A Multi-Perspective Approach to Resident Segmentation Analysis for HDB Towns in Singapore

In this paper, we introduce a multi-perspective resident segmentation analysis approach to identify different demographic segments of people, and their place preferences from a survey dataset collected from residents in three HDB towns in Singapore. By using k-medoids clustering, we identified eight demographic resident segments, and using a multi-perspective approach with k-means, we identified their place preferences in terms of place visit frequency, and place indication. Shopping Mall, Eateries, and Market have found to be the most popular places in terms of visit frequency. In terms of place indication, our results show that segments from different age groups have a difference in their preference for certain place types. Moreover, we identified town based characteristics in place preference through our analysis.