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Mobility as a Service (MaaS) is a novel brand of transport that promises to replace private cars with multimodal personalised mobility packages enabled by a digital platform capable of integrating travel planning, booking and ticketing, and real-time information services. It is an intervention that through its digitisation, connectivity, information and sharing merits intends to inspire and support the transition to a more sustainable mobility paradigm. Recent research suggests, however, that the potential uptake of MaaS might not be overwhelming; current car drivers could face considerable difficulties in bypassing their personal car for it and, more worryingly, future MaaS users may substitute not only personal car trips but also public transport journeys with car-sharing and ride-sharing services. This means that MaaS might not be able to create travel behaviour change, and even if it does, the changes may not be always towards the right direction. Through conducting 40 semi-structured interviews in three different UK cities, namely London, Birmingham and Huddersfield, and employing a robust Thematic Analysis approach, this study explores the factors underpinning the uptake and potential success of MaaS as a sustainable travel mechanism. The challenges and opportunities reflecting and affecting potential for responsible MaaS usage refer to five core themes Car Dependence; Trust; Human Element Externalities; Value; and Cost, each of them with distinctive and diverse dimensions. Policy-makers and mobility providers should realise that MaaS success relies on changing people’s attitudes to private cars (something very challenging) and thus they should incentivise responsible MaaS use, promote public transport as its backbone, use public engagement exercises and trials to expose people to the concept and somewhat demonise private car ownership and car use.
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Mobility as a service and sustainable travel behaviour: A
thematic analysis study
Elena Alyavina, Alexandros Nikitas
, Eric Tchouamou Njoya
Department of Logistics, Marketing, Hospitality and Analytics, Huddersfield Business School, University of Huddersfield, HD1 3DH Huddersfield, UK
article info
Article history:
Received 10 February 2020
Received in revised form 2 July 2020
Accepted 5 July 2020
Mobility as a Service
Travel behaviour
Sustainable mobility
Qualitative study
Thematic analysis
Mobility as a Service (MaaS) is a novel brand of transport that promises to replace private
cars with multimodal personalised mobility packages enabled by a digital platform capable
of integrating travel planning, booking and ticketing, and real-time information services. It
is an intervention that through its digitisation, connectivity, information and sharing mer-
its intends to inspire and support the transition to a more sustainable mobility paradigm.
Recent research suggests, however, that the potential uptake of MaaS might not be over-
whelming; current car drivers could face considerable difficulties in bypassing their per-
sonal car for it and, more worryingly, future MaaS users may substitute not only
personal car trips but also public transport journeys with car-sharing and ride-sharing ser-
vices. This means that MaaS might not be able to create travel behaviour change, and even
if it does, the changes may not be always towards the right direction. Through conducting
40 semi-structured interviews in three different UK cities, namely London, Birmingham
and Huddersfield, and employing a robust Thematic Analysis approach, this study explores
the factors underpinning the uptake and potential success of MaaS as a sustainable travel
mechanism. The challenges and opportunities reflecting and affecting potential for respon-
sible MaaS usage refer to five core themes Car Dependence; Trust; Human Element
Externalities; Value; and Cost, each of them with distinctive and diverse dimensions.
Policy-makers and mobility providers should realise that MaaS success relies on changing
people’s attitudes to private cars (something very challenging) and thus they should incen-
tivise responsible MaaS use, promote public transport as its backbone, use public engage-
ment exercises and trials to expose people to the concept and somewhat demonise private
car ownership and car use.
Ó2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY
license (
1. Introduction
A car-centric transport paradigm has been the foundation of urban growth on a worldwide scale for decades now, which,
despite its ‘user convenience’ merits, has been associated with severely adverse effects on the grounds of social, environmen-
tal and economic sustainability (Nikitas, 2018). Hence, planning bodies are embracing innovative ways for enabling people
to travel more responsibly. Mobility as a Service (MaaS) is a novel concept that could facilitate a shift in individuals’ travel
behaviour away from private car dependence. According to the MaaS paradigm, privately owned vehicles will be replaced by
personalised multimodal mobility service packages on a contract or ‘pay-as-you-go’ basis (Kamargianni & Matyas, 2017;
1369-8478/Ó2020 The Authors. Published by Elsevier Ltd.
This is an open access article under the CC BY license (
Corresponding author.
E-mail address: (A. Nikitas).
Transportation Research Part F 73 (2020) 362–381
Contents lists available at ScienceDirect
Transportation Research Part F
journal homepage:
Nikitas, Kougias, Alyavina, & Njoya Tchouamou, 2017). MaaS is predicted to contribute to sustainability by increased sharing
of mobility resources, reducing the number of vehicles needed as well as simplifying multimodality through integration
(Strömberg, Karlsson, & Sochor, 2018). MaaS allows access to transport services (which themselves could be new) via mobile
apps and represents a window of opportunity to establish the age of sharing economies in transport (Bardhi & Eckhardt,
2012). To enhance the reaches of public transport, MaaS relies on shared use alternatives to private car, such as taxi, car-
sharing, ride-sharing, ride-hailing and bike-sharing (Jittrapirom et al., 2017). Recent research suggests, however, that the
potential uptake of MaaS might not be overwhelming (Ho, Hensher, Mulley, & Wong, 2018); current car drivers could face
considerable difficulties in bypassing their attachment to personal car (Storme, De Vos, De Paepe, & Witlox, 2020), and future
MaaS users may substitute not only personal car trips but also public transport journeys with car-sharing and ride-sharing
services (Hensher, 2017) - a phenomenon called ‘‘Uberisation” of MaaS. This means that MaaS penetration, contrary to
expectations, may lead in numerous cases to unsustainable travel practices among its users and to limited results in terms
of modal shift and car ownership reduction. At present, there is a scarcity of research trying to understand the drivers of the
observed behaviourial (or in most cases intentional behavioural) patterns with MaaS. Therefore, this study makes its purpose
(1) Explore the factors underpinning the potential uptake of MaaS and its pathway for being established as a mainstream
travel mechanism;
(2) Identify challenges and opportunities in creating genuinely sustainable travel behaviour with MaaS.
The next section of this study provides a more detailed background justifying the need for this study. This is followed by a
detailed description of the methodology used. Then, this study’s key findings are presented. Finally, the paper provides a dis-
cussion section that integrates the key messages of this study and initial policy recommendations that would be necessary
for those with the task to build effective and widely acceptable MaaS schemes that create more sustainable and liveable
2. Literature review
This section aims to provide a background for the primary findings of this study. Relevant points from an emerging, yet
underdeveloped, literature are identified and synthesised to support the study’s primary research contributions.
2.1. Introducing MaaS trends
Mobility as a Service (MaaS) is a concept still in its infancy that aims to integrate multimodal transportation options into a
single on-demand mobility service accessible via a single digital interface. Propelled by global trends such as digitalisation
and servitisation, MaaS has rapidly grown in popularity and hype but, due to its novelty, large-scale scope, unprecedented
coordination and collaboration needs and disruptive nature, represents a challenging transition (Smith, Sochor, & Karlsson,
2019). MaaS is a natural fit with a lifestyle emerging among younger generations, who nowadays drive less, are more
enthused about the latest technological products and alternative forms of mobility and are less likely to learn to drive or
own a car (Lyons, Hammond, & Mackay, 2020; Mulley, 2017). Wireless connectivity, technology savviness but also, as
Lee, Circella, Mokhtarian, and Guhathakurta (2019) suggested, the impact of the economic crisis and fundamentally different
travel preferences from those of older birth cohorts led the younger traveller to open up to digitally enabled multimodal
mobility. Yet, those transport services are unimodal in their nature, and create barriers to older users and others discouraged
by the complexities (and uncertainties) associated with such procedures (Kamargianni, Li, Matyas, & Schäfer, 2016), and to
those still resistant to abandon the era of the privately owned vehicle (Nikitas, Njoya, & Dani, 2019).
2.2. MaaS uptake
One of the most prominent examples of operational MaaS platforms is Whim, developed by Finnish start-up MaaS Global
and introduced in Helsinki in 2016. The Whim user can combine, plan, and pay, both in pay-as-you-go or monthly subscrip-
tion forms, for public transport, taxi, car rental, car-sharing and city bike trips. By July 2018, operational for over two years,
Whim had been used by around 45,000 Helsinki residents, which accounts for only 7% of the city’s population (House of
Commons Transport Committee, 2018). Put against Uber alone, Whim appears to be falling behind. Whim is now up and run-
ning in West Midlands, UK, and despite being piloted twice since August 2017, the latest launch of the app received just
around 500 downloads (House of Commons Transport Committee, 2018).
Ho et al. (2018, 2020) studied the potential uptake and willingness to pay for MaaS among 252 transport users in Sydney,
Australia and 290 transport users in Tyneside, UK. The participants, who were first introduced to MaaS by viewing a video
explaining the concept, were then to make a distinction between the proposed mobility packages, evolving around their
demographics, personal circumstances and travel patterns, pay-as-you-go option, or no subscription. Interestingly, as many
as 53% of participants in Sydney and 55% of participants in Tyneside chose not to subscribe to MaaS even on a hypothetical
E. Alyavina et al. / Transportation Research Part F 73 (2020) 362–381 363
Fioreze, de Gruijter, and Geurs (2019) looked at the willingness to use MaaS in the city of ’s-Hertogenbosch, Netherlands.
A survey, which introduced a concept of MaaS through MaaS app screenshots and asked a series of questions focusing on
attitudes towards different transport modes and the intention to use MaaS, was completed by 568 residents of Paleiskwar-
tier, a district of ’s-Hertogenbosch. The findings indicated that only 20% of participants were, to some degree, willing to use
MaaS be it available to them. As many as 60% of respondents had no interest in using MaaS, while another 20% remained
neutral towards the concept. Another study (Caiati, Rasouli, & Timmermans, 2020), conducted in Netherlands, explored,
through the use of a panel survey, the willingness to subscribe to MaaS among 1078 residents of Amsterdam and Eindhoven.
The study revealed that only in 17% of all choices the participants demonstrated an interest in the MaaS subscription.
2.3. MaaS and travel behaviour
The industry and academia both express excitement about the MaaS approach, due to its promise in facilitating sustain-
able travel behaviour (Matyas & Kamargianni, 2019). Inappropriate consumption of MaaS and the integrated car- and ride-
sharing services, can, however, aggravate transport related sustainability issues. Hensher (2017), for instance, notes that car-
sharing services, rather than making car owners switch to sharing, give access to cars to those who are not in possession of
one, therefore increasing car agglomeration. Rayle, Daia, Chanc, Cervero, and Shaheen (2016) revealed that many car owners
became ride-hailing users simply to avoid the hassle of driving and, otherwise, would drive themselves or take a taxi, while
the study by Shaheen, Cohen, and Zohdy (2016) stated that 75% of ride-sharing users were previous public transport riders.
Fioreze et al. (2019) argued that the people most likely to use MaaS are not frequent car drivers, but people primarily using
public transport; there is, therefore, a risk that by facilitating the use of other modes, such as car-sharing and ride-sharing,
MaaS may induce an adverse effect leading road users to give up public transport, and not their cars, in favour of ride-sharing
trips as it has been the case for Uber and Lyft in major cities. Any shift from public transport to car-centric solutions however
is not in line with what MaaS, in theory at least, is set to achieve, in terms of sustainability gains (Nikitas, Michalakopoulou,
Njoya, & Karampatzakis, 2020).
Kamargianni, Matyas, Li, and Muscat (2018) studied the attitudes of 1570 car-owning and non-car-owning Londoners
towards car ownership and MaaS, and the potential of MaaS to alter their travel behaviour. The respondents did not show
prominent willingness to alter their travel behaviour if equipped with MaaS. Only 33% of car owners agreed MaaS would help
them depend on car less. Even when offered unlimited access to car-sharing with MaaS, 61% of the car owners remained
reluctant to sell their cars, while 64% of non-car owners would not delay buying a car. As many as 22% of all respondents
were willing to substitute public transport trips with taxi when equipped with MaaS. Integrated within MaaS car-sharing
was an attractive public transport trips’ replacement for another 11% of respondents.
Hartikainen, Pitkänen, Riihelä, Räsänen, Sacs, Sirkiä, and Uteng (2019) looked at the potential commonalities and differ-
ences in travel behaviour of an average Helsinki resident against the Whim app user. Whim users appeared to ride public
transport 15% more often than an average Helsinki resident. Yet, the Whim user combined taxis with public transport three
times more often and used taxi alone 2.1 times more often than a typical Helsinki resident, while also showing an increasing
interest in incorporating car rentals into daily trips.
