上海管理科学2025，Vol.47Issue(1)：59-66,8.
中国农业新质生产力发展水平测度与影响因素分析
The Development Level of New Quality Productive Forces in Chinese Agriculture and Analysis of Influencing Factors:Empirical Evidence Based on the XGBoost Model
吴展 1瞿廷鸿1
作者信息
- 1. 上海海洋大学经济管理学院,上海 201306
- 折叠
摘要
Abstract
The development of agricultural new quality productivity plays an important role in promot-ing the modernization of China's agriculture and achieving the strategic goal of a strong agricultural country.In order to objectively quantify the nonlinear effects and importance of key factors affecting the level of agricultural new quality productivity.The article aims to propose a framework for measuring and analyzing the development level of agricultural new quality productivity based on machine learning methods.The Extreme Gradient Boosting(XGBoost)algorithm,SHAP machine learning interpreta-tion method and TOPSIS model are utilized to measure and analyze the development level of agricul-tural new quality productivity in China from 2012 to 2022.In addition,five-fold cross-validation is ap-plied to test the robustness of the machine learning regression model results.Finally,the SHAP model is used to deeply analyze the key driving factors affecting the level of China's agricultural new quality productivity and explore the path to promote the development of China's agricultural new qual-ity productivity.The results of the study show that:the overall level of China's agricultural new quality productivity level is on an upward trend,but the overall level is low;scientific and technological inno-vation talents,the scale of development of high-tech industry and the level of development of the digi-tal economy are the key driving factors affecting the level of development of China's agricultural new quality productivity,and they have a significant positive effect and non-linear characteristics.关键词
机器学习/SHAP模型/XGBoost算法/农业新质生产力/驱动因素Key words
machine learning/SHAP model/XGBoost algorithm/new quality productivity/driving factors分类
计算机与自动化引用本文复制引用
吴展,瞿廷鸿..中国农业新质生产力发展水平测度与影响因素分析[J].上海管理科学,2025,47(1):59-66,8.
