Drivers and barriers in adopting Mobility as a Service (MaaS) – A latent class cluster analysis of attitudes
Autor: | Serge P. Hoogendoorn, Oded Cats, Sascha Hoogendoorn-Lanser, María J. Alonso-González, Niels van Oort |
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Rok vydání: | 2020 |
Předmět: |
050210 logistics & transportation
Class (computer programming) Latent class cluster analysis 05 social sciences 0211 other engineering and technologies Aerospace Engineering Transportation Context (language use) 02 engineering and technology Management Science and Operations Research Adoption barriers Attitudes 0502 economics and business Cluster (physics) Business Management and Accounting (miscellaneous) 021108 energy Business Pooled on-demand services Marketing Mobility as a Service (MaaS) Mobility as a service Civil and Structural Engineering Low technology |
Zdroj: | Transportation Research. Part A: Policy & Practice, 132 |
ISSN: | 0965-8564 |
DOI: | 10.1016/j.tra.2019.11.022 |
Popis: | Mobility as a Service (MaaS) is expected to significantly change mobility patterns, yet it is still not clear who will embrace this new mobility paradigm and how MaaS will impact passengers’ transportation. In the paper, we identify factors relevant for MaaS adoption based on a survey comprised of over thousand respondents in the Netherlands. We find five clusters in relation to individuals’ inclinations to adopt MaaS in the context of urban mobility. We characterize each of the clusters, allowing for the examining of different customer segments regarding MaaS. The cluster with the highest inclination for future MaaS adoption is also the largest cluster (representing one third of respondents). Individuals in this cluster have multimodal weekly mobility patterns. On the contrary, current unimodal car users are the least likely to adopt MaaS. We identify high (mobility) ownership need and low technology adoption (present in three of the five clusters) as the main barriers that can hinder MaaS adoption. Policies that directly address these two barriers can stimulate MaaS adoption. |
Databáze: | OpenAIRE |
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