UbiGo was the MaaS web interface piloted to 195 car-owning residents of Gothenburg, Sweden between November 2013
and April 2014. The platform offered its users access to combinations of various transport modes in a form of monthly pack-
age, for a subscription fee starting at
135 per month. At the end of the pilot, 64% of all participants used private car less.
Abnegating personal car use, though, was the precondition of participation in the UbiGo experiment. The reduction in private
car use caused an increase in the use of bus and tram services, local railways and bike-sharing with accordingly 50%, 18% and
23% of participants using the services more often. However, non-private cars faced even greater interest: as many as 57% of
participants used car-sharing services more frequently and another 20% of participants reported the increase in the use of
taxi (Karlsson, Sochor, & Strömberg, 2016; Sochor et al., 2015, 2016).
Another pilot study (Storme et al., 2020) took place in Ghent, Belgium with 73 car owners using a MaaS application for
two and a half months. Study participants were given free access to MaaS packages of value varying between
150 and
and were asked to minimise their car use to the largest possible extent, with it being penalised at
0.50/km and deducted
from the value of their MaaS package. Despite the strict rules, participants demonstrated rather unsustainable behaviours: a
third of all MaaS budget offered to participants was spent on the use of personal cars whilst another third was used to access
car-sharing services. Over the study period participants purchased a total of 545 bus and tram tickets and 162 train tickets,
which refer roughly to just four public transport trips per participant per month.
2.4. Research gaps
While the number of studies on the potential uptake of MaaS and its impacts on travel behaviour is slowly developing,
there is little research examining the reasons behind such low rates of MaaS acceptance and shift to public and active trans-
port. Some of the recognised-to-date underpinnings of MaaS acceptance on user level include: added value (Fioreze et al.,
2019); car convenience and the associated comfort, ease of planning, and the need to chauffer dependants (Fioreze et al.,
2019; Polydoropoulou, Pagoni, & Tsirimpa, 2018; Storme et al., 2020); perceived usefulness and ease of use of MaaS platform,
the hedonic motives, previous experiences, and the motivation to achieve autonomy, competence and relatedness to like-
minded people (Schikofsky, Dannewald, & Kowald, 2020); social influences (Caiati et al., 2020); digitalisation in the popula-
364 E. Alyavina et al. / Transportation Research Part F 73 (2020) 362–381
tion, reliance on internet and mobile devices, integration, personalisation, compatibility and trust in monetary transactions
(Polydoropoulou et al., 2018); and cost (Caiati et al., 2020; Ho et al., 2020; Karlsson et al., 2020). Our study will focus on gen-
erating more insights about the expected consequences MaaS may have on the ability to travel more sustainably, exploring
the determinants of sustainable MaaS uptake on user level that the existing literature has not yet identified or paid enough
attention to, and offer recommendations on how to promote sustainable travel through MaaS.
3. Research methodology
3.1. The choice of semi-structured interviews
This study aims to explore the barriers and facilitators of MaaS acceptance and uptake on the user level and to generate
insights about the expected consequences MaaS may have on the ability to travel more sustainably, which implies the use of
a qualitative approach. Qualitative methods have been scarcely used in the MaaS literature despite the important role these
can play in travel behaviour analysis grounds (Matyas, 2020). Individual semi-structured interviews, based on an interview
guide but at the same time allowing some flexibility in the questioning approach, were chosen over other qualitative meth-
ods as they, although laborious, allow researchers to get rich data (Walle, 2015) and understand the reasons for the decisions
individuals make by capturing their attitudes and opinions (Saunders, Lewis, & Thornhill, 2016, p. 394). The interview guide,
a data collection instrument designed to improve consistency between different interview sessions, had six parts: introduc-
tion; individual demographics; current travel practices and attitudes towards different transport modes; familiarising with
MaaS through an infographic; attitudes towards MaaS; and summing up. The interview guide is available in the Appendix A.
The interviews were fully recorded and transcribed solely by the authors to ensure accuracy of the insights given by each
3.2. The use of infographic
In order to explain the concept of MaaS to our study participants and aid the interviewing process, a literature-infused
infographic (Fig. 1) was developed adopting key MaaS characteristics as presented in Jittrapirom et al. (2017) and Mulley
(2017). Infographics provide an engaging visual display communication tool that offers to researchers the ability to present
intense and sophisticated information on a certain subject in a more comprehensible manner (Dur, 2014). The infographic
contains the textual conceptual description of MaaS as well as some graphic MaaS elements, such as a hypothetical app
mock-up. Similar methods aiding data elicitation were previously applied in MaaS related research. For example,
Schikofsky et al. (2020) used a conceptual description of MaaS to make focus groups participants aware of MaaS and its func-
tionalities. The authors then enhanced conceptual description with MaaS app mock-ups to aid the data collection through a
survey. Similarly, Fioreze et al. (2019) used conceptual description and MaaS app mock-ups to explain the concept to their
survey participants.
We aimed to be value-neutral in the way we presented MaaS features in our infographic. MaaS as a concept was
explained using four conceptual features, each supplied with a brief description in the infographic: consolidated transport
offering; all-in-one digital platform; payment options; and effective cooperation. We then also described the MaaS experi-
ence as a five-step process of: creating account; planning the journey; booking and paying for travel; accessing transport
modes; and resolving on-route issues. During the interview, participants were given an opportunity to ask questions in case
something in the infographic appeared ambiguous to them.
3.3. Study locations
This study focuses on three geographical areas in the UK, namely London, Birmingham and Huddersfield (see Fig. 2). With
its population being close to 9 million in 2019 (ONS, 2019) London is the largest city in the UK. Despite the highly developed
transportation system in place and the introduction of congestion charging and Ultra Low Emission zone, London remains
the most congested city in the UK with 227 h lost in congestion per capita on annual basis (INRIX, 2018), and also one of
the most car-centric cities with 2.66 million privately owned cars registered to its residents (Statista, 2020). Birmingham
is the second largest British city by population with over a million inhabitants (ONS, 2019), and the 12th most congested
city in the country with 134 h lost in congestion per capita in 2017 (INRIX, 2018). Birmingham is of particular interest to
this study because it currently serves as a pilot ground for Whim app, the most well-known active MaaS scheme. Hudder-
sfield is Kirklees’ biggest town in West Yorkshire, with close to 150,000 inhabitants (Kirklees Council, 2019) and is home to
the fourth most congested transport corridor in the UK outside London, the Huddersfield Road (INRIX, 2018). So, located in
the South, the Midlands and the North of England, these geographical locations differ significantly in size and transportation,
offering a study cohort that includes a metropolis, a city and a town, all suffering from high levels of congestion, largely influ-
enced by residents’ car-centric behaviours. This choice facilitates capturing a diversity of views on MaaS and how these
potentially align with key built environment specifics and urban planning considerations.
E. Alyavina et al. / Transportation Research Part F 73 (2020) 362–381 365
3.4. Sampling approach and recruitment
Given the explorative nature of this study and, thus, needlessness of statistical inferences about the characteristics of
studied population (Saunders et al., 2016, p. 276), non-probability sampling was used. The participants were not incentivised
in any way to take part in this study. The prerequisite for participant selection included the residency in one of the chosen
study locations and daily travel activity. Achieving a diverse sample in age, gender, family status, educational background,
Fig. 1. Infographic explaining MaaS.
366 E. Alyavina et al. / Transportation Research Part F 73 (2020) 362–381
employment types, levels of income and, obviously, household car ownership was also a consideration. Self-selection tech-
nique, where individuals chose to take part in the study on their own accord once the latter was advertised to them via social
media platforms and e-mail distribution lists, was used to recruit 21 of the participants. The other 19 participants were
recruited through a snowballing technique: the already recruited participants suggested future participants from among
their acquaintances. Saunders et al. (2016, p. 297) suggest that the minimum non-probability sample size for semi-
structured interviews should be between 5 and 25, which this study has significantly exceeded. It is important to note,
though, that it was not the number of participants the interviewing process focused on but rather reaching the point of sat-
uration where the collected data began to provide little, if any, new information. Prior the interview, study participants were
contacted via e-mail and were provided with a participant information sheet explaining the nature of the study, a consent
form that would allow us to record, store, transcribe and use the interview output solely for academic and research purposes,
and the MaaS infographic. In this pre-interview correspondence, our participants were also given an opportunity to select
the convenient date and time for the interview as well their preferred means of communication: face-to-face, skype or
Table 1 lists the key characteristics of the participants providing their demographic information, and the presence of car
within household. Participant ID consists of the location identifier (L for London, B for Birmingham, and H for Huddersfield)
and the associated participant number. Thereby, this qualitative study is based on interviews with 40 road users living in the
UK, 14 from London, 12 from Birmingham, and 14 from Huddersfield. The study largely focuses on car-owners, though, non-
car-owners also took part for enabling a better identification of possible unsustainable side-effects referring to people that
may actually see MaaS as an opportunity to access cars on a more frequent basis.
Fig. 2. Study locations.
E. Alyavina et al. / Transportation Research Part F 73 (2020) 362–381 367
3.5. Method of analysis
Inspired by the six-step Thematic Analysis approach proposed by Braun and Clarke (2006) this work adopts the system-
atic line of work of Nikitas et al. (2018, 2019). Thematic Analysis is a method for identifying, organising, and offering insights
into patterns of themes across several items of qualitative data. It provides the mechanics of systematically coding and ana-
lysing data and linking it to broader theoretical concepts.
Table 1
Sample characteristics of study participants.
ID Gender Age Marital Status Children Driving
Education Employment
Household Income (Monthly
L01 Male 28 Single None Yes None Master’s Employed FT £3,200
L02 Male 50 Married 2 Yes 1 Bachelor’s Employed FT £5,500
L03 Male 48 Domestic
5 Yes 4 Secondary
Employed FT £4,600
L04 Male 35 Domestic
None Yes 1 Bachelor’s Employed FT £6,500
L05 Female 39 Domestic
1 Yes 2 Master’s Employed FT £6,500
L06 Female 36 Married None No 1 Secondary
Employed FT £4,600
L07 Female 28 Single None Yes None Master’s Employed FT £1,800
L08 Male 53 Single None Yes 1 Bachelor’s Employed FT £3,600
L09 Male 31 Domestic
None Yes 1 Master’s Employed FT £3,200
L10 Female 34 Married None Yes 2 Secondary
Employed FT £6,500
L11 Male 35 Married 2 Yes 1 Master’s Employed FT £5,000
L12 Male 48 Married 2 Yes 1 Secondary
Employed FT £5,500
L13 Male 27 Domestic
None Yes None Master’s Employed FT £6,500
L14 Male 28 Single None Yes 1 Master’s Employed FT £3,200
B01 Female 27 Domestic
None Yes 1 Secondary
Employed FT £1,500
B02 Male 64 Married 2 Yes 1 Secondary
Employed FT £1,300
B03 Male 32 Single None Yes None Doctorate Employed PT £2,000
B04 Male 29 Single None Yes None Doctorate Employed FT £2,300
B05 Male 27 Single None Yes 1 Secondary
Employed FT £3,800
B06 Female 24 Single None Yes 1 Master’s Employed FT £2,000
B07 Female 29 Domestic
None Yes 1 Bachelor’s Employed FT £3,400
B08 Male 36 Married 2 Yes 1 Doctorate Employed FT £2,600
B09 Male 39 Single None Yes None Master’s Employed FT £2,600
B10 Female 34 Married 3 Yes 2 Master’s Student £5,000
B11 Male 36 Married 3 Yes 1 Bachelor’s Employed FT £2,600
B12 Male 20 Single None Yes 1 Secondary
Student £1,000
H01 Female 26 Married 1 No 1 Master’s Student £1,900
H02 Female 36 Married 2 No 1 Doctorate Employed FT £3,000
H03 Female 51 Married 2 Yes 2 Master’s Employed FT £3,000
H04 Female 53 Domestic
None Yes 2 Doctorate Employed FT £3,000
H05 Male 24 Single None Yes 1 Secondary
Student £1,000
H06 Male 29 Single None Yes 3 Master’s Employed FT £8,000
H07 Male 56 Single 5 Yes 1 Secondary
Student £1,000
H08 Male 41 Married 1 Yes 1 Master’s Employed PT £2,000
H09 Male 28 Married None Yes 1 Master’s Employed FT £2,000
H10 Male 25 Married 1 Yes 1 Master’s Employed FT £1,900
H11 Female 25 Domestic
None Yes 1 Bachelor’s Employed PT £1,000
H12 Male 19 Single None Yes 1 Secondary
Student £1,000
H13 Male 24 Domestic
1 Yes 1 Master’s Student £1,500
H14 Male 36 Married 2 Yes 1 Doctorate Employed FT £3,000
368 E. Alyavina et al. / Transportation Research Part F 73 (2020) 362–381
The interviews were conducted, transcribed and analysed by the authors. The analysis procedure included: fully tran-
scribing the interviews; familiarising with written data and identifying codes; searching, reviewing and defining themes;
and, ultimately, generating findings. The coding and theme identification processes in this analysis were data-driven to les-
sen analyst-oriented biases. The identified key themes and their sub-themes were linked to the theoretical literature upon
completion of the analysis and not prior. The coding process was performed manually through repeated reading of and mak-
ing notes on interview transcripts. Therefore, every one of the 40 transcripts were fully coded, with some data extracts, or
quotes, falling under more than one code. Next, an Excel spreadsheet was created for organising the codes and matching data
extracts, with surrounding data kept in order to maintain the context, into a manageable format for theme identification. The
codes, and the related extracts, were then scrutinised, and combined to form overarching themes repeatedly to ensure that
the final thematic map thoroughly meets the research aims of the study. It is important to note that the themes were not
built by looking for the wealth of textual evidence but, as also approached by Nikitas, Wang, and Knamiller (2019), by iden-
tifying structures within the data that have an explanatory capacity. To ensure reliability and avoid bias, the three authors
analysed the data independently for the coding stage and then compared and synthesised their independent coding analyses
to create a single ‘‘bigger-picture’’ narrative. During the synthesis procedure we reached a 90% consensus on the codes that
were eventually the building blocks of our themes; this very high intercoder reliability helped us triangulate and validate our
During the theme identification process, it became obvious that, although some extracts belong to the same theme, they
interpret different, at times contradicting, theme dimensions. Moreover, as on occasion the extracts matched more than one
theme, some of the themes also appear logically interlinked. There were also a few cases where two different sub-themes
both discussed a specific agenda from an entirely different angle like, for example, capacity and user behaviour risks, using
quotes that might represent two entirely different viewpoints. Braun and Clarke (2006) suggest that the themes and relation-
ships among them do not have to smooth out or ignore but instead retain the tensions and inconsistencies within and across
data, which our study has conformed to.
