Clustering Analysis of Chinese Urban Household Types Based on Consumption Behavior

Abstract

This study investigates the heterogeneity of urban household types in China through a clustering analysis of consumption behavior patterns. Against the backdrop of rapid economic growth and evolving consumption structures, understanding household consumption dynamics is critical for market segmentation and policy formulation. Using data from the China Household Finance Survey, this research applies the K-means clustering algorithm to categorize urban households based on expenditure variables across categories such as food, housing, education, healthcare, and leisure. The analysis identifies four distinct household clusters: necessity-oriented, education-focused, healthcare-prioritized, and balanced-spending types. Key findings reveal significant regional and socioeconomic disparities in consumption preferences, with education and healthcare expenditures becoming increasingly prominent among middle-to-high-income households. These results highlight the shifting consumption trends in urban China and offer valuable insights for businesses in tailoring marketing strategies and for policymakers in designing targeted social and economic programs.