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User attitudes towards a corporate Mobility as a Service
KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL. CTS. (ITRL)ORCID iD: 0000-0003-4512-9054
KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL.ORCID iD: 0000-0001-7124-7164
KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.ORCID iD: 0000-0001-8901-5978
2018 (English)Manuscript (preprint) (Other academic)
Abstract [en]

Mobility as a service (MaaS) envisages enabling a co-operative and interconnected single transport market which provides users with hassle free mobility. Among MaaS postulated benefits, MaaS enthusiasts claim that MaaS solutions could persuade people to give up their car. Conversely, there is a fear that MaaS could in fact induce less sustainable travel, by means of inducing extra demand, and even attract current public transport users towards taxi and car-pool alternatives.

 

In this study we investigate user attitudes and expectations towards a corporate MaaS solution, through a latent class and latent variable model. Results support that there is a trend from car ownership to usership. We also find no evidence that MaaS solutions could produce a shift from public transport users to other less space-efficient shared-mobility solutions such as taxis or car-pool alternatives under our experiment conditions. In connection with user’s preference to share a car journey with strangers, we find the existence of two opposite trends. This finding suggests that there might be appetite for both types of solutions, where users could choose between private or shared journeys by car. Moreover, we find that normative beliefs impact user mobility styles, and that the need and feeling for flexibility is found to be one of the key factors for users to embrace a MaaS solution.

Place, publisher, year, edition, pages
2018.
Keywords [en]
Mobility as a Service, MaaS, Travel behaviour, Attitudes, Norms, Latent Class and Latent Variable Model (LCLVM).
National Category
Transport Systems and Logistics Economics
Identifiers
URN: urn:nbn:se:kth:diva-240357OAI: oai:DiVA.org:kth-240357DiVA, id: diva2:1271367
Funder
Integrated Transport Research Lab (ITRL)VINNOVA, 2017-01976
Note

QC 20181218

Available from: 2018-12-17 Created: 2018-12-17 Last updated: 2018-12-18Bibliographically approved
In thesis
1. Learning about the unobservable: The role of attitudes, measurement errors, norms and perceptions in user behaviour.
Open this publication in new window or tab >>Learning about the unobservable: The role of attitudes, measurement errors, norms and perceptions in user behaviour.
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Unobservable factors are important to understand user behaviour. Moreover, they contain information to help design services that willsolve today’s challenges. Yet, we have barely scratched the surface ofthe underlying mechanisms ruling user behaviour. For decades, userbehaviour analysis has focused on the capabilities of observable variables,as well as assumptions of regular preferences and rational behaviourto explain user choices; and amalgamated unobservable factorsinto ”black-box” variables. As a response, the field of behaviouraleconomics has produced an array of so-called choice anomalies, wherepeople seem not to be fully rational. Furthermore, as a consequence of the ”digital revolution”, nowwe harvest data on an unprecedented scale -both in quantity andresolution- that is nurturing the golden age of analytics. This explosionof analytics contributes to reveal fascinating patterns of humanbehaviour and shows that when users face difficult choices, predictionsbased only on observable variables result in wider gaps between observedand predicted behaviour, than predictions including observableand unobservable factors. Impacts of the ”digital revolution” are not limited to data and analyticsbut they have filtered through the whole tissue of society. Forinstance, telecommunications allow users to telework, and telework allowsusers to change their travel patterns, which in turn contributes toincrease the overall system complexity. In addition to the new worlddynamics facilitated by Information and Communications Technology,megatrends such as hyper-urbanization or increase demand of personalisedtransport services are imposing pressures on transport networksat a furious pace, which also contributes to increase the complexity ofthe choices needed in order to navigate the networks efficiently. In an effort to alleviate these pressures, new mobility services suchas electric and autonomous vehicles; bicycle and car sharing schemes;mobility as a service; vacuum rail systems or even flying cars are evolving. Each of these services entails a different set of observable variableslike travel time and cost, but also a completely different set of unobservableones such as expectations, normative beliefs or perceptionsthat will impact user behaviour. Hence, a good understanding of theimpact of underlying, unobservable, factors -especially when servicesare radically different from what users know and have experienced inthe past- will help us to predict user behaviour in uncharted scenarios. Unobservable factors are elusive by nature, hence to incorporatethem into our models is an arduous task. Furthermore, there is evidence showing that the importance of these factors might differ across time and space, as user preferences, perceptions, normative beliefs, etc.are influenced by local conditions and cultures. As a consequence, we have witnessed a surge of interest in behavioural economics over the past two decades, due to its ability to increase the explanatory and predictive power of models based on economic theory by adding a more psychologically plausible foundation. This thesis contributes to the existing body of literature in TransportScience in the areas of user perceptions, measurement errors, and the influence of attitudes and social norms in the adoption of new mobility solutions. The work builds on the behavioural economics theoretical framework, underpinned by economic theory, discrete choice analysis -rational behaviour and random utility maximization-, as well as social and cognitive psychology. Methodological contributions include a framework to systematically test differences in user preferences for a set of public transport modes, relating to observed and unobserved attributes; and a framework to assess the magnitude of unobservable measurement errors in the input variables of large-scale travel demand models. On an empirical dimension, findings support the existence of a ”rail factor”, the impact of modelling assumptions on parameter estimates of hybrid choice models, the presence of larger measurement errors in the cost variables than in the time variables, -which in turn translates into diluted parameters that under-estimate the response to pricing interventions-, and that the model with the best fit does not guarantee better parameter estimates. Therefore, I expect this thesis to be of interest not only to modellers, but also to decision makers; and that its findings will contribute to the design of the mobility solutions that users need and desire, but also that will benefit society as a whole.

Place, publisher, year, edition, pages
Stockholm: Kungliga Tekniska högskolan, 2019. p. 48
Series
TRITA-ABE-DLT ; 1837
Keywords
Attitudes, Measurement errors, Discrete choice analysis, Latent variables, Model misspecification, Normative beliefs, Rail factor, User perceptions, Social norms, Value of travel time savings
National Category
Transport Systems and Logistics Economics
Research subject
Transport Science
Identifiers
urn:nbn:se:kth:diva-240362 (URN)978-91-7873-022-3 (ISBN)
Public defence
2019-01-31, F3, Lindstedtsvägen 26, Stockholm, 14:00 (English)
Opponent
Supervisors
Note

QC 20181217

Available from: 2018-12-18 Created: 2018-12-17 Last updated: 2018-12-18Bibliographically approved

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Lorenzo Varela, Juan ManuelSusilo, YusakJonsson, R. Daniel

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