Abstract: In the era of accelerated population aging, the proportion of older adults in the consumer group also increases tremendously. Based on data from China Longitudinal Aging Social Survey, this article employs the analytical framework of Kotler's consumption behavior model and K-means clustering analysis method to categorize different types of consumption structure for Chinese older adults. Logistic regression method is conducted to analyze the factors affecting the consumption structure upgrading. The results show that the consumption patterns of the older adults are diverse, and their upgrades have not been hindered. The transformation from the basic to the developmental consumption structure is driven by demand factors and restricted by resource factors, and also supported by social networks, technology, and other external factors. These factors have heterogeneous impacts on older adults from urban/rural areas at different ages and income levels. These differences call for differentiated policies targeting on different subgroups.

Keywords: Older Adults, Types of Consumption Structure, Cluster Analysis, Logistic Regression

摘要： 随着中国进入人口老龄化加速发展的新阶段，老年人在消费群体中的比重快速增加，成为日益重要的消费人群。利用中国老年社会追踪调查（CLASS）数据，以科特勒消费行为模型为分析框架，运用Kmeans聚类分析方法对中国老年人消费结构的类型进行划分和描述，采用Logistic回归模型对影响老年人消费结构升级的因素进行研究，并考虑不同群体的异质性。结果表明，老年人的消费类型趋向多样化，并没有表现出阻碍消费升级的情况；老年人要实现从基本型向发展型消费结构的升级，受到需求要素的驱动和资源要素的影响，还需要社会网络、技术等信息渠道要素的支持；影响老年人消费结构升级的因素存在城乡、年龄和收入水平的异质性，促进老年人消费升级需要分类精准施策。

关键词: 老年人, 消费结构, 聚类分析, Logistic回归