Ridesplitting is a new form of for-hire service that riders with similar origins and destinations are matched to the same vehicle in real-time via Internet. However, the market share of ridesplitting only accounts for a small fraction of total travel. Understanding cognitive factors affecting ridesplitting preference would be helpful in designing its market measures, regulations, and incentives to achieve high-level customer attractions. This paper identifies the cognitive determinants affecting ridesplitting preference and their inner relationships via the structural equation model. The data from an online survey conducted in Shanghai were implemented for model calibration. The modal fitness results are reasonable, and the path coefficients are significant, exhibiting that the proposed hypothesis cannot be rejected. Specifically, attitude towards incentives and management issues, perceived benefit, and perceived usefulness appear to be strong active driving forces that encourage the desire to adopt ridesplitting.


    Access

    Download


    Export, share and cite



    Title :

    Structure Analysis of Factors Influencing the Preference of Ridesplitting


    Contributors:
    Xinghua Li (author) / Feiyu Feng (author) / Wei Wang (author) / Cheng Cheng (author) / Tianzuo Wang (author) / Pengcheng Tang (author)


    Publication date :

    2021




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




    A dynamic multi-region MFD model for ride-sourcing with ridesplitting

    Beojone, Caio Vitor / Geroliminis, Nikolas | Elsevier | 2023


    Analysis of multi-modal commute behavior with feeding and competing ridesplitting services

    Zhu, Zheng / Qin, Xiaoran / Ke, Jintao et al. | Elsevier | 2019



    Scale effects in ridesplitting: A case study of the City of Chicago

    Liu, Hao / Devunuri, Saipraneeth / Lehe, Lewis et al. | Elsevier | 2023


    Understanding Ridesplitting Behavior with Interpretable Machine Learning Models Using Chicago Transportation Network Company Data

    Abkarian, Hoseb / Chen, Ying / Mahmassani, Hani S. | Transportation Research Record | 2021