Can bike sharing achieve self-balancing distribution? Evidence from dockless and station-based cases

Author:

Hua Mingzhuang,Yu Xinlian,Chen Xuewu,Chen Jingxu,Cheng Long

Funder

Jiangsu Province Natural Science Foundation

Henan Provincial Key Laboratory of Medical Polymer Materials Technology and Application, Tuoren Medical Device Co., Ltd.

National Aerospace Science Foundation of China

National Natural Science Foundation of China

National Natural Science Foundation of China-Shandong Joint Fund for Marine Science Research Centers

Publisher

Elsevier BV

Reference59 articles.

1. Aranganayagi, S., Thangavel, K., 2007. Clustering Categorical Data Using Silhouette Coefficient as a Relocating Measure, in: International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007). pp. 13–17. Doi: 10.1109/ICCIMA.2007.328.

2. Exploring micromobility services: Characteristics of station-based bike-sharing users and their relationship with dockless services;Arias-Molinares;J. Urban Mobil.,2021

3. China Road Transport Associations, 2023. Report on Statistics and Analysis of Data and Information on the Dockless Bike Sharing Industry (2022 Issue 1).

4. Investigation on the joint travel behavior in bike sharing systems during the COVID-19 pandemic: Insights from New York City;Bi;J. Transp. Geogr.,2024

5. Optimizing bike rebalancing strategies in free-floating bike-sharing systems: An enhanced distributionally robust approach;Chen;Transp. Res. E Logist. Transp. Rev.,2024

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