When writing up, the main considerations were to provide ‘‘a concise, coherent, logical, non-repetitive and interesting
account of the story the data tell” (Braun & Clarke, 2006) and to demonstrate prevalence of the themes by selecting the most
characteristic and convincing individual responses (Nikitas et al., 2018;Vaismoradi et al., 2013). Therefore, the findings of
this study, presented in the following section, will take a form of a narrative with Themes and sub-themes signposted in bold
and bold italics accordingly and followed by raw data extracts which capture the essence of the point demonstrated in the
narrative. These selected participant quotes are presented in italics so that they can be easily separated by our analysis com-
mentary. The findings will then be linked to theoretical literature in the Discussion section.
4. Findings
There were five core themes that our analysis identified as critical determinants underpinning MaaS acceptance and suc-
cess: Car Dependence; Trust; Human Element Externalities; Value; and Cost. Each of them has distinctive dimensions,
expressed as their sub-themes, that affect and reflect user intention to commit to sustainable travel with MaaS.
4.1. Overview of findings
None of the study participants had previous knowledge about MaaS, yet, the majority had used various travel apps, and
therefore, when reading through the speculative infographic, easily comprehended the nature of the concept. Attitudes
towards MaaS were largely positive with study participants demonstrating willingness to accept, or at least to consider using
MaaS for travel once it is available to them.
B06: ‘‘I think it’s a good idea, and I would use it.
L09: ‘‘I like the concept of it, though. I think it’s a good idea.
The acceptance and potential application of MaaS, however, came in many different forms, influenced by a variety of fac-
tors emerging from car ownership and use, technology intricacies and the nitty-gritty of non-car travel.
4.2. Car Dependence
The theme of Car Dependence in this analysis reveals the effects of MaaS on participants’ bonds with cars and car related
travel decisions. MaaS was viewed for many through the lens of owning a car:
B05:‘‘I like my car, and it is fun. Would you give up your shoes if you were offered a pair of sandals?
B01: ‘‘I think a lot of people get used to the comfort of cars, and it is very difficult to change this. Now that I don’t have a car, I
would absolutely use MaaS.
Indisputably, MaaS showed the potential to induce modal shift considerations. Some participants, after familiarising with
possible features that MaaS has to offer, assumed they could cease car use:
L02: ‘‘If MaaS is as good as it says and my personal time isn’t impacted greatly, then it makes sense and I don’t really need a car.
E. Alyavina et al. / Transportation Research Part F 73 (2020) 362–381 369
L14: ‘‘I would consider giving up my car, that’s for sure. MaaS could eliminate the need for car.
Others, although accepting the possibility to change the way they travel and to reduce car use, pulled out quasi-
sustainable behaviours:
L03: ‘‘I would definitely try and use MaaS more. I guess I’d use more taxis and possibly car-sharing. I never used car-sharing
before, but I would try that. Ride-sharing maybe not as much!‘‘
L07: ‘‘To be honest, if I could use those ZipCars, for example, I would much rather do that than have a car myself.
Some participants took a stance where their decision to own and use a car could not be influenced altogether:
B11: ‘‘All things being equal, if my health is okay, and I am not banned from driving, for me MaaS would be a no.
B04: ‘‘I and a lot of people would not hold back from buying a car, no matter what alternative is presented.
Yet, while MaaS did not seem to be able to fully substitute car use for every individual, partial substitution was thought
B07: ‘‘I would be interested in using this as well as having my own car.
H07: ‘‘I would probably reduce the amount of times I use my own car.
It was practically unanimous that MaaS could not replicate the convenience of a private car:
B03: ‘‘MaaS might affect the frequency of my driving. Yet, it will not change my mind from driving because it doesn’t resolve all
the issues that push me to drive.‘‘
The convenience of car was particularly valued in terms of control over the journey, independence from timetable, and
privacy the car allows its owner to have as well as for family travel, travel with luggage, and cases of emergency:
H10: ‘‘I don’t have to wait around for other transport means. If I go shopping, I have the entire boot to put everything in it. I can
plan my own trip when I want it, so I don’t depend on any other time constraints from other transport means.
B12: ‘‘If you are in your car, even with friends, you are not sharing with other people, with strangers.‘‘
L09: ‘‘If there was an emergency, whatever that might be, a trip to a hospital or going to see someone quickly, you’ve got your
own car, you can drop everything and go, whereas with MaaS there is always going to be a lag.
B08: ‘‘I think the convenience and the comfort for my family is more important. For that, I would not want to swap my personal
car for MaaS.
The car came across as a preferred transport option not only because of the convenience but also because of the general
enjoyment of its ‘‘personal space” aspect as well as of ownership and use:
L13: ‘‘I generally enjoy cars. From a linear point of view, you can view cars plainly as transport, but they can be for enjoyment,
they can be for general social aspects. They are a trend.
B06: ‘‘I just got my car in January, so it’s like my little baby at the moment, and I love it.
H08: ‘‘It is also self-esteem to some extent because if you’re driving a car, if you are satisfied with the car, if you drive the car you
really like, that becomes the point of it. That’s what we are looking for in our life. It’s a way of treating ourselves.
The context of morality came up too. Sustainability indifference and misinterpretation of the impacts of car use on soci-
ety and environment were yet another explanation to the pursuit of driving habits:
L10: ‘‘Whilst I am very aware that there is a problem, it’s not a big enough problem for me to say that I’m not going to use my car
B11: ‘‘If everyone uses a car that is environmentally safe in terms of emissions it produces, like I do, then we would have a safer
environment. So, on my part I know that I use something environmentally friendly.
Car-related sustainability concerns, however, resulted not only in cognitive dissonance in individuals when deciding to
drive but also a change in travel practices:
H08: ‘‘Recently the British government announced that diesel cars are rather dangerous, and because I’ve got one, that makes
me a bit uncomfortable.
H03: ‘‘I’m challenged quite often because I do have an interest in sustainability, but I also like to drive.
B10: ‘‘Whenever I go to university, I would call a colleague of mine and tell her in advance that I’m going, say, tomorrow and ask
whether she would like to join. She doesn’t pay me for it, by the way, but I feel good doing it.
H05: ‘‘Cars are noisy, and pollutants are smelly. It’s not ideal. I try to cycle in cities, or walk, or use public transport.
Therefore, concerns around diverse sustainability implications were likely to have a positive influence on the uptake of
MaaS as users saw it as a tool that would help them travel in a more sustainable manner:
L05: ‘‘It would be interesting to actually put something there [in MaaS] that would tell you about the carbon footprint of each
travel mode. I think that would be a bit of an eye-opener for some people and maybe influence their decision.
H03: ‘‘Going back to the sustainability thing, using MaaS would make me feel like I was contributing more to maintaining
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B09: ‘‘If there was a proper service like this [MaaS], which could locate other users at the same area where I am and match the
destinations, I would rather do that for all the environmental and social reasons.
4.3. Trust
Trust in this analysis developed as a factor explaining how perceptions of MaaS’ functionality influence its acceptance and
viability as a travel mechanism. While on a theoretical level MaaS generated a great deal of enthusiasm among study par-
ticipants, many of them did not trust that the concept could actually work as advertised:
L13: ‘‘It’s the release of a new service, and then how much trust would you have in it to deliver? If it had any sort of issues, then
you’d be left to your old ways of doing things.
B01: ‘‘If I could just get to work in the morning by, say, Uber, after work take a bus to the train station, get down to London by
train and then travel around there, and it all would be for that one fixed monthly price, it would be great, but I find it hard to
believe. I don’t believe it’s possible.
To make sure that the ‘‘impossible” is achieved and MaaS delivers on its promise some participants demonstrated the
need for trialling the tool:
B04: ‘‘I can actually use this service to test the accuracy in the city I live, with travel routes that I’m confident of, and if I see it is
very accurate, then I could travel from Birmingham to, say, Leeds, and I’d want to use MaaS.
Many interviewees doubted the efficiency of MaaS. Some participants, certain of their transport knowledge and planning
capabilities, demonstrated a strong sense of self-efficacy and, thus, did not believe that MaaS could do better than them:
L04: ‘‘I can probably work out all my alternative routes quicker in my head than this app can.
L12: ‘‘The only thing I find with using apps is when you’ve got an idea of a system, and you go on the app, and you go ‘‘how am I
getting from A to B?and the app tells you to go there, and you go there. And I think, well, actually, if I go that way it’s better
because it’s cheaper, but because it’s a minute longer than the other way, the app will tend to give you the quickest time, and it’s
not necessarily as flexible and giving you as many options.
The above partially occurred as participants doubted MaaS information would be always accurate:
L09: ‘‘I think with the on-route issues often the information that comes through is poor, and that’s exactly the reason why, if
something happens, no one quite knows what’s gone wrong and why. And then you almost end up making that decision
Participants expressed capacity concerns suggesting that MaaS may offer limited alternatives, or reduced capacity in
H08: ‘‘If we imagine that everyone uses MaaS, we then need more public transport in terms of numbers; we need more taxis,
buses, because everyone would use it. I’m thinking about peak times. If you want to book a taxi around school time in the morn-
ing, you won’t be able to do it because it’s so busy. If many people abandoned their cars, such things could become more
H11: ‘‘On the bus or on the train, you’d have to worry if you’d get a seat or not, if it’s a long journey.
It was acknowledged by participants that trusting the technology could become yet another challenge when travelling
with MaaS. Participants thought of MaaS as an app-based tool, which induced concerns about simple practicalities like
mobile phone battery life, network coverage, and inclusion of all modes under the MaaS umbrella:
H05: ‘‘If your phone is not charged, you can’t get access to it [MaaS], and then you’re lost. You can’t just rely on it.
H02: ‘‘The only thing is Wi-Fi, the internet connection.
B12: ‘‘You expect everything to be seamless, but then you turn up on a bus and they say they don’t accept MaaS.
Some also demonstrated their concerns about possible cybersecurity threats that could affect MaaS systems:
L06: ‘‘It’s asking for payment through the app, and I would want some kind of reassurance that this is fine.
