Segmenting the potential users of MaaS by combining latent class cluster analysis and structural equation modeling

Author:

Kriswardhana WillyORCID,Esztergár-Kiss DomokosORCID

Funder

Hungarian Scientific Research Fund

Nemzeti Kutatási Fejlesztési és Innovációs Hivatal

National Research Development and Innovation Office

Publisher

Elsevier BV

Reference90 articles.

1. Which factors influence the use of shared and privately-owned e-scooters in the city of Madrid? Implications for urban mobility;Aguilera-García;Cities (London, England),2024

2. Exploring the adoption of moped scooter-sharing systems in Spanish urban areas;Aguilera-García;Cities (London, England),2020

3. What influences travelers to use Uber? Exploring the factors affecting the adoption of on-demand ride services in California;Alemi;Travel Behaviour and Society,2018

4. Drivers and barriers in adopting Mobility as a Service (MaaS) – A latent class cluster analysis of attitudes;Alonso-González;Transportation Research Part A: Policy and Practice,2020

5. Mobility-as-a-Service and unsustainable travel behaviour: Exploring the car ownership and public transport trip replacement side-effects of the MaaS paradigm;Alyavina;Transport Policy,2024

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