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Investigating individual preferences for new mobility services: the case of “mobility as a service” products

Matyas, Melinda Beatrix; (2020) Investigating individual preferences for new mobility services: the case of “mobility as a service” products. Doctoral thesis (Ph.D), UCL (University College London). Green open access

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Abstract

In just a few years, the Mobility as a Service (MaaS) concept has gone from an idea discussed by very few, to being a prominent topic in any transportation related debate. However, within this time, there have only been few rigorous studies that explore the various aspects of MaaS. This thesis aims to contribute to existing knowledge by providing empirical evidence on individual preferences for MaaS plans and their components. In doing so, first desk-research is conducted to summarise existing MaaS schemes and outline the MaaS ecosystem. Next, MaaS surveys that are able to capture individual preferences for MaaS products are designed and specific challenges in the design process identified. The MaaS surveys, including MaaS plan stated preference experiments, are applied in two case study areas of London and Greater Manchester. Using the novel data collected, individual preferences for MaaS plans are examined using two distinct studies: (1) a mixed methods research conducted in London, which expands the survey by adding a qualitative (in-depth interview) element to examine user preferences for MaaS plans and the ways individuals choose between them; and (2) a latent class choice model based on data collected from Manchester to examine whether there is heterogeneity in preferences. Finally, implications for industry and policy stakeholders are discussed as well as interventions that can best support the widespread adoption of MaaS. The results of this thesis show there is interest in the concept of MaaS among potential users as many see value in a single app that integrates different transport modes into a single service. In general, individuals are hesitant in purchasing pre-payed MaaS plans and would be more comfortable with a pay-as-you-go product option. While many people are reluctant towards MaaS plans, the results indicate that heterogeneity exists in preferences towards them and there are different user groups based on socio-demographic characteristics and current mobility habits. Smaller, less expensive plans including modes such as public transport and bike sharing can be used to target students or middle-income people with have high overall mode usage. Larger, more expensive plans that include modes such as taxi and car sharing in addition to public transport, will be attritive to individuals who are likely younger, male, well-educated, have higher income and already use many transport modes. Older population groups, individuals with low income and those that do not use any transport modes or are uni-modal are least likely to adopt MaaS plans. The thesis also provides insights into individuals’ preferences towards transport modes within MaaS plans. The analysis showed that respondents classify modes within MaaS plans into three categories: ‘essential’ modes that are pivotal to the individual and which they most likely already frequently use; ‘considered’ modes are those that they would be willing to include but may not yet use; and ‘excluded’ modes are those that they definitely do not want in their plans and would eliminate any plan that included these. Public transport consistently proved to be an essential mode, while taxi, car sharing and bike sharing could be ‘essential’, ‘considered’ or ‘excluded’ depending on the characteristics of the individual. The main contributions of this thesis are the novel data collected in two case study cities about individuals’ preferences for MaaS plans and the findings gained through the analysis providing insights into possible target audiences and product designs for MaaS plans.

Type: Thesis (Doctoral)
Qualification: Ph.D
Title: Investigating individual preferences for new mobility services: the case of “mobility as a service” products
Event: UCL
Open access status: An open access version is available from UCL Discovery
Language: English
Additional information: Copyright © The Author 2020. Original content in this thesis is licensed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) Licence (https://creativecommons.org/licenses/by/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request.
Keywords: MaaS, Behaviour, Choice Modelling, Mixed Methods
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Bartlett School Env, Energy and Resources
URI: https://discovery.ucl.ac.uk/id/eprint/10091070
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