L07: ‘‘If something goes wrong with it, if payments are charged when they shouldn’t be or if there is overpayment or anything
like that, people might not want to rely on it.
H07: ‘‘It could endanger lives one way or another if the hackers, terrorists break into this system [MaaS].
The trust in MaaS and its capabilities were also largely influenced by the individual state of digital readiness, which
appeared to be shaped by one’s age and innovativeness:
H12: ‘‘I suppose people who are a little bit older would probably struggle with the concept of using a mobile phone app to access
different transport modes.
B05: ‘‘I don’t think my brother has ever even used Uber. He calls taxis because he is not very good with phones.
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4.4. Human element externalities
The participants worried that MaaS would be operating in a framework defined by negative aspects of human behaviour
that can be traced in the user and provider levels including negligence, discourtesy and disobedience. These issues come
under the umbrella term Human Element Externalities. This is a theme that highlights some of the grey areas for the tran-
sition to a MaaS-based transport paradigm that relate to social environment barriers.
B01: ‘‘The problem is not with the transport itself. The problem is with people.‘‘
Participants worried about receiving honest, safe and reliable service due to having already experienced the negligence of
those who cater for them, which is not guaranteed to be battled through MaaS:
L13: ‘‘Will those offering driving services be malicious and want to go via routes that take longer and cost you more purposely to
get more money?
B07: ‘‘The reason I would still use a car over this would be independence. With MaaS you’re still reliant on people, you’re still
reliant on someone for a taxi, a bus, a train, and anything can happen.
L04: ‘‘They [drivers] don’t really care. They, most of the time, just fly about, and not safely, to get you there as quickly as possible.
I think they can cancel on you quite easily, there is no repercussions. You’re completely in their hands. I’ve been in some pretty
scary journeys in different parts of the world, where I wasn’t sure if I was going to live or die because drivers were mental.
Participants also discussed the negative impact discourtesy of other transport users has on their transport related expe-
riences. A few talked about fellow travellers being inconsiderate of others’ personal space, privacy and the need for peace and
H01: ‘‘And then, there are other people on the bus: some are considerate and think about the fact that they are not alone, and
then others can listen to loud music or talk as if they were on their own on that bus, and everyone has to listen to their plans or
whatever they did.
H04: ‘‘If the train was nice and quiet, it would be great. But you know, if it’s really busy, you can’t get a seat, and that’s a pain,
and then obviously if it’s full of noisy people you can’t concentrate on reading.‘‘
People abusing the rules and the infrastructure put in place for everyone’s good, thus demonstrating abuse and disobe-
dience, could also become an issue even in the MaaS era:
B07: ‘‘For me buses are just not well looked after, you’ve got a lot of abusive people on there, you’ve got some people smoking in
the back though smoking is clearly not allowed. There are also regular attacks on the bus against women.
B05: ‘‘Public transport is usually full of young people coming from parties, and they like to swear and smash stuff.
B12: ‘‘It’s all about the way people behave. People should understand rules, otherwise they will make things inefficient.‘‘
B02: ‘‘A lot of people cannot even drive their own cars, so they are not going to drive nicely somebody else’s car that’s not their
Consequently, many anticipated that travelling by non-private transport could impose danger to their health and well-
being, and even life, which makes them reluctant to sharing the travel with others:
H11: ‘‘At the train station, you get all these drugged, drunk people late at night, and if you’re arriving late and waiting for your
taxi there, then you’re susceptible to harm. Not that you would definitely get harmed, but it puts that fear in your head, that it’s
really dark, the train station staff are not there, and you might have your possessions with you, like laptops, so you might feel
more susceptible to harm.
L10: ‘‘I’m not very good with the sole security element, with not knowing who I’m with. I don’t know how I feel about sharing.
B05: ‘‘The area of my work is not nice, and you wouldn’t want to be on a bus there, unfortunately, unless you’ve got a stab-proof
vest on.
4.5. Value
This theme discusses what users would Value when shifting to a MaaS-dictated travel paradigm; the things that make a
difference and the benefits those could bring to the logistics of their trips.
Whilst being challenging for a few, the appification of travel planning with MaaS was what excited many participants and
was even referred to as a major selling point as it was something they were already accustomed to:
L08: ‘‘MaaS being an app is one of its major selling points I would have thought.
H02: ‘‘It’s easy enough. Anyone these days has a phone that can support it. I already have a few apps on my phone.
The integration of a variety of transport options with information, booking and payment services in MaaS was perceived
as another value-adding opportunity, making travel easier and more accessible even to those who are older and not techno-
logically enthused:
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B03: ‘‘It makes things much more convenient because you are able to get everything in one particular point. You are able to get
information, you are able to get payments, and you are able to get tickets for the different services that you might be using.
L12: ‘‘Trying to find out the local bus operator, you might need to find their app, or use Google, so that takes time. If there was an
app that gave you the opportunity to easily search for any location, without having to resort to different operators and stuff, that
would be of interest to use. [...] Someone who’s older or not so strong with IT, might struggle with MaaS. But then they would
also struggle to find a local bus operator in a different town.‘‘
The integration feature tempted participants to consider a change in their travel routine, thus showing potential to break
H05: ‘‘It might encourage people, if it’s aimed that way, to walk or cycle more, if it could take them through routes which are
more walking- and cycling- friendly.
L02: ‘‘If you go shopping on a Saturday, instead of parking the car, if you book a taxi normally you would wait for it 10–15 min,
do your shopping, book another taxi, wait another 10–15 min, whereas using this, you could walk a bit to the bus, get a bus, do
the shopping, and then get a taxi because you have stuff to carry potentially. Or by the sounds of it, you could actually have it
saying ‘‘well, you can get a bus now instead of a taxi. So, I think it might make a more engaged experience, the fact that you can
go ‘‘let’s try that or that or that.
B05: ‘‘If I had MaaS and I could find a ride share that goes to my work, I would never drive. I could completely stop driving and
find an easy way to get there cheaper and simpler.
Much thought was given to the analytics behind MaaS systems. Participants speculated that the data MaaS gathers from
its users could be employed, one way or another, in improving travel experience. A few spoke about the ability of MaaS to
manage capacity:
L05: ‘‘I think, in terms of trains, they could do some research and actually let you know on what train you are likely to get a seat,
or at what time it is going to be less busy. That would probably be quite beneficial because that could influence your decision
positively if you knew the train that has actually got seats.
L14: ‘‘It could be useful if this system had all this data about all the individual journeys taking place at the same time, so they
could all be interrelated to each other depending on where everybody is going and where from. Say, there could be a hundred
people trying to get from A to B. It could then start making decisions for everyone, so that not everyone goes from A to B the
same way as that would cause problems. So, by understanding what journeys people are trying to make, this system could elim-
inate bottlenecks potentially.
Participants also speculated that MaaS could, at least to some extent, eliminate the risks associated with service and other
users by allowing to create accounts and give feedback:
B09: ‘‘It’s the safety the application provides. All the accounts are connected to the user, so there is transparency. If something
happens, you are able to identify and locate the person who was responsible for the issue occurred.
B04: ‘‘Another positive is that you can use feedback systems to rate your experience with every driver: it is an incentive for the
drivers to be well-behaved because they know that the negative feedback will affect their own service.
H10: ‘‘I think they should cover everything, not just the car, but also the people you share that car with. You may feel a bit safer
that way.
Ultimately, by rationally processing user data, MaaS could become a socially inclusive transport tool and create a more
enjoyable travel experience:
L04: ‘‘MaaS might make transportation become more social, which at the moment is not. So, you end up on trains where every-
one is very passive aggressive, or just aggressive, people don’t really talk to each other. You might end up with more people who
travel together and enjoy their journey a little bit more.
It was for the purpose of leisure and tourism MaaS was found most useful as it would allow to easily get around unfa-
miliar places and do long-distance trips:
L06: ‘‘This sort of app would be really helpful for me, going to places and destinations I’m not really familiar with.
H02: ‘‘For a long-distance trip, though, I would use it, and that would be interesting.
H05: ‘‘If it had points of interest or something like that, the things you could do when you get off that transport. It’s like when
you go into a new city, it could offer you bus tours and include that. Rather than just having transport offering across the city,
you can go here and then see something.
All of the above, however would mean nothing, as stated by participants, if the level of service provision, for public trans-
port in particular, remains as it is at present:
H13: ‘‘I get where other people come from, like they live in the middle of the town and they could get the bus quite easily, but I
come from quite a rural area, so I am dependant on that car.
B07: ‘‘If I’d like to get in the centre of Birmingham, I would usually go on a train, not drive, whereas if I was going to the Isle of
Skye in Scotland, I’d drive instead of getting a train if you know what I mean.
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B09: ‘‘At times I would so much rather use the car if I had one, but this thought is highly connected to the quality of public trans-
port service.
Thus, the true value of MaaS is in providing users with a robust transportation network that encourages public transport
and meets their everyday needs:
H14: ‘‘On a Sunday there is a bus only every 30 min, so of course I usually use my car. If MaaS offered me the flexibility of the
public transport and a better frequency, then I might use that instead. If on a Sunday it is still difficult to do that, then MaaS
makes no sense. I would want that to be 24/7 the same. Public transport is not the same 24/7. That guarantee that I would have
the opportunity to use public transport whenever I want, that would be something.‘‘
L09: ‘‘Encourage public transport networks that work with each other, that serve what people actually want, that run late in the
night, that run at weekends, a bus that departs 5 min after a train arrives. You can’t do this anymore in this country. We have
lost that ability of actually getting everything to interwork with each other but that would actually make a big difference in
choices people make.‘‘
4.6. Cost
The Cost of MaaS was projected to be perhaps the most critical factor for its uptake. Although there was a specific cost
related question within the interview guide, cost as an influencing factor appeared in the responses long before the question
was asked. So, the following were some of the responses to the question on whether the participants were willing to use
MaaS at the start of the interview:
H01: ‘‘My decision would probably depend on price.
L11: ‘‘It depends on the cost.
H14: ‘‘If MaaS was more expensive than what I am doing, I don’t think I would even try it.
The ways participants expressed their views on what the cost of MaaS should be took many different directions. One of
the ways to express the acceptable cost of MaaS was to do benchmarking against status quo. Some participants wanted to
see the cost of their travel reduced:
H13: ‘‘I would use it if it worked out cheaper than going individually, like if I took a taxi to Huddersfield centre, it would be one
price, but if it was a taxi and a bus ride it would be cheaper. Then I’d be more inclined to use it.
L01: ‘‘I am topping up my Oyster card £30 a week and that’s to cover all my transport. So, I would want to see that reduced.
Though it was noted that fixed costs of car ownership and use were often neglected when choosing to drive, car users
specifically noted that travelling with MaaS should work out cheaper than using their own car:
H03: ‘‘If MaaS didn’t make my trip more cost-effective, then I would question why I am using it really. So, I would expect it to be
less expensive than using my own car. But then, if you were to weigh up all the fixed costs of having your own car, then I think it
will be cheaper because you don’t have to pay for all the outlay of the car, the insurance, and everything that goes with it.
L03: ‘‘MaaS would need to work out cheaper than the car.
H12: ‘‘It is like £25 for me to get home on a train. If it was the same with MaaS, I would probably just get in my car.
Some participants appreciated the fact that MaaS was providing them not only with transportation, but also the bundling,
payment and guidance services, for which they were ready to pay:
L10: ‘‘I think I’d be willing to pay a little bit extra to get the full service.
B06: ‘‘I think people would pay that little bit more because it does more, and I’d be ready to pay a little bit more.
Many discussed the importance of time against the cost and would like to see that factored in:
L08: ‘‘Comparing the costs would certainly be interesting as well as comparing the journey times.
L11: ‘‘Say, I’m going from A to B, and it normally takes me an hour. I can go with MaaS if it takes me an hour and 10 min. I
wouldn’t mind the 10 min as long as it’s cheaper.
B02: ‘‘If a trip was going to cost me less and take roughly the same amount of time, I would use MaaS.
While some study participants were ready to pay for the digital services MaaS provided, others considered it unjust and
developed a ‘‘Why to pay? Can do myself”’ attitude:
B04: ‘‘If I see that in the end this works out, say, £10 more expensive than just using Google maps and doing it yourself, like
dealing with Virgin trains and so on, me and other people will just go for a cheaper option, because the more travel is done
by a more cost-effective option, the more you would end up saving as well.
