forces is expected to further enhance the eficiency level of fishery ecological resources.To quantify the nonlinear effects and importance of key factors influencing fishery eco-resource eficiency，this study measures the fishery eco-resource eficiency，digital economy development，and new quality productive forces in China's coastal provinces and municipalities. Utilizing the XGBoost algorithm and SHAP visualization model， it explores new pathways to promote sustainable development of China's fishery resources.The research findings indicate that while China's coastal regions generally show an upward trend in fishery eco-resource efficiency，some provinces and cities still maintain relatively low efficiency levels. Both the digital economy and new quality productive forces demonstrate positive promotional effects on fishery eco-resource efciency.Moreover，interaction analysis reveals synergistic enhancement mechanisms between the digital economy and industrial structure，as wellas between new quality productive forces and per capita GDP.

Key words： machine learning; SHAP model; new quality productivity; digital economy; fishery eco logical resource efficiency

0 引言

渔业在中国乃至世界范围内仍是关乎民生的重要产业，我国2023年渔业产值达到3万2000余亿元，全球范围内渔业与水产养殖初级部门有超过6000万人就业，辐射就业人数则更加庞大。（剩余8519字）