K-means clustering-based young users’ kitchen needs analysis and personalized design strategy

Abstract

Objectives: This study aimed to understand the kitchen use behaviors and design preferences that cater to the needs of young people, encouraging their intention to cook and promoting healthy living. Methods: This study conducted a survey with 310 young people (aged 18 to 40) and applied the K-means clustering method for analysis. The silhouette coefficient feature in R was used to automatically assess the impact of different K-values on the clustering outcome, thereby determining the ideal number of clusters. After identifying the optimal number of clusters, K-means clustering was performed in R to segment the survey data and identify the primary user personas. Results: The analysis identified two user categories: 1. Health-Convenience Advocates, that is, young people with a high level of education who seek efficient lifestyles but due to their busy schedules have a significant need for quick and healthy dietary solutions; 2. Cooking Explorers, typically modern, educated young individuals who are passionate about cooking, viewing it not only as a necessity but also as a personal interest and a realm for exploration. Conclusion: This study provides valuable guidance for kitchen designers and home product developers to better understand the actual needs and preferences of young users, highlighting the importance of excellent kitchen design in promoting a healthy lifestyle and improving quality of life.