H04: ‘‘If that was a journey that I could easily do myself and that journey was going to be a lot more expensive through MaaS,
then I perhaps would be inclined to just do it myself.‘‘
A number of proposals to provide MaaS users with financial incentives,reliefs and motives within the pricing structure in
order to influence their travel behaviour occurred. Some spoke about incentivising users through the app:
374 E. Alyavina et al. / Transportation Research Part F 73 (2020) 362–381
L05: ‘‘If you were to pick one way, and you had a train, for example, would you get a discount for using the train through the app
because you are choosing to do that over taking your own car? I think that would influence people.
B05: ‘‘You could give people bonuses, something like reward points every now and then: a free trip after 10 trips done with
MaaS, or a free mile after every 100 miles travelled. Give people an incentive to use it. Bribe them. Freebies usually work.
L08: ‘‘If you wanted this to take off in any sort of big numbers, then you have to be very careful of what you offer because a lot of
people only want things that are free.
The government interference, with both ‘‘push” and ‘‘pull” pricing measures, was also considered a mechanism to influ-
ence participants’ decision to use MaaS:
L02: ‘‘The government should offer credits, where you get your money back, or you’re not taxed as much because you don’t have
a personal car. If you pay £100 for your car emissions, then you’re not paying it, but maybe you should get a flipside where they
say ok, because you use MaaS you get some return as an incentive.‘‘
H09: ‘‘If they would make travelling by my own car, like through taxes, extremely, unbearably expensive, then I would be forced
to use public transport, but I wouldn’t like to see that. But it can be an option the government could look at, increasing the cost of
owning a car, and that could push people to use MaaS.
5. Discussion
Our study identifies and analyses the five key themes that underpin MaaS and its potential to inspire (or not) travel beha-
vioural change. Car dependence, Trust, Human Element Externalities, Value and Cost, each with a number of distinctive
dimensions expressed as their sub-themes, shown on Fig. 3, in cases interlinked and difficult to isolate per se, underpin peo-
ple’s acceptance and potential uptake of MaaS.
Fig. 3. Factors affecting acceptance and uptake of MaaS as a sustainable travel mechanism.
E. Alyavina et al. / Transportation Research Part F 73 (2020) 362–381 375
While the idea of MaaS received generally positive commentary, with participants willing to see the system in action,
many still looked at MaaS through the lens of Car Dependence. So, the potential modal shift was not radical: the majority
of participants were inclined to still depend on car by giving preference to modes like car-sharing, ride-sharing and ride-
hailing and/or using their own car as well as using MaaS. All in all, at this point in time MaaS is viewed as a complement
to personal car rather than a substitute for it, which is in line with Storme et al. (2020). Much like Fioreze et al. (2019)
and Ho et al. (2020) suggested, our study revealed that potential users remain dependant on cars due to perceiving MaaS
as unable to beat private car convenience. It has been long recognised, however, that car is more than just a convenient mode
of transport (Steg, 2005). The findings of our study suggest that cars to this day are viewed as the most enjoyable transport
mode; owning and using the car stimulates self-esteem, serves as a means of representing self and provides a sense of free-
dom, independence and joy on top of removing the complexities and uncertainties of relying on others and on a digital-based
system to travel. These are sensations that MaaS cannot replicate. Sustainability attitudes have been found to have an influ-
ence on driving habits and modal choice (Bamberg & Schmidt, 2003; Gardner, 2009) and the decision to use multimodal tra-
vel applications (Dastjerdi, Kaplan, Silva, Nielsen, & Pereira, 2019a, 2019b). Similarly, our study suggests that people with
limited moral considerations or, in other words, people with the mindset that their unsustainable driving habits are ‘‘a drop
in the ocean” appear the least likely to travel with MaaS sustainably, if at all. Those who voiced concerns about the environ-
ment were more likely to look for ways to reduce their dependence on cars and see MaaS as a means for identifying more
sustainable travel options, at least for some of their trips, and as a way of contributing to maintaining sustainability.
The affection for privately owned cars and personal driving was not however the only reason study participants did not
show much enthusiasm about extensively relying on MaaS. There were a number of Trust issues underpinning incidents of
MaaS disapproval. According to Rogers (2005) Diffusion of Innovations Theory, an individual often expresses the need to trial
an innovation before its full adoption in order to give meaning to an innovation, to eliminate uncertainty and to find out how
it functions in real terms. Similarly, our study participants demonstrated the desire of trialling MaaS to test its efficiency in
providing timely and reliable information, reasonable itineraries, and alternative routes in cases of disruption. MaaS could
only be as good as the transportation network behind it, thus participants demonstrated their concerns with the potential
MaaS capacity; when today at peak hours, the demand for public transport and shared use mobility can severely outweigh
the system’s capacity, what would happen on the much larger scale of a MaaS paradigm, when most users will abandon their
cars? The latter is closely related to the notion of crowding (Li & Hensher, 2013), associated with a high density of passengers
on vehicles, access ways and stations, which has a significant influence on modal choice (Tirachini, Hensher, & Rose, 2013;
Vedel, Bredahl Jacobsen, & Skov-Petersen, 2017; Wardman & Whelan, 2011). When travelling with MaaS, users would have
to rely on technology and often worry whether the battery of their mobile device is sufficiently charged, whether they would
have appropriate mobile network coverage where they are travelling, or whether the device would be accepted as a means of
access to the many transport modes MaaS promises to integrate, an issue previously highlighted by Giesecke, Surakka, and
Hakonen (2016). This means that any MaaS system should also work offline and offer back-up access options if it is to be
embraced as also suggested by Polydoropoulou et al. (2018). Moreover, the mobile app form of MaaS could be a major barrier
to its uptake as not every potential MaaS user at present is at the desired level of digital readiness (Polydoropoulou et al.,
2018), and older people specifically, as noted by Pangbourne, Mladenovic
´, Stead, and Milakis (2020), seem to be left out.
While individual data privacy and protection, and safety around monetary transactions within MaaS have been considered
in recent research (Cottrill, 2020), little attention has been paid to the possible cybersecurity vulnerabilities of MaaS and
their mitigation, although cybersecurity and resilience planning have been signposted as areas of priority for years now
for the broader context of public transport (Beecroft & Pangbourne, 2015a). The frequency of fraud and cyberattacks, often
severe, in contemporary times caused our participants to fear relying on not just MaaS but any digital system. In the MaaS
era cyber-attacks may impose a great amount of risk as they could spread over, and endanger, an entire MaaS coverage area
in a very short time.
Reliability, safety on board, and privacy, associated with vehicle occupancy, are the known attributes influencing user
perceptions of and satisfaction with transport service quality (Beirão & Sarsfield Cabral, 2007; Garvill, Marell, & Nordlund,
2003; Prioni & Hensher, 2000; Spears, Houston, & Boarnet, 2013) and affecting travel behaviour and modal choice (De
Vos & Witlox, 2017). In our study, similar attributes developed for the context of MaaS and, as they appeared to be largely
of human nature, were defined as the Human Element Externalities. Social environments, perceived by some participants
as psychologically and physically hazardous, negatively affected the potential acceptance and uptake of MaaS. Study partic-
ipants reflected on their previous experiences and, realising the service in MaaS was still dependant on the responsibility of
its providers, were troubled by the possibility of transport provider staff deceiving them, getting them to their destination
with little consideration for their health and safety, and simply not providing the service at the required time, thus demon-
strating negligence in relation to users. The discourtesy of fellow travellers was yet another worry: inappropriateness of
some conversations, profanity of the language, and the inability of other transport users to keep noise to a minimum was
what made the experiences of sharing transport even with MaaS a non-ideal scenario for some people. Another barrier iden-
tified was the possible disobedience of safety rules, the misuse of dedicated transportation infrastructure for irrelevant pur-
poses, and the abuse on shared means of transport. Thus, some participants anticipated danger and expected harm when
sharing with others, and, ultimately, generated negative perceptions of travelling with MaaS. The above is in line with
Gardner and Abraham (2007), who argued that the provision of personal space and security pose real challenges to car
reduction schemes, and Beecroft and Pangbourne (2015b) who concluded that personal security considerations tacitly influ-
376 E. Alyavina et al. / Transportation Research Part F 73 (2020) 362–381
ence passenger choice. For the MaaS context this agenda is barely touched, with a few exceptions perhaps (e.g. Jittrapirom,
Marchau, van der Heijden, & Meurs, 2018).
While Fioreze et al. (2019) uncovered that the low potential uptake of MaaS was the result of survey participants not
recognising the added value of the service, our study offers an insight on what users consider things of Value when travelling
with MaaS. Although digital illiteracy of some potential users could complicate the realisation of MaaS as a web- or app-
based product, the appification was still regarded as a valuable feature as it was something the majority of participants
already had experience with, which goes along with the findings of Schikofsky et al. (2020). The travel choice making qual-
ities and integration capacity of MaaS were also highlighted by some of our participants, which is in line with the results of
Polydoropoulou et al. (2018). With MaaS, individuals will not have to deal with a variety of apps and webpages but do every-
thing from a single app. Furthermore, the all-in-one service could help breaking existing travel habits by offering the user
more sustainable travel modes. MaaS was found to be a valuable tool for organising short- and long-distance trips with the
purpose of leisure and tourism, confirming the hypothesis of Ho et al. (2020) that tourists may represent the largest market
group for MaaS and be its first adopters. Our study suggests that a MaaS feature for creating accounts and giving feedback
about drivers delivering the service and fellow travellers, could make sharing, at least car-based (Casprini, Di Minin, &
Paraboschi, 2019), more transparent and easier to get used to. The sensation of knowing that everyone is registered and
can be easily identified in case a situation occurs might make sharing public and shared means of transport more pleasant
and trustworthy. Our study participants also recognised that MaaS, having access to individual trip and user data, could use
analytics to help eliminating traffic bottlenecks. This supports the findings of Milne and Watling (2019). Yet, the transporta-
tion network itself, as it is as present, is far from being able to seamlessly serve user needs and offers no resilience when
dealing with disruption. Significant improvements in the level of service provision, however, are of paramount value to users
and tend to induce a positive change in travel behaviour (Redman, Friman, Gärling, & Hartig, 2013).
Our participants considerations about MaaS’ Cost made it clear that travel by alternatives is still considered inferior to car
use. Although valuing some of the features MaaS may potentially offer, only a few, as also recognised by Ho et al. (2020),
wished to pay extra for the MaaS service. Many demonstrated a ‘‘Why to pay? Can do myself”’ attitude and took a stance
where they would rather plan the trips themselves than pay MaaS for creating an integrated offer as there were already free
of charge apps and services in place that they could easily use instead. Some participants were ready to accept a slight
increase in travel time provided the cost of travel with MaaS was lower than what they paid previously, in a way bench-
marking against status quo. Others wished to be incentivised to use MaaS by getting, through the MaaS platform, motives
such as bonus points and discounts for every trip. The latter reward instruments could be successful in promoting sustain-
able multimodal options (Dastjerdi et al., 2019b; Tsirimpa, Polydoropoulou, Pagoni, & Tsouros, 2019) and thereby facilitating
a positive change in individual travel behaviour (Poslad, Ma, Wang, & Mei, 2015). Some car users mentioned, rather reluc-
tantly, that the only way out of driving for them would be the policy makers putting in place environmental laws and exces-
sive charges for personal car use and ownership. Indeed, road pricing schemes, although often challenged by public
resistance, grant more significant reduction in emissions as opposed to, for example, shared use mobility schemes
(Cavallaro, Giaretta, & Nocera, 2018), which could be a consequence of reduced car use. Car users were more open to ‘‘pull”
measures such as being offered tax reliefs for switching from their car to more sustainable alternatives. Such policy, also
referred to as tax break or tax exemption, has been successfully utilised to promote the use of electric and more fuel-
efficient cars (Bjerkan, Nørbech, & Nordtømme, 2016; Orlov & Kallbekken, 2019) and appears to also have potential to reduce
overall car use (Gardner & Abraham, 2007).
6. Limitations and future work
The present work responds to a significant literature gap and helps addressing the lack of qualitative research studies in
the topic of MaaS and travel behaviour. We need to acknowledge that the qualitative nature of our study might not have the
same potential to offer generalisable results for broader contexts, than the UK cases we studied herein, when compared with
quantitative studies that perform statistical analysis in big datasets. We also recognise that although Birmingham is the
home of the first English MaaS pilot and London is a city with one of Europe’s biggest and most versatile and integrated pub-
lic transport networks our study was not about capturing real-life experience from MaaS use since very few of our intervie-
wees had ever heard before about MaaS; however capturing attitudes and intentional travel behaviour is of crucial
importance too. Studies experimenting with actual MaaS-related travel behaviour although advantageous are very rare
because MaaS is in an embryonic stage of its development; furthermore, the systems tested might not even be full scale
MaaS systems but MaaS-lite. The next phase of our research will be based on an online quantitative survey and the statistical
analysis of its results. This follow-up study will aim to triangulate, complement and extend our present findings.
