Identifying low-to-middle-income residents’ secondary activity patterns using smart card data

Abstract

The enrichment of urban lifestyles necessitates a comprehensive understanding of individuals’ secondary activity patterns. For low-to-middle-income residents, secondary activities assume a crucial role in understanding their living conditions. Accordingly, this study proposes a method to extract secondary activities from smart card data and to analyze its spatio-temporal patterns. Corroborated by travel survey data, a significant portion of smart card users have low to middle incomes, we contend that the derived patterns effectively represent the living circumstances of low-to-middle-income individuals travel by public transportation. These patterns are characterized from three aspects, e.g., quantity, spatial coverage, and preference based on home and workplace. A case study in Shenzhen, China identifies several meaningful patterns in the secondary activities of the low-to-middle-income groups who travel frequently by public transportation: groups whose activity patterns are occasional and with strong home-workplace constraints, groups with small activity coverages and strong home-workplace constraints, groups with wide activity coverages and weak home-workplace constraints, and groups with multiple activities and weak home-workplace constraints. The case study indicates that the majority of low-to-middle-income groups who frequently use public transportation either have very few secondary activities by public transportation, or are severely constrained by home and workplace. These discoveries have the potential to assist urban planners in enhancing the accessibility of urban amenities for low-to-middle-income residents, thereby enhancing both the quantitative and qualitative aspects of their secondary activities.