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基于随机森林和可解释AI (SHAP) 的预测消费者购买预制餐的意图:中国吉林省的一项研究
Xiaodan Qi1, Hongyan Zhao1, Xihe Yu1
1School of Public Health, Jilin University, Changchun 130021, China.
Foods (Basel, Switzerland)
|March 14, 2026
概括
消费者愿意推预先准备的餐饮驱动购买决策,方便是次要因素. 营销应该专注于建立愿意减轻对行业增长的感知风险的意愿.
科学领域:
- 消费者行为 消费者行为
- 食品行业分析 食品行业分析
- 机器学习应用 机器学习应用
背景情况:
- 预制餐饮行业对于中国的食品部门发展至关重要.
- 了解消费者购买驱动因素是行业增长的关键.
研究的目的:
- 调查消费者购买预制餐的意图的决定因素.
- 分析决策中的非线性和不对称的相互作用.
主要方法:
- 使用集成机器学习框架分析了805份问卷.
- 用基线平衡测试和SMOTE-Tomek进行数据验证以纠正不平衡.
- 模型优化使用基于高斯过程的贝叶斯优化,包括随机森林 (RF) 和XGBoost.
主要成果:
- 购买决策主要取决于意愿 (推意愿>72%).
- 方便性和道可访问性是基本的推动因素.
- 推意愿显示了一个S形的非线性值,表示营销干预窗口.
结论:
- 高意愿可以抵消产品的缺点,而低意愿则作为障碍.
- 研究结果将ML与行为理论相结合,量化了有限的理性.
- 建议转向以保留为重点的战略和协作治理,以促进行业的繁荣.
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