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Evaluating the Level of Balance Between Demand and Supply at Bus Stops Using Smartcard Data

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  • Shin-Hyung Cho

    (Department of Transportation Engineering, University of Seoul, Seoul 02504, Republic of Korea)

Abstract

The efficient operation of urban bus systems necessitates the alignment of service supply with passenger demand. An inadequate supply of services results in passenger inconvenience, whereas excessive supply leads to inefficiencies for operators. This study introduces a performance measure to evaluate the equilibrium between demand and supply at bus stops. The methodology involves deriving cumulative distribution functions (CDFs) of passenger waiting times during peak (High Ridership Period, HRP) and non-peak hours (Non-High Ridership Period, NHRP) using smartcard data. The maximum vertical distance between these CDFs, along with their definite integrals, serves as the basis for the performance metric. Using a reference threshold of 0.16, bus stops are categorized into three groups: those experiencing excessive demand, those operating in a balanced state, and those with insufficient supply during non-peak hours. This method was applied to 1785 bus stops in Seoul, demonstrating that balanced stops exhibited the shortest average waiting times. The analysis also revealed that stops with excessive demand had significantly higher ridership, whereas stops with lower supply showed ambiguous boundaries between the HRP and NHRP. The proposed performance measure offers a valuable tool for assessing and enhancing the service levels of public transport systems.

Suggested Citation

  • Shin-Hyung Cho, 2025. "Evaluating the Level of Balance Between Demand and Supply at Bus Stops Using Smartcard Data," Sustainability, MDPI, vol. 17(7), pages 1-16, April.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:7:p:3278-:d:1629774
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    References listed on IDEAS

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    1. Daniel Hörcher & Daniel J. Graham, 2021. "The Gini index of demand imbalances in public transport," Transportation, Springer, vol. 48(5), pages 2521-2544, October.
    2. Eun Hak Lee & Inmook Lee & Shin-Hyung Cho & Seung-Young Kho & Dong-Kyu Kim, 2019. "A Travel Behavior-Based Skip-Stop Strategy Considering Train Choice Behaviors Based on Smartcard Data," Sustainability, MDPI, vol. 11(10), pages 1-18, May.
    3. Tu, Wei & Cao, Rui & Yue, Yang & Zhou, Baoding & Li, Qiuping & Li, Qingquan, 2018. "Spatial variations in urban public ridership derived from GPS trajectories and smart card data," Journal of Transport Geography, Elsevier, vol. 69(C), pages 45-57.
    4. Jahun Koo & Gyeongjae Lee & Sujae Kim & Sangho Choo, 2024. "Evaluation of Public Transportation System through Social Network Analysis Approach," Sustainability, MDPI, vol. 16(16), pages 1-21, August.
    5. Sijing Liu & Jiuping Xu & Xiaoyuan Shi & Guoqi Li & Dinglong Liu, 2018. "Sustainable Distribution Organization Based on the Supply–Demand Coordination in Large Chinese Cities," Sustainability, MDPI, vol. 10(9), pages 1-25, August.
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