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Multi-Activity Access: How Activity Choice Affects Opportunity

Author

Listed:
  • Mengying Cui
  • David Levinson

    (TransportLab, School of Civil Engineering, University of Sydney)

Abstract

It is commonly seen that accessibility is measured considering only one opportunity or activity type or purpose of interest, e.g., jobs. The value of a location, and thus the overall access, however, depends on the ability to reach many different types of opportunities. This paper clarifies the concept of multi-activity accessibility, which combines multiple types of opportunities into a single aggregated access measure, and aims to find more comprehensive answers for the questions: what is being accessed, by what extent, and how it varies by employment status and by gender. The Minneapolis - St. Paul metropolitan region is selected for the measurement of multi-activity accessibility, using both primal and dual measures of cumulative access, for auto and transit. It is hypothesized that workers and non-workers, and males and females have different accessibility profiles. This research demonstrates its practicality at the scale of a metropolitan area, and highlights the differences in access for workers and non-workers, and men and women, because of differences in their activity participation.

Suggested Citation

  • Mengying Cui & David Levinson, 2020. "Multi-Activity Access: How Activity Choice Affects Opportunity," Working Papers 2022-01, University of Minnesota: Nexus Research Group.
    • Handle: RePEc:nex:wpaper:multiactivityaccess
    DOI: 10.1016/j.trd.2020.102364
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    File URL: https://hdl.handle.net/2123/22849
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    References listed on IDEAS

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    Cited by:

    1. Wang, Hui & Loo, Becky P.Y., 2024. "The public transport disadvantaged in a highly transit-oriented city: An analytical framework, key challenges and opportunities," Journal of Transport Geography, Elsevier, vol. 120(C).
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    3. Klumpenhouwer, Willem & Huang, Wei, 2021. "A flexible framework for measuring accessibility with destination bundling," Journal of Transport Geography, Elsevier, vol. 91(C).
    4. Liang, Yuan & Wang, Donggen & Zhou, Xingang & Hao, Jingjing & Guo, Yi, 2025. "Assessing the impact of network and station accessibility on station-level rail transit ridership during peak and off-peak hours," Transportation Research Part A: Policy and Practice, Elsevier, vol. 199(C).
    5. Sharma, Gajanand & Patil, Gopal R., 2024. "Urban spatial structure and equity for urban services through the lens of accessibility," Transport Policy, Elsevier, vol. 146(C), pages 72-90.
    6. Cui, Mengying & Yu, Lijie & Nie, Shaoyu & Dai, Zhe & Ge, Ying-en & Levinson, David, 2025. "How do access and spatial dependency shape metro passenger flows," Journal of Transport Geography, Elsevier, vol. 123(C).
    7. Guo, Jing & Brakewood, Candace, 2024. "Analysis of spatiotemporal transit accessibility and transit inequity of essential services in low-density cities, a case study of Nashville, TN," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
    8. Oviedo, Daniel & Sabogal-Cardona, Orlando, 2022. "Arguments for cycling as a mechanism for sustainable modal shifts in Bogotá," Journal of Transport Geography, Elsevier, vol. 99(C).

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    Keywords

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    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • R14 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Land Use Patterns

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