7. Conclusions and recommendations
MaaS as a whole seems to be portrayed as an attractive mechanism, yet it does not guarantee the desired behavioural
change, to the extent, where transport-caused sustainability challenges could be overcome. Car remains the convenient
but also enjoyable option for transport users, who at present also have little consideration for sustainability and, if not
forced, are bound to stick to their existing driving habits. Acceptance and intended usage of public transport services, even
E. Alyavina et al. / Transportation Research Part F 73 (2020) 362–381 377
enhanced by shared use mobility modes, is falling well behind the private automobile, meaning that a major reform of these
services and their overall design should happen coupled with travel demand measures designed to push people out of their
cars. Therefore, all MaaS can offer to the potential user at present is the comfort and ease of ‘‘appified” access which may
reduce the cognitive load for preparing and undertaking a journey, in line with Lyons et al. (2020). The ease of access, though,
is not something transport users are willing to pay for as it only allows them to easily access services that do not work up to
the required standards and, consequently, do not meet their needs.
Moreover, transport users do not trust that MaaS could make the access truly easy and see many issues that could hinder
the provision of transport services via a digital interface. It is also due to the contemporary social environment that the MaaS
paradigm may not develop sustainably: both transport staff and users, according to some of our participants, show little
respect to rules, transport infrastructure, and even each other, which could make the use of shared transport means ineffi-
cient, unpleasant and at times dangerous. It appears that the society, although perceiving MaaS positively, is not yet ready to
change their existing travel practices (Ho et al., 2020; Karlsson et al., 2020). Hence, policy makers and transport providers
need to think very carefully of what they offer through a MaaS platform.
The value of MaaS is not in beating the convenience of the private car, which is rather unrealistic, but in creating a mul-
timodal travel option that offers the opportunity to people to be part of an initiative designed to create more liveable, socially
inclusive and sustainable futures. Thus, transport users should be incentivised to travel responsibly with MaaS through
bonuses and tax reliefs, and be persuaded to think ‘big’ and ‘out of the box’, possibly via dedicated awareness, information
provision and social engagement exercises designed to make the concept more familiar to them and highlight its importance
in sustainability terms if used responsibly. Transport providers and policy-makers need to test out and work on improving
MaaS through the use of pilots, trials and living labs; this will give a window of opportunity to users to familiarise with
change and abort negative (usually unsustained) perceptions about risks that a real-life scheme application would make
apparent that they should not exist. Their next and more important step however should be to make public transport the
backbone of any MaaS system by putting major efforts into encouraging integrated, demand-responsive, timely and inexpen-
sive public transit networks where many modes, enhanced with well-timed, reliable and honest information provision, work
together to satisfy the very diverse user needs. Car- and ride-sharing should be less accessible in contrast (via monetary dis-
incentives within the MaaS pricing framework or car-free and parking-free zones) and perhaps provided primarily for emer-
gencies and as neighbourhood feeders to mass-transit systems. But this marginalisation of car solutions embedded in this
sustainability-enhancing approach might go against the usual MaaS rhetoric of ‘‘individual unfettered freedom” (as covered
by Pangbourne et al., 2020). So, the society of the future, and the research community, should be facing a dilemma: ‘‘do we
want a genuinely sustainable MaaS?” or ‘‘one that is more easily accepted but might be uberised?”
CRediT authorship contribution statement
Elena Alyavina: Conceptualization, Methodology, Data curation, Formal analysis, Writing - original draft, Writing -
review & editing. Alexandros Nikitas: Conceptualization, Methodology, Formal analysis, Writing - original draft, Writing -
review & editing. Eric Tchouamou Njoya: Formal analysis, Writing - review & editing.
Appendix A. Interview guide
(1) What is your date of birth?
(2) What is your marital status? Are you single/in domestic partnership/married/divorced/etc.? How many children are in
your household?
(3) What is the highest degree or level of school you have completed? If currently enrolled, highest degree received. What
is your current status of employment (employed/self-employed/unemployed/student/ retired/etc.)? What is your job
(4) What is your personal/household income?
(5) Do you have a driving license?
(6) Do you have your personal car (household car)?
(7) How often do you use your own car (either as a driver or as a passenger?)
(8) Every time you make a decision to travel by car, do you compare it to other available options?
(9) What is usually the purpose of the trips that you use your own car for?
(10) Would it be difficult for you not to use your car for those trips?
(11) What benefits of travelling by car do you consider when making your travel decisions?
(12) Are there any drawbacks of the use of your own car which you consider when making your travel decisions?
378 E. Alyavina et al. / Transportation Research Part F 73 (2020) 362–381
(13) Many people think that cars and their excessive use generate problems for society, the environment and even the
economy. What do you think about that?
(14) Do you feel responsible for the above? What actions are you taking to change that?
(15) How often do you use public transport as a travel mode?
(16) What is the purpose of the trips you use public transport for?
(17) What do you consider beneficial about travelling by public transport when making your travel decisions?
(18) Are there any public transport drawbacks you consider when making your travel decisions?
(19) How often do you use Taxi or Uber as a travel mode? Why do/don’t you use it?
(20) What is the purpose of the trips you use Taxi or Uber for?
(21) Do you usually use those transport modes as substitute for or in combination with other transport options?
(22) What are the benefits of taxi travel, in your opinion? What are the drawbacks?
(23) How do you feel about the smartphone app experience that services like Uber offer? How easy/how difficult do you
find to use those?
(24) What is your opinion on the use of active transportation, such as walking and cycling?
(25) What do you think of sharing a ride with a friend/a stranger?
(26) What is your opinion on car-sharing schemes? Do you see any benefits/drawbacks in using those?
(27) What circumstances make it easy for you to travel the way you do at present?
(28) What circumstances make it difficult for you to travel the way you do at present?
(29) Are there any particular individuals or groups of people who influence your decisions regarding transport and travel-
ling? In what way?
Infographic exercise: go through definitions of MaaS, highlight its features and their functions, and describe the experi-
ence it offers to its users in detail.
(30) Would you be willing to use MaaS for your everyday travel? Why? Why not?
(31) What are the opportunities of using MaaS for travel? What are the barriers to using MaaS, in your opinion?
(32) What do you think about the technological aspects of MaaS, to wit the provision of travel related services and infor-
mation through a single smartphone application? What are the benefits to you? What are the barriers?
(33) To what extent your decision to use MaaS would depend on the cost of the service?
(34) Could MaaS change the way you travel right now?
(35) If people most important to you were in favour of using MaaS, would you be in favour of using MaaS yourself? What
about the influences of general public?
(36) Having MaaS, would you be willing to give up your personal car? Why do you feel so?
(37) Is there anything transport providers and policy makers could add to MaaS that would help you switch from your car
to other transport modes and help you depend on car less?
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... The study finds that there are three emerging MaaS scenarios including market-driven, public-controlled, and public-private with two critical roles such as MaaS integrators and MaaS operators that public and private can play in MaaS development. Alyavina et al. (2020) investigate the factors underpinning the uptake and potential success of MaaS as a sustainable travel mechanism. The study reveals that the success of MaaS as a sustainable travel mode depends on changing the attitude of users to car ownership and using public transport as a backbone of MaaS models. ...
... These costs vary depending on the mode of transactions since transactions between suppliers and customers, business-to-business or within a firm entail different costs. In this study, it is hypothesized that an individual choosing to use MaaS will incur two transaction costs: (a) resources (effort, time and cost) that might be involved in searching, choosing and using MaaS; and (b) resources (effort, time and cost) that might be involved in redressing the problem that might be encountered using MaaS (Alyavina et al., 2020). In addition to the transaction cost, this study also examines the influence of the comparative cost of getting the same mobility service from a private car (Wang et al., 2012;Yoo et al., 2020). ...
... To facilitate transactions, digital platforms require the appropriate architecture, design, governance, and regulations to maximise public trust (Tomaino et al., 2020) and minimise friction in the delivery of products and services (Ruggieri et al., 2018, Hirschhorn et al., 2019. In the area of MaaS, studies have indicated that consumers' safety, trust, and service administration concerns can either facilitate or inhibit the acceptance and success of MaaS (Alyavina et al., 2020;Matyas, 2020). These concerns can be closely related to the public or private or public-private partnership approaches for developing MaaS (Smith et al., 2018) and highlight the importance of MaaS platform ownership and governance (Smith et al., 2018;Brunswickera and Schecterb, 2019). ...
Mobility as a Service (MaaS) has gained popularity as a means of sustainable urban transport which makes the understanding of MaaS use critical for its design and promotion. Studies have contributed to the growing understanding of MaaS, its design features, and consumers’ willingness to pay for MaaS in general, without recourse to the differences in traveling for work, social and general purposes. This paper develops and tests models to predict MaaS use by applying artificial neural network analysis, following the cross industry standard process and data mining framework. It also estimates separate models for social, general, and work trips, using 33 input variables reflecting network externality, transaction cost, behaviour, institutional, environmental concern, personal travel, and socio-economic factors. Data are collected from a survey of 331 Australians. The study reveals different sets of socio-economic factors, the impact of Covid-19, and personal travel factors as key predictors of MaaS use for general, social, and work trips with an average prediction accuracy of 68%, 68%, and 75% respectively. The findings can be used to inform strategies and policies on how to attract a user base with respect to socio-economic and personal travel factors for promoting MaaS use.
... Hirschhorn et al. (2019) qualitatively investigate possible governance approaches for PT drawing on three use cases. Using semi-structured interviews in three cities, Alyavina et al. (2020) find car dependence, value, and cost as crucial factors affecting MaaS usage. Empirically, more integrated modes, thus increased flexibility, are found to be more attractive for customers (Guidon et al., 2020;Kamargianni et al., 2016;Strömberg et al., 2018;Sochor et al., 2015;Karlsson et al., 2016), especially when taking account of mode-chains (Song et al., 2021) and seamlessness for PT (Lee et al., 2022;Hensher and Xi, 2022;Matyas and Kamargianni, 2019b). ...
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Mobility-as-a-Service (MaaS) bundle design has recently gained increasing attention. Previous work has identified socio-demographics and current travel behaviour as drivers towards adopting MaaS bundles. Yet, the focus has been on (scientific) trials in one specific area or on one specific service. We extend this work by analysing the influence of transport supply and mobility behaviour on preferences for MaaS bundles in multiple cities. To this end, we conduct a stated preference experiment in 83 cities in Germany. Respondents choose between two MaaS bundle options and one pay-as-you-go option. Besides public transport, we include shared e-scooters and bikes or carsharing and ridepooling in the bundles. To integrate city characteristics we merge this data with supply data from the shared services and data about public transport quality in the respective cities. We find previous shared mobility usage to positively and car usage to negatively influence bundle uptake. While included units are crucial for bundles integrating car-based shared modes, additional prices beyond these units are more important for shared micro-mobility services. The quality of the local transport system and shared mobility supply is an important precondition for MaaS bundle uptake.
... At the local and national levels, MaaS aspires to bridge the gap between public and private transportation carriers, shifting away from personally owned modes of transportation toward providing mobility as a service. The primary idea behind MaaS is integrated and seamless mobility providing travelers with mobility options tailored to their specific travel requirements (Kamargianni et al. 2016;Esztergár-Kiss, 2020;Alyavina et al. 2020;). It is a practical mobility option that most likely will be crucial in the reform of urban transportation in the future. ...
As the population of urban centers grows, there is a significant challenge of adjusting the transportation needs of urban mobility, as well as pursuing environmental protection strategies and ensuring social inclusion. The major bottleneck of urban mobility includes the constant traffic congestion in major cities because of excessive use of private cars. Developing an accessible, attractive transportation system that caters to people's individual mobility needs and preferences is one possible solution to these problems. It is important to have a coordinated system connecting the various modes of transportation so that people's homes and destinations can be reached with ease. The first and last miles of commuters, which are the weakest linkages in the transportation network, should be developed first before the system can be integrated. Shared mobility which involves using a shared vehicle (car, bike, scooter, etc.) often serves as a first or last mile connection to other modes of transportation such as public transit. Understanding the factors that influence the adoption of shared mobility services is crucial to ensuring that they become a significant component of the urban mobility system. This paper provides an overview of existing and emerging last mile solutions, particularly in the concept of shared mobility. The objective of this study is to add and enrich knowledge in the area of shared mobility in bridging the last mile toward an integrated mobility system.
... Therefore, being a relatively new concept, there is still no clear consensus upon what 'Mobility as a Service' means and which are the exact goals to be attained through this concept (Lyons, Hammond & Mackay, 2020;Alyavina, Nikitas and Njoya, 2020). To better clarify the topic, we, therefore, propose a summarizing recent definitions of the emerging concept in Table 1. ...
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Our study aims to provide scientific research to the disrupting peer-to-peer asset utilisation practices of emergent organisations, testing the robustness of said business models for gradual adoption into organisational design norms. The tourism industry, the optimum platform to host our hypothesis and findings, hosts two successful business models that have been popularly adopted worldwide: home-sharing and car-sharing platforms. Disseminating these innovative business models by means of thorough scientific qualitative research through secondary data collection will result in a descriptive study of the peer-to-peer asset utilisation model that can be adopted by parallel industries. The peer-to-peer models studies came into existence from asset availability or excess demand, coercing the regulatory systems that govern the industries they disrupt into adapting for them. Norms and regulations restrain these newly formed systems into complying with more than the economic outcomes of business processes, forcing their evolution onto a sustainable path. Apart from other studies in the field, our research stresses the utility of "Home Sharing" and "Mobility as a Service" (MaaS) as common grounds between corporations and the communities they serve. Private asset owners can thus either compete with businesses, or the public can collaborate with the economic environment for mutual advantages. The findings of this study have practical implications in organisation design management, as our research reveals that asset and inventory ownership can easily be substituted by available external resources, benefiting the community while improving financial yield. Abstract. Our study aims to provide scientific research to the disrupting peer-to-peer asset utilisation practices of emergent organisations, testing the robustness of said business models for gradual adoption into organisational design norms. The tourism industry, the optimum platform to host our hypothesis and findings, hosts two successful business models that have been popularly adopted worldwide: home-sharing and car-sharing platforms. Disseminating these innovative business models by means of thorough scientific qualitative research through secondary data collection will result in a descriptive study of the peer-to-peer asset utilisation model that can be adopted by parallel industries. More precisely, we propose a clear illustration of peer-to-peer real estate and Mobility as a Service concepts towards forming more sustainable business models. We find that efficient disruptive businesses gradually become the new norm in organisation design. The peer-to-peer models studies came into existence from asset availability or excess demand, coercing the regulatory systems that govern the industries they disrupt into adapting for them. Norms and regulations restrain these newly formed systems into complying with more than the economic outcomes of business processes, forcing their evolution onto a sustainable path. Apart from other studies in the field, our research stresses the utility of "Home Sharing" and "Mobility as a Service" (MaaS) as common grounds between corporations and the communities they serve. Private asset owners can thus either compete with businesses, or the public can collaborate with the economic environment for mutual advantages. The findings of this study have practical implications in organisation design management, as our research reveals that asset and inventory ownership can easily be substituted by available external resources, benefiting the community while improving financial yield.
... Based on five core themes of car dependence, trust, human element externalities, value, and cost, four participant subgroups were identified as car shedders, car accessors, simplifiers, and economizers by Alyavina et al. (2020). It could be argued that MaaS has the potential to reduce the demand for private car and enable people to change their mode choices and travel patterns, based on the empirical findings by Strömberg et al. (2018). ...
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Mobility-as-a-Service can be customized in various forms depending on the regional and activity travel contexts. Unlike the previous studies dealing with the daily trip and general characteristics of MaaS, this study focuses on more specific contexts like MaaS in tourism transport. An online survey and stated preference experiments were conducted for the first time in China to evaluate consumer preference for different MaaS packages bundled with tourism service, and six discrete choice models were constructed which reflects the interaction of propensity to consume with other attributes. Survey results indicate that MaaS in tourism will find a promising market in China, and more than 50 percent of respondents would choose to use MaaS packages. MaaS consumers can be divided into three categories based on average propensity to consume that conservative consumer group has the highest proportion of the sample, followed by moderate consumer group and aggressive consumer group. Model estimations illustrate those factors affecting whether to subscribe to the MaaS package mainly include MaaS app-related attributes, social environment, and the living location of the respondents; individual socio-demographics, tour preference, and daily travel habits have influences on their choice behaviors of MaaS service pattern. It also reveals that the interaction items of propensity to consume and package-related attributes (i.e., subscription price, period of validity, and tourism preferential price) play significant and heterogeneous roles to consumer interests and preferences for MaaS in tourism.
... Via a digital platform or interface it enables users to plan, book, and pay for multiple types of mobility needs. Ideally, in order to offer user centric mobility services, MaaS allows for personalization and customization (Alyavina et al., 2020;Utriainen and Pöllänen, 2018;Jittrapirom et al., 2017). However, despite numerous potential benefits and advantages, progress from MaaS pilots to large-scale implementation has been relatively slow (Karlsson et al., 2020). ...
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Mobility as a Service (MaaS) refers to the concept of integrating new mobility services electronically, thereby enabling users to access various public and private transport services via a single digital platform. Through MaaS, service providers aim at developing an integrated service that caters to various demands by mobility users. Personal data such as travel behavior is key in this context, because it allows the development, customization, and personalization of mobility services. Hence, for MaaS to become successful, service providers need to collect users' personal information, and users need to accept data collection. In turn, privacy concerns represent a potential hurdle for the success of MaaS. Therefore, understanding privacy concerns from the users' side can help MaaS providers to increase the users' willingness to share their information. This study aims to add on to earlier research findings on privacy concerns by shedding light on new dimensions emerging from the MaaS service. Understanding privacy concerns from the users' side is key in that regard, as it may enable improved service and system development. A sequential mixed-methods approach is used to collect, analyze, and “mix” both quantitative and qualitative research methods. The primary findings are as follows: (1) Privacy concerns specific to the mobility data collection context exist; (2) users are not necessarily personally worried about their privacy even though they claim privacy is an issue; (3) in contrast to traditional privacy thinking, users' trust in mobility service providers may override their privacy concerns. The study's results indicate trust is the key to MaaS adoption. Policy recommendations are explored in the end.
... Yet such aspirations can only be achieved if all transport users benefit through an inclusive mobility service, regardless of their socio-economic status, such as gender, age, or (dis)ability. Such an approach would improve accessibility to employment opportunities, training and education facilities, healthcare services, and recreational activities both for commuting and non-commuting travel (Alyavina et al., 2020;Nikitas et al., 2017;Polydoropoulou et al., 2020b;. Not considering the needs of specific user groups, in this case VSGs, will have a negative impact on MaaS adoption, since a similar trend has been found by studies on autonomous vehicles (Kyriakidis et al., 2020;Polydoropoulou et al., 2021). ...
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According to UN statistics, the population of people in vulnerable social groups, namely elderly people, people with disabilities, and low-income populations, has increased over the recent decades. It is projected that this trend will continue in the future. Thus, their mobility and access to transport services are important areas to study. Mobility as a Service (MaaS) is a digital platform (smartphone application) that aims to encourage more sustainable travel. MaaS is promoted as being accessible to all user groups. However, there are limited studies linking MaaS with vulnerable social groups and their particular needs. This paper comprehensively reviews studies on the emergence of such platforms since 2014 until today to identify the research gaps with respect to vulnerable social groups. A framework and MaaS Inclusion Index (MaaSINI) are then proposed to evaluate the inclusion in MaaS services, focusing on vulnerable social groups’ needs at a service level instead of a city/area level. The framework and policy recommendations proposed in this study will make a significant contribution in guiding stakeholders and policymakers in implementing accessible-for-all-users MaaS services targeting sustainable and inclusive transport.
... Although sustainable mobility projects are typically considered as part of soft and small-scale interventions mainly focusing on aesthetics, in practice, they are the outcome of a deeper process. Their goal is to create a new resource-efficient ethos in transport provision (Nikitas, 2019), promote social equity (Zhao and Yu, 2020), support environmental preservation (Alyavina et al., 2020), boost economic efficiency (Canitez, 2020) and introduce people-centric and holistic policy practices genuinely applicable to cities (Sdoukopoulos,, 2019). Indeed, in such projects, motor traffic is usually re-organised and emphasis is set on public transport and non-motorised mobility (cyclists and users of micromobility) while pedestrian movement is strengthened. ...
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COVID-19, the most wide-spread and disruptive pandemic in over a century, enforced emergency urban design responses meaning to recalibrate transport provision globally. This is the first work that systematically evaluates the ‘public acceptance’ as a proxy for ‘policy success’ and ‘potential for longer-term viability’ of the high-profile sustainable transport intervention package introduced in 2020 in the capital city of Greece known as the Great Walk of Athens (GWA). This is achieved through a twin statistical analysis of an e-survey that looked into the attitudes and urban mobility experiences of Athenians accessing the area of the trial daily. The research enabled a comparison between the pre- and post-implementation traffic situations and provided details about specific measures packaged in the GWA project. Our results suggest that walking and cycling uptake were only marginally improved. Traffic delays for car users were considerable. Car usage declined somewhat, with the exception of ride-sharing. Public transport ridership numbers suffered a lot because of concerns about sharing closed space with many others during a pandemic. Men and people on low income were more likely to agree with the ‘change’. Naturally this was the case for people identified as primarily cyclists and pedestrians. The most impactful package elements in terms of car lane sacrifices (i.e., the redevelopment of Panepistimiou Street) had the lowest acceptability rates. A key reason that underpinned people's hesitation to approve the GWA initiative was the lack of public consultation in the decision-making that shaped the project. Our study provides evidence-based generalisable lessons for similar metropolitan environments looking to implement more or evaluate for possibly making permanent ‘rushed’ anti-Covid street redevelopment measures.
... Организационноэкономическим аспектам внедрения концепции «мобильность как услуга» в городскую среду [1][2][3][4]. Влиянию инновационной мобильности на изменение поведенческих паттернов пассажиров [5][6][7]. Анализу потенциальных барьеров и выгод от развития инновационной городской мобильности [8][9]. ...
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Background: For several decades now, the problem of the "auto-centric" model of megacity transport systems development has been a burning issue, which is characterized by serious negative consequences in the long run, despite certain conveniences for individual users. Urban mobility provides the population with access to economic resources, so a reliable transport system is a key condition for the sustainable development of modern agglomerations. The usage of digital technologies together with innovative products can ensure the efficient operation and competitiveness of public transport. "Mobility as a service" is an end-user-oriented model of urban mobility, which can promote the gradual abandonment of personal car use. Aim: Consider organizational models for implementing the concept of innovative mobility, identify the potential benefits of digital transformation of the urban transportation system, based on the model of efficient mobility "mobility as a service". Methods: General scientific research methods such as the systematic approach, analogy, generalization and synthesis were used. Results: The article explores the innovative urban mobility model based on mobility-as-a-service technology, examines the organizational models of MaaS, identifying the main barriers to implementing this concept along with potential advantages and disadvantages.
Megatrends such as urbanization, digitalization, and decarbonization have created the necessity for new and creative approaches to the urban transportation system. As a solution to the problems of the increasingly digitalized urban transportation environment, “Mobility-as-a-Service” (MaaS) was proposed as a new sustainable transportation concept in Helsinki in 2014. With the use of the MaaS concept, residents of a large emerging metropolis, such as Istanbul, Turkey, can be offered a fast, efficient, environment-friendly, and inexpensive way of travel. However, despite the significant benefits of MaaS, there are several factors that can hinder the adoption of MaaS. This paper aims to analyze these barriers and their contextual relationships with each other using Total Interpretive Structural Modeling (TISM) and Matrix-based-Multiplication-Applied-to-a-Classification (MICMAC) methods. The case study has been conducted on an expert group to explore which significant barriers might be encountered during the adoption of a MaaS system in Istanbul. This study also addresses how these barriers should be overcome, and the MaaS concept should be adopted in Istanbul. The results showed that the most significant barrier to adopting the MaaS concept in Istanbul are Laws, Regulations, and Guidelines that primarily include the legal nature of this mobility service. The least important barriers are found to be Customer Acceptance and Labor Shortage. Therefore, the case study results provided a unique perspective for emerging countries in terms of barriers to successful MaaS implementations and revealed significant differences from the developed countries.
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Artificial intelligence (AI) is a powerful concept still in its infancy that has the potential, if utilised responsibly, to provide a vehicle for positive change that could promote sustainable transitions to a more resource-efficient livability paradigm. AI with its deep learning functions and capabilities can be employed as a tool which empowers machines to solve problems that could reform urban landscapes as we have known them for decades now and help with establishing a new era; the era of the "smart city". One of the key areas that AI can redefine is transport. Mobility provision and its impact on urban development can be significantly improved by the employment of intelligent transport systems in general and automated transport in particular. This new breed of AI-based mobility, despite its machine-orientation, has to be a user-centred technology that "understands" and "satisfies" the human user, the markets and the society as a whole. Trust should be built, and risks should be eliminated, for this transition to take off. This paper provides a novel conceptual contribution that thoroughly discusses the scarcely studied nexus of AI, transportation and the smart city and how this will affect urban futures. It specifically covers key smart mobility initiatives referring to Connected and Autonomous Vehicles (CAVs), autonomous Personal and Unmanned Aerial Vehicles (PAVs and UAVs) and Mobility-as-a-Service (MaaS), but also interventions that may work as enabling technologies for transport, such as the Internet of Things (IoT) and Physical Internet (PI) or reflect broader transformations like Industry 4.0. This work is ultimately a reference tool for researchers and city planners that provides clear and systematic definitions of the ambiguous smart mobility terms of tomorrow and describes their individual and collective roles underpinning the nexus in scope.
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Abstract With the emergence of the Mobility as a Service (MaaS) concept, it is important to understand whether it has the potential to support behaviour change and the shift away from private vehicle ownership and use. This paper aims to identify potential ways that MaaS (specifically MaaS plans) could help encourage behavioural change; and understand the barriers to using alternative transport modes. In-depth interviews and qualitative analysis are applied to the case study of London. The results indicate that individuals segment the transport modes offered via MaaS into three categories: essential, considered and excluded. Soft measures should target each individuals’ consideration set as this is where the most impact can be made regarding behaviour change. Respondents also highlighted factors that make them apprehensive towards certain modes, such as safety, service characteristics and administration. Interventions that focus on the socio-demographic groups that are most affected could help make these modes more appealing.
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Mobility-as-a-Service (MaaS) has been argued as part of the solution to prevalent transport problems. However, progress from pilots to large-scale implementation has hitherto been slow. The aim of the research reported in this paper was to empirically and in-depth investigate how, and to what extent, different factors affect the development and implementation of MaaS. A framework was developed, with a basis in institutional theory and the postulation that formal as well informal factors on different analytical levels (macro, meso and micro) must be considered. The research was organised as a multiple case study in Finland and Sweden and a qualitative approach was chosen for data collection and analysis. A number of factors with a claimed impact on the development and implementation of MaaS was revealed. At the macro level, these factors included legislation concerning transport, innovation and public administration, and the presence (or not) of a shared vision for MaaS. At the meso level, (the lack of) appropriate business models, cultures of collaboration, and assumed roles and responsibilities within the MaaS ecosystem were identified as significant factors. At the micro level, people’s attitudes and habits were recognised as important factors to be considered. However, how the ‘S’ in MaaS fits (or not) the transport needs of the individual/household appears to play a more important role in adoption or rejection of MaaS than what has often been acknowledged in previous papers on MaaS. The findings presented in this paper provide several implications for public and private sector actors. Law-making authorities can facilitate MaaS developments by adjusting relevant regulations and policies such as transport-related subsidies, taxation policies and the definition of public transport. Regional and local authorities could additionally contribute to creating conducive conditions for MaaS by, for example, planning urban designs and transport infrastructures to support service-based travelling. Moreover, private actors have key roles to play in future MaaS developments, as both public and private transport services are needed if MaaS is to become a viable alternative to privately owned cars. Thus, the advance of MaaS business models that benefit all involved actors is vital for the prosperity of the emerging MaaS ecosystem.
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As mobility as a service (MaaS) continues to evolve with increasing interest throughout many countries, a key driver of its success will be the take up by the community of users seeking an alternative way of accessing individual modal options. Whether a packaging of modal services into a mobility bundle will appeal to the travelling population will depend on what appeal such packages can offer compared to purchasing travel via mode-specific outlets. This paper is one of a growing number exploring the role that everyday travel needs and socio-economic setting might play in defining mobility plans that gather significant appeal from the community. Building on our research in Sydney, Australia, we undertake a stated choice analysis in Tyneside, UK to see the extent to which differences in preferences and possible similarities exist in the demand for different subscription models and willingness to pay for mobility services in the two settings. Barriers to a widespread adoption of MaaS are also analysed, as are the potential impacts of MaaS adoption on public transport use and the way people access public transport services. A decision supporting system was developed to translate the modelling results into a practical and user-friendly tool for MaaS developers/innovators to assess market potential based on customer willingness to pay.
Based on digital transformation processes, public mobility is experiencing tremendous and far-reaching change. The use of information and communication technology (ICT) enables disruptive mobility solutions that have recently became known as mobility as a service (MaaS). MaaS promises great economic potential and supports the idea of a more efficient allocation of transport resources. However, the main motivational mechanisms behind travelers’ adoption intention are still unknown. This research identifies key motivational determinants and investigates their structural interrelations. Based on a literature review we first identify the fundamental characteristics of MaaS. Building on this common understanding, we conduct qualitative in-depth interviews with potential end-users to explore motivational acceptance factors. We draw from our inductive findings to postulate a structural causal equation model that captures motivational mechanisms behind the intention to adopt MaaS. Finally, the model will be quantitatively validated based on a comprehensive survey and the use of partial least squares (PLS) analysis. We show that psychological needs play a crucial role in the acceptance of MaaS. The results demonstrate that anticipated advantages of autonomy, competence and the feeling of being related to a social peer group affect hedonic motivation and the expected usefulness of MaaS offerings, which equally affect behavioral intention. We also introduce a novel theoretical construct and show that – in the present disruptive context – cognitive congruency between existing habit schemata and anticipated MaaS usage patterns significantly affect the judgment process and behavioral intention. Finally, important implications for market strategy, product development and policy measures will be discussed.
Mobility as a Service (MaaS) represents an innovative solution expected to induce people abandoning their cars in favor of more sustainable ways of travelling. However, a precondition for the successful implementation and diffusion of MaaS is public acceptance. In this paper, the latent demand for MaaS is estimated using a choice model based on a stated preference survey, conducted in the Netherlands. Specifically, a sequential experimental design approach based on portfolio choice is developed. It consists of two steps aimed to investigate (i) individual intention to subscribe to MaaS and preferences for bundle configurations, (ii) willingness to pay for extra features of the service. This article reports results of the analysis of the first step of the experiment. Two different mixed logit models are estimated to capture unobserved heterogeneity in individual’s preferences. First, a binary mixed logit model is formulated to estimate the effect of service attributes, social influence, socio-demographics and transportation-related characteristics on the decision to subscribe. Then, a mixed logit model is formulated to analyze the effects of transportation mode pricing schemes, and cross effects between transportation modes and individual characteristics on the choice which transportation modes to include in the subscription. The estimation results indicate that, overall, respondents are not yet inclined to subscribe to this new service. The service attribute characteristics, especially the price of the monthly subscription, and the social influence variables have an important effect on the subscription intention. The results also show that public transportation is the most preferred transportation mode, revealing that it may play a key role in MaaS platforms. The decision to subscribe and the choice which transportation modes to include in the bundle, appear to be significantly related to socio-demographic profiles and individuals’ transportation-related characteristics. The findings can be used as a valuable source of information for transportation planners and policy makers.
The concept of Mobility as a Service (MaaS) is seeing increasing attention from researchers, industry, and the public sector. MaaS, which posits that traditional models of car ownership and travel may be supplanted by models focused on packages of shared vehicle access, use of public transport, active transport, and teleworking, is currently viewed as having potential beneficial impacts including reductions in single-occupancy vehicle trips, with concomitant reductions in travel cost, congestion, and environmental concerns. MaaS, however, relies upon a number of social expectations, including trust, reliability, and transparency, each of which is reliant upon both the social network that enables MaaS to work efficiently, and upon the ways in which data are handled within the enabling framework. In light of this, it is anticipated that the recently-enacted General Data Protection Regulation (GDPR) has the potential to significantly impact upon the further implementation of MaaS. MaaS services are predicated upon the sharing of personal travel information (vehicle availability, origins, destinations, financial information, social network data, etc.) that, under GDPR, may be considered personal, subject to the regulations and restrictions this categorisation implies. For MaaS to work in a European context, then, it must be responsive to GDPR requirements related to issues such as Privacy by Design, Consent, and Protection. In this paper, we explore the concept of MaaS in relation to privacy considerations raised by GDPR requirements, with attention to methods and techniques related to relevant data acquisition, sharing, and protection processes. A case study of the Whim application’s privacy policy is presented to demonstrate the potential implications of this policy in an applied context.
Mobility-as-a-Service (MaaS) has received widespread attention over the past couple of years amongst scholars, businesses, policymakers and mainstream media. Most coverage is oriented towards its possible gains for traveling individuals and the travel industry, while still lacking conceptual clarity and sufficient detail about its potential acceptance by the general public. This leads to varying perspectives on what MaaS precisely is and will be in the near future. In this study, we reflect upon the relationship between MaaS use and private car ownership, based on insights gained from a MaaS pilot study organized mid-2017 in Ghent (Belgium). This exploratory pilot study targeted 100 car-owning participants (i.e., Ghent University employees) and explored how these motivated people can replace or significantly reduce car use in return for a monthly mobility budget which they could spend on MaaS services. The study reveals that most respondents were apt to explore MaaS services (especially public transport and car sharing services), but a clear reduction of private car use remained difficult in a real-life setting. Despite being highly motivated to reduce car use and being given incentives, participants faced considerable difficulties in bypassing their personal car, especially for (non-repetitive) leisure trips. By drawing parallels with a similar debate in the transport literature from a couple of decades ago, we suggest that MaaS should be regarded as a complement rather than a substitution of private car use in the near future. The relationship between MaaS use and car ownership might in reality be more complex than generally acknowledged. In addressing these parallels, the paper opens up new critical questions for MaaS research in the future.
This research study aims at providing new insights regarding attitudes among residents towards the introduction of Mobility-as- a-Service (MaaS). We were especially interested in finding out how likely residents would be willing to use MaaS when introduced in their place of residence. The study involved a quantitative survey and focus group interviews with residents in the Paleiskwartier district, in the city of ’s-Hertogenbosch, the Netherlands. Our results show that positive attitudes towards MaaS are the most important factors for the intention to use MaaS, whereas socio-economic characteristics seem not to play a role. Moreover, our results also indicate that most residents are more likely to not use MaaS in the long run, but a considerable amount of them would be interested in trying it out, at least. Equally important, the introduction of MaaS pilots may experience a greater receptivity among residents who do not see car ownership and usage as very important aspects, who regularly use public transport and who are mostly concerned with the environment and with a healthy commuting lifestyle. Conversely, people who use the car on a daily basis and regard car ownership as a very important aspect are far less receptive to MaaS pilots. Therefore, the sole idea of MaaS as an environmentally friendly alternative to make car ownership superfluous may potentially be inefficient against avid car users.
Reward-based instruments have the potential to encourage individuals’ shift towards multimodal mobility options, thus contributing to a more sustainable and resilient transport environment. This paper aims to investigate the effects of reward-based instruments on promoting emerging mobility schemes and active transport, through real-world demonstrations in two European cities. Specifically, a route planning mobile application which tracks users’ travel patterns was used to integrate a reward program offering points to incentivize people towards sustainable multimodal choices, including public transport, cycling and walking. In addition, a web-based questionnaire survey was conducted, and a discrete choice model was developed to model individuals’ multimodal choice in the presence of different reward types, including monetary rewards, points and the provision of added value services. Overall, our findings indicate that reward-based instruments can contribute to the promotion of sustainable and emerging transport services. In particular, participants spent more time in public transport usage and walking during the reward-based period. Our results indicate that rewards could increase individuals’ time spent in public transport usage and walking by about 21 min and 14 min per day respectively. Furthermore, it is found that public transport users were mostly motivated by rewards, while car users and walkers were not motivated towards cycling. Finally, the results indicate that Birmingham’s users were more motivated than Vienna’s participants, as public transport usage increased by about 209 min per week in Birmingham vs. 74 min per week in Vienna. Similar patterns of increase in the cities were observed for walking, while some population groups in Vienna were found insensitive to the prospect of earning rewards for using sustainable